Combined array CGH plus SNP genome analyses in a single assay for optimized clinical testing

PubMed Central

Wiszniewska, Joanna; Bi, Weimin; Shaw, Chad; Stankiewicz, Pawel; Kang, Sung-Hae L; Pursley, Amber N; Lalani, Seema; Hixson, Patricia; Gambin, Tomasz; Tsai, Chun-hui; Bock, Hans-Georg; Descartes, Maria; Probst, Frank J; Scaglia, Fernando; Beaudet, Arthur L; Lupski, James R; Eng, Christine; Wai Cheung, Sau; Bacino, Carlos; Patel, Ankita

2014-01-01

In clinical diagnostics, both array comparative genomic hybridization (array CGH) and single nucleotide polymorphism (SNP) genotyping have proven to be powerful genomic technologies utilized for the evaluation of developmental delay, multiple congenital anomalies, and neuropsychiatric disorders. Differences in the ability to resolve genomic changes between these arrays may constitute an implementation challenge for clinicians: which platform (SNP vs array CGH) might best detect the underlying genetic cause for the disease in the patient? While only SNP arrays enable the detection of copy number neutral regions of absence of heterozygosity (AOH), they have limited ability to detect single-exon copy number variants (CNVs) due to the distribution of SNPs across the genome. To provide comprehensive clinical testing for both CNVs and copy-neutral AOH, we enhanced our custom-designed high-resolution oligonucleotide array that has exon-targeted coverage of 1860 genes with 60 000 SNP probes, referred to as Chromosomal Microarray Analysis – Comprehensive (CMA-COMP). Of the 3240 cases evaluated by this array, clinically significant CNVs were detected in 445 cases including 21 cases with exonic events. In addition, 162 cases (5.0%) showed at least one AOH region >10 Mb. We demonstrate that even though this array has a lower density of SNP probes than other commercially available SNP arrays, it reliably detected AOH events >10 Mb as well as exonic CNVs beyond the detection limitations of SNP genotyping. Thus, combining SNP probes and exon-targeted array CGH into one platform provides clinically useful genetic screening in an efficient manner. PMID:23695279

Development and validation of a 20K single nucleotide polymorphism (SNP) whole genome genotyping array for apple (Malus × domestica Borkh).

PubMed

Bianco, Luca; Cestaro, Alessandro; Sargent, Daniel James; Banchi, Elisa; Derdak, Sophia; Di Guardo, Mario; Salvi, Silvio; Jansen, Johannes; Viola, Roberto; Gut, Ivo; Laurens, Francois; Chagné, David; Velasco, Riccardo; van de Weg, Eric; Troggio, Michela

2014-01-01

High-density SNP arrays for genome-wide assessment of allelic variation have made high resolution genetic characterization of crop germplasm feasible. A medium density array for apple, the IRSC 8K SNP array, has been successfully developed and used for screens of bi-parental populations. However, the number of robust and well-distributed markers contained on this array was not sufficient to perform genome-wide association analyses in wider germplasm sets, or Pedigree-Based Analysis at high precision, because of rapid decay of linkage disequilibrium. We describe the development of an Illumina Infinium array targeting 20K SNPs. The SNPs were predicted from re-sequencing data derived from the genomes of 13 Malus × domestica apple cultivars and one accession belonging to a crab apple species (M. micromalus). A pipeline for SNP selection was devised that avoided the pitfalls associated with the inclusion of paralogous sequence variants, supported the construction of robust multi-allelic SNP haploblocks and selected up to 11 entries within narrow genomic regions of ±5 kb, termed focal points (FPs). Broad genome coverage was attained by placing FPs at 1 cM intervals on a consensus genetic map, complementing them with FPs to enrich the ends of each of the chromosomes, and by bridging physical intervals greater than 400 Kbps. The selection also included ∼3.7K validated SNPs from the IRSC 8K array. The array has already been used in other studies where ∼15.8K SNP markers were mapped with an average of ∼6.8K SNPs per full-sib family. The newly developed array with its high density of polymorphic validated SNPs is expected to be of great utility for Pedigree-Based Analysis and Genomic Selection. It will also be a valuable tool to help dissect the genetic mechanisms controlling important fruit quality traits, and to aid the identification of marker-trait associations suitable for the application of Marker Assisted Selection in apple breeding programs.

Development and Validation of a 20K Single Nucleotide Polymorphism (SNP) Whole Genome Genotyping Array for Apple (Malus × domestica Borkh)

PubMed Central

Bianco, Luca; Cestaro, Alessandro; Sargent, Daniel James; Banchi, Elisa; Derdak, Sophia; Di Guardo, Mario; Salvi, Silvio; Jansen, Johannes; Viola, Roberto; Gut, Ivo; Laurens, Francois; Chagné, David; Velasco, Riccardo; van de Weg, Eric; Troggio, Michela

2014-01-01

High-density SNP arrays for genome-wide assessment of allelic variation have made high resolution genetic characterization of crop germplasm feasible. A medium density array for apple, the IRSC 8K SNP array, has been successfully developed and used for screens of bi-parental populations. However, the number of robust and well-distributed markers contained on this array was not sufficient to perform genome-wide association analyses in wider germplasm sets, or Pedigree-Based Analysis at high precision, because of rapid decay of linkage disequilibrium. We describe the development of an Illumina Infinium array targeting 20K SNPs. The SNPs were predicted from re-sequencing data derived from the genomes of 13 Malus × domestica apple cultivars and one accession belonging to a crab apple species (M. micromalus). A pipeline for SNP selection was devised that avoided the pitfalls associated with the inclusion of paralogous sequence variants, supported the construction of robust multi-allelic SNP haploblocks and selected up to 11 entries within narrow genomic regions of ±5 kb, termed focal points (FPs). Broad genome coverage was attained by placing FPs at 1 cM intervals on a consensus genetic map, complementing them with FPs to enrich the ends of each of the chromosomes, and by bridging physical intervals greater than 400 Kbps. The selection also included ∼3.7K validated SNPs from the IRSC 8K array. The array has already been used in other studies where ∼15.8K SNP markers were mapped with an average of ∼6.8K SNPs per full-sib family. The newly developed array with its high density of polymorphic validated SNPs is expected to be of great utility for Pedigree-Based Analysis and Genomic Selection. It will also be a valuable tool to help dissect the genetic mechanisms controlling important fruit quality traits, and to aid the identification of marker-trait associations suitable for the application of Marker Assisted Selection in apple breeding programs. PMID:25303088

A high-density, multi-parental SNP genetic map on apple validates a new mapping approach for outcrossing species.

PubMed

Di Pierro, Erica A; Gianfranceschi, Luca; Di Guardo, Mario; Koehorst-van Putten, Herma Jj; Kruisselbrink, Johannes W; Longhi, Sara; Troggio, Michela; Bianco, Luca; Muranty, Hélène; Pagliarani, Giulia; Tartarini, Stefano; Letschka, Thomas; Lozano Luis, Lidia; Garkava-Gustavsson, Larisa; Micheletti, Diego; Bink, Marco Cam; Voorrips, Roeland E; Aziz, Ebrahimi; Velasco, Riccardo; Laurens, François; van de Weg, W Eric

2016-01-01

Quantitative trait loci (QTL) mapping approaches rely on the correct ordering of molecular markers along the chromosomes, which can be obtained from genetic linkage maps or a reference genome sequence. For apple ( Malus domestica Borkh), the genome sequence v1 and v2 could not meet this need; therefore, a novel approach was devised to develop a dense genetic linkage map, providing the most reliable marker-loci order for the highest possible number of markers. The approach was based on four strategies: (i) the use of multiple full-sib families, (ii) the reduction of missing information through the use of HaploBlocks and alternative calling procedures for single-nucleotide polymorphism (SNP) markers, (iii) the construction of a single backcross-type data set including all families, and (iv) a two-step map generation procedure based on the sequential inclusion of markers. The map comprises 15 417 SNP markers, clustered in 3 K HaploBlock markers spanning 1 267 cM, with an average distance between adjacent markers of 0.37 cM and a maximum distance of 3.29 cM. Moreover, chromosome 5 was oriented according to its homoeologous chromosome 10. This map was useful to improve the apple genome sequence, design the Axiom Apple 480 K SNP array and perform multifamily-based QTL studies. Its collinearity with the genome sequences v1 and v3 are reported. To our knowledge, this is the shortest published SNP map in apple, while including the largest number of markers, families and individuals. This result validates our methodology, proving its value for the construction of integrated linkage maps for any outbreeding species.

A high-density, multi-parental SNP genetic map on apple validates a new mapping approach for outcrossing species

PubMed Central

Di Pierro, Erica A; Gianfranceschi, Luca; Di Guardo, Mario; Koehorst-van Putten, Herma JJ; Kruisselbrink, Johannes W; Longhi, Sara; Troggio, Michela; Bianco, Luca; Muranty, Hélène; Pagliarani, Giulia; Tartarini, Stefano; Letschka, Thomas; Lozano Luis, Lidia; Garkava-Gustavsson, Larisa; Micheletti, Diego; Bink, Marco CAM; Voorrips, Roeland E; Aziz, Ebrahimi; Velasco, Riccardo; Laurens, François; van de Weg, W Eric

2016-01-01

Quantitative trait loci (QTL) mapping approaches rely on the correct ordering of molecular markers along the chromosomes, which can be obtained from genetic linkage maps or a reference genome sequence. For apple (Malus domestica Borkh), the genome sequence v1 and v2 could not meet this need; therefore, a novel approach was devised to develop a dense genetic linkage map, providing the most reliable marker-loci order for the highest possible number of markers. The approach was based on four strategies: (i) the use of multiple full-sib families, (ii) the reduction of missing information through the use of HaploBlocks and alternative calling procedures for single-nucleotide polymorphism (SNP) markers, (iii) the construction of a single backcross-type data set including all families, and (iv) a two-step map generation procedure based on the sequential inclusion of markers. The map comprises 15 417 SNP markers, clustered in 3 K HaploBlock markers spanning 1 267 cM, with an average distance between adjacent markers of 0.37 cM and a maximum distance of 3.29 cM. Moreover, chromosome 5 was oriented according to its homoeologous chromosome 10. This map was useful to improve the apple genome sequence, design the Axiom Apple 480 K SNP array and perform multifamily-based QTL studies. Its collinearity with the genome sequences v1 and v3 are reported. To our knowledge, this is the shortest published SNP map in apple, while including the largest number of markers, families and individuals. This result validates our methodology, proving its value for the construction of integrated linkage maps for any outbreeding species. PMID:27917289

Development of a dense SNP-based linkage map of an apple rootstock progeny using the Malus Infinium whole genome genotyping array.

PubMed

Antanaviciute, Laima; Fernández-Fernández, Felicidad; Jansen, Johannes; Banchi, Elisa; Evans, Katherine M; Viola, Roberto; Velasco, Riccardo; Dunwell, Jim M; Troggio, Michela; Sargent, Daniel J

2012-05-25

A whole-genome genotyping array has previously been developed for Malus using SNP data from 28 Malus genotypes. This array offers the prospect of high throughput genotyping and linkage map development for any given Malus progeny. To test the applicability of the array for mapping in diverse Malus genotypes, we applied the array to the construction of a SNP-based linkage map of an apple rootstock progeny. Of the 7,867 Malus SNP markers on the array, 1,823 (23.2%) were heterozygous in one of the two parents of the progeny, 1,007 (12.8%) were heterozygous in both parental genotypes, whilst just 2.8% of the 921 Pyrus SNPs were heterozygous. A linkage map spanning 1,282.2 cM was produced comprising 2,272 SNP markers, 306 SSR markers and the S-locus. The length of the M432 linkage map was increased by 52.7 cM with the addition of the SNP markers, whilst marker density increased from 3.8 cM/marker to 0.5 cM/marker. Just three regions in excess of 10 cM remain where no markers were mapped. We compared the positions of the mapped SNP markers on the M432 map with their predicted positions on the 'Golden Delicious' genome sequence. A total of 311 markers (13.7% of all mapped markers) mapped to positions that conflicted with their predicted positions on the 'Golden Delicious' pseudo-chromosomes, indicating the presence of paralogous genomic regions or mis-assignments of genome sequence contigs during the assembly and anchoring of the genome sequence. We incorporated data for the 2,272 SNP markers onto the map of the M432 progeny and have presented the most complete and saturated map of the full 17 linkage groups of M. pumila to date. The data were generated rapidly in a high-throughput semi-automated pipeline, permitting significant savings in time and cost over linkage map construction using microsatellites. The application of the array will permit linkage maps to be developed for QTL analyses in a cost-effective manner, and the identification of SNPs that have been assigned erroneous positions on the 'Golden Delicious' reference sequence will assist in the continued improvement of the genome sequence assembly for that variety.

Tumor Touch Imprints as Source for Whole Genome Analysis of Neuroblastoma Tumors

PubMed Central

Brunner, Clemens; Brunner-Herglotz, Bettina; Ziegler, Andrea; Frech, Christian; Amann, Gabriele; Ladenstein, Ruth; Ambros, Inge M.; Ambros, Peter F.

2016-01-01

Introduction Tumor touch imprints (TTIs) are routinely used for the molecular diagnosis of neuroblastomas by interphase fluorescence in-situ hybridization (I-FISH). However, in order to facilitate a comprehensive, up-to-date molecular diagnosis of neuroblastomas and to identify new markers to refine risk and therapy stratification methods, whole genome approaches are needed. We examined the applicability of an ultra-high density SNP array platform that identifies copy number changes of varying sizes down to a few exons for the detection of genomic changes in tumor DNA extracted from TTIs. Material and Methods DNAs were extracted from TTIs of 46 neuroblastoma and 4 other pediatric tumors. The DNAs were analyzed on the Cytoscan HD SNP array platform to evaluate numerical and structural genomic aberrations. The quality of the data obtained from TTIs was compared to that from randomly chosen fresh or fresh frozen solid tumors (n = 212) and I-FISH validation was performed. Results SNP array profiles were obtained from 48 (out of 50) TTI DNAs of which 47 showed genomic aberrations. The high marker density allowed for single gene analysis, e.g. loss of nine exons in the ATRX gene and the visualization of chromothripsis. Data quality was comparable to fresh or fresh frozen tumor SNP profiles. SNP array results were confirmed by I-FISH. Conclusion TTIs are an excellent source for SNP array processing with the advantage of simple handling, distribution and storage of tumor tissue on glass slides. The minimal amount of tumor tissue needed to analyze whole genomes makes TTIs an economic surrogate source in the molecular diagnostic work up of tumor samples. PMID:27560999

Characterization of genetic variability of Venezuelan equine encephalitis viruses

DOE PAGES

Gardner, Shea N.; McLoughlin, Kevin; Be, Nicholas A.; ...

2016-04-07

Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne alphavirus that has caused large outbreaks of severe illness in both horses and humans. New approaches are needed to rapidly infer the origin of a newly discovered VEEV strain, estimate its equine amplification and resultant epidemic potential, and predict human virulence phenotype. We performed whole genome single nucleotide polymorphism (SNP) analysis of all available VEE antigenic complex genomes, verified that a SNP-based phylogeny accurately captured the features of a phylogenetic tree based on multiple sequence alignment, and developed a high resolution genome-wide SNP microarray. We used the microarray to analyze a broadmore » panel of VEEV isolates, found excellent concordance between array- and sequence-based SNP calls, genotyped unsequenced isolates, and placed them on a phylogeny with sequenced genomes. The microarray successfully genotyped VEEV directly from tissue samples of an infected mouse, bypassing the need for viral isolation, culture and genomic sequencing. Lastly, we identified genomic variants associated with serotypes and host species, revealing a complex relationship between genotype and phenotype.« less

Population structure and genome-wide association analysis for frost tolerance in oat using continuous SNP array signal intensity ratios.

PubMed

Tumino, Giorgio; Voorrips, Roeland E; Rizza, Fulvia; Badeck, Franz W; Morcia, Caterina; Ghizzoni, Roberta; Germeier, Christoph U; Paulo, Maria-João; Terzi, Valeria; Smulders, Marinus J M

2016-09-01

Infinium SNP data analysed as continuous intensity ratios enabled associating genotypic and phenotypic data from heterogeneous oat samples, showing that association mapping for frost tolerance is a feasible option. Oat is sensitive to freezing temperatures, which restricts the cultivation of fall-sown or winter oats to regions with milder winters. Fall-sown oats have a longer growth cycle, mature earlier, and have a higher productivity than spring-sown oats, therefore improving frost tolerance is an important goal in oat breeding. Our aim was to test the effectiveness of a Genome-Wide Association Study (GWAS) for mapping QTLs related to frost tolerance, using an approach that tolerates continuously distributed signals from SNPs in bulked samples from heterogeneous accessions. A collection of 138 European oat accessions, including landraces, old and modern varieties from 27 countries was genotyped using the Infinium 6K SNP array. The SNP data were analyzed as continuous intensity ratios, rather than converting them into discrete values by genotype calling. PCA and Ward's clustering of genetic similarities revealed the presence of two main groups of accessions, which roughly corresponded to Continental Europe and Mediterranean/Atlantic Europe, although a total of eight subgroups can be distinguished. The accessions were phenotyped for frost tolerance under controlled conditions by measuring fluorescence quantum yield of photosystem II after a freezing stress. GWAS were performed by a linear mixed model approach, comparing different corrections for population structure. All models detected three robust QTLs, two of which co-mapped with QTLs identified earlier in bi-parental mapping populations. The approach used in the present work shows that SNP array data of heterogeneous hexaploid oat samples can be successfully used to determine genetic similarities and to map associations to quantitative phenotypic traits.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, Shea; Slezak, Tom

With the flood of whole genome finished and draft microbial sequences, we need faster, more scalable bioinformatics tools for sequence comparison. An algorithm is described to find single nucleotide polymorphisms (SNPs) in whole genome data. It scales to hundreds of bacterial or viral genomes, and can be used for finished and/or draft genomes available as unassembled contigs. The method is fast to compute, finding SNPs and building a SNP phylogeny in seconds to hours. We use it to identify thousands of putative SNPs from all publicly available Filoviridae, Poxviridae, foot-and-mouth disease virus, Bacillus, and Escherichia coli genomes and plasmids. Themore » SNP-based trees that result are consistent with known taxonomy and trees determined in other studies. The approach we describe can handle as input hundreds of gigabases of sequence in a single run. The algorithm is based on k-mer analysis using a suffix array, so we call it saSNP.« less

Mismatch and G-Stack Modulated Probe Signals on SNP Microarrays

PubMed Central

Binder, Hans; Fasold, Mario; Glomb, Torsten

2009-01-01

Background Single nucleotide polymorphism (SNP) arrays are important tools widely used for genotyping and copy number estimation. This technology utilizes the specific affinity of fragmented DNA for binding to surface-attached oligonucleotide DNA probes. We analyze the variability of the probe signals of Affymetrix GeneChip SNP arrays as a function of the probe sequence to identify relevant sequence motifs which potentially cause systematic biases of genotyping and copy number estimates. Methodology/Principal Findings The probe design of GeneChip SNP arrays enables us to disentangle different sources of intensity modulations such as the number of mismatches per duplex, matched and mismatched base pairings including nearest and next-nearest neighbors and their position along the probe sequence. The effect of probe sequence was estimated in terms of triple-motifs with central matches and mismatches which include all 256 combinations of possible base pairings. The probe/target interactions on the chip can be decomposed into nearest neighbor contributions which correlate well with free energy terms of DNA/DNA-interactions in solution. The effect of mismatches is about twice as large as that of canonical pairings. Runs of guanines (G) and the particular type of mismatched pairings formed in cross-allelic probe/target duplexes constitute sources of systematic biases of the probe signals with consequences for genotyping and copy number estimates. The poly-G effect seems to be related to the crowded arrangement of probes which facilitates complex formation of neighboring probes with at minimum three adjacent G's in their sequence. Conclusions The applied method of “triple-averaging” represents a model-free approach to estimate the mean intensity contributions of different sequence motifs which can be applied in calibration algorithms to correct signal values for sequence effects. Rules for appropriate sequence corrections are suggested. PMID:19924253

A Discovery Resource of Rare Copy Number Variations in Individuals with Autism Spectrum Disorder

PubMed Central

Prasad, Aparna; Merico, Daniele; Thiruvahindrapuram, Bhooma; Wei, John; Lionel, Anath C.; Sato, Daisuke; Rickaby, Jessica; Lu, Chao; Szatmari, Peter; Roberts, Wendy; Fernandez, Bridget A.; Marshall, Christian R.; Hatchwell, Eli; Eis, Peggy S.; Scherer, Stephen W.

2012-01-01

The identification of rare inherited and de novo copy number variations (CNVs) in human subjects has proven a productive approach to highlight risk genes for autism spectrum disorder (ASD). A variety of microarrays are available to detect CNVs, including single-nucleotide polymorphism (SNP) arrays and comparative genomic hybridization (CGH) arrays. Here, we examine a cohort of 696 unrelated ASD cases using a high-resolution one-million feature CGH microarray, the majority of which were previously genotyped with SNP arrays. Our objective was to discover new CNVs in ASD cases that were not detected by SNP microarray analysis and to delineate novel ASD risk loci via combined analysis of CGH and SNP array data sets on the ASD cohort and CGH data on an additional 1000 control samples. Of the 615 ASD cases analyzed on both SNP and CGH arrays, we found that 13,572 of 21,346 (64%) of the CNVs were exclusively detected by the CGH array. Several of the CGH-specific CNVs are rare in population frequency and impact previously reported ASD genes (e.g., NRXN1, GRM8, DPYD), as well as novel ASD candidate genes (e.g., CIB2, DAPP1, SAE1), and all were inherited except for a de novo CNV in the GPHN gene. A functional enrichment test of gene-sets in ASD cases over controls revealed nucleotide metabolism as a potential novel pathway involved in ASD, which includes several candidate genes for follow-up (e.g., DPYD, UPB1, UPP1, TYMP). Finally, this extensively phenotyped and genotyped ASD clinical cohort serves as an invaluable resource for the next step of genome sequencing for complete genetic variation detection. PMID:23275889

Evaluation of copy number variation detection for a SNP array platform

PubMed Central

2014-01-01

Background Copy Number Variations (CNVs) are usually inferred from Single Nucleotide Polymorphism (SNP) arrays by use of some software packages based on given algorithms. However, there is no clear understanding of the performance of these software packages; it is therefore difficult to select one or several software packages for CNV detection based on the SNP array platform. We selected four publicly available software packages designed for CNV calling from an Affymetrix SNP array, including Birdsuite, dChip, Genotyping Console (GTC) and PennCNV. The publicly available dataset generated by Array-based Comparative Genomic Hybridization (CGH), with a resolution of 24 million probes per sample, was considered to be the “gold standard”. Compared with the CGH-based dataset, the success rate, average stability rate, sensitivity, consistence and reproducibility of these four software packages were assessed compared with the “gold standard”. Specially, we also compared the efficiency of detecting CNVs simultaneously by two, three and all of the software packages with that by a single software package. Results Simply from the quantity of the detected CNVs, Birdsuite detected the most while GTC detected the least. We found that Birdsuite and dChip had obvious detecting bias. And GTC seemed to be inferior because of the least amount of CNVs it detected. Thereafter we investigated the detection consistency produced by one certain software package and the rest three software suits. We found that the consistency of dChip was the lowest while GTC was the highest. Compared with the CNVs detecting result of CGH, in the matching group, GTC called the most matching CNVs, PennCNV-Affy ranked second. In the non-overlapping group, GTC called the least CNVs. With regards to the reproducibility of CNV calling, larger CNVs were usually replicated better. PennCNV-Affy shows the best consistency while Birdsuite shows the poorest. Conclusion We found that PennCNV outperformed the other three packages in the sensitivity and specificity of CNV calling. Obviously, each calling method had its own limitations and advantages for different data analysis. Therefore, the optimized calling methods might be identified using multiple algorithms to evaluate the concordance and discordance of SNP array-based CNV calling. PMID:24555668

Development and Validation of a High-Density SNP Genotyping Array for African Oil Palm.

PubMed

Kwong, Qi Bin; Teh, Chee Keng; Ong, Ai Ling; Heng, Huey Ying; Lee, Heng Leng; Mohamed, Mohaimi; Low, Joel Zi-Bin; Apparow, Sukganah; Chew, Fook Tim; Mayes, Sean; Kulaveerasingam, Harikrishna; Tammi, Martti; Appleton, David Ross

2016-08-01

High-density single nucleotide polymorphism (SNP) genotyping arrays are powerful tools that can measure the level of genetic polymorphism within a population. To develop a whole-genome SNP array for oil palms, SNP discovery was performed using deep resequencing of eight libraries derived from 132 Elaeis guineensis and Elaeis oleifera palms belonging to 59 origins, resulting in the discovery of >3 million putative SNPs. After SNP filtering, the Illumina OP200K custom array was built with 170 860 successful probes. Phenetic clustering analysis revealed that the array could distinguish between palms of different origins in a way consistent with pedigree records. Genome-wide linkage disequilibrium declined more slowly for the commercial populations (ranging from 120 kb at r(2) = 0.43 to 146 kb at r(2) = 0.50) when compared with the semi-wild populations (19.5 kb at r(2) = 0.22). Genetic fixation mapping comparing the semi-wild and commercial population identified 321 selective sweeps. A genome-wide association study (GWAS) detected a significant peak on chromosome 2 associated with the polygenic component of the shell thickness trait (based on the trait shell-to-fruit; S/F %) in tenera palms. Testing of a genomic selection model on the same trait resulted in good prediction accuracy (r = 0.65) with 42% of the S/F % variation explained. The first high-density SNP genotyping array for oil palm has been developed and shown to be robust for use in genetic studies and with potential for developing early trait prediction to shorten the oil palm breeding cycle. Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

Development of a dense SNP-based linkage map of an apple rootstock progeny using the Malus Infinium whole genome genotyping array

PubMed Central

2012-01-01

Background A whole-genome genotyping array has previously been developed for Malus using SNP data from 28 Malus genotypes. This array offers the prospect of high throughput genotyping and linkage map development for any given Malus progeny. To test the applicability of the array for mapping in diverse Malus genotypes, we applied the array to the construction of a SNP-based linkage map of an apple rootstock progeny. Results Of the 7,867 Malus SNP markers on the array, 1,823 (23.2%) were heterozygous in one of the two parents of the progeny, 1,007 (12.8%) were heterozygous in both parental genotypes, whilst just 2.8% of the 921 Pyrus SNPs were heterozygous. A linkage map spanning 1,282.2 cM was produced comprising 2,272 SNP markers, 306 SSR markers and the S-locus. The length of the M432 linkage map was increased by 52.7 cM with the addition of the SNP markers, whilst marker density increased from 3.8 cM/marker to 0.5 cM/marker. Just three regions in excess of 10 cM remain where no markers were mapped. We compared the positions of the mapped SNP markers on the M432 map with their predicted positions on the ‘Golden Delicious’ genome sequence. A total of 311 markers (13.7% of all mapped markers) mapped to positions that conflicted with their predicted positions on the ‘Golden Delicious’ pseudo-chromosomes, indicating the presence of paralogous genomic regions or mis-assignments of genome sequence contigs during the assembly and anchoring of the genome sequence. Conclusions We incorporated data for the 2,272 SNP markers onto the map of the M432 progeny and have presented the most complete and saturated map of the full 17 linkage groups of M. pumila to date. The data were generated rapidly in a high-throughput semi-automated pipeline, permitting significant savings in time and cost over linkage map construction using microsatellites. The application of the array will permit linkage maps to be developed for QTL analyses in a cost-effective manner, and the identification of SNPs that have been assigned erroneous positions on the ‘Golden Delicious’ reference sequence will assist in the continued improvement of the genome sequence assembly for that variety. PMID:22631220

SNPchiMp v.3: integrating and standardizing single nucleotide polymorphism data for livestock species.

PubMed

Nicolazzi, Ezequiel L; Caprera, Andrea; Nazzicari, Nelson; Cozzi, Paolo; Strozzi, Francesco; Lawley, Cindy; Pirani, Ali; Soans, Chandrasen; Brew, Fiona; Jorjani, Hossein; Evans, Gary; Simpson, Barry; Tosser-Klopp, Gwenola; Brauning, Rudiger; Williams, John L; Stella, Alessandra

2015-04-10

In recent years, the use of genomic information in livestock species for genetic improvement, association studies and many other fields has become routine. In order to accommodate different market requirements in terms of genotyping cost, manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species: ranging from one for goats to more than ten for cattle, and the number of arrays available is increasing rapidly. However, there is limited or no effort to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. past and current assemblies) SNP information. Here we present SNPchiMp v.3, a solution to these issues for the six major livestock species (cow, pig, horse, sheep, goat and chicken). Original data was collected directly from SNP array producers and specific international genome consortia, and stored in a MySQL database. The database was then linked to an open-access web tool and to public databases. SNPchiMp v.3 ensures fast access to the database (retrieving within/across SNP array data) and the possibility of annotating SNP array data in a user-friendly fashion. This platform allows easy integration and standardization, and it is aimed at both industry and research. It also enables users to easily link the information available from the array producer with data in public databases, without the need of additional bioinformatics tools or pipelines. In recognition of the open-access use of Ensembl resources, SNPchiMp v.3 was officially credited as an Ensembl E!mpowered tool. Availability at http://bioinformatics.tecnoparco.org/SNPchimp.

Evaluation of Bovine High-Density SNP Genotyping Array in Indigenous Dairy Cattle Breeds.

PubMed

Dash, S; Singh, A; Bhatia, A K; Jayakumar, S; Sharma, A; Singh, S; Ganguly, I; Dixit, S P

2018-04-03

In total 52 samples of Sahiwal ( 19 ), Tharparkar ( 17 ), and Gir ( 16 ) were genotyped by using BovineHD SNP chip to analyze minor allele frequency (MAF), genetic diversity, and linkage disequilibrium among these cattle. The common SNPs of BovineHD and 54K SNP Chips were also extracted and evaluated for their performance. Only 40%-50% SNPs of these arrays was found informative for genetic analysis in these cattle breeds. The overall mean of MAF for SNPs of BovineHD SNPChip was 0.248 ± 0.006, 0.241 ± 0.007, and 0.242 ± 0.009 in Sahiwal, Tharparkar and Gir, respectively, while that for 54K SNPs was on lower side. The average Reynold's genetic distance between breeds ranged from 0.042 to 0.055 based on BovineHD Beadchip, and from 0.052 to 0.084 based on 54K SNP Chip. The estimates of genetic diversity based on HD and 54K chips were almost same and, hence, low density chip seems to be good enough to decipher genetic diversity of these cattle breeds. The linkage disequilibrium started decaying (r 2  < 0.2) at 140 kb inter-marker distance and, hence, a 20K low density customized SNP array from HD chip could be designed for genomic selection in these cattle else the 54K Bead Chip as such will be useful.

Glossary

MedlinePlus

... array, and oligo/SNP combination array. Related terms: comparative genomic hybridization ; copy number variant ; SNP array chromosome ... for example, the AB blood groups in humans comparative genomic hybridization Method in which two DNA samples ( ...

High-throughput informative single nucleotide polymorphism-based typing of Neisseria gonorrhoeae using the Sequenom MassARRAY iPLEX platform.

PubMed

Trembizki, Ella; Smith, Helen; Lahra, Monica M; Chen, Marcus; Donovan, Basil; Fairley, Christopher K; Guy, Rebecca; Kaldor, John; Regan, David; Ward, James; Nissen, Michael D; Sloots, Theo P; Whiley, David M

2014-06-01

Neisseria gonorrhoeae antimicrobial resistance (AMR) is a global problem heightened by emerging resistance to ceftriaxone. Appropriate molecular typing methods are important for understanding the emergence and spread of N. gonorrhoeae AMR. We report on the development, validation and testing of a Sequenom MassARRAY iPLEX method for multilocus sequence typing (MLST)-style genotyping of N. gonorrhoeae isolates. An iPLEX MassARRAY method (iPLEX14SNP) was developed targeting 14 informative gonococcal single nucleotide polymorphisms (SNPs) previously shown to predict MLST types. The method was initially validated using 24 N. gonorrhoeae control isolates and was then applied to 397 test isolates collected throughout Queensland, Australia in the first half of 2012. The iPLEX14SNP method provided 100% accuracy for the control isolates, correctly identifying all 14 SNPs for all 24 isolates (336/336). For the 397 test isolates, the iPLEX14SNP assigned results for 5461 of the possible 5558 SNPs (SNP call rate 98.25%), with complete 14 SNP profiles obtained for 364 isolates. Based on the complete SNP profile data, there were 49 different sequence types identified in Queensland, with 11 of the 49 SNP profiles accounting for the majority (n = 280; 77%) of isolates. AMR was dominated by several geographically clustered sequence types. Using the iPLEX14SNP method, up to 384 isolates could be tested within 1 working day for less than Aus$10 per isolate. The iPLEX14SNP offers an accurate and high-throughput method for the MLST-style genotyping of N. gonorrhoeae and may prove particularly useful for large-scale studies investigating the emergence and spread of gonococcal AMR. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Development of a Medium Density Combined-Species SNP Array for Pacific and European Oysters (Crassostrea gigas and Ostrea edulis).

PubMed

Gutierrez, Alejandro P; Turner, Frances; Gharbi, Karim; Talbot, Richard; Lowe, Natalie R; Peñaloza, Carolina; McCullough, Mark; Prodöhl, Paulo A; Bean, Tim P; Houston, Ross D

2017-07-05

SNP arrays are enabling tools for high-resolution studies of the genetic basis of complex traits in farmed and wild animals. Oysters are of critical importance in many regions from both an ecological and economic perspective, and oyster aquaculture forms a key component of global food security. The aim of our study was to design a combined-species, medium density SNP array for Pacific oyster ( Crassostrea gigas ) and European flat oyster ( Ostrea edulis ), and to test the performance of this array on farmed and wild populations from multiple locations, with a focus on European populations. SNP discovery was carried out by whole-genome sequencing (WGS) of pooled genomic DNA samples from eight C. gigas populations, and restriction site-associated DNA sequencing (RAD-Seq) of 11 geographically diverse O. edulis populations. Nearly 12 million candidate SNPs were discovered and filtered based on several criteria, including preference for SNPs segregating in multiple populations and SNPs with monomorphic flanking regions. An Affymetrix Axiom Custom Array was created and tested on a diverse set of samples ( n = 219) showing ∼27 K high quality SNPs for C. gigas and ∼11 K high quality SNPs for O. edulis segregating in these populations. A high proportion of SNPs were segregating in each of the populations, and the array was used to detect population structure and levels of linkage disequilibrium (LD). Further testing of the array on three C. gigas nuclear families ( n = 165) revealed that the array can be used to clearly distinguish between both families based on identity-by-state (IBS) clustering parental assignment software. This medium density, combined-species array will be publicly available through Affymetrix, and will be applied for genome-wide association and evolutionary genetic studies, and for genomic selection in oyster breeding programs. Copyright © 2017 Gutierrez et al.

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel.

PubMed

Delaneau, Olivier; Marchini, Jonathan

2014-06-13

A major use of the 1000 Genomes Project (1000 GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000 GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants.

A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array.

PubMed

Unterseer, Sandra; Bauer, Eva; Haberer, Georg; Seidel, Michael; Knaak, Carsten; Ouzunova, Milena; Meitinger, Thomas; Strom, Tim M; Fries, Ruedi; Pausch, Hubert; Bertani, Christofer; Davassi, Alessandro; Mayer, Klaus Fx; Schön, Chris-Carolin

2014-09-29

High density genotyping data are indispensable for genomic analyses of complex traits in animal and crop species. Maize is one of the most important crop plants worldwide, however a high density SNP genotyping array for analysis of its large and highly dynamic genome was not available so far. We developed a high density maize SNP array composed of 616,201 variants (SNPs and small indels). Initially, 57 M variants were discovered by sequencing 30 representative temperate maize lines and then stringently filtered for sequence quality scores and predicted conversion performance on the array resulting in the selection of 1.2 M polymorphic variants assayed on two screening arrays. To identify high-confidence variants, 285 DNA samples from a broad genetic diversity panel of worldwide maize lines including the samples used for sequencing, important founder lines for European maize breeding, hybrids, and proprietary samples with European, US, semi-tropical, and tropical origin were used for experimental validation. We selected 616 k variants according to their performance during validation, support of genotype calls through sequencing data, and physical distribution for further analysis and for the design of the commercially available Affymetrix® Axiom® Maize Genotyping Array. This array is composed of 609,442 SNPs and 6,759 indels. Among these are 116,224 variants in coding regions and 45,655 SNPs of the Illumina® MaizeSNP50 BeadChip for study comparison. In a subset of 45,974 variants, apart from the target SNP additional off-target variants are detected, which show only a minor bias towards intermediate allele frequencies. We performed principal coordinate and admixture analyses to determine the ability of the array to detect and resolve population structure and investigated the extent of LD within a worldwide validation panel. The high density Affymetrix® Axiom® Maize Genotyping Array is optimized for European and American temperate maize and was developed based on a diverse sample panel by applying stringent quality filter criteria to ensure its suitability for a broad range of applications. With 600 k variants it is the largest currently publically available genotyping array in crop species.

SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data.

PubMed

Zhang, Zhongyang; Hao, Ke

2015-11-01

Cancer genomes exhibit profound somatic copy number alterations (SCNAs). Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1) extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample; 2) performing joint segmentation on the two signal dimensions; 3) correcting the copy number baseline from which the SCNA state is determined; 4) calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS) as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity.

SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data

PubMed Central

Zhang, Zhongyang; Hao, Ke

2015-01-01

Cancer genomes exhibit profound somatic copy number alterations (SCNAs). Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1) extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample; 2) performing joint segmentation on the two signal dimensions; 3) correcting the copy number baseline from which the SCNA state is determined; 4) calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS) as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity. PMID:26583378

Genome-Wide Association Mapping of Barley Yellow Dwarf Virus Tolerance in Spring Oat (Avena sativa L.)

PubMed Central

Foresman, Bradley J.; Oliver, Rebekah E.; Jackson, Eric W.; Chao, Shiaoman; Arruda, Marcio P.; Kolb, Frederic L.

2016-01-01

Barley yellow dwarf viruses (BYDVs) are responsible for the disease barley yellow dwarf (BYD) and affect many cereals including oat (Avena sativa L.). Until recently, the molecular marker technology in oat has not allowed for many marker-trait association studies to determine the genetic mechanisms for tolerance. A genome-wide association study (GWAS) was performed on 428 spring oat lines using a recently developed high-density oat single nucleotide polymorphism (SNP) array as well as a SNP-based consensus map. Marker-trait associations were performed using a Q-K mixed model approach to control for population structure and relatedness. Six significant SNP-trait associations representing two QTL were found on chromosomes 3C (Mrg17) and 18D (Mrg04). This is the first report of BYDV tolerance QTL on chromosome 3C (Mrg17) and 18D (Mrg04). Haplotypes using the two QTL were evaluated and distinct classes for tolerance were identified based on the number of favorable alleles. A large number of lines carrying both favorable alleles were observed in the panel. PMID:27175781

MixHMM: Inferring Copy Number Variation and Allelic Imbalance Using SNP Arrays and Tumor Samples Mixed with Stromal Cells

PubMed Central

Schulz, Vincent; Chen, Min; Tuck, David

2010-01-01

Background Genotyping platforms such as single nucleotide polymorphism (SNP) arrays are powerful tools to study genomic aberrations in cancer samples. Allele specific information from SNP arrays provides valuable information for interpreting copy number variation (CNV) and allelic imbalance including loss-of-heterozygosity (LOH) beyond that obtained from the total DNA signal available from array comparative genomic hybridization (aCGH) platforms. Several algorithms based on hidden Markov models (HMMs) have been designed to detect copy number changes and copy-neutral LOH making use of the allele information on SNP arrays. However heterogeneity in clinical samples, due to stromal contamination and somatic alterations, complicates analysis and interpretation of these data. Methods We have developed MixHMM, a novel hidden Markov model using hidden states based on chromosomal structural aberrations. MixHMM allows CNV detection for copy numbers up to 7 and allows more complete and accurate description of other forms of allelic imbalance, such as increased copy number LOH or imbalanced amplifications. MixHMM also incorporates a novel sample mixing model that allows detection of tumor CNV events in heterogeneous tumor samples, where cancer cells are mixed with a proportion of stromal cells. Conclusions We validate MixHMM and demonstrate its advantages with simulated samples, clinical tumor samples and a dilution series of mixed samples. We have shown that the CNVs of cancer cells in a tumor sample contaminated with up to 80% of stromal cells can be detected accurately using Illumina BeadChip and MixHMM. Availability The MixHMM is available as a Python package provided with some other useful tools at http://genecube.med.yale.edu:8080/MixHMM. PMID:20532221

Genetic loci associated with delayed clearance of Plasmodium falciparum following artemisinin treatment in Southeast Asia

DTIC Science & Technology

2013-01-02

intensity data from the SNP array were normalized using the Affymetrix GeneChip Targeted Genotyping Analysis Software ( GTGS ). To assess robustness of SNP...calls, genotypes were called using three algorithms: (i) GTGS , (ii) illuminus (27), and (iii) a heuristic algorithm based on discrete cutoffs of

Elucidation of the ‘Honeycrisp’ pedigree through haplotype analysis with a multi-family integrated SNP linkage map and a large apple (Malus×domestica) pedigree-connected SNP data set

PubMed Central

Howard, Nicholas P; van de Weg, Eric; Bedford, David S; Peace, Cameron P; Vanderzande, Stijn; Clark, Matthew D; Teh, Soon Li; Cai, Lichun; Luby, James J

2017-01-01

The apple (Malus×domestica) cultivar Honeycrisp has become important economically and as a breeding parent. An earlier study with SSR markers indicated the original recorded pedigree of ‘Honeycrisp’ was incorrect and ‘Keepsake’ was identified as one putative parent, the other being unknown. The objective of this study was to verify ‘Keepsake’ as a parent and identify and genetically describe the unknown parent and its grandparents. A multi-family based dense and high-quality integrated SNP map was created using the apple 8 K Illumina Infinium SNP array. This map was used alongside a large pedigree-connected data set from the RosBREED project to build extended SNP haplotypes and to identify pedigree relationships. ‘Keepsake’ was verified as one parent of ‘Honeycrisp’ and ‘Duchess of Oldenburg’ and ‘Golden Delicious’ were identified as grandparents through the unknown parent. Following this finding, siblings of ‘Honeycrisp’ were identified using the SNP data. Breeding records from several of these siblings suggested that the previously unreported parent is a University of Minnesota selection, MN1627. This selection is no longer available, but now is genetically described through imputed SNP haplotypes. We also present the mosaic grandparental composition of ‘Honeycrisp’ for each of its 17 chromosome pairs. This new pedigree and genetic information will be useful in future pedigree-based genetic studies to connect ‘Honeycrisp’ with other cultivars used widely in apple breeding programs. The created SNP linkage map will benefit future research using the data from the Illumina apple 8 and 20 K and Affymetrix 480 K SNP arrays. PMID:28243452

Single nucleotide polymorphism array karyotyping: a diagnostic and prognostic tool in myelodysplastic syndromes with unsuccessful conventional cytogenetic testing.

PubMed

Arenillas, Leonor; Mallo, Mar; Ramos, Fernando; Guinta, Kathryn; Barragán, Eva; Lumbreras, Eva; Larráyoz, María-José; De Paz, Raquel; Tormo, Mar; Abáigar, María; Pedro, Carme; Cervera, José; Such, Esperanza; José Calasanz, María; Díez-Campelo, María; Sanz, Guillermo F; Hernández, Jesús María; Luño, Elisa; Saumell, Sílvia; Maciejewski, Jaroslaw; Florensa, Lourdes; Solé, Francesc

2013-12-01

Cytogenetic aberrations identified by metaphase cytogenetics (MC) have diagnostic, prognostic, and therapeutic implications in myelodysplastic syndromes (MDS). However, in some MDS patients MC study is unsuccesful. Single nucleotide polymorphism array (SNP-A) based karyotyping could be helpful in these cases. We performed SNP-A in 62 samples from bone marrow or peripheral blood of primary MDS with an unsuccessful MC study. SNP-A analysis enabled the detection of aberrations in 31 (50%) patients. We used the copy number alteration information to apply the International Prognostic Scoring System (IPSS) and we observed differences in survival between the low/intermediate-1 and intermediate-2/high risk patients. We also saw differences in survival between very low/low/intermediate and the high/very high patients when we applied the revised IPSS (IPSS-R). In conclusion, SNP-A can be used successfully in PB samples and the identification of CNA by SNP-A improve the diagnostic and prognostic evaluation of this group of MDS patients. Copyright © 2013 Wiley Periodicals, Inc.

R classes and methods for SNP array data.

PubMed

Scharpf, Robert B; Ruczinski, Ingo

2010-01-01

The Bioconductor project is an "open source and open development software project for the analysis and comprehension of genomic data" (1), primarily based on the R programming language. Infrastructure packages, such as Biobase, are maintained by Bioconductor core developers and serve several key roles to the broader community of Bioconductor software developers and users. In particular, Biobase introduces an S4 class, the eSet, for high-dimensional assay data. Encapsulating the assay data as well as meta-data on the samples, features, and experiment in the eSet class definition ensures propagation of the relevant sample and feature meta-data throughout an analysis. Extending the eSet class promotes code reuse through inheritance as well as interoperability with other R packages and is less error-prone. Recently proposed class definitions for high-throughput SNP arrays extend the eSet class. This chapter highlights the advantages of adopting and extending Biobase class definitions through a working example of one implementation of classes for the analysis of high-throughput SNP arrays.

Using RNA-Seq to assemble a rose transcriptome with more than 13,000 full-length expressed genes and to develop the WagRhSNP 68k Axiom SNP array for rose (Rosa L.).

PubMed

Koning-Boucoiran, Carole F S; Esselink, G Danny; Vukosavljev, Mirjana; van 't Westende, Wendy P C; Gitonga, Virginia W; Krens, Frans A; Voorrips, Roeland E; van de Weg, W Eric; Schulz, Dietmar; Debener, Thomas; Maliepaard, Chris; Arens, Paul; Smulders, Marinus J M

2015-01-01

In order to develop a versatile and large SNP array for rose, we set out to mine ESTs from diverse sets of rose germplasm. For this RNA-Seq libraries containing about 700 million reads were generated from tetraploid cut and garden roses using Illumina paired-end sequencing, and from diploid Rosa multiflora using 454 sequencing. Separate de novo assemblies were performed in order to identify single nucleotide polymorphisms (SNPs) within and between rose varieties. SNPs among tetraploid roses were selected for constructing a genotyping array that can be employed for genetic mapping and marker-trait association discovery in breeding programs based on tetraploid germplasm, both from cut roses and from garden roses. In total 68,893 SNPs were included on the WagRhSNP Axiom array. Next, an orthology-guided assembly was performed for the construction of a non-redundant rose transcriptome database. A total of 21,740 transcripts had significant hits with orthologous genes in the strawberry (Fragaria vesca L.) genome. Of these 13,390 appeared to contain the full-length coding regions. This newly established transcriptome resource adds considerably to the currently available sequence resources for the Rosaceae family in general and the genus Rosa in particular.

[Prenatal genetic diagnosis for a fetus with atypical neurofibromatosis type 1 microdeletion].

PubMed

Lin, Shaobin; Wu, Jianzhu; Zhang, Zhiqiang; Ji, Yuanjun; Fang, Qun; Chen, Baojiang; Luo, Yanmin

2016-04-01

To analyze the correlation between atypical neurofibromatosis type 1(NF1) microdeletion and fetal phenotype. Fetal blood sampling was carried out for a woman bearing a fetus with talipes equinovarus. G-banded karyotyping and single nucleotide polymorphism array (SNP-array) were performed on the fetal blood sample. Fluorescence in situ hybridization (FISH) was used to confirm the result of SNP array analysis. FISH assay was also carried out on peripheral blood specimens from the parents to ascertain the origin of mutation. The karyotype of fetus was found to be 46, XY by G-banding analysis. However, a 3.132 Mb microdeletion was detected in chromosome region 17q11.2 by SNP array, which overlaped with the region of NF1 microdeletion syndrome. Analyzing of the specimens from the fetus and its parents with FISH has confirmed it to be a de novo deletion. Talipes equinovarus may be an abnormal sonographic feature of fetus with atypical NF1 microdeletion which can be accurately diagnosed with SNP array.

Haplotype-Based Genotyping in Polyploids.

PubMed

Clevenger, Josh P; Korani, Walid; Ozias-Akins, Peggy; Jackson, Scott

2018-01-01

Accurate identification of polymorphisms from sequence data is crucial to unlocking the potential of high throughput sequencing for genomics. Single nucleotide polymorphisms (SNPs) are difficult to accurately identify in polyploid crops due to the duplicative nature of polyploid genomes leading to low confidence in the true alignment of short reads. Implementing a haplotype-based method in contrasting subgenome-specific sequences leads to higher accuracy of SNP identification in polyploids. To test this method, a large-scale 48K SNP array (Axiom Arachis2) was developed for Arachis hypogaea (peanut), an allotetraploid, in which 1,674 haplotype-based SNPs were included. Results of the array show that 74% of the haplotype-based SNP markers could be validated, which is considerably higher than previous methods used for peanut. The haplotype method has been implemented in a standalone program, HAPLOSWEEP, which takes as input bam files and a vcf file and identifies haplotype-based markers. Haplotype discovery can be made within single reads or span paired reads, and can leverage long read technology by targeting any length of haplotype. Haplotype-based genotyping is applicable in all allopolyploid genomes and provides confidence in marker identification and in silico-based genotyping for polyploid genomics.

Development and validation of a high density SNP genotyping array for Atlantic salmon (Salmo salar).

PubMed

Houston, Ross D; Taggart, John B; Cézard, Timothé; Bekaert, Michaël; Lowe, Natalie R; Downing, Alison; Talbot, Richard; Bishop, Stephen C; Archibald, Alan L; Bron, James E; Penman, David J; Davassi, Alessandro; Brew, Fiona; Tinch, Alan E; Gharbi, Karim; Hamilton, Alastair

2014-02-06

Dense single nucleotide polymorphism (SNP) genotyping arrays provide extensive information on polymorphic variation across the genome of species of interest. Such information can be used in studies of the genetic architecture of quantitative traits and to improve the accuracy of selection in breeding programs. In Atlantic salmon (Salmo salar), these goals are currently hampered by the lack of a high-density SNP genotyping platform. Therefore, the aim of the study was to develop and test a dense Atlantic salmon SNP array. SNP discovery was performed using extensive deep sequencing of Reduced Representation (RR-Seq), Restriction site-Associated DNA (RAD-Seq) and mRNA (RNA-Seq) libraries derived from farmed and wild Atlantic salmon samples (n = 283) resulting in the discovery of > 400 K putative SNPs. An Affymetrix Axiom® myDesign Custom Array was created and tested on samples of animals of wild and farmed origin (n = 96) revealing a total of 132,033 polymorphic SNPs with high call rate, good cluster separation on the array and stable Mendelian inheritance in our sample. At least 38% of these SNPs are from transcribed genomic regions and therefore more likely to include functional variants. Linkage analysis utilising the lack of male recombination in salmonids allowed the mapping of 40,214 SNPs distributed across all 29 pairs of chromosomes, highlighting the extensive genome-wide coverage of the SNPs. An identity-by-state clustering analysis revealed that the array can clearly distinguish between fish of different origins, within and between farmed and wild populations. Finally, Y-chromosome-specific probes included on the array provide an accurate molecular genetic test for sex. This manuscript describes the first high-density SNP genotyping array for Atlantic salmon. This array will be publicly available and is likely to be used as a platform for high-resolution genetics research into traits of evolutionary and economic importance in salmonids and in aquaculture breeding programs via genomic selection.

Development and validation of a high density SNP genotyping array for Atlantic salmon (Salmo salar)

PubMed Central

2014-01-01

Background Dense single nucleotide polymorphism (SNP) genotyping arrays provide extensive information on polymorphic variation across the genome of species of interest. Such information can be used in studies of the genetic architecture of quantitative traits and to improve the accuracy of selection in breeding programs. In Atlantic salmon (Salmo salar), these goals are currently hampered by the lack of a high-density SNP genotyping platform. Therefore, the aim of the study was to develop and test a dense Atlantic salmon SNP array. Results SNP discovery was performed using extensive deep sequencing of Reduced Representation (RR-Seq), Restriction site-Associated DNA (RAD-Seq) and mRNA (RNA-Seq) libraries derived from farmed and wild Atlantic salmon samples (n = 283) resulting in the discovery of > 400 K putative SNPs. An Affymetrix Axiom® myDesign Custom Array was created and tested on samples of animals of wild and farmed origin (n = 96) revealing a total of 132,033 polymorphic SNPs with high call rate, good cluster separation on the array and stable Mendelian inheritance in our sample. At least 38% of these SNPs are from transcribed genomic regions and therefore more likely to include functional variants. Linkage analysis utilising the lack of male recombination in salmonids allowed the mapping of 40,214 SNPs distributed across all 29 pairs of chromosomes, highlighting the extensive genome-wide coverage of the SNPs. An identity-by-state clustering analysis revealed that the array can clearly distinguish between fish of different origins, within and between farmed and wild populations. Finally, Y-chromosome-specific probes included on the array provide an accurate molecular genetic test for sex. Conclusions This manuscript describes the first high-density SNP genotyping array for Atlantic salmon. This array will be publicly available and is likely to be used as a platform for high-resolution genetics research into traits of evolutionary and economic importance in salmonids and in aquaculture breeding programs via genomic selection. PMID:24524230

Detection of clonal evolution in hematopoietic malignancies by combining comparative genomic hybridization and single nucleotide polymorphism arrays.

PubMed

Hartmann, Luise; Stephenson, Christine F; Verkamp, Stephanie R; Johnson, Krystal R; Burnworth, Bettina; Hammock, Kelle; Brodersen, Lisa Eidenschink; de Baca, Monica E; Wells, Denise A; Loken, Michael R; Zehentner, Barbara K

2014-12-01

Array comparative genomic hybridization (aCGH) has become a powerful tool for analyzing hematopoietic neoplasms and identifying genome-wide copy number changes in a single assay. aCGH also has superior resolution compared with fluorescence in situ hybridization (FISH) or conventional cytogenetics. Integration of single nucleotide polymorphism (SNP) probes with microarray analysis allows additional identification of acquired uniparental disomy, a copy neutral aberration with known potential to contribute to tumor pathogenesis. However, a limitation of microarray analysis has been the inability to detect clonal heterogeneity in a sample. This study comprised 16 samples (acute myeloid leukemia, myelodysplastic syndrome, chronic lymphocytic leukemia, plasma cell neoplasm) with complex cytogenetic features and evidence of clonal evolution. We used an integrated manual peak reassignment approach combining analysis of aCGH and SNP microarray data for characterization of subclonal abnormalities. We compared array findings with results obtained from conventional cytogenetic and FISH studies. Clonal heterogeneity was detected in 13 of 16 samples by microarray on the basis of log2 values. Use of the manual peak reassignment analysis approach improved resolution of the sample's clonal composition and genetic heterogeneity in 10 of 13 (77%) patients. Moreover, in 3 patients, clonal disease progression was revealed by array analysis that was not evident by cytogenetic or FISH studies. Genetic abnormalities originating from separate clonal subpopulations can be identified and further characterized by combining aCGH and SNP hybridization results from 1 integrated microarray chip by use of the manual peak reassignment technique. Its clinical utility in comparison to conventional cytogenetic or FISH studies is demonstrated. © 2014 American Association for Clinical Chemistry.

Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan

PubMed Central

Ting, Jason C; Ye, Ying; Thomas, George H; Ruczinski, Ingo; Pevsner, Jonathan

2006-01-01

Background A variety of diseases are caused by chromosomal abnormalities such as aneuploidies (having an abnormal number of chromosomes), microdeletions, microduplications, and uniparental disomy. High density single nucleotide polymorphism (SNP) microarrays provide information on chromosomal copy number changes, as well as genotype (heterozygosity and homozygosity). SNP array studies generate multiple types of data for each SNP site, some with more than 100,000 SNPs represented on each array. The identification of different classes of anomalies within SNP data has been challenging. Results We have developed SNPscan, a web-accessible tool to analyze and visualize high density SNP data. It enables researchers (1) to visually and quantitatively assess the quality of user-generated SNP data relative to a benchmark data set derived from a control population, (2) to display SNP intensity and allelic call data in order to detect chromosomal copy number anomalies (duplications and deletions), (3) to display uniparental isodisomy based on loss of heterozygosity (LOH) across genomic regions, (4) to compare paired samples (e.g. tumor and normal), and (5) to generate a file type for viewing SNP data in the University of California, Santa Cruz (UCSC) Human Genome Browser. SNPscan accepts data exported from Affymetrix Copy Number Analysis Tool as its input. We validated SNPscan using data generated from patients with known deletions, duplications, and uniparental disomy. We also inspected previously generated SNP data from 90 apparently normal individuals from the Centre d'Étude du Polymorphisme Humain (CEPH) collection, and identified three cases of uniparental isodisomy, four females having an apparently mosaic X chromosome, two mislabelled SNP data sets, and one microdeletion on chromosome 2 with mosaicism from an apparently normal female. These previously unrecognized abnormalities were all detected using SNPscan. The microdeletion was independently confirmed by fluorescence in situ hybridization, and a region of homozygosity in a UPD case was confirmed by sequencing of genomic DNA. Conclusion SNPscan is useful to identify chromosomal abnormalities based on SNP intensity (such as chromosomal copy number changes) and heterozygosity data (including regions of LOH and some cases of UPD). The program and source code are available at the SNPscan website . PMID:16420694

Exploiting sequence similarity to validate the sensitivity of SNP arrays in detecting fine-scaled copy number variations.

PubMed

Wong, Gerard; Leckie, Christopher; Gorringe, Kylie L; Haviv, Izhak; Campbell, Ian G; Kowalczyk, Adam

2010-04-15

High-density single nucleotide polymorphism (SNP) genotyping arrays are efficient and cost effective platforms for the detection of copy number variation (CNV). To ensure accuracy in probe synthesis and to minimize production costs, short oligonucleotide probe sequences are used. The use of short probe sequences limits the specificity of binding targets in the human genome. The specificity of these short probeset sequences has yet to be fully analysed against a normal reference human genome. Sequence similarity can artificially elevate or suppress copy number measurements, and hence reduce the reliability of affected probe readings. For the purpose of detecting narrow CNVs reliably down to the width of a single probeset, sequence similarity is an important issue that needs to be addressed. We surveyed the Affymetrix Human Mapping SNP arrays for probeset sequence similarity against the reference human genome. Utilizing sequence similarity results, we identified a collection of fine-scaled putative CNVs between gender from autosomal probesets whose sequence matches various loci on the sex chromosomes. To detect these variations, we utilized our statistical approach, Detecting REcurrent Copy number change using rank-order Statistics (DRECS), and showed that its performance was superior and more stable than the t-test in detecting CNVs. Through the application of DRECS on the HapMap population datasets with multi-matching probesets filtered, we identified biologically relevant SNPs in aberrant regions across populations with known association to physical traits, such as height, covered by the span of a single probe. This provided empirical confirmation of the existence of naturally occurring narrow CNVs as well as the sensitivity of the Affymetrix SNP array technology in detecting them. The MATLAB implementation of DRECS is available at http://ww2.cs.mu.oz.au/ approximately gwong/DRECS/index.html.

FSR: feature set reduction for scalable and accurate multi-class cancer subtype classification based on copy number.

PubMed

Wong, Gerard; Leckie, Christopher; Kowalczyk, Adam

2012-01-15

Feature selection is a key concept in machine learning for microarray datasets, where features represented by probesets are typically several orders of magnitude larger than the available sample size. Computational tractability is a key challenge for feature selection algorithms in handling very high-dimensional datasets beyond a hundred thousand features, such as in datasets produced on single nucleotide polymorphism microarrays. In this article, we present a novel feature set reduction approach that enables scalable feature selection on datasets with hundreds of thousands of features and beyond. Our approach enables more efficient handling of higher resolution datasets to achieve better disease subtype classification of samples for potentially more accurate diagnosis and prognosis, which allows clinicians to make more informed decisions in regards to patient treatment options. We applied our feature set reduction approach to several publicly available cancer single nucleotide polymorphism (SNP) array datasets and evaluated its performance in terms of its multiclass predictive classification accuracy over different cancer subtypes, its speedup in execution as well as its scalability with respect to sample size and array resolution. Feature Set Reduction (FSR) was able to reduce the dimensions of an SNP array dataset by more than two orders of magnitude while achieving at least equal, and in most cases superior predictive classification performance over that achieved on features selected by existing feature selection methods alone. An examination of the biological relevance of frequently selected features from FSR-reduced feature sets revealed strong enrichment in association with cancer. FSR was implemented in MATLAB R2010b and is available at http://ww2.cs.mu.oz.au/~gwong/FSR.

Noninvasive Prenatal Paternity Testing (NIPAT) through Maternal Plasma DNA Sequencing: A Pilot Study.

PubMed

Jiang, Haojun; Xie, Yifan; Li, Xuchao; Ge, Huijuan; Deng, Yongqiang; Mu, Haofang; Feng, Xiaoli; Yin, Lu; Du, Zhou; Chen, Fang; He, Nongyue

2016-01-01

Short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs) have been already used to perform noninvasive prenatal paternity testing from maternal plasma DNA. The frequently used technologies were PCR followed by capillary electrophoresis and SNP typing array, respectively. Here, we developed a noninvasive prenatal paternity testing (NIPAT) based on SNP typing with maternal plasma DNA sequencing. We evaluated the influence factors (minor allele frequency (MAF), the number of total SNP, fetal fraction and effective sequencing depth) and designed three different selective SNP panels in order to verify the performance in clinical cases. Combining targeted deep sequencing of selective SNP and informative bioinformatics pipeline, we calculated the combined paternity index (CPI) of 17 cases to determine paternity. Sequencing-based NIPAT results fully agreed with invasive prenatal paternity test using STR multiplex system. Our study here proved that the maternal plasma DNA sequencing-based technology is feasible and accurate in determining paternity, which may provide an alternative in forensic application in the future.

A girl with incomplete Prader-Willi syndrome and negative MS-PCR, found to have mosaic maternal UPD-15 at SNP array.

PubMed

Morandi, Anita; Bonnefond, Amélie; Lobbens, Stéphane; Carotenuto, Marco; Del Giudice, Emanuele Miraglia; Froguel, Philippe; Maffeis, Claudio

2015-11-01

The Prader-Willi syndrome (PWS) is caused by lack of expression of paternal allele of the 15q11.2-q13 region, due to deletions at paternal 15q11.2-q13 (<70%), maternal uniparental disomy of chromosome 15 (mat-UPD 15) (30%) or imprinting defects (1%). Hyperphagia, intellectual disabilities/behavioral disorders, neonatal hypotonia, and hypogonadism are cardinal features for PWS. Methylation sensitive PCR (MS-PCR) of the SNRPN locus, which assesses the presence of both the unmethylated (paternal) and the methylated (maternal) allele of 15q11.2-q13, is considered a sensitive reference technique for PWS diagnosis regardless of genetic subtype. We describe a 17-year-old girl with severe obesity, short stature, and intellectual disability, without hypogonadism and history of neonatal hypotonia, who was suspected to have an incomplete PWS. The MS-PCR showed a normal pattern with similar maternal and paternal electrophoretic bands. Afterwards, a SNP array showed the presence of iso-UPD 15, that is, UPD15 with two copies of the same chromosome 15, in about 50% of cells, suggesting a diagnosis of partial PWS due to mosaic maternal iso-UPD15 arisen as rescue of a post-fertilization error. A quantitative methylation analysis confirmed the presence of mosaic UPD15 in about 50% of cells. We propose that complete clinical criteria for PWS and MS-PCR should not be considered sensitive in suspecting and diagnosing partial PWS due to mosaic UPD15. In contrast, clinical suspicion based on less restrictive criteria followed by SNP array is a more powerful approach to diagnose atypical PWS due to UPD15 mosaicism. © 2015 Wiley Periodicals, Inc.

Whole-genome sequence-based genomic prediction in laying chickens with different genomic relationship matrices to account for genetic architecture.

PubMed

Ni, Guiyan; Cavero, David; Fangmann, Anna; Erbe, Malena; Simianer, Henner

2017-01-16

With the availability of next-generation sequencing technologies, genomic prediction based on whole-genome sequencing (WGS) data is now feasible in animal breeding schemes and was expected to lead to higher predictive ability, since such data may contain all genomic variants including causal mutations. Our objective was to compare prediction ability with high-density (HD) array data and WGS data in a commercial brown layer line with genomic best linear unbiased prediction (GBLUP) models using various approaches to weight single nucleotide polymorphisms (SNPs). A total of 892 chickens from a commercial brown layer line were genotyped with 336 K segregating SNPs (array data) that included 157 K genic SNPs (i.e. SNPs in or around a gene). For these individuals, genome-wide sequence information was imputed based on data from re-sequencing runs of 25 individuals, leading to 5.2 million (M) imputed SNPs (WGS data), including 2.6 M genic SNPs. De-regressed proofs (DRP) for eggshell strength, feed intake and laying rate were used as quasi-phenotypic data in genomic prediction analyses. Four weighting factors for building a trait-specific genomic relationship matrix were investigated: identical weights, -(log 10 P) from genome-wide association study results, squares of SNP effects from random regression BLUP, and variable selection based weights (known as BLUP|GA). Predictive ability was measured as the correlation between DRP and direct genomic breeding values in five replications of a fivefold cross-validation. Averaged over the three traits, the highest predictive ability (0.366 ± 0.075) was obtained when only genic SNPs from WGS data were used. Predictive abilities with genic SNPs and all SNPs from HD array data were 0.361 ± 0.072 and 0.353 ± 0.074, respectively. Prediction with -(log 10 P) or squares of SNP effects as weighting factors for building a genomic relationship matrix or BLUP|GA did not increase accuracy, compared to that with identical weights, regardless of the SNP set used. Our results show that little or no benefit was gained when using all imputed WGS data to perform genomic prediction compared to using HD array data regardless of the weighting factors tested. However, using only genic SNPs from WGS data had a positive effect on prediction ability.

Making a chocolate chip: development and evaluation of a 6K SNP array for Theobroma cacao

PubMed Central

Livingstone, Donald; Royaert, Stefan; Stack, Conrad; Mockaitis, Keithanne; May, Greg; Farmer, Andrew; Saski, Christopher; Schnell, Ray; Kuhn, David; Motamayor, Juan Carlos

2015-01-01

Theobroma cacao, the key ingredient in chocolate production, is one of the world's most important tree fruit crops, with ∼4,000,000 metric tons produced across 50 countries. To move towards gene discovery and marker-assisted breeding in cacao, a single-nucleotide polymorphism (SNP) identification project was undertaken using RNAseq data from 16 diverse cacao cultivars. RNA sequences were aligned to the assembled transcriptome of the cultivar Matina 1-6, and 330,000 SNPs within coding regions were identified. From these SNPs, a subset of 6,000 high-quality SNPs were selected for inclusion on an Illumina Infinium SNP array: the Cacao6kSNP array. Using Cacao6KSNP array data from over 1,000 cacao samples, we demonstrate that our custom array produces a saturated genetic map and can be used to distinguish among even closely related genotypes. Our study enhances and expands the genetic resources available to the cacao research community, and provides the genome-scale set of tools that are critical for advancing breeding with molecular markers in an agricultural species with high genetic diversity. PMID:26070980

Discovery of 100K SNP array and its utilization in sugarcane

USDA-ARS?s Scientific Manuscript database

Next generation sequencing (NGS) enable us to identify thousands of single nucleotide polymorphisms (SNPs) marker for genotyping and fingerprinting. However, the process requires very precise bioinformatics analysis and filtering process. High throughput SNP array with predefined genomic location co...

Development of a 63K SNP Array for Cotton and High-Density Mapping of Intraspecific and Interspecific Populations of Gossypium spp.

PubMed Central

Hulse-Kemp, Amanda M.; Lemm, Jana; Plieske, Joerg; Ashrafi, Hamid; Buyyarapu, Ramesh; Fang, David D.; Frelichowski, James; Giband, Marc; Hague, Steve; Hinze, Lori L.; Kochan, Kelli J.; Riggs, Penny K.; Scheffler, Jodi A.; Udall, Joshua A.; Ulloa, Mauricio; Wang, Shirley S.; Zhu, Qian-Hao; Bag, Sumit K.; Bhardwaj, Archana; Burke, John J.; Byers, Robert L.; Claverie, Michel; Gore, Michael A.; Harker, David B.; Islam, Md S.; Jenkins, Johnie N.; Jones, Don C.; Lacape, Jean-Marc; Llewellyn, Danny J.; Percy, Richard G.; Pepper, Alan E.; Poland, Jesse A.; Mohan Rai, Krishan; Sawant, Samir V.; Singh, Sunil Kumar; Spriggs, Andrew; Taylor, Jen M.; Wang, Fei; Yourstone, Scott M.; Zheng, Xiuting; Lawley, Cindy T.; Ganal, Martin W.; Van Deynze, Allen; Wilson, Iain W.; Stelly, David M.

2015-01-01

High-throughput genotyping arrays provide a standardized resource for plant breeding communities that are useful for a breadth of applications including high-density genetic mapping, genome-wide association studies (GWAS), genomic selection (GS), complex trait dissection, and studying patterns of genomic diversity among cultivars and wild accessions. We have developed the CottonSNP63K, an Illumina Infinium array containing assays for 45,104 putative intraspecific single nucleotide polymorphism (SNP) markers for use within the cultivated cotton species Gossypium hirsutum L. and 17,954 putative interspecific SNP markers for use with crosses of other cotton species with G. hirsutum. The SNPs on the array were developed from 13 different discovery sets that represent a diverse range of G. hirsutum germplasm and five other species: G. barbadense L., G. tomentosum Nuttal × Seemann, G. mustelinum Miers × Watt, G. armourianum Kearny, and G. longicalyx J.B. Hutchinson and Lee. The array was validated with 1,156 samples to generate cluster positions to facilitate automated analysis of 38,822 polymorphic markers. Two high-density genetic maps containing a total of 22,829 SNPs were generated for two F2 mapping populations, one intraspecific and one interspecific, and 3,533 SNP markers were co-occurring in both maps. The produced intraspecific genetic map is the first saturated map that associates into 26 linkage groups corresponding to the number of cotton chromosomes for a cross between two G. hirsutum lines. The linkage maps were shown to have high levels of collinearity to the JGI G. raimondii Ulbrich reference genome sequence. The CottonSNP63K array, cluster file and associated marker sequences constitute a major new resource for the global cotton research community. PMID:25908569

SNP-array reveals genome-wide patterns of geographical and potential adaptive divergence across the natural range of Atlantic salmon (Salmo salar).

PubMed

Bourret, Vincent; Kent, Matthew P; Primmer, Craig R; Vasemägi, Anti; Karlsson, Sten; Hindar, Kjetil; McGinnity, Philip; Verspoor, Eric; Bernatchez, Louis; Lien, Sigbjørn

2013-02-01

Atlantic salmon (Salmo salar) is one of the most extensively studied fish species in the world due to its significance in aquaculture, fisheries and ongoing conservation efforts to protect declining populations. Yet, limited genomic resources have hampered our understanding of genetic architecture in the species and the genetic basis of adaptation to the wide range of natural and artificial environments it occupies. In this study, we describe the development of a medium-density Atlantic salmon single nucleotide polymorphism (SNP) array based on expressed sequence tags (ESTs) and genomic sequencing. The array was used in the most extensive assessment of population genetic structure performed to date in this species. A total of 6176 informative SNPs were successfully genotyped in 38 anadromous and freshwater wild populations distributed across the species natural range. Principal component analysis clearly differentiated European and North American populations, and within Europe, three major regional genetic groups were identified for the first time in a single analysis. We assessed the potential for the array to disentangle neutral and putative adaptive divergence of SNP allele frequencies across populations and among regional groups. In Europe, secondary contact zones were identified between major clusters where endogenous and exogenous barriers could be associated, rendering the interpretation of environmental influence on potentially adaptive divergence equivocal. A small number of markers highly divergent in allele frequencies (outliers) were observed between (multiple) freshwater and anadromous populations, between northern and southern latitudes, and when comparing Baltic populations to all others. We also discuss the potential future applications of the SNP array for conservation, management and aquaculture. © 2012 Blackwell Publishing Ltd.

[Genetic analysis of two cases with Dandy-Walker deformed fetus].

PubMed

Yao, Juan; Fang, Rong; Shen, Xueping; Shen, Guosong; Zhang, Su

2017-10-10

To explore the genetic etiology of two fetuses with Dandy-Walker malformation using single nucleotide polymorphism microarray (SNP-array). The fetuses and their parents were subjected to G banding karyotype analysis. The fetuses were also subjected to SNP-array analysis. The parents of both fetuses showed a normal karyotype. One fetus has a 46,X,?i(X)(q10), while for another conventional cell culture has failed. SNP-array showed that one fetus carried a 6p25.3p25.2 microdeletion, and another carried a Xp22.33p22.2 deletion and a Yq11.221q11 duplication. The abnormal fragments have involved FOXC1, SHOX and STS genes, which are associated with Dandy-Walker malformation. Alteration of 6p25.3p25.2, Xp22.33p22.2 copy numbers probably underlies the Dandy-Walker syndrome in the fetuses. The disorder may be attributed to abnormal expression of FOXC1, SHOX, and STS genes. SNP-array can provide an important supplement for prenatal diagnosis.

Automated SNP detection from a large collection of white spruce expressed sequences: contributing factors and approaches for the categorization of SNPs

PubMed Central

Pavy, Nathalie; Parsons, Lee S; Paule, Charles; MacKay, John; Bousquet, Jean

2006-01-01

Background High-throughput genotyping technologies represent a highly efficient way to accelerate genetic mapping and enable association studies. As a first step toward this goal, we aimed to develop a resource of candidate Single Nucleotide Polymorphisms (SNP) in white spruce (Picea glauca [Moench] Voss), a softwood tree of major economic importance. Results A white spruce SNP resource encompassing 12,264 SNPs was constructed from a set of 6,459 contigs derived from Expressed Sequence Tags (EST) and by using the bayesian-based statistical software PolyBayes. Several parameters influencing the SNP prediction were analysed including the a priori expected polymorphism, the probability score (PSNP), and the contig depth and length. SNP detection in 3' and 5' reads from the same clones revealed a level of inconsistency between overlapping sequences as low as 1%. A subset of 245 predicted SNPs were verified through the independent resequencing of genomic DNA of a genotype also used to prepare cDNA libraries. The validation rate reached a maximum of 85% for SNPs predicted with either PSNP ≥ 0.95 or ≥ 0.99. A total of 9,310 SNPs were detected by using PSNP ≥ 0.95 as a criterion. The SNPs were distributed among 3,590 contigs encompassing an array of broad functional categories, with an overall frequency of 1 SNP per 700 nucleotide sites. Experimental and statistical approaches were used to evaluate the proportion of paralogous SNPs, with estimates in the range of 8 to 12%. The 3,789 coding SNPs identified through coding region annotation and ORF prediction, were distributed into 39% nonsynonymous and 61% synonymous substitutions. Overall, there were 0.9 SNP per 1,000 nonsynonymous sites and 5.2 SNPs per 1,000 synonymous sites, for a genome-wide nonsynonymous to synonymous substitution rate ratio (Ka/Ks) of 0.17. Conclusion We integrated the SNP data in the ForestTreeDB database along with functional annotations to provide a tool facilitating the choice of candidate genes for mapping purposes or association studies. PMID:16824208

Association, effects and validation of polymorphisms within the NCAPG - LCORL locus located on BTA6 with feed intake, gain, meat and carcass traits in beef cattle

USDA-ARS?s Scientific Manuscript database

Background: In a previously reported genome-wide association study based on a high-density bovine SNP genotyping array, 8 SNP were nominally associated (P

Optimal design of low-density SNP arrays for genomic prediction: algorithm and applications

USDA-ARS?s Scientific Manuscript database

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for their optimal design. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optim...

Comparative genome-wide mapping versus extreme pool-genotyping and development of diagnostic SNP markers linked to QTL for adult plant resistance to stripe rust in common wheat.

PubMed

Wu, Jianhui; Huang, Shuo; Zeng, Qingdong; Liu, Shengjie; Wang, Qilin; Mu, Jingmei; Yu, Shizhou; Han, Dejun; Kang, Zhensheng

2018-06-16

A major stripe rust resistance QTL on chromosome 4BL was localized to a 4.5-Mb interval using comparative QTL mapping methods and validated in 276 wheat genotypes by haplotype analysis. CYMMIT-derived wheat line P10103 was previously identified to have adult plant resistance (APR) to stripe rust in the greenhouse and field. The conventional approach for QTL mapping in common wheat is laborious. Here, we performed QTL detection of APR using a combination of genome-wide scanning and extreme pool-genotyping. SNP-based genetic maps were constructed using the Wheat55 K SNP array to genotype a recombinant inbred line (RIL) population derived from the cross Mingxian 169 × P10103. Five stable QTL were detected across multiple environments. A fter comparing SNP profiles from contrasting, extreme DNA pools of RILs six putative QTL were located to approximate chromosome positions. A major QTL on chromosome 4B was identified in F 2:4 contrasting pools from cross Zhengmai 9023 × P10103. A consensus QTL (LOD = 26-40, PVE = 42-55%), named QYr.nwafu-4BL, was defined and localized to a 4.5-Mb interval flanked by SNP markers AX-110963704 and AX-110519862 in chromosome arm 4BL. Based on stripe rust response, marker genotypes, pedigree analysis and mapping data, QYr.nwafu-4BL is likely to be a new APR QTL. The applicability of the SNP-based markers flanking QYr.nwafu-4BL was validated on a diversity panel of 276 wheat lines. The additional minor QTL on chromosomes 4A, 5A, 5B and 6A enhanced the level of resistance conferred by QYr.nwafu-4BL. Marker-assisted pyramiding of QYr.nwafu-4BL and other favorable minor QTL in new wheat cultivars should improve the level of APR to stripe rust.

Increasing feed efficiency and reducing methane emissions using genomics: An international approach

USDA-ARS?s Scientific Manuscript database

Genomic technology (including SNP arrays and next-generation sequencing) is a powerful driver for the genetic improvement of livestock. Phenotype recording can now, to an extent, be partitioned from selection, and even limited to several thousand animals. Rapid development of new technologies and pr...

Linkage Disequilibrium And Genome-Wide Association Studies In O. sativa

USDA-ARS?s Scientific Manuscript database

There is increasing evidence that genome-wide association studies provide a powerful approach to find the genetic basis of complex phenotypic variation in all kinds of species. For this purpose, we developed the first generation 44K Affymetrix SNP array in rice (see Tung et al. poster). We genotyped...

Genomic analysis using high density SNP based oligonucleotide arrays and MLPA provides a comprehensive analysis of INI1/SMARCB1 in malignant rhabdoid tumors

PubMed Central

Jackson, Eric M.; Sievert, Angela J.; Gai, Xiaowu; Hakonarson, Hakon; Judkins, Alexander R; Tooke, Laura; Perin, Juan Carlos; Xie, Hongbo; Shaikh, Tamim H.; Biegel, Jaclyn A.

2009-01-01

Translational Relevance Previous reports suggested that abnormalities of INI1 could be detected in 70–75% of malignant rhabdoid tumors. The mechanism of inactivation in the other 25% remained unclear. The goal of this study was to perform a high-resolution genomic analysis of a large series of rhabdoid tumors with the expectation of identifying additional loci related to the initiation or progression of these malignancies. We also developed a comprehensive set of assays, including a new MLPA assay, to interrogate the INI1 locus in 22q11.2. Intragenic deletions could be detected using the Illumina 550K Beadchip, whereas single exon deletions could be detected using MLPA. The current study demonstrates that with a multi-platform approach, alterations at the INI1 locus can be detected in almost all cases. Thus, appropriate molecular genetic testing can be used as an aid in the diagnosis and for treatment planning for most patients. Purpose A high-resolution genomic profiling and comprehensive targeted analysis of INI1/SMARCB1 of a large series of pediatric rhabdoid tumors was performed. The aim was to identify regions of copy number change and loss of heterozygosity that might pinpoint additional loci involved in the development or progression of rhabdoid tumors, and define the spectrum of genomic alterations of INI1 in this malignancy. Experimental Design A multi-platform approach, utilizing Illumina single nucleotide polymorphism (SNP) based oligonucleotide arrays, multiplex ligation dependent probe amplification (MLPA), fluorescence in situ hybridization (FISH), and coding sequence analysis was used to characterize genome wide copy number changes, loss of heterozygosity, and genomic alterations of INI1/SMARCB1 in a series of pediatric rhabdoid tumors. Results The bi-allelic alterations of INI1 that led to inactivation were elucidated in 50 of 51 tumors. INI1 inactivation was demonstrated by a variety of mechanisms, including deletions, mutations, and loss of heterozygosity. The results from the array studies highlighted the complexity of rearrangements of chromosome 22, compared to the low frequency of alterations involving the other chromosomes. Conclusions The results from the genome wide SNP-array analysis suggest that INI1 is the primary tumor suppressor gene involved in the development of rhabdoid tumors with no second locus identified. In addition, we did not identify hot spots for the breakpoints in sporadic tumors with deletions of chromosome 22q11.2. By employing a multimodality approach, the wide spectrum of alterations of INI1 can be identified in the majority of patients, which increases the clinical utility of molecular diagnostic testing. PMID:19276269

Making a chocolate chip: development and evaluation of a 6K SNP array for Theobroma cacao.

PubMed

Livingstone, Donald; Royaert, Stefan; Stack, Conrad; Mockaitis, Keithanne; May, Greg; Farmer, Andrew; Saski, Christopher; Schnell, Ray; Kuhn, David; Motamayor, Juan Carlos

2015-08-01

Theobroma cacao, the key ingredient in chocolate production, is one of the world's most important tree fruit crops, with ∼4,000,000 metric tons produced across 50 countries. To move towards gene discovery and marker-assisted breeding in cacao, a single-nucleotide polymorphism (SNP) identification project was undertaken using RNAseq data from 16 diverse cacao cultivars. RNA sequences were aligned to the assembled transcriptome of the cultivar Matina 1-6, and 330,000 SNPs within coding regions were identified. From these SNPs, a subset of 6,000 high-quality SNPs were selected for inclusion on an Illumina Infinium SNP array: the Cacao6kSNP array. Using Cacao6KSNP array data from over 1,000 cacao samples, we demonstrate that our custom array produces a saturated genetic map and can be used to distinguish among even closely related genotypes. Our study enhances and expands the genetic resources available to the cacao research community, and provides the genome-scale set of tools that are critical for advancing breeding with molecular markers in an agricultural species with high genetic diversity. © The Author 2015. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Measuring diversity in Gossypium hirsutum using the CottonSNP63K Array

USDA-ARS?s Scientific Manuscript database

A CottonSNP63K array and accompanying cluster file has been developed and includes 45,104 intra-specific SNPs and 17,954 inter-specific SNPs for automated genotyping of cotton (Gossypium spp.) samples. Development of the cluster file included genotyping of 1,156 samples, a subset of which were iden...

Performance comparison of SNP detection tools with illumina exome sequencing data—an assessment using both family pedigree information and sample-matched SNP array data

PubMed Central

Yi, Ming; Zhao, Yongmei; Jia, Li; He, Mei; Kebebew, Electron; Stephens, Robert M.

2014-01-01

To apply exome-seq-derived variants in the clinical setting, there is an urgent need to identify the best variant caller(s) from a large collection of available options. We have used an Illumina exome-seq dataset as a benchmark, with two validation scenarios—family pedigree information and SNP array data for the same samples, permitting global high-throughput cross-validation, to evaluate the quality of SNP calls derived from several popular variant discovery tools from both the open-source and commercial communities using a set of designated quality metrics. To the best of our knowledge, this is the first large-scale performance comparison of exome-seq variant discovery tools using high-throughput validation with both Mendelian inheritance checking and SNP array data, which allows us to gain insights into the accuracy of SNP calling through such high-throughput validation in an unprecedented way, whereas the previously reported comparison studies have only assessed concordance of these tools without directly assessing the quality of the derived SNPs. More importantly, the main purpose of our study was to establish a reusable procedure that applies high-throughput validation to compare the quality of SNP discovery tools with a focus on exome-seq, which can be used to compare any forthcoming tool(s) of interest. PMID:24831545

Comparison of array comparative genomic hybridization and quantitative real-time PCR-based aneuploidy screening of blastocyst biopsies.

PubMed

Capalbo, Antonio; Treff, Nathan R; Cimadomo, Danilo; Tao, Xin; Upham, Kathleen; Ubaldi, Filippo Maria; Rienzi, Laura; Scott, Richard T

2015-07-01

Comprehensive chromosome screening (CCS) methods are being extensively used to select chromosomally normal embryos in human assisted reproduction. Some concerns related to the stage of analysis and which aneuploidy screening method to use still remain. In this study, the reliability of blastocyst-stage aneuploidy screening and the diagnostic performance of the two mostly used CCS methods (quantitative real-time PCR (qPCR) and array comparative genome hybridization (aCGH)) has been assessed. aCGH aneuploid blastocysts were rebiopsied, blinded, and evaluated by qPCR. Discordant cases were subsequently rebiopsied, blinded, and evaluated by single-nucleotide polymorphism (SNP) array-based CCS. Although 81.7% of embryos showed the same diagnosis when comparing aCGH and qPCR-based CCS, 18.3% (22/120) of embryos gave a discordant result for at least one chromosome. SNP array reanalysis showed that a discordance was reported in ten blastocysts for aCGH, mostly due to false positives, and in four cases for qPCR. The discordant aneuploidy call rate per chromosome was significantly higher for aCGH (5.7%) compared with qPCR (0.6%; P<0.01). To corroborate these findings, 39 embryos were simultaneously biopsied for aCGH and qPCR during blastocyst-stage aneuploidy screening cycles. 35 matched including all 21 euploid embryos. Blinded SNP analysis on rebiopsies of the four embryos matched qPCR. These findings demonstrate the high reliability of diagnosis performed at the blastocyst stage with the use of different CCS methods. However, the application of aCGH can be expected to result in a higher aneuploidy rate than other contemporary methods of CCS.

Whole-exome sequencing for RH genotyping and alloimmunization risk in children with sickle cell anemia

PubMed Central

Flanagan, Jonathan M.; Vege, Sunitha; Luban, Naomi L. C.; Brown, R. Clark; Ware, Russell E.; Westhoff, Connie M.

2017-01-01

RH genes are highly polymorphic and encode the most complex of the 35 human blood group systems. This genetic diversity contributes to Rh alloimmunization in patients with sickle cell anemia (SCA) and is not avoided by serologic Rh-matched red cell transfusions. Standard serologic testing does not distinguish variant Rh antigens. Single nucleotide polymorphism (SNP)–based DNA arrays detect many RHD and RHCE variants, but the number of alleles tested is limited. We explored a next-generation sequencing (NGS) approach using whole-exome sequencing (WES) in 27 Rh alloimmunized and 27 matched non-alloimmunized patients with SCA who received chronic red cell transfusions and were enrolled in a multicenter study. We demonstrate that WES provides a comprehensive RH genotype, identifies SNPs not interrogated by DNA array, and accurately determines RHD zygosity. Among this multicenter cohort, we demonstrate an association between an altered RH genotype and Rh alloimmunization: 52% of Rh immunized vs 19% of non-immunized patients expressed variant Rh without co-expression of the conventional protein. Our findings suggest that RH allele variation in patients with SCA is clinically relevant, and NGS technology can offer a comprehensive alternative to targeted SNP-based testing. This is particularly relevant as NGS data becomes more widely available and could provide the means for reducing Rh alloimmunization in children with SCA. PMID:29296782

Imputation across genotyping arrays for genome-wide association studies: assessment of bias and a correction strategy.

PubMed

Johnson, Eric O; Hancock, Dana B; Levy, Joshua L; Gaddis, Nathan C; Saccone, Nancy L; Bierut, Laura J; Page, Grier P

2013-05-01

A great promise of publicly sharing genome-wide association data is the potential to create composite sets of controls. However, studies often use different genotyping arrays, and imputation to a common set of SNPs has shown substantial bias: a problem which has no broadly applicable solution. Based on the idea that using differing genotyped SNP sets as inputs creates differential imputation errors and thus bias in the composite set of controls, we examined the degree to which each of the following occurs: (1) imputation based on the union of genotyped SNPs (i.e., SNPs available on one or more arrays) results in bias, as evidenced by spurious associations (type 1 error) between imputed genotypes and arbitrarily assigned case/control status; (2) imputation based on the intersection of genotyped SNPs (i.e., SNPs available on all arrays) does not evidence such bias; and (3) imputation quality varies by the size of the intersection of genotyped SNP sets. Imputations were conducted in European Americans and African Americans with reference to HapMap phase II and III data. Imputation based on the union of genotyped SNPs across the Illumina 1M and 550v3 arrays showed spurious associations for 0.2 % of SNPs: ~2,000 false positives per million SNPs imputed. Biases remained problematic for very similar arrays (550v1 vs. 550v3) and were substantial for dissimilar arrays (Illumina 1M vs. Affymetrix 6.0). In all instances, imputing based on the intersection of genotyped SNPs (as few as 30 % of the total SNPs genotyped) eliminated such bias while still achieving good imputation quality.

Comprehensive replication of the relationship between myopia-related genes and refractive errors in a large Japanese cohort.

PubMed

Yoshikawa, Munemitsu; Yamashiro, Kenji; Miyake, Masahiro; Oishi, Maho; Akagi-Kurashige, Yumiko; Kumagai, Kyoko; Nakata, Isao; Nakanishi, Hideo; Oishi, Akio; Gotoh, Norimoto; Yamada, Ryo; Matsuda, Fumihiko; Yoshimura, Nagahisa

2014-10-21

We investigated the association between refractive error in a Japanese population and myopia-related genes identified in two recent large-scale genome-wide association studies. Single-nucleotide polymorphisms (SNPs) in 51 genes that were reported by the Consortium for Refractive Error and Myopia and/or the 23andMe database were genotyped in 3712 healthy Japanese volunteers from the Nagahama Study using HumanHap610K Quad, HumanOmni2.5M, and/or HumanExome Arrays. To evaluate the association between refractive error and recently identified myopia-related genes, we used three approaches to perform quantitative trait locus analyses of mean refractive error in both eyes of the participants: per-SNP, gene-based top-SNP, and gene-based all-SNP analyses. Association plots of successfully replicated genes also were investigated. In our per-SNP analysis, eight myopia gene associations were replicated successfully: GJD2, RASGRF1, BICC1, KCNQ5, CD55, CYP26A1, LRRC4C, and B4GALNT2.Seven additional gene associations were replicated in our gene-based analyses: GRIA4, BMP2, QKI, BMP4, SFRP1, SH3GL2, and EHBP1L1. The signal strength of the reported SNPs and their tagging SNPs increased after considering different linkage disequilibrium patterns across ethnicities. Although two previous studies suggested strong associations between PRSS56, LAMA2, TOX, and RDH5 and myopia, we could not replicate these results. Our results confirmed the significance of the myopia-related genes reported previously and suggested that gene-based replication analyses are more effective than per-SNP analyses. Our comparison with two previous studies suggested that BMP3 SNPs cause myopia primarily in Caucasian populations, while they may exhibit protective effects in Asian populations. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Development and Evaluation of a 9K SNP Array for Peach by Internationally Coordinated SNP Detection and Validation in Breeding Germplasm

PubMed Central

Scalabrin, Simone; Gilmore, Barbara; Lawley, Cynthia T.; Gasic, Ksenija; Micheletti, Diego; Rosyara, Umesh R.; Cattonaro, Federica; Vendramin, Elisa; Main, Dorrie; Aramini, Valeria; Blas, Andrea L.; Mockler, Todd C.; Bryant, Douglas W.; Wilhelm, Larry; Troggio, Michela; Sosinski, Bryon; Aranzana, Maria José; Arús, Pere; Iezzoni, Amy; Morgante, Michele; Peace, Cameron

2012-01-01

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs. The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species. PMID:22536421

High-Resolution SNP/CGH Microarrays Reveal the Accumulation of Loss of Heterozygosity in Commonly Used Candida albicans Strains

PubMed Central

Abbey, Darren; Hickman, Meleah; Gresham, David; Berman, Judith

2011-01-01

Phenotypic diversity can arise rapidly through loss of heterozygosity (LOH) or by the acquisition of copy number variations (CNV) spanning whole chromosomes or shorter contiguous chromosome segments. In Candida albicans, a heterozygous diploid yeast pathogen with no known meiotic cycle, homozygosis and aneuploidy alter clinical characteristics, including drug resistance. Here, we developed a high-resolution microarray that simultaneously detects ∼39,000 single nucleotide polymorphism (SNP) alleles and ∼20,000 copy number variation loci across the C. albicans genome. An important feature of the array analysis is a computational pipeline that determines SNP allele ratios based upon chromosome copy number. Using the array and analysis tools, we constructed a haplotype map (hapmap) of strain SC5314 to assign SNP alleles to specific homologs, and we used it to follow the acquisition of loss of heterozygosity (LOH) and copy number changes in a series of derived laboratory strains. This high-resolution SNP/CGH microarray and the associated hapmap facilitated the phasing of alleles in lab strains and revealed detrimental genome changes that arose frequently during molecular manipulations of laboratory strains. Furthermore, it provided a useful tool for rapid, high-resolution, and cost-effective characterization of changes in allele diversity as well as changes in chromosome copy number in new C. albicans isolates. PMID:22384363

A parallel SNP array study of genomic aberrations associated with mental retardation in patients and general population in Estonia.

PubMed

Männik, Katrin; Parkel, Sven; Palta, Priit; Zilina, Olga; Puusepp, Helen; Esko, Tõnu; Mägi, Reedik; Nõukas, Margit; Veidenberg, Andres; Nelis, Mari; Metspalu, Andres; Remm, Maido; Ounap, Katrin; Kurg, Ants

2011-01-01

The increasing use of whole-genome array screening has revealed the important role of DNA copy-number variations in the pathogenesis of neurodevelopmental disorders and several recurrent genomic disorders have been defined during recent years. However, some variants considered to be pathogenic have also been observed in phenotypically normal individuals. This underlines the importance of further characterization of genomic variants with potentially variable expressivity in both patient and general population cohorts to clarify their phenotypic consequence. In this study whole-genome SNP arrays were used to investigate genomic rearrangements in 77 Estonian families with idiopathic mental retardation. In addition to this family-based approach, phenotype and genotype data from a cohort of 1000 individuals in the general population were used for accurate interpretation of aberrations found in mental retardation patients. Relevant structural aberrations were detected in 18 of the families analyzed (23%). Fifteen of those were in genomic regions where clinical significance has previously been established. In 3 families, 4 novel aberrations associated with intellectual disability were detected in chromosome regions 2p25.1-p24.3, 3p12.1-p11.2, 7p21.2-p21.1 and Xq28. Carriers of imbalances in 15q13.3, 16p11.2 and Xp22.31 were identified among reference individuals, affirming the variable phenotypic consequence of rare variants in some genomic regions considered as pathogenic. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Increased genomic prediction accuracy in wheat breeding using a large Australian panel.

PubMed

Norman, Adam; Taylor, Julian; Tanaka, Emi; Telfer, Paul; Edwards, James; Martinant, Jean-Pierre; Kuchel, Haydn

2017-12-01

Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction. In recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom Axiom TM Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.

A low-density SNP array for analyzing differential selection in freshwater and marine populations of threespine stickleback (Gasterosteus aculeatus).

PubMed

Ferchaud, Anne-Laure; Pedersen, Susanne H; Bekkevold, Dorte; Jian, Jianbo; Niu, Yongchao; Hansen, Michael M

2014-10-06

The threespine stickleback (Gasterosteus aculeatus) has become an important model species for studying both contemporary and parallel evolution. In particular, differential adaptation to freshwater and marine environments has led to high differentiation between freshwater and marine stickleback populations at the phenotypic trait of lateral plate morphology and the underlying candidate gene Ectodysplacin (EDA). Many studies have focused on this trait and candidate gene, although other genes involved in marine-freshwater adaptation may be equally important. In order to develop a resource for rapid and cost efficient analysis of genetic divergence between freshwater and marine sticklebacks, we generated a low-density SNP (Single Nucleotide Polymorphism) array encompassing markers of chromosome regions under putative directional selection, along with neutral markers for background. RAD (Restriction site Associated DNA) sequencing of sixty individuals representing two freshwater and one marine population led to the identification of 33,993 SNP markers. Ninety-six of these were chosen for the low-density SNP array, among which 70 represented SNPs under putatively directional selection in freshwater vs. marine environments, whereas 26 SNPs were assumed to be neutral. Annotation of these regions revealed several genes that are candidates for affecting stickleback phenotypic variation, some of which have been observed in previous studies whereas others are new. We have developed a cost-efficient low-density SNP array that allows for rapid screening of polymorphisms in threespine stickleback. The array provides a valuable tool for analyzing adaptive divergence between freshwater and marine stickleback populations beyond the well-established candidate gene Ectodysplacin (EDA).

Surface invasive cleavage assay on a maskless light-directed diamond DNA microarray for genome-wide human SNP mapping.

PubMed

Nie, Bei; Yang, Min; Fu, Weiling; Liang, Zhiqing

2015-07-07

The surface invasive cleavage assay, because of its innate accuracy and ability for self-signal amplification, provides a potential route for the mapping of hundreds of thousands of human SNP sites. However, its performance on a high density DNA array has not yet been established, due to the unusual "hairpin" probe design on the microarray and the lack of chemical stability of commercially available substrates. Here we present an applicable method to implement a nanocrystalline diamond thin film as an alternative substrate for fabricating an addressable DNA array using maskless light-directed photochemistry, producing the most chemically stable and biocompatible system for genetic analysis and enzymatic reactions. The surface invasive cleavage reaction, followed by degenerated primer ligation and post-rolling circle amplification is consecutively performed on the addressable diamond DNA array, accurately mapping SNP sites from PCR-amplified human genomic target DNA. Furthermore, a specially-designed DNA array containing dual probes in the same pixel is fabricated by following a reverse light-directed DNA synthesis protocol. This essentially enables us to decipher thousands of SNP alleles in a single-pot reaction by the simple addition of enzyme, target and reaction buffers.

Recovery of Native Genetic Background in Admixed Populations Using Haplotypes, Phenotypes, and Pedigree Information – Using Cika Cattle as a Case Breed

PubMed Central

Simčič, Mojca; Smetko, Anamarija; Sölkner, Johann; Seichter, Doris; Gorjanc, Gregor; Kompan, Dragomir; Medugorac, Ivica

2015-01-01

The aim of this study was to obtain unbiased estimates of the diversity parameters, the population history, and the degree of admixture in Cika cattle which represents the local admixed breeds at risk of extinction undergoing challenging conservation programs. Genetic analyses were performed on the genome-wide Single Nucleotide Polymorphism (SNP) Illumina Bovine SNP50 array data of 76 Cika animals and 531 animals from 14 reference populations. To obtain unbiased estimates we used short haplotypes spanning four markers instead of single SNPs to avoid an ascertainment bias of the BovineSNP50 array. Genome-wide haplotypes combined with partial pedigree and type trait classification show the potential to improve identification of purebred animals with a low degree of admixture. Phylogenetic analyses demonstrated unique genetic identity of Cika animals. Genetic distance matrix presented by rooted Neighbour-Net suggested long and broad phylogenetic connection between Cika and Pinzgauer. Unsupervised clustering performed by the admixture analysis and two-dimensional presentation of the genetic distances between individuals also suggest Cika is a distinct breed despite being similar in appearance to Pinzgauer. Animals identified as the most purebred could be used as a nucleus for a recovery of the native genetic background in the current admixed population. The results show that local well-adapted strains, which have never been intensively managed and differentiated into specific breeds, exhibit large haplotype diversity. They suggest a conservation and recovery approach that does not rely exclusively on the search for the original native genetic background but rather on the identification and removal of common introgressed haplotypes would be more powerful. Successful implementation of such an approach should be based on combining phenotype, pedigree, and genome-wide haplotype data of the breed of interest and a spectrum of reference breeds which potentially have had direct or indirect historical contribution to the genetic makeup of the breed of interest. PMID:25923207

"Gap hunting" to characterize clustered probe signals in Illumina methylation array data.

PubMed

Andrews, Shan V; Ladd-Acosta, Christine; Feinberg, Andrew P; Hansen, Kasper D; Fallin, M Daniele

2016-01-01

The Illumina 450k array has been widely used in epigenetic association studies. Current quality-control (QC) pipelines typically remove certain sets of probes, such as those containing a SNP or with multiple mapping locations. An additional set of potentially problematic probes are those with DNA methylation distributions characterized by two or more distinct clusters separated by gaps. Data-driven identification of such probes may offer additional insights for downstream analyses. We developed a procedure, termed "gap hunting," to identify probes showing clustered distributions. Among 590 peripheral blood samples from the Study to Explore Early Development, we identified 11,007 "gap probes." The vast majority (9199) are likely attributed to an underlying SNP(s) or other variant in the probe, although SNP-affected probes exist that do not produce a gap signals. Specific factors predict which SNPs lead to gap signals, including type of nucleotide change, probe type, DNA strand, and overall methylation state. These expected effects are demonstrated in paired genotype and 450k data on the same samples. Gap probes can also serve as a surrogate for the local genetic sequence on a haplotype scale and can be used to adjust for population stratification. The characteristics of gap probes reflect potentially informative biology. QC pipelines may benefit from an efficient data-driven approach that "flags" gap probes, rather than filtering such probes, followed by careful interpretation of downstream association analyses. Our results should translate directly to the recently released Illumina EPIC array given the similar chemistry and content design.

A High-Density Consensus Map of Common Wheat Integrating Four Mapping Populations Scanned by the 90K SNP Array

PubMed Central

Wen, Weie; He, Zhonghu; Gao, Fengmei; Liu, Jindong; Jin, Hui; Zhai, Shengnan; Qu, Yanying; Xia, Xianchun

2017-01-01

A high-density consensus map is a powerful tool for gene mapping, cloning and molecular marker-assisted selection in wheat breeding. The objective of this study was to construct a high-density, single nucleotide polymorphism (SNP)-based consensus map of common wheat (Triticum aestivum L.) by integrating genetic maps from four recombinant inbred line populations. The populations were each genotyped using the wheat 90K Infinium iSelect SNP assay. A total of 29,692 SNP markers were mapped on 21 linkage groups corresponding to 21 hexaploid wheat chromosomes, covering 2,906.86 cM, with an overall marker density of 10.21 markers/cM. Compared with the previous maps based on the wheat 90K SNP chip detected 22,736 (76.6%) of the SNPs with consistent chromosomal locations, whereas 1,974 (6.7%) showed different chromosomal locations, and 4,982 (16.8%) were newly mapped. Alignment of the present consensus map and the wheat expressed sequence tags (ESTs) Chromosome Bin Map enabled assignment of 1,221 SNP markers to specific chromosome bins and 819 ESTs were integrated into the consensus map. The marker orders of the consensus map were validated based on physical positions on the wheat genome with Spearman rank correlation coefficients ranging from 0.69 (4D) to 0.97 (1A, 4B, 5B, and 6A), and were also confirmed by comparison with genetic position on the previously 40K SNP consensus map with Spearman rank correlation coefficients ranging from 0.84 (6D) to 0.99 (6A). Chromosomal rearrangements reported previously were confirmed in the present consensus map and new putative rearrangements were identified. In addition, an integrated consensus map was developed through the combination of five published maps with ours, containing 52,607 molecular markers. The consensus map described here provided a high-density SNP marker map and a reliable order of SNPs, representing a step forward in mapping and validation of chromosomal locations of SNPs on the wheat 90K array. Moreover, it can be used as a reference for quantitative trait loci (QTL) mapping to facilitate exploitation of genes and QTL in wheat breeding. PMID:28848588

Potential and limits to unravel the genetic architecture and predict the variation of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.).

PubMed

Jiang, Y; Zhao, Y; Rodemann, B; Plieske, J; Kollers, S; Korzun, V; Ebmeyer, E; Argillier, O; Hinze, M; Ling, J; Röder, M S; Ganal, M W; Mette, M F; Reif, J C

2015-03-01

Genome-wide mapping approaches in diverse populations are powerful tools to unravel the genetic architecture of complex traits. The main goals of our study were to investigate the potential and limits to unravel the genetic architecture and to identify the factors determining the accuracy of prediction of the genotypic variation of Fusarium head blight (FHB) resistance in wheat (Triticum aestivum L.) based on data collected with a diverse panel of 372 European varieties. The wheat lines were phenotyped in multi-location field trials for FHB resistance and genotyped with 782 simple sequence repeat (SSR) markers, and 9k and 90k single-nucleotide polymorphism (SNP) arrays. We applied genome-wide association mapping in combination with fivefold cross-validations and observed surprisingly high accuracies of prediction for marker-assisted selection based on the detected quantitative trait loci (QTLs). Using a random sample of markers not selected for marker-trait associations revealed only a slight decrease in prediction accuracy compared with marker-based selection exploiting the QTL information. The same picture was confirmed in a simulation study, suggesting that relatedness is a main driver of the accuracy of prediction in marker-assisted selection of FHB resistance. When the accuracy of prediction of three genomic selection models was contrasted for the three marker data sets, no significant differences in accuracies among marker platforms and genomic selection models were observed. Marker density impacted the accuracy of prediction only marginally. Consequently, genomic selection of FHB resistance can be implemented most cost-efficiently based on low- to medium-density SNP arrays.

High-density SNP assay development for genetic analysis in maritime pine (Pinus pinaster).

PubMed

Plomion, C; Bartholomé, J; Lesur, I; Boury, C; Rodríguez-Quilón, I; Lagraulet, H; Ehrenmann, F; Bouffier, L; Gion, J M; Grivet, D; de Miguel, M; de María, N; Cervera, M T; Bagnoli, F; Isik, F; Vendramin, G G; González-Martínez, S C

2016-03-01

Maritime pine provides essential ecosystem services in the south-western Mediterranean basin, where it covers around 4 million ha. Its scattered distribution over a range of environmental conditions makes it an ideal forest tree species for studies of local adaptation and evolutionary responses to climatic change. Highly multiplexed single nucleotide polymorphism (SNP) genotyping arrays are increasingly used to study genetic variation in living organisms and for practical applications in plant and animal breeding and genetic resource conservation. We developed a 9k Illumina Infinium SNP array and genotyped maritime pine trees from (i) a three-generation inbred (F2) pedigree, (ii) the French breeding population and (iii) natural populations from Portugal and the French Atlantic coast. A large proportion of the exploitable SNPs (2052/8410, i.e. 24.4%) segregated in the mapping population and could be mapped, providing the densest ever gene-based linkage map for this species. Based on 5016 SNPs, natural and breeding populations from the French gene pool exhibited similar level of genetic diversity. Population genetics and structure analyses based on 3981 SNP markers common to the Portuguese and French gene pools revealed high levels of differentiation, leading to the identification of a set of highly differentiated SNPs that could be used for seed provenance certification. Finally, we discuss how the validated SNPs could facilitate the identification of ecologically and economically relevant genes in this species, improving our understanding of the demography and selective forces shaping its natural genetic diversity, and providing support for new breeding strategies. © 2015 John Wiley & Sons Ltd.

Predicting Breed Composition Using Breed Frequencies of 50,000 Markers from the U.S. Meat Animal Research Center 2,000 Bull Project

USDA-ARS?s Scientific Manuscript database

Our objective was to evaluate whether breed composition of crossbred cattle could be predicted using reference breed frequencies of SNP markers on the BovineSNP50 array. Semen DNA samples of over 2,000 bulls from 16 common commercial beef breeds were genotyped using the array and used to estimate cu...

Fine mapping of copy number variations on two cattle genome assemblies using high density SNP array

USDA-ARS?s Scientific Manuscript database

Btau_4.0 and UMD3.1 are two distinct cattle reference genome assemblies. In our previous study using the low density BovineSNP50 array, we reported a copy number variation (CNV) analysis on Btau_4.0 with 521 animals of 21 cattle breeds, yielding 682 CNV regions with a total length of 139.8 megabases...

Application of LogitBoost Classifier for Traceability Using SNP Chip Data

PubMed Central

Kang, Hyunsung; Cho, Seoae; Kim, Heebal; Seo, Kang-Seok

2015-01-01

Consumer attention to food safety has increased rapidly due to animal-related diseases; therefore, it is important to identify their places of origin (POO) for safety purposes. However, only a few studies have addressed this issue and focused on machine learning-based approaches. In the present study, classification analyses were performed using a customized SNP chip for POO prediction. To accomplish this, 4,122 pigs originating from 104 farms were genotyped using the SNP chip. Several factors were considered to establish the best prediction model based on these data. We also assessed the applicability of the suggested model using a kinship coefficient-filtering approach. Our results showed that the LogitBoost-based prediction model outperformed other classifiers in terms of classification performance under most conditions. Specifically, a greater level of accuracy was observed when a higher kinship-based cutoff was employed. These results demonstrated the applicability of a machine learning-based approach using SNP chip data for practical traceability. PMID:26436917

Application of LogitBoost Classifier for Traceability Using SNP Chip Data.

PubMed

Kim, Kwondo; Seo, Minseok; Kang, Hyunsung; Cho, Seoae; Kim, Heebal; Seo, Kang-Seok

2015-01-01

Consumer attention to food safety has increased rapidly due to animal-related diseases; therefore, it is important to identify their places of origin (POO) for safety purposes. However, only a few studies have addressed this issue and focused on machine learning-based approaches. In the present study, classification analyses were performed using a customized SNP chip for POO prediction. To accomplish this, 4,122 pigs originating from 104 farms were genotyped using the SNP chip. Several factors were considered to establish the best prediction model based on these data. We also assessed the applicability of the suggested model using a kinship coefficient-filtering approach. Our results showed that the LogitBoost-based prediction model outperformed other classifiers in terms of classification performance under most conditions. Specifically, a greater level of accuracy was observed when a higher kinship-based cutoff was employed. These results demonstrated the applicability of a machine learning-based approach using SNP chip data for practical traceability.

High-Performance Multiplex SNP Analysis of Three Hemochromatosis-Related Mutations With Capillary Array Electrophoresis Microplates

PubMed Central

Medintz, Igor; Wong, Wendy W.; Berti, Lorenzo; Shiow, Lawrence; Tom, Jennifer; Scherer, James; Sensabaugh, George; Mathies, Richard A.

2001-01-01

An assay is described for high-throughput single nucleotide polymorphism (SNP) genotyping on a microfabricated capillary array electrophoresis (CAE) microchip. The assay targets the three common variants at the HFE locus associated with the genetic disease hereditary hemochromatosis (HHC). The assay employs allele-specific PCR (ASPCR) for the C282Y (845g->a), H63D (187c->g), and S65C (193a->t) variants using fluorescently-labeled energy-transfer (ET) allele-specific primers. Using a 96-channel radial CAE microplate, the labeled ASPCR products generated from 96 samples in a reference Caucasian population are simultaneously separated with single-base-pair resolution and genotyped in under 10 min. Detection is accomplished with a laser-excited rotary four-color fluorescence scanner. The allele-specific amplicons are differentiated on the basis of both their size and the color of the label emission. This study is the first demonstration of the combined use of ASPCR with ET primers and microfabricated radial CAE microplates to perform multiplex SNP analyses in a clinically relevant population. PMID:11230165

Transcriptomic SNP discovery for custom genotyping arrays: impacts of sequence data, SNP calling method and genotyping technology on the probability of validation success.

PubMed

Humble, Emily; Thorne, Michael A S; Forcada, Jaume; Hoffman, Joseph I

2016-08-26

Single nucleotide polymorphism (SNP) discovery is an important goal of many studies. However, the number of 'putative' SNPs discovered from a sequence resource may not provide a reliable indication of the number that will successfully validate with a given genotyping technology. For this it may be necessary to account for factors such as the method used for SNP discovery and the type of sequence data from which it originates, suitability of the SNP flanking sequences for probe design, and genomic context. To explore the relative importance of these and other factors, we used Illumina sequencing to augment an existing Roche 454 transcriptome assembly for the Antarctic fur seal (Arctocephalus gazella). We then mapped the raw Illumina reads to the new hybrid transcriptome using BWA and BOWTIE2 before calling SNPs with GATK. The resulting markers were pooled with two existing sets of SNPs called from the original 454 assembly using NEWBLER and SWAP454. Finally, we explored the extent to which SNPs discovered using these four methods overlapped and predicted the corresponding validation outcomes for both Illumina Infinium iSelect HD and Affymetrix Axiom arrays. Collating markers across all discovery methods resulted in a global list of 34,718 SNPs. However, concordance between the methods was surprisingly poor, with only 51.0 % of SNPs being discovered by more than one method and 13.5 % being called from both the 454 and Illumina datasets. Using a predictive modeling approach, we could also show that SNPs called from the Illumina data were on average more likely to successfully validate, as were SNPs called by more than one method. Above and beyond this pattern, predicted validation outcomes were also consistently better for Affymetrix Axiom arrays. Our results suggest that focusing on SNPs called by more than one method could potentially improve validation outcomes. They also highlight possible differences between alternative genotyping technologies that could be explored in future studies of non-model organisms.

Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array.

PubMed

Zhu, Bo; Niu, Hong; Zhang, Wengang; Wang, Zezhao; Liang, Yonghu; Guan, Long; Guo, Peng; Chen, Yan; Zhang, Lupei; Guo, Yong; Ni, Heming; Gao, Xue; Gao, Huijiang; Xu, Lingyang; Li, Junya

2017-06-14

Fatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this study, we performed GWAS using high density SNP array to analyze the association between SNPs and fatty acids and evaluated the accuracy of genomic prediction for fatty acids in Chinese Simmental cattle. Using the BayesB method, we identified 35 and 7 regions in Chinese Simmental cattle that displayed significant associations with individual fatty acids and fatty acid groups, respectively. We further obtained several candidate genes which may be involved in fatty acid biosynthesis including elongation of very long chain fatty acids protein 5 (ELOVL5), fatty acid synthase (FASN), caspase 2 (CASP2) and thyroglobulin (TG). Specifically, we obtained strong evidence of association signals for one SNP located at 51.3 Mb for FASN using Genome-wide Rapid Association Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approaches. Also, region-based association test identified multiple SNPs within FASN and ELOVL5 for C14:0. In addition, our result revealed that the effectiveness of genomic prediction for fatty acid composition using BayesB was slightly superior over GBLUP in Chinese Simmental cattle. We identified several significantly associated regions and loci which can be considered as potential candidate markers for genomics-assisted breeding programs. Using multiple methods, our results revealed that FASN and ELOVL5 are associated with fatty acids with strong evidence. Our finding also suggested that it is feasible to perform genomic selection for fatty acids in Chinese Simmental cattle.

affy2sv: an R package to pre-process Affymetrix CytoScan HD and 750K arrays for SNP, CNV, inversion and mosaicism calling.

PubMed

Hernandez-Ferrer, Carles; Quintela Garcia, Ines; Danielski, Katharina; Carracedo, Ángel; Pérez-Jurado, Luis A; González, Juan R

2015-05-20

The well-known Genome-Wide Association Studies (GWAS) had led to many scientific discoveries using SNP data. Even so, they were not able to explain the full heritability of complex diseases. Now, other structural variants like copy number variants or DNA inversions, either germ-line or in mosaicism events, are being studies. We present the R package affy2sv to pre-process Affymetrix CytoScan HD/750k array (also for Genome-Wide SNP 5.0/6.0 and Axiom) in structural variant studies. We illustrate the capabilities of affy2sv using two different complete pipelines on real data. The first one performing a GWAS and a mosaic alterations detection study, and the other detecting CNVs and performing an inversion calling. Both examples presented in the article show up how affy2sv can be used as part of more complex pipelines aimed to analyze Affymetrix SNP arrays data in genetic association studies, where different types of structural variants are considered.

GPHMM: an integrated hidden Markov model for identification of copy number alteration and loss of heterozygosity in complex tumor samples using whole genome SNP arrays

PubMed Central

Li, Ao; Liu, Zongzhi; Lezon-Geyda, Kimberly; Sarkar, Sudipa; Lannin, Donald; Schulz, Vincent; Krop, Ian; Winer, Eric; Harris, Lyndsay; Tuck, David

2011-01-01

There is an increasing interest in using single nucleotide polymorphism (SNP) genotyping arrays for profiling chromosomal rearrangements in tumors, as they allow simultaneous detection of copy number and loss of heterozygosity with high resolution. Critical issues such as signal baseline shift due to aneuploidy, normal cell contamination, and the presence of GC content bias have been reported to dramatically alter SNP array signals and complicate accurate identification of aberrations in cancer genomes. To address these issues, we propose a novel Global Parameter Hidden Markov Model (GPHMM) to unravel tangled genotyping data generated from tumor samples. In contrast to other HMM methods, a distinct feature of GPHMM is that the issues mentioned above are quantitatively modeled by global parameters and integrated within the statistical framework. We developed an efficient EM algorithm for parameter estimation. We evaluated performance on three data sets and show that GPHMM can correctly identify chromosomal aberrations in tumor samples containing as few as 10% cancer cells. Furthermore, we demonstrated that the estimation of global parameters in GPHMM provides information about the biological characteristics of tumor samples and the quality of genotyping signal from SNP array experiments, which is helpful for data quality control and outlier detection in cohort studies. PMID:21398628

Whole-genome single-nucleotide polymorphism (SNP) marker discovery and association analysis with the eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content in Larimichthys crocea

PubMed Central

Xiao, Shijun; Wang, Panpan; Dong, Linsong; Zhang, Yaguang; Han, Zhaofang; Wang, Qiurong

2016-01-01

Whole-genome single-nucleotide polymorphism (SNP) markers are valuable genetic resources for the association and conservation studies. Genome-wide SNP development in many teleost species are still challenging because of the genome complexity and the cost of re-sequencing. Genotyping-By-Sequencing (GBS) provided an efficient reduced representative method to squeeze cost for SNP detection; however, most of recent GBS applications were reported on plant organisms. In this work, we used an EcoRI-NlaIII based GBS protocol to teleost large yellow croaker, an important commercial fish in China and East-Asia, and reported the first whole-genome SNP development for the species. 69,845 high quality SNP markers that evenly distributed along genome were detected in at least 80% of 500 individuals. Nearly 95% randomly selected genotypes were successfully validated by Sequenom MassARRAY assay. The association studies with the muscle eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) content discovered 39 significant SNP markers, contributing as high up to ∼63% genetic variance that explained by all markers. Functional genes that involved in fat digestion and absorption pathway were identified, such as APOB, CRAT and OSBPL10. Notably, PPT2 Gene, previously identified in the association study of the plasma n-3 and n-6 polyunsaturated fatty acid level in human, was re-discovered in large yellow croaker. Our study verified that EcoRI-NlaIII based GBS could produce quality SNP markers in a cost-efficient manner in teleost genome. The developed SNP markers and the EPA and DHA associated SNP loci provided invaluable resources for the population structure, conservation genetics and genomic selection of large yellow croaker and other fish organisms. PMID:28028455

Development and evaluation of the first high-throughput SNP array for common carp (Cyprinus carpio)

PubMed Central

2014-01-01

Background A large number of single nucleotide polymorphisms (SNPs) have been identified in common carp (Cyprinus carpio) but, as yet, no high-throughput genotyping platform is available for this species. C. carpio is an important aquaculture species that accounts for nearly 14% of freshwater aquaculture production worldwide. We have developed an array for C. carpio with 250,000 SNPs and evaluated its performance using samples from various strains of C. carpio. Results The SNPs used on the array were selected from two resources: the transcribed sequences from RNA-seq data of four strains of C. carpio, and the genome re-sequencing data of five strains of C. carpio. The 250,000 SNPs on the resulting array are distributed evenly across the reference C.carpio genome with an average spacing of 6.6 kb. To evaluate the SNP array, 1,072 C. carpio samples were collected and tested. Of the 250,000 SNPs on the array, 185,150 (74.06%) were found to be polymorphic sites. Genotyping accuracy was checked using genotyping data from a group of full-siblings and their parents, and over 99.8% of the qualified SNPs were found to be reliable. Analysis of the linkage disequilibrium on all samples and on three domestic C.carpio strains revealed that the latter had the longer haplotype blocks. We also evaluated our SNP array on 80 samples from eight species related to C. carpio, with from 53,526 to 71,984 polymorphic SNPs. An identity by state analysis divided all the samples into three clusters; most of the C. carpio strains formed the largest cluster. Conclusions The Carp SNP array described here is the first high-throughput genotyping platform for C. carpio. Our evaluation of this array indicates that it will be valuable for farmed carp and for genetic and population biology studies in C. carpio and related species. PMID:24762296

Development and evaluation of the first high-throughput SNP array for common carp (Cyprinus carpio).

PubMed

Xu, Jian; Zhao, Zixia; Zhang, Xiaofeng; Zheng, Xianhu; Li, Jiongtang; Jiang, Yanliang; Kuang, Youyi; Zhang, Yan; Feng, Jianxin; Li, Chuangju; Yu, Juhua; Li, Qiang; Zhu, Yuanyuan; Liu, Yuanyuan; Xu, Peng; Sun, Xiaowen

2014-04-24

A large number of single nucleotide polymorphisms (SNPs) have been identified in common carp (Cyprinus carpio) but, as yet, no high-throughput genotyping platform is available for this species. C. carpio is an important aquaculture species that accounts for nearly 14% of freshwater aquaculture production worldwide. We have developed an array for C. carpio with 250,000 SNPs and evaluated its performance using samples from various strains of C. carpio. The SNPs used on the array were selected from two resources: the transcribed sequences from RNA-seq data of four strains of C. carpio, and the genome re-sequencing data of five strains of C. carpio. The 250,000 SNPs on the resulting array are distributed evenly across the reference C.carpio genome with an average spacing of 6.6 kb. To evaluate the SNP array, 1,072 C. carpio samples were collected and tested. Of the 250,000 SNPs on the array, 185,150 (74.06%) were found to be polymorphic sites. Genotyping accuracy was checked using genotyping data from a group of full-siblings and their parents, and over 99.8% of the qualified SNPs were found to be reliable. Analysis of the linkage disequilibrium on all samples and on three domestic C.carpio strains revealed that the latter had the longer haplotype blocks. We also evaluated our SNP array on 80 samples from eight species related to C. carpio, with from 53,526 to 71,984 polymorphic SNPs. An identity by state analysis divided all the samples into three clusters; most of the C. carpio strains formed the largest cluster. The Carp SNP array described here is the first high-throughput genotyping platform for C. carpio. Our evaluation of this array indicates that it will be valuable for farmed carp and for genetic and population biology studies in C. carpio and related species.

Two combinatorial optimization problems for SNP discovery using base-specific cleavage and mass spectrometry.

PubMed

Chen, Xin; Wu, Qiong; Sun, Ruimin; Zhang, Louxin

2012-01-01

The discovery of single-nucleotide polymorphisms (SNPs) has important implications in a variety of genetic studies on human diseases and biological functions. One valuable approach proposed for SNP discovery is based on base-specific cleavage and mass spectrometry. However, it is still very challenging to achieve the full potential of this SNP discovery approach. In this study, we formulate two new combinatorial optimization problems. While both problems are aimed at reconstructing the sample sequence that would attain the minimum number of SNPs, they search over different candidate sequence spaces. The first problem, denoted as SNP - MSP, limits its search to sequences whose in silico predicted mass spectra have all their signals contained in the measured mass spectra. In contrast, the second problem, denoted as SNP - MSQ, limits its search to sequences whose in silico predicted mass spectra instead contain all the signals of the measured mass spectra. We present an exact dynamic programming algorithm for solving the SNP - MSP problem and also show that the SNP - MSQ problem is NP-hard by a reduction from a restricted variation of the 3-partition problem. We believe that an efficient solution to either problem above could offer a seamless integration of information in four complementary base-specific cleavage reactions, thereby improving the capability of the underlying biotechnology for sensitive and accurate SNP discovery.

Development and evaluation of high-density Axiom® CicerSNP Array for high-resolution genetic mapping and breeding applications in chickpea.

PubMed

Roorkiwal, Manish; Jain, Ankit; Kale, Sandip M; Doddamani, Dadakhalandar; Chitikineni, Annapurna; Thudi, Mahendar; Varshney, Rajeev K

2018-04-01

To accelerate genomics research and molecular breeding applications in chickpea, a high-throughput SNP genotyping platform 'Axiom ® CicerSNP Array' has been designed, developed and validated. Screening of whole-genome resequencing data from 429 chickpea lines identified 4.9 million SNPs, from which a subset of 70 463 high-quality nonredundant SNPs was selected using different stringent filter criteria. This was further narrowed down to 61 174 SNPs based on p-convert score ≥0.3, of which 50 590 SNPs could be tiled on array. Among these tiled SNPs, a total of 11 245 SNPs (22.23%) were from the coding regions of 3673 different genes. The developed Axiom ® CicerSNP Array was used for genotyping two recombinant inbred line populations, namely ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261). Genotyping data reflected high success and polymorphic rate, with 15 140 (29.93%; ICCRIL03) and 20 018 (39.57%; ICCRIL04) polymorphic SNPs. High-density genetic maps comprising 13 679 SNPs spanning 1033.67 cM and 7769 SNPs spanning 1076.35 cM were developed for ICCRIL03 and ICCRIL04 populations, respectively. QTL analysis using multilocation, multiseason phenotyping data on these RILs identified 70 (ICCRIL03) and 120 (ICCRIL04) main-effect QTLs on genetic map. Higher precision and potential of this array is expected to advance chickpea genetics and breeding applications. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications.

PubMed

Wu, Xiao-Lin; Xu, Jiaqi; Feng, Guofei; Wiggans, George R; Taylor, Jeremy F; He, Jun; Qian, Changsong; Qiu, Jiansheng; Simpson, Barry; Walker, Jeremy; Bauck, Stewart

2016-01-01

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal.

Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications

PubMed Central

Wu, Xiao-Lin; Xu, Jiaqi; Feng, Guofei; Wiggans, George R.; Taylor, Jeremy F.; He, Jun; Qian, Changsong; Qiu, Jiansheng; Simpson, Barry; Walker, Jeremy; Bauck, Stewart

2016-01-01

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal. PMID:27583971

High-density single nucleotide polymorphism (SNP) array mapping in Brassica oleracea: identification of QTL associated with carotenoid variation in broccoli florets.

PubMed

Brown, Allan F; Yousef, Gad G; Chebrolu, Kranthi K; Byrd, Robert W; Everhart, Koyt W; Thomas, Aswathy; Reid, Robert W; Parkin, Isobel A P; Sharpe, Andrew G; Oliver, Rebekah; Guzman, Ivette; Jackson, Eric W

2014-09-01

A high-resolution genetic linkage map of B. oleracea was developed from a B. napus SNP array. The work will facilitate genetic and evolutionary studies in Brassicaceae. A broccoli population, VI-158 × BNC, consisting of 150 F2:3 families was used to create a saturated Brassica oleracea (diploid: CC) linkage map using a recently developed rapeseed (Brassica napus) (tetraploid: AACC) Illumina Infinium single nucleotide polymorphism (SNP) array. The map consisted of 547 non-redundant SNP markers spanning 948.1 cM across nine chromosomes with an average interval size of 1.7 cM. As the SNPs are anchored to the genomic reference sequence of the rapid cycling B. oleracea TO1000, we were able to estimate that the map provides 96 % coverage of the diploid genome. Carotenoid analysis of 2 years data identified 3 QTLs on two chromosomes that are associated with up to half of the phenotypic variation associated with the accumulation of total or individual compounds. By searching the genome sequences of the two related diploid species (B. oleracea and B. rapa), we further identified putative carotenoid candidate genes in the region of these QTLs. This is the first description of the use of a B. napus SNP array to rapidly construct high-density genetic linkage maps of one of the constituent diploid species. The unambiguous nature of these markers with regard to genomic sequences provides evidence to the nature of genes underlying the QTL, and demonstrates the value and impact this resource will have on Brassica research.

Genomewide single nucleotide polymorphism discovery in Atlantic salmon (Salmo salar): validation in wild and farmed American and European populations.

PubMed

Yáñez, J M; Naswa, S; López, M E; Bassini, L; Correa, K; Gilbey, J; Bernatchez, L; Norris, A; Neira, R; Lhorente, J P; Schnable, P S; Newman, S; Mileham, A; Deeb, N; Di Genova, A; Maass, A

2016-07-01

A considerable number of single nucleotide polymorphisms (SNPs) are required to elucidate genotype-phenotype associations and determine the molecular basis of important traits. In this work, we carried out de novo SNP discovery accounting for both genome duplication and genetic variation from American and European salmon populations. A total of 9 736 473 nonredundant SNPs were identified across a set of 20 fish by whole-genome sequencing. After applying six bioinformatic filtering steps, 200 K SNPs were selected to develop an Affymetrix Axiom(®) myDesign Custom Array. This array was used to genotype 480 fish representing wild and farmed salmon from Europe, North America and Chile. A total of 159 099 (79.6%) SNPs were validated as high quality based on clustering properties. A total of 151 509 validated SNPs showed a unique position in the genome. When comparing these SNPs against 238 572 markers currently available in two other Atlantic salmon arrays, only 4.6% of the SNP overlapped with the panel developed in this study. This novel high-density SNP panel will be very useful for the dissection of economically and ecologically relevant traits, enhancing breeding programmes through genomic selection as well as supporting genetic studies in both wild and farmed populations of Atlantic salmon using high-resolution genomewide information. © 2016 John Wiley & Sons Ltd.

AA9int: SNP Interaction Pattern Search Using Non-Hierarchical Additive Model Set.

PubMed

Lin, Hui-Yi; Huang, Po-Yu; Chen, Dung-Tsa; Tung, Heng-Yuan; Sellers, Thomas A; Pow-Sang, Julio; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Hamdy, Freddie; Neal, David E; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen N; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lu, Yong-Jie; Park, Jong Y

2018-06-07

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. hlin1@lsuhsc.edu. Supplementary data are available at Bioinformatics online.

KinSNP software for homozygosity mapping of disease genes using SNP microarrays

PubMed Central

2010-01-01

Consanguineous families affected with a recessive genetic disease caused by homozygotisation of a mutation offer a unique advantage for positional cloning of rare diseases. Homozygosity mapping of patient genotypes is a powerful technique for the identification of the genomic locus harbouring the causing mutation. This strategy relies on the observation that in these patients a large region spanning the disease locus is also homozygous with high probability. The high marker density in single nucleotide polymorphism (SNP) arrays is extremely advantageous for homozygosity mapping. We present KinSNP, a user-friendly software tool for homozygosity mapping using SNP arrays. The software searches for stretches of SNPs which are homozygous to the same allele in all ascertained sick individuals. User-specified parameters control the number of allowed genotyping 'errors' within homozygous blocks. Candidate disease regions are then reported in a detailed, coloured Excel file, along with genotypes of family members and healthy controls. An interactive genome browser has been included which shows homozygous blocks, individual genotypes, genes and further annotations along the chromosomes, with zooming and scrolling capabilities. The software has been used to identify the location of a mutated gene causing insensitivity to pain in a large Bedouin family. KinSNP is freely available from http://bioinfo.bgu.ac.il/bsu/software/kinSNP. PMID:20846928

Genotype imputation in the domestic dog

PubMed Central

Meurs, K. M.

2016-01-01

Application of imputation methods to accurately predict a dense array of SNP genotypes in the dog could provide an important supplement to current analyses of array-based genotyping data. Here, we developed a reference panel of 4,885,283 SNPs in 83 dogs across 15 breeds using whole genome sequencing. We used this panel to predict the genotypes of 268 dogs across three breeds with 84,193 SNP array-derived genotypes as inputs. We then (1) performed breed clustering of the actual and imputed data; (2) evaluated several reference panel breed combinations to determine an optimal reference panel composition; and (3) compared the accuracy of two commonly used software algorithms (Beagle and IMPUTE2). Breed clustering was well preserved in the imputation process across eigenvalues representing 75 % of the variation in the imputed data. Using Beagle with a target panel from a single breed, genotype concordance was highest using a multi-breed reference panel (92.4 %) compared to a breed-specific reference panel (87.0 %) or a reference panel containing no breeds overlapping with the target panel (74.9 %). This finding was confirmed using target panels derived from two other breeds. Additionally, using the multi-breed reference panel, genotype concordance was slightly higher with IMPUTE2 (94.1 %) compared to Beagle; Pearson correlation coefficients were slightly higher for both software packages (0.946 for Beagle, 0.961 for IMPUTE2). Our findings demonstrate that genotype imputation from SNP array-derived data to whole genome-level genotypes is both feasible and accurate in the dog with appropriate breed overlap between the target and reference panels. PMID:27129452

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

PubMed Central

Wang, Shichen; Wong, Debbie; Forrest, Kerrie; Allen, Alexandra; Chao, Shiaoman; Huang, Bevan E; Maccaferri, Marco; Salvi, Silvio; Milner, Sara G; Cattivelli, Luigi; Mastrangelo, Anna M; Whan, Alex; Stephen, Stuart; Barker, Gary; Wieseke, Ralf; Plieske, Joerg; International Wheat Genome Sequencing Consortium; Lillemo, Morten; Mather, Diane; Appels, Rudi; Dolferus, Rudy; Brown-Guedira, Gina; Korol, Abraham; Akhunova, Alina R; Feuillet, Catherine; Salse, Jerome; Morgante, Michele; Pozniak, Curtis; Luo, Ming-Cheng; Dvorak, Jan; Morell, Matthew; Dubcovsky, Jorge; Ganal, Martin; Tuberosa, Roberto; Lawley, Cindy; Mikoulitch, Ivan; Cavanagh, Colin; Edwards, Keith J; Hayden, Matthew; Akhunov, Eduard

2014-01-01

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat. PMID:24646323

A novel approach to analyzing fMRI and SNP data via parallel independent component analysis

NASA Astrophysics Data System (ADS)

Liu, Jingyu; Pearlson, Godfrey; Calhoun, Vince; Windemuth, Andreas

2007-03-01

There is current interest in understanding genetic influences on brain function in both the healthy and the disordered brain. Parallel independent component analysis, a new method for analyzing multimodal data, is proposed in this paper and applied to functional magnetic resonance imaging (fMRI) and a single nucleotide polymorphism (SNP) array. The method aims to identify the independent components of each modality and the relationship between the two modalities. We analyzed 92 participants, including 29 schizophrenia (SZ) patients, 13 unaffected SZ relatives, and 50 healthy controls. We found a correlation of 0.79 between one fMRI component and one SNP component. The fMRI component consists of activations in cingulate gyrus, multiple frontal gyri, and superior temporal gyrus. The related SNP component is contributed to significantly by 9 SNPs located in sets of genes, including those coding for apolipoprotein A-I, and C-III, malate dehydrogenase 1 and the gamma-aminobutyric acid alpha-2 receptor. A significant difference in the presences of this SNP component is found between the SZ group (SZ patients and their relatives) and the control group. In summary, we constructed a framework to identify the interactions between brain functional and genetic information; our findings provide new insight into understanding genetic influences on brain function in a common mental disorder.

Development of new SNP derived cleaved amplified polymorphic sequence marker set and its successful utilization in the genetic analysis of seed color variation in barley.

PubMed

Bungartz, Annemarie; Klaus, Marius; Mathew, Boby; Léon, Jens; Naz, Ali Ahmad

2016-03-01

The aim of the present study was to develop a new cost effective PCR based CAPS marker set using advantages of high-throughput SNP genotyping. Initially, SNP survey was made using 20 diverse barley genotypes via 9k iSelect array genotyping that resulted in 6334 polymorphic SNP markers. Principle component analysis using this marker data showed fine differentiation of barley diverse gene pool. Till this end, we developed 200 SNP derived CAPS markers distributed across the genome covering around 991cM with an average marker density of 5.09cM. Further, we genotyped 68 CAPS markers in an F2 population (Cheri×ICB181160) segregating for seed color variation in barley. Genetic mapping of seed color revealed putative linkage of single nuclear gene on chromosome 1H. These findings showed the proof of concept for the development and utility of a newer cost effective genomic tool kit to analyze broader genetic resources of barley worldwide. Copyright © 2016 Elsevier Inc. All rights reserved.

Coverage and efficiency in current SNP chips

PubMed Central

Ha, Ngoc-Thuy; Freytag, Saskia; Bickeboeller, Heike

2014-01-01

To answer the question as to which commercial high-density SNP chip covers most of the human genome given a fixed budget, we compared the performance of 12 chips of different sizes released by Affymetrix and Illumina for the European, Asian, and African populations. These include Affymetrix' relatively new population-optimized arrays, whose SNP sets are each tailored toward a specific ethnicity. Our evaluation of the chips included the use of two measures, efficiency and cost–benefit ratio, which we developed as supplements to genetic coverage. Unlike coverage, these measures factor in the price of a chip or its substitute size (number of SNPs on chip), allowing comparisons to be drawn between differently priced chips. In this fashion, we identified the Affymetrix population-optimized arrays as offering the most cost-effective coverage for the Asian and African population. For the European population, we established the Illumina Human Omni 2.5-8 as the preferred choice. Interestingly, the Affymetrix chip tailored toward an Eastern Asian subpopulation performed well for all three populations investigated. However, our coverage estimates calculated for all chips proved much lower than those advertised by the producers. All our analyses were based on the 1000 Genome Project as reference population. PMID:24448550

GEE-based SNP set association test for continuous and discrete traits in family-based association studies.

PubMed

Wang, Xuefeng; Lee, Seunggeun; Zhu, Xiaofeng; Redline, Susan; Lin, Xihong

2013-12-01

Family-based genetic association studies of related individuals provide opportunities to detect genetic variants that complement studies of unrelated individuals. Most statistical methods for family association studies for common variants are single marker based, which test one SNP a time. In this paper, we consider testing the effect of an SNP set, e.g., SNPs in a gene, in family studies, for both continuous and discrete traits. Specifically, we propose a generalized estimating equations (GEEs) based kernel association test, a variance component based testing method, to test for the association between a phenotype and multiple variants in an SNP set jointly using family samples. The proposed approach allows for both continuous and discrete traits, where the correlation among family members is taken into account through the use of an empirical covariance estimator. We derive the theoretical distribution of the proposed statistic under the null and develop analytical methods to calculate the P-values. We also propose an efficient resampling method for correcting for small sample size bias in family studies. The proposed method allows for easily incorporating covariates and SNP-SNP interactions. Simulation studies show that the proposed method properly controls for type I error rates under both random and ascertained sampling schemes in family studies. We demonstrate through simulation studies that our approach has superior performance for association mapping compared to the single marker based minimum P-value GEE test for an SNP-set effect over a range of scenarios. We illustrate the application of the proposed method using data from the Cleveland Family GWAS Study. © 2013 WILEY PERIODICALS, INC.

Comprehensive performance comparison of high-resolution array platforms for genome-wide Copy Number Variation (CNV) analysis in humans.

PubMed

Haraksingh, Rajini R; Abyzov, Alexej; Urban, Alexander Eckehart

2017-04-24

High-resolution microarray technology is routinely used in basic research and clinical practice to efficiently detect copy number variants (CNVs) across the entire human genome. A new generation of arrays combining high probe densities with optimized designs will comprise essential tools for genome analysis in the coming years. We systematically compared the genome-wide CNV detection power of all 17 available array designs from the Affymetrix, Agilent, and Illumina platforms by hybridizing the well-characterized genome of 1000 Genomes Project subject NA12878 to all arrays, and performing data analysis using both manufacturer-recommended and platform-independent software. We benchmarked the resulting CNV call sets from each array using a gold standard set of CNVs for this genome derived from 1000 Genomes Project whole genome sequencing data. The arrays tested comprise both SNP and aCGH platforms with varying designs and contain between ~0.5 to ~4.6 million probes. Across the arrays CNV detection varied widely in number of CNV calls (4-489), CNV size range (~40 bp to ~8 Mbp), and percentage of non-validated CNVs (0-86%). We discovered strikingly strong effects of specific array design principles on performance. For example, some SNP array designs with the largest numbers of probes and extensive exonic coverage produced a considerable number of CNV calls that could not be validated, compared to designs with probe numbers that are sometimes an order of magnitude smaller. This effect was only partially ameliorated using different analysis software and optimizing data analysis parameters. High-resolution microarrays will continue to be used as reliable, cost- and time-efficient tools for CNV analysis. However, different applications tolerate different limitations in CNV detection. Our study quantified how these arrays differ in total number and size range of detected CNVs as well as sensitivity, and determined how each array balances these attributes. This analysis will inform appropriate array selection for future CNV studies, and allow better assessment of the CNV-analytical power of both published and ongoing array-based genomics studies. Furthermore, our findings emphasize the importance of concurrent use of multiple analysis algorithms and independent experimental validation in array-based CNV detection studies.

Diversity analysis of cotton (Gossypium hirsutum L.) germplasm using the CottonSNP63K Array

USDA-ARS?s Scientific Manuscript database

Cotton germplasm resources contain beneficial alleles that can be exploited to develop germplasm adapting to emerging environmental and climate conditions, and this germplasm has commonly been characterized based on phenotypes. However, phenotypic profiles are limited by what can be observed and me...

GACT: a Genome build and Allele definition Conversion Tool for SNP imputation and meta-analysis in genetic association studies.

PubMed

Sulovari, Arvis; Li, Dawei

2014-07-19

Genome-wide association studies (GWAS) have successfully identified genes associated with complex human diseases. Although much of the heritability remains unexplained, combining single nucleotide polymorphism (SNP) genotypes from multiple studies for meta-analysis will increase the statistical power to identify new disease-associated variants. Meta-analysis requires same allele definition (nomenclature) and genome build among individual studies. Similarly, imputation, commonly-used prior to meta-analysis, requires the same consistency. However, the genotypes from various GWAS are generated using different genotyping platforms, arrays or SNP-calling approaches, resulting in use of different genome builds and allele definitions. Incorrect assumptions of identical allele definition among combined GWAS lead to a large portion of discarded genotypes or incorrect association findings. There is no published tool that predicts and converts among all major allele definitions. In this study, we have developed a tool, GACT, which stands for Genome build and Allele definition Conversion Tool, that predicts and inter-converts between any of the common SNP allele definitions and between the major genome builds. In addition, we assessed several factors that may affect imputation quality, and our results indicated that inclusion of singletons in the reference had detrimental effects while ambiguous SNPs had no measurable effect. Unexpectedly, exclusion of genotypes with missing rate > 0.001 (40% of study SNPs) showed no significant decrease of imputation quality (even significantly higher when compared to the imputation with singletons in the reference), especially for rare SNPs. GACT is a new, powerful, and user-friendly tool with both command-line and interactive online versions that can accurately predict, and convert between any of the common allele definitions and between genome builds for genome-wide meta-analysis and imputation of genotypes from SNP-arrays or deep-sequencing, particularly for data from the dbGaP and other public databases. http://www.uvm.edu/genomics/software/gact.

A SNP resource for Douglas-fir: de novo transcriptome assembly and SNP detection and validation.

PubMed

Howe, Glenn T; Yu, Jianbin; Knaus, Brian; Cronn, Richard; Kolpak, Scott; Dolan, Peter; Lorenz, W Walter; Dean, Jeffrey F D

2013-02-28

Douglas-fir (Pseudotsuga menziesii), one of the most economically and ecologically important tree species in the world, also has one of the largest tree breeding programs. Although the coastal and interior varieties of Douglas-fir (vars. menziesii and glauca) are native to North America, the coastal variety is also widely planted for timber production in Europe, New Zealand, Australia, and Chile. Our main goal was to develop a SNP resource large enough to facilitate genomic selection in Douglas-fir breeding programs. To accomplish this, we developed a 454-based reference transcriptome for coastal Douglas-fir, annotated and evaluated the quality of the reference, identified putative SNPs, and then validated a sample of those SNPs using the Illumina Infinium genotyping platform. We assembled a reference transcriptome consisting of 25,002 isogroups (unique gene models) and 102,623 singletons from 2.76 million 454 and Sanger cDNA sequences from coastal Douglas-fir. We identified 278,979 unique SNPs by mapping the 454 and Sanger sequences to the reference, and by mapping four datasets of Illumina cDNA sequences from multiple seed sources, genotypes, and tissues. The Illumina datasets represented coastal Douglas-fir (64.00 and 13.41 million reads), interior Douglas-fir (80.45 million reads), and a Yakima population similar to interior Douglas-fir (8.99 million reads). We assayed 8067 SNPs on 260 trees using an Illumina Infinium SNP genotyping array. Of these SNPs, 5847 (72.5%) were called successfully and were polymorphic. Based on our validation efficiency, our SNP database may contain as many as ~200,000 true SNPs, and as many as ~69,000 SNPs that could be genotyped at ~20,000 gene loci using an Infinium II array-more SNPs than are needed to use genomic selection in tree breeding programs. Ultimately, these genomic resources will enhance Douglas-fir breeding and allow us to better understand landscape-scale patterns of genetic variation and potential responses to climate change.

In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species?

PubMed Central

Lepoittevin, Camille; Frigerio, Jean-Marc; Garnier-Géré, Pauline; Salin, Franck; Cervera, María-Teresa; Vornam, Barbara; Harvengt, Luc; Plomion, Christophe

2010-01-01

Background There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (Pinus pinaster Ait.), a conifer characterized by a huge genome size (∼23.8 Gb/C). Methodology/Principal Findings A 384-SNPs GoldenGate genotyping array was built from i/ 184 SNPs originally detected in a set of 40 re-sequenced candidate genes (in vitro SNPs), chosen on the basis of functionality scores, presence of neighboring polymorphisms, minor allele frequencies and linkage disequilibrium and ii/ 200 SNPs screened from ESTs (in silico SNPs) selected based on the number of ESTs used for SNP detection, the SNP minor allele frequency and the quality of SNP flanking sequences. The global success rate of the assay was 66.9%, and a conversion rate (considering only polymorphic SNPs) of 51% was achieved. In vitro SNPs showed significantly higher genotyping-success and conversion rates than in silico SNPs (+11.5% and +18.5%, respectively). The reproducibility was 100%, and the genotyping error rate very low (0.54%, dropping down to 0.06% when removing four SNPs showing elevated error rates). Conclusions/Significance This study demonstrates that ESTs provide a resource for SNP identification in non-model species, which do not require any additional bench work and little bio-informatics analysis. However, the time and cost benefits of in silico SNPs are counterbalanced by a lower conversion rate than in vitro SNPs. This drawback is acceptable for population-based experiments, but could be dramatic in experiments involving samples from narrow genetic backgrounds. In addition, we showed that both the visual inspection of genotyping clusters and the estimation of a per SNP error rate should help identify markers that are not suitable to the GoldenGate technology in species characterized by a large and complex genome. PMID:20543950

A Coordinated Approach to Peach SNP Discovery in RosBREED

USDA-ARS?s Scientific Manuscript database

In the USDA-funded multi-institutional and trans-disciplinary project, “RosBREED”, crop-specific SNP genome scan platforms are being developed for peach, apple, strawberry, and cherry at a resolution of at least one polymorphic SNP marker every 5 cM in any random cross, for use in Pedigree-Based Ana...

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.

PubMed

Pendergrass, Sarah A; Verma, Shefali S; Holzinger, Emily R; Moore, Carrie B; Wallace, John; Dudek, Scott M; Huggins, Wayne; Kitchner, Terrie; Waudby, Carol; Berg, Richard; McCarty, Catherine A; Ritchie, Marylyn D

2013-01-01

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

Partitioned learning of deep Boltzmann machines for SNP data.

PubMed

Hess, Moritz; Lenz, Stefan; Blätte, Tamara J; Bullinger, Lars; Binder, Harald

2017-10-15

Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen the joint distribution of SNPs, followed by training several DBMs on SNP partitions that were identified by the screening. Aggregate features representing SNP patterns and the corresponding SNPs are extracted from the DBMs by a combination of statistical tests and sparse regression. In simulated case-control data, we show how this can uncover complex SNP patterns and augment results from univariate approaches, while maintaining type 1 error control. Time-to-event endpoints are considered in an application with acute myeloid leukemia patients, where SNP patterns are modeled after a pre-screening based on gene expression data. The proposed approach identified three SNPs that seem to jointly influence survival in a validation dataset. This indicates the added value of jointly investigating SNPs compared to standard univariate analyses and makes partitioned learning of DBMs an interesting complementary approach when analyzing SNP data. A Julia package is provided at 'http://github.com/binderh/BoltzmannMachines.jl'. binderh@imbi.uni-freiburg.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Comprehensive high-resolution genomic profiling and cytogenetics of human chondrocyte cultures by GTG-banding, locus-specific FISH, SKY and SNP array.

PubMed

Wallenborn, M; Petters, O; Rudolf, D; Hantmann, H; Richter, M; Ahnert, P; Rohani, L; Smink, J J; Bulwin, G C; Krupp, W; Schulz, R M; Holland, H

2018-04-23

In the development of cell-based medicinal products, it is crucial to guarantee that the application of such an advanced therapy medicinal product (ATMP) is safe for the patients. The consensus of the European regulatory authorities is: "In conclusion, on the basis of the state of art, conventional karyotyping can be considered a valuable and useful technique to analyse chromosomal stability during preclinical studies". 408 chondrocyte samples (84 monolayers and 324 spheroids) from six patients were analysed using trypsin-Giemsa staining, spectral karyotyping and fluorescence in situ hybridisation, to evaluate the genetic stability of chondrocyte samples from non-clinical studies. Single nucleotide polymorphism (SNP) array analysis was performed on chondrocyte spheroids from five of the six donors. Applying this combination of techniques, the genetic analyses performed revealed no significant genetic instability until passage 3 in monolayer cells and interphase cells from spheroid cultures at different time points. Clonal occurrence of polyploid metaphases and endoreduplications were identified associated with prolonged cultivation time. Also, gonosomal losses were observed in chondrocyte spheroids, with increasing passage and duration of the differentiation phase. Interestingly, in one of the donors, chromosomal aberrations that are also described in extraskeletal myxoid chondrosarcoma were identified. The SNP array analysis exhibited chromosomal aberrations in two donors and copy neutral losses of heterozygosity regions in four donors. This study showed the necessity of combined genetic analyses at defined cultivation time points in quality studies within the field of cell therapy.

Combination of RNAseq and SNP nanofluidic array reveals the center of genetic diversity of cacao pathogen Moniliophthora roreri in the upper Magdalena Valley of Colombia and its clonality.

PubMed

Ali, Shahin S; Shao, Jonathan; Strem, Mary D; Phillips-Mora, Wilberth; Zhang, Dapeng; Meinhardt, Lyndel W; Bailey, Bryan A

2015-01-01

Moniliophthora roreri is the fungal pathogen that causes frosty pod rot (FPR) disease of Theobroma cacao L., the source of chocolate. FPR occurs in most of the cacao producing countries in the Western Hemisphere, causing yield losses up to 80%. Genetic diversity within the FPR pathogen population may allow the population to adapt to changing environmental conditions and adapt to enhanced resistance in the host plant. The present study developed single nucleotide polymorphism (SNP) markers from RNASeq results for 13 M. roreri isolates and validated the markers for their ability to reveal genetic diversity in an international M. roreri collection. The SNP resources reported herein represent the first study of RNA sequencing (RNASeq)-derived SNP validation in M. roreri and demonstrates the utility of RNASeq as an approach for de novo SNP identification in M. roreri. A total of 88 polymorphic SNPs were used to evaluate the genetic diversity of 172 M. roreri cacao isolates resulting in 37 distinct genotypes (including 14 synonymous groups). Absence of heterozygosity for the 88 SNP markers indicates reproduction in M. roreri is clonal and likely due to a homothallic life style. The upper Magdalena Valley of Colombia showed the highest levels of genetic diversity with 20 distinct genotypes of which 13 were limited to this region, and indicates this region as the possible center of origin for M. roreri.

Combination of RNAseq and SNP nanofluidic array reveals the center of genetic diversity of cacao pathogen Moniliophthora roreri in the upper Magdalena Valley of Colombia and its clonality

PubMed Central

Ali, Shahin S.; Shao, Jonathan; Strem, Mary D.; Phillips-Mora, Wilberth; Zhang, Dapeng; Meinhardt, Lyndel W.; Bailey, Bryan A.

2015-01-01

Moniliophthora roreri is the fungal pathogen that causes frosty pod rot (FPR) disease of Theobroma cacao L., the source of chocolate. FPR occurs in most of the cacao producing countries in the Western Hemisphere, causing yield losses up to 80%. Genetic diversity within the FPR pathogen population may allow the population to adapt to changing environmental conditions and adapt to enhanced resistance in the host plant. The present study developed single nucleotide polymorphism (SNP) markers from RNASeq results for 13 M. roreri isolates and validated the markers for their ability to reveal genetic diversity in an international M. roreri collection. The SNP resources reported herein represent the first study of RNA sequencing (RNASeq)-derived SNP validation in M. roreri and demonstrates the utility of RNASeq as an approach for de novo SNP identification in M. roreri. A total of 88 polymorphic SNPs were used to evaluate the genetic diversity of 172 M. roreri cacao isolates resulting in 37 distinct genotypes (including 14 synonymous groups). Absence of heterozygosity for the 88 SNP markers indicates reproduction in M. roreri is clonal and likely due to a homothallic life style. The upper Magdalena Valley of Colombia showed the highest levels of genetic diversity with 20 distinct genotypes of which 13 were limited to this region, and indicates this region as the possible center of origin for M. roreri. PMID:26379633

Sequential sentinel SNP Regional Association Plots (SSS-RAP): an approach for testing independence of SNP association signals using meta-analysis data.

PubMed

Zheng, Jie; Gaunt, Tom R; Day, Ian N M

2013-01-01

Genome-Wide Association Studies (GWAS) frequently incorporate meta-analysis within their framework. However, conditional analysis of individual-level data, which is an established approach for fine mapping of causal sites, is often precluded where only group-level summary data are available for analysis. Here, we present a numerical and graphical approach, "sequential sentinel SNP regional association plot" (SSS-RAP), which estimates regression coefficients (beta) with their standard errors using the meta-analysis summary results directly. Under an additive model, typical for genes with small effect, the effect for a sentinel SNP can be transformed to the predicted effect for a possibly dependent SNP through a 2×2 2-SNP haplotypes table. The approach assumes Hardy-Weinberg equilibrium for test SNPs. SSS-RAP is available as a Web-tool (http://apps.biocompute.org.uk/sssrap/sssrap.cgi). To develop and illustrate SSS-RAP we analyzed lipid and ECG traits data from the British Women's Heart and Health Study (BWHHS), evaluated a meta-analysis for ECG trait and presented several simulations. We compared results with existing approaches such as model selection methods and conditional analysis. Generally findings were consistent. SSS-RAP represents a tool for testing independence of SNP association signals using meta-analysis data, and is also a convenient approach based on biological principles for fine mapping in group level summary data. © 2012 Blackwell Publishing Ltd/University College London.

KinSNP software for homozygosity mapping of disease genes using SNP microarrays.

PubMed

Amir, El-Ad David; Bartal, Ofer; Morad, Efrat; Nagar, Tal; Sheynin, Jony; Parvari, Ruti; Chalifa-Caspi, Vered

2010-08-01

Consanguineous families affected with a recessive genetic disease caused by homozygotisation of a mutation offer a unique advantage for positional cloning of rare diseases. Homozygosity mapping of patient genotypes is a powerful technique for the identification of the genomic locus harbouring the causing mutation. This strategy relies on the observation that in these patients a large region spanning the disease locus is also homozygous with high probability. The high marker density in single nucleotide polymorphism (SNP) arrays is extremely advantageous for homozygosity mapping. We present KinSNP, a user-friendly software tool for homozygosity mapping using SNP arrays. The software searches for stretches of SNPs which are homozygous to the same allele in all ascertained sick individuals. User-specified parameters control the number of allowed genotyping 'errors' within homozygous blocks. Candidate disease regions are then reported in a detailed, coloured Excel file, along with genotypes of family members and healthy controls. An interactive genome browser has been included which shows homozygous blocks, individual genotypes, genes and further annotations along the chromosomes, with zooming and scrolling capabilities. The software has been used to identify the location of a mutated gene causing insensitivity to pain in a large Bedouin family. KinSNP is freely available from.

Validation of Pooled Whole-Genome Re-Sequencing in Arabidopsis lyrata.

PubMed

Fracassetti, Marco; Griffin, Philippa C; Willi, Yvonne

2015-01-01

Sequencing pooled DNA of multiple individuals from a population instead of sequencing individuals separately has become popular due to its cost-effectiveness and simple wet-lab protocol, although some criticism of this approach remains. Here we validated a protocol for pooled whole-genome re-sequencing (Pool-seq) of Arabidopsis lyrata libraries prepared with low amounts of DNA (1.6 ng per individual). The validation was based on comparing single nucleotide polymorphism (SNP) frequencies obtained by pooling with those obtained by individual-based Genotyping By Sequencing (GBS). Furthermore, we investigated the effect of sample number, sequencing depth per individual and variant caller on population SNP frequency estimates. For Pool-seq data, we compared frequency estimates from two SNP callers, VarScan and Snape; the former employs a frequentist SNP calling approach while the latter uses a Bayesian approach. Results revealed concordance correlation coefficients well above 0.8, confirming that Pool-seq is a valid method for acquiring population-level SNP frequency data. Higher accuracy was achieved by pooling more samples (25 compared to 14) and working with higher sequencing depth (4.1× per individual compared to 1.4× per individual), which increased the concordance correlation coefficient to 0.955. The Bayesian-based SNP caller produced somewhat higher concordance correlation coefficients, particularly at low sequencing depth. We recommend pooling at least 25 individuals combined with sequencing at a depth of 100× to produce satisfactory frequency estimates for common SNPs (minor allele frequency above 0.05).

Three gangliogliomas: results of GTG-banding, SKY, genome-wide high resolution SNP-array, gene expression and review of the literature.

PubMed

Xu, Li-Xin; Holland, Heidrun; Kirsten, Holger; Ahnert, Peter; Krupp, Wolfgang; Bauer, Manfred; Schober, Ralf; Mueller, Wolf; Fritzsch, Dominik; Meixensberger, Jürgen; Koschny, Ronald

2015-04-01

According to the World Health Organization gangliogliomas are classified as well-differentiated and slowly growing neuroepithelial tumors, composed of neoplastic mature ganglion and glial cells. It is the most frequent tumor entity observed in patients with long-term epilepsy. Comprehensive cytogenetic and molecular cytogenetic data including high-resolution genomic profiling (single nucleotide polymorphism (SNP)-array) of gangliogliomas are scarce but necessary for a better oncological understanding of this tumor entity. For a detailed characterization at the single cell and cell population levels, we analyzed genomic alterations of three gangliogliomas using trypsin-Giemsa banding (GTG-banding) and by spectral karyotyping (SKY) in combination with SNP-array and gene expression array experiments. By GTG and SKY, we could confirm frequently detected chromosomal aberrations (losses within chromosomes 10, 13 and 22; gains within chromosomes 5, 7, 8 and 12), and identify so far unknown genetic aberrations like the unbalanced non-reciprocal translocation t(1;18)(q21;q21). Interestingly, we report on the second so far detected ganglioglioma with ring chromosome 1. Analyses of SNP-array data from two of the tumors and respective germline DNA (peripheral blood) identified few small gains and losses and a number of copy-neutral regions with loss of heterozygosity (LOH) in germline and in tumor tissue. In comparison to germline DNA, tumor tissues did not show substantial regions with significant loss or gain or with newly developed LOH. Gene expression analyses of tumor-specific genes revealed similarities in the profile of the analyzed samples regarding different relevant pathways. Taken together, we describe overlapping but also distinct and novel genetic aberrations of three gangliogliomas. © 2014 Japanese Society of Neuropathology.

Haplotype-based approach to known MS-associated regions increases the amount of explained risk

PubMed Central

Khankhanian, Pouya; Gourraud, Pierre-Antoine; Lizee, Antoine; Goodin, Douglas S

2015-01-01

Genome-wide association studies (GWAS), using single nucleotide polymorphisms (SNPs), have yielded 110 non-human leucocyte antigen genomic regions that are associated with multiple sclerosis (MS). Despite this large number of associations, however, only 28% of MS-heritability can currently be explained. Here we compare the use of multi-SNP-haplotypes to the use of single-SNPs as alternative methods to describe MS genetic risk. SNP-haplotypes (of various lengths from 1 up to 15 contiguous SNPs) were constructed at each of the 110 previously identified, MS-associated, genomic regions. Even after correcting for the larger number of statistical comparisons made when using the haplotype-method, in 32 of the regions, the SNP-haplotype based model was markedly more significant than the single-SNP based model. By contrast, in no region was the single-SNP based model similarly more significant than the SNP-haplotype based model. Moreover, when we included the 932 MS-associated SNP-haplotypes (that we identified from 102 regions) as independent variables into a logistic linear model, the amount of MS-heritability, as assessed by Nagelkerke's R-squared, was 38%, which was considerably better than 29%, which was obtained by using only single-SNPs. This study demonstrates that SNP-haplotypes can be used to fine-map the genetic associations within regions of interest previously identified by single-SNP GWAS. Moreover, the amount of the MS genetic risk explained by the SNP-haplotype associations in the 110 MS-associated genomic regions was considerably greater when using SNP-haplotypes than when using single-SNPs. Also, the use of SNP-haplotypes can lead to the discovery of new regions of interest, which have not been identified by a single-SNP GWAS. PMID:26185143

Insights Into Upland Cotton (Gossypium hirsutum L.) Genetic Recombination Based on 3 High-Density Single-Nucleotide Polymorphism and a Consensus Map Developed Independently With Common Parents.

PubMed

Ulloa, Mauricio; Hulse-Kemp, Amanda M; De Santiago, Luis M; Stelly, David M; Burke, John J

2017-01-01

High-density linkage maps are vital to supporting the correct placement of scaffolds and gene sequences on chromosomes and fundamental to contemporary organismal research and scientific approaches to genetic improvement, especially in paleopolyploids with exceptionally complex genomes, eg, upland cotton ( Gossypium hirsutum L., "2n = 52"). Three independently developed intraspecific upland mapping populations were analyzed to generate 3 high-density genetic linkage single-nucleotide polymorphism (SNP) maps and a consensus map using the CottonSNP63K array. The populations consisted of a previously reported F 2 , a recombinant inbred line (RIL), and reciprocal RIL population, from "Phytogen 72" and "Stoneville 474" cultivars. The cluster file provided 7417 genotyped SNP markers, resulting in 26 linkage groups corresponding to the 26 chromosomes (c) of the allotetraploid upland cotton (AD) 1 arisen from the merging of 2 genomes ("A" Old World and "D" New World). Patterns of chromosome-specific recombination were largely consistent across mapping populations. The high-density genetic consensus map included 7244 SNP markers that spanned 3538 cM and comprised 3824 SNP bins, of which 1783 and 2041 were in the A t and D t subgenomes with 1825 and 1713 cM map lengths, respectively. Subgenome average distances were nearly identical, indicating that subgenomic differences in bin number arose due to the high numbers of SNPs on the D t subgenome. Examination of expected recombination frequency or crossovers (COs) on the chromosomes within each population of the 2 subgenomes revealed that COs were also not affected by the SNPs or SNP bin number in these subgenomes. Comparative alignment analyses identified historical ancestral A t -subgenomic translocations of c02 and c03, as well as of c04 and c05. The consensus map SNP sequences aligned with high congruency to the NBI assembly of Gossypium hirsutum . However, the genomic comparisons revealed evidence of additional unconfirmed possible duplications, inversions and translocations, and unbalance SNP sequence homology or SNP sequence/loci genomic dominance, or homeolog loci bias of the upland tetraploid A t and D t subgenomes. The alignments indicated that 364 SNP-associated previously unintegrated scaffolds can be placed in pseudochromosomes of the NBI G hirsutum assembly. This is the first intraspecific SNP genetic linkage consensus map assembled in G hirsutum with a core of reproducible mendelian SNP markers assayed on different populations and it provides further knowledge of chromosome arrangement of genic and nongenic SNPs. Together, the consensus map and RIL populations provide a synergistically useful platform for localizing and identifying agronomically important loci for improvement of the cotton crop.

Analysis of genetic diversity using SNP markers in oat

USDA-ARS?s Scientific Manuscript database

A large-scale single nucleotide polymorphism (SNP) discovery was carried out in cultivated oat using Roche 454 sequencing methods. DNA sequences were generated from cDNAs originating from a panel of 20 diverse oat cultivars, and from Diversity Array Technology (DArT) genomic complexity reductions fr...

SNP-based genotyping in lentil: linking sequence information with phenotypes

USDA-ARS?s Scientific Manuscript database

Lentil (Lens culinaris) has been late to enter the world of high throughput molecular analysis due to a general lack of genomic resources. Using a 454 sequencing-based approach, SNPs have been identified in genes across the lentil genome. Several hundred have been turned into single SNP KASP assay...

Estimation and partitioning of (co)heritability of inflammatory bowel disease from GWAS and immunochip data.

PubMed

Chen, Guo-Bo; Lee, Sang Hong; Brion, Marie-Jo A; Montgomery, Grant W; Wray, Naomi R; Radford-Smith, Graham L; Visscher, Peter M

2014-09-01

As custom arrays are cheaper than generic GWAS arrays, larger sample size is achievable for gene discovery. Custom arrays can tag more variants through denser genotyping of SNPs at associated loci, but at the cost of losing genome-wide coverage. Balancing this trade-off is important for maximizing experimental designs. We quantified both the gain in captured SNP-heritability at known candidate regions and the loss due to imperfect genome-wide coverage for inflammatory bowel disease using immunochip (iChip) and imputed GWAS data on 61,251 and 38.550 samples, respectively. For Crohn's disease (CD), the iChip and GWAS data explained 19 and 26% of variation in liability, respectively, and SNPs in the densely genotyped iChip regions explained 13% of the SNP-heritability for both the iChip and GWAS data. For ulcerative colitis (UC), the iChip and GWAS data explained 15 and 19% of variation in liability, respectively, and the dense iChip regions explained 10 and 9% of the SNP-heritability in the iChip and the GWAS data. From bivariate analyses, estimates of the genetic correlation in risk between CD and UC were 0.75 (SE 0.017) and 0.62 (SE 0.042) for the iChip and GWAS data, respectively. We also quantified the SNP-heritability of genomic regions that did or did not contain the previous 163 GWAS hits for CD and UC, and SNP-heritability of the overlapping loci between the densely genotyped iChip regions and the 163 GWAS hits. For both diseases, over different genomic partitioning, the densely genotyped regions on the iChip tagged at least as much variation in liability as in the corresponding regions in the GWAS data, however a certain amount of tagged SNP-heritability in the GWAS data was lost using the iChip due to the low coverage at unselected regions. These results imply that custom arrays with a GWAS backbone will facilitate more gene discovery, both at associated and novel loci. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

CIDR

Science.gov Websites

NIH CIDR Program Studies For whole exome sequencing projects, we pretest all samples using a high -density SNP array (>200,000 markers). For custom targeted sequencing, we pretest all samples using a 96 pretest samples using a 96 SNP GoldenGate assay. This extensive pretesting allows us to unambiguously tie

Novel applications of array comparative genomic hybridization in molecular diagnostics.

PubMed

Cheung, Sau W; Bi, Weimin

2018-05-31

In 2004, the implementation of array comparative genomic hybridization (array comparative genome hybridization [CGH]) into clinical practice marked a new milestone for genetic diagnosis. Array CGH and single-nucleotide polymorphism (SNP) arrays enable genome-wide detection of copy number changes in a high resolution, and therefore microarray has been recognized as the first-tier test for patients with intellectual disability or multiple congenital anomalies, and has also been applied prenatally for detection of clinically relevant copy number variations in the fetus. Area covered: In this review, the authors summarize the evolution of array CGH technology from their diagnostic laboratory, highlighting exonic SNP arrays developed in the past decade which detect small intragenic copy number changes as well as large DNA segments for the region of heterozygosity. The applications of array CGH to human diseases with different modes of inheritance with the emphasis on autosomal recessive disorders are discussed. Expert commentary: An exonic array is a powerful and most efficient clinical tool in detecting genome wide small copy number variants in both dominant and recessive disorders. However, whole-genome sequencing may become the single integrated platform for detection of copy number changes, single-nucleotide changes as well as balanced chromosomal rearrangements in the near future.

Genomic patterns of introgression in rainbow and westslope cutthroat trout illuminated by overlapping paired-end RAD sequencing

USGS Publications Warehouse

Hohenlohe, Paul A.; Day, Mitch D.; Amish, Stephen J.; Miller, Michael R.; Kamps-Hughes, Nick; Boyer, Matthew C.; Muhlfeld, Clint C.; Allendorf, Fred W.; Johnson, Eric A.; Luikart, Gordon

2013-01-01

Rapid and inexpensive methods for genomewide single nucleotide polymorphism (SNP) discovery and genotyping are urgently needed for population management and conservation. In hybridized populations, genomic techniques that can identify and genotype thousands of species-diagnostic markers would allow precise estimates of population- and individual-level admixture as well as identification of 'super invasive' alleles, which show elevated rates of introgression above the genomewide background (likely due to natural selection). Techniques like restriction-site-associated DNA (RAD) sequencing can discover and genotype large numbers of SNPs, but they have been limited by the length of continuous sequence data they produce with Illumina short-read sequencing. We present a novel approach, overlapping paired-end RAD sequencing, to generate RAD contigs of >300–400 bp. These contigs provide sufficient flanking sequence for design of high-throughput SNP genotyping arrays and strict filtering to identify duplicate paralogous loci. We applied this approach in five populations of native westslope cutthroat trout that previously showed varying (low) levels of admixture from introduced rainbow trout (RBT). We produced 77 141 RAD contigs and used these data to filter and genotype 3180 previously identified species-diagnostic SNP loci. Our population-level and individual-level estimates of admixture were generally consistent with previous microsatellite-based estimates from the same individuals. However, we observed slightly lower admixture estimates from genomewide markers, which might result from natural selection against certain genome regions, different genomic locations for microsatellites vs. RAD-derived SNPs and/or sampling error from the small number of microsatellite loci (n = 7). We also identified candidate adaptive super invasive alleles from RBT that had excessively high admixture proportions in hybridized cutthroat trout populations.

Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data.

PubMed

Favero, F; Joshi, T; Marquard, A M; Birkbak, N J; Krzystanek, M; Li, Q; Szallasi, Z; Eklund, A C

2015-01-01

Exome or whole-genome deep sequencing of tumor DNA along with paired normal DNA can potentially provide a detailed picture of the somatic mutations that characterize the tumor. However, analysis of such sequence data can be complicated by the presence of normal cells in the tumor specimen, by intratumor heterogeneity, and by the sheer size of the raw data. In particular, determination of copy number variations from exome sequencing data alone has proven difficult; thus, single nucleotide polymorphism (SNP) arrays have often been used for this task. Recently, algorithms to estimate absolute, but not allele-specific, copy number profiles from tumor sequencing data have been described. We developed Sequenza, a software package that uses paired tumor-normal DNA sequencing data to estimate tumor cellularity and ploidy, and to calculate allele-specific copy number profiles and mutation profiles. We applied Sequenza, as well as two previously published algorithms, to exome sequence data from 30 tumors from The Cancer Genome Atlas. We assessed the performance of these algorithms by comparing their results with those generated using matched SNP arrays and processed by the allele-specific copy number analysis of tumors (ASCAT) algorithm. Comparison between Sequenza/exome and SNP/ASCAT revealed strong correlation in cellularity (Pearson's r = 0.90) and ploidy estimates (r = 0.42, or r = 0.94 after manual inspecting alternative solutions). This performance was noticeably superior to previously published algorithms. In addition, in artificial data simulating normal-tumor admixtures, Sequenza detected the correct ploidy in samples with tumor content as low as 30%. The agreement between Sequenza and SNP array-based copy number profiles suggests that exome sequencing alone is sufficient not only for identifying small scale mutations but also for estimating cellularity and inferring DNA copy number aberrations. © The Author 2014. Published by Oxford University Press on behalf of the European Society for Medical Oncology.

Single Nucleotide Polymorphism Array Analysis of Bone Marrow Failure Patients Reveals Characteristic Patterns of Genetic Changes

PubMed Central

Babushok, Daria V.; Xie, Hongbo M.; Roth, Jacquelyn J.; Perdigones, Nieves; Olson, Timothy S.; Cockroft, Joshua D.; Gai, Xiaowu; Perin, Juan C.; Li, Yimei; Paessler, Michele E.; Hakonarson, Hakon; Podsakoff, Gregory M.; Mason, Philip J.; Biegel, Jaclyn A.; Bessler, Monica

2013-01-01

Summary The bone marrow failure syndromes (BMFS) are a heterogeneous group of rare blood disorders characterized by inadequate haematopoiesis, clonal evolution, and increased risk of leukaemia. Single nucleotide polymorphism arrays (SNP-A) have been proposed as a tool for surveillance of clonal evolution in BMFS. To better understand the natural history of BMFS and to assess the clinical utility of SNP-A in these disorders, we analysed 124 SNP-A from a comprehensively characterized cohort of 91 patients at our BMFS centre. SNP-A were correlated with medical histories, haematopathology, cytogenetic and molecular data. To assess clonal evolution, longitudinal analysis of SNP-A was performed in 25 patients. We found that acquired copy number-neutral loss of heterozygosity (CN-LOH) was significantly more frequent in acquired aplastic anaemia (aAA) than in other BMFS (odds ratio 12.2, p<0.01). Homozygosity by descent was most common in congenital BMFS, frequently unmasking autosomal recessive mutations. Copy number variants (CNVs) were frequently polymorphic, and we identified CNVs enriched in neutropenia and aAA. Our results suggest that acquired CN-LOH is a general phenomenon in aAA that is probably mechanistically and prognostically distinct from typical CN-LOH of myeloid malignancies. Our analysis of clinical utility of SNP-A shows the highest yield of detecting new clonal haematopoiesis at diagnosis and at relapse. PMID:24116929

Single nucleotide polymorphism array analysis of bone marrow failure patients reveals characteristic patterns of genetic changes.

PubMed

Babushok, Daria V; Xie, Hongbo M; Roth, Jacquelyn J; Perdigones, Nieves; Olson, Timothy S; Cockroft, Joshua D; Gai, Xiaowu; Perin, Juan C; Li, Yimei; Paessler, Michele E; Hakonarson, Hakon; Podsakoff, Gregory M; Mason, Philip J; Biegel, Jaclyn A; Bessler, Monica

2014-01-01

The bone marrow failure syndromes (BMFS) are a heterogeneous group of rare blood disorders characterized by inadequate haematopoiesis, clonal evolution, and increased risk of leukaemia. Single nucleotide polymorphism arrays (SNP-A) have been proposed as a tool for surveillance of clonal evolution in BMFS. To better understand the natural history of BMFS and to assess the clinical utility of SNP-A in these disorders, we analysed 124 SNP-A from a comprehensively characterized cohort of 91 patients at our BMFS centre. SNP-A were correlated with medical histories, haematopathology, cytogenetic and molecular data. To assess clonal evolution, longitudinal analysis of SNP-A was performed in 25 patients. We found that acquired copy number-neutral loss of heterozygosity (CN-LOH) was significantly more frequent in acquired aplastic anaemia (aAA) than in other BMFS (odds ratio 12·2, P < 0·01). Homozygosity by descent was most common in congenital BMFS, frequently unmasking autosomal recessive mutations. Copy number variants (CNVs) were frequently polymorphic, and we identified CNVs enriched in neutropenia and aAA. Our results suggest that acquired CN-LOH is a general phenomenon in aAA that is probably mechanistically and prognostically distinct from typical CN-LOH of myeloid malignancies. Our analysis of clinical utility of SNP-A shows the highest yield of detecting new clonal haematopoiesis at diagnosis and at relapse. © 2013 John Wiley & Sons Ltd.

Learning about human population history from ancient and modern genomes.

PubMed

Stoneking, Mark; Krause, Johannes

2011-08-18

Genome-wide data, both from SNP arrays and from complete genome sequencing, are becoming increasingly abundant and are now even available from extinct hominins. These data are providing new insights into population history; in particular, when combined with model-based analytical approaches, genome-wide data allow direct testing of hypotheses about population history. For example, genome-wide data from both contemporary populations and extinct hominins strongly support a single dispersal of modern humans from Africa, followed by two archaic admixture events: one with Neanderthals somewhere outside Africa and a second with Denisovans that (so far) has only been detected in New Guinea. These new developments promise to reveal new stories about human population history, without having to resort to storytelling.

Genetic Linkage Mapping of Economically Important Traits in Cultivated Tetraploid Potato (Solanum tuberosum L.).

PubMed

Massa, Alicia N; Manrique-Carpintero, Norma C; Coombs, Joseph J; Zarka, Daniel G; Boone, Anne E; Kirk, William W; Hackett, Christine A; Bryan, Glenn J; Douches, David S

2015-09-14

The objective of this study was to construct a single nucleotide polymorphism (SNP)-based genetic map at the cultivated tetraploid level to locate quantitative trait loci (QTL) contributing to economically important traits in potato (Solanum tuberosum L.). The 156 F1 progeny and parents of a cross (MSL603) between "Jacqueline Lee" and "MSG227-2" were genotyped using the Infinium 8303 Potato Array. Furthermore, the progeny and parents were evaluated for foliar late blight reaction to isolates of the US-8 genotype of Phytophthora infestans (Mont.) de Bary and vine maturity. Linkage analyses and QTL mapping were performed using a novel approach that incorporates allele dosage information. The resulting genetic maps contained 1972 SNP markers with an average density of 1.36 marker per cM. QTL mapping identified the major source of late blight resistance in "Jacqueline Lee." The best SNP marker mapped ~0.54 Mb from a resistance hotspot on the long arm of chromosome 9. For vine maturity, the major-effect QTL was located on chromosome 5 with allelic effects from both parents. A candidate SNP marker for this trait mapped ~0.25 Mb from the StCDF1 gene, which is a candidate gene for the maturity trait. The identification of markers for P. infestans resistance will enable the introgression of multiple sources of resistance through marker-assisted selection. Moreover, the discovery of a QTL for late blight resistance not linked to the QTL for vine maturity provides the opportunity to use marker-assisted selection for resistance independent of the selection for vine maturity classifications. Copyright © 2015 Massa et al.

Genetic Linkage Mapping of Economically Important Traits in Cultivated Tetraploid Potato (Solanum tuberosum L.)

PubMed Central

Massa, Alicia N.; Manrique-Carpintero, Norma C.; Coombs, Joseph J.; Zarka, Daniel G.; Boone, Anne E.; Kirk, William W.; Hackett, Christine A.; Bryan, Glenn J.; Douches, David S.

2015-01-01

The objective of this study was to construct a single nucleotide polymorphism (SNP)-based genetic map at the cultivated tetraploid level to locate quantitative trait loci (QTL) contributing to economically important traits in potato (Solanum tuberosum L.). The 156 F1 progeny and parents of a cross (MSL603) between “Jacqueline Lee” and “MSG227-2” were genotyped using the Infinium 8303 Potato Array. Furthermore, the progeny and parents were evaluated for foliar late blight reaction to isolates of the US-8 genotype of Phytophthora infestans (Mont.) de Bary and vine maturity. Linkage analyses and QTL mapping were performed using a novel approach that incorporates allele dosage information. The resulting genetic maps contained 1972 SNP markers with an average density of 1.36 marker per cM. QTL mapping identified the major source of late blight resistance in “Jacqueline Lee.” The best SNP marker mapped ∼0.54 Mb from a resistance hotspot on the long arm of chromosome 9. For vine maturity, the major-effect QTL was located on chromosome 5 with allelic effects from both parents. A candidate SNP marker for this trait mapped ∼0.25 Mb from the StCDF1 gene, which is a candidate gene for the maturity trait. The identification of markers for P. infestans resistance will enable the introgression of multiple sources of resistance through marker-assisted selection. Moreover, the discovery of a QTL for late blight resistance not linked to the QTL for vine maturity provides the opportunity to use marker-assisted selection for resistance independent of the selection for vine maturity classifications. PMID:26374597

Slider--maximum use of probability information for alignment of short sequence reads and SNP detection.

PubMed

Malhis, Nawar; Butterfield, Yaron S N; Ester, Martin; Jones, Steven J M

2009-01-01

A plethora of alignment tools have been created that are designed to best fit different types of alignment conditions. While some of these are made for aligning Illumina Sequence Analyzer reads, none of these are fully utilizing its probability (prb) output. In this article, we will introduce a new alignment approach (Slider) that reduces the alignment problem space by utilizing each read base's probabilities given in the prb files. Compared with other aligners, Slider has higher alignment accuracy and efficiency. In addition, given that Slider matches bases with probabilities other than the most probable, it significantly reduces the percentage of base mismatches. The result is that its SNP predictions are more accurate than other SNP prediction approaches used today that start from the most probable sequence, including those using base quality.

ITALICS: an algorithm for normalization and DNA copy number calling for Affymetrix SNP arrays.

PubMed

Rigaill, Guillem; Hupé, Philippe; Almeida, Anna; La Rosa, Philippe; Meyniel, Jean-Philippe; Decraene, Charles; Barillot, Emmanuel

2008-03-15

Affymetrix SNP arrays can be used to determine the DNA copy number measurement of 11 000-500 000 SNPs along the genome. Their high density facilitates the precise localization of genomic alterations and makes them a powerful tool for studies of cancers and copy number polymorphism. Like other microarray technologies it is influenced by non-relevant sources of variation, requiring correction. Moreover, the amplitude of variation induced by non-relevant effects is similar or greater than the biologically relevant effect (i.e. true copy number), making it difficult to estimate non-relevant effects accurately without including the biologically relevant effect. We addressed this problem by developing ITALICS, a normalization method that estimates both biological and non-relevant effects in an alternate, iterative manner, accurately eliminating irrelevant effects. We compared our normalization method with other existing and available methods, and found that ITALICS outperformed these methods for several in-house datasets and one public dataset. These results were validated biologically by quantitative PCR. The R package ITALICS (ITerative and Alternative normaLIzation and Copy number calling for affymetrix Snp arrays) has been submitted to Bioconductor.

Development and validation of the Axiom(®) Apple480K SNP genotyping array.

PubMed

Bianco, Luca; Cestaro, Alessandro; Linsmith, Gareth; Muranty, Hélène; Denancé, Caroline; Théron, Anthony; Poncet, Charles; Micheletti, Diego; Kerschbamer, Emanuela; Di Pierro, Erica A; Larger, Simone; Pindo, Massimo; Van de Weg, Eric; Davassi, Alessandro; Laurens, François; Velasco, Riccardo; Durel, Charles-Eric; Troggio, Michela

2016-04-01

Cultivated apple (Malus × domestica Borkh.) is one of the most important fruit crops in temperate regions, and has great economic and cultural value. The apple genome is highly heterozygous and has undergone a recent duplication which, combined with a rapid linkage disequilibrium decay, makes it difficult to perform genome-wide association (GWA) studies. Single nucleotide polymorphism arrays offer highly multiplexed assays at a relatively low cost per data point and can be a valid tool for the identification of the markers associated with traits of interest. Here, we describe the development and validation of a 487K SNP Affymetrix Axiom(®) genotyping array for apple and discuss its potential applications. The array has been built from the high-depth resequencing of 63 different cultivars covering most of the genetic diversity in cultivated apple. The SNPs were chosen by applying a focal points approach to enrich genic regions, but also to reach a uniform coverage of non-genic regions. A total of 1324 apple accessions, including the 92 progenies of two mapping populations, have been genotyped with the Axiom(®) Apple480K to assess the effectiveness of the array. A large majority of SNPs (359 994 or 74%) fell in the stringent class of poly high resolution polymorphisms. We also devised a filtering procedure to identify a subset of 275K very robust markers that can be safely used for germplasm surveys in apple. The Axiom(®) Apple480K has now been commercially released both for public and proprietary use and will likely be a reference tool for GWA studies in apple. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Identification of the varietal origin of loose leaf tea based on analysis of a single leaf by SNP nanofluidic array

USDA-ARS?s Scientific Manuscript database

Tea [Camellia sinensis (L.) O Kuntze] is an economically important crop cultivated in more than 50 countries. Production and marketing of premium specialty tea products provides opportunities for tea growers, the tea industry and consumers. Rapid market segmentation in the tea industry has resulted ...

Genome-Wide Association Study of a Varroa-Specific Defense Behavior in Honeybees (Apis mellifera)

PubMed Central

Spötter, Andreas; Gupta, Pooja; Mayer, Manfred; Reinsch, Norbert

2016-01-01

Honey bees are exposed to many damaging pathogens and parasites. The most devastating is Varroa destructor, which mainly affects the brood. A promising approach for preventing its spread is to breed Varroa-resistant honey bees. One trait that has been shown to provide significant resistance against the Varroa mite is hygienic behavior, which is a behavioral response of honeybee workers to brood diseases in general. Here, we report the use of an Affymetrix 44K SNP array to analyze SNPs associated with detection and uncapping of Varroa-parasitized brood by individual worker bees (Apis mellifera). For this study, 22 000 individually labeled bees were video-monitored and a sample of 122 cases and 122 controls was collected and analyzed to determine the dependence/independence of SNP genotypes from hygienic and nonhygienic behavior on a genome-wide scale. After false-discovery rate correction of the P values, 6 SNP markers had highly significant associations with the trait investigated (α < 0.01). Inspection of the genomic regions around these SNPs led to the discovery of putative candidate genes. PMID:26774061

A high-density intraspecific SNP linkage map of pigeonpea (Cajanas cajan L. Millsp.)

PubMed Central

Mandal, Paritra; Bhutani, Shefali; Dutta, Sutapa; Kumawat, Giriraj; Singh, Bikram Pratap; Chaudhary, A. K.; Yadav, Rekha; Gaikwad, K.; Sevanthi, Amitha Mithra; Datta, Subhojit; Raje, Ranjeet S.; Sharma, Tilak R.; Singh, Nagendra Kumar

2017-01-01

Pigeonpea (Cajanus cajan (L.) Millsp.) is a major food legume cultivated in semi-arid tropical regions including the Indian subcontinent, Africa, and Southeast Asia. It is an important source of protein, minerals, and vitamins for nearly 20% of the world population. Due to high carbon sequestration and drought tolerance, pigeonpea is an important crop for the development of climate resilient agriculture and nutritional security. However, pigeonpea productivity has remained low for decades because of limited genetic and genomic resources, and sparse utilization of landraces and wild pigeonpea germplasm. Here, we present a dense intraspecific linkage map of pigeonpea comprising 932 markers that span a total adjusted map length of 1,411.83 cM. The consensus map is based on three different linkage maps that incorporate a large number of single nucleotide polymorphism (SNP) markers derived from next generation sequencing data, using Illumina GoldenGate bead arrays, and genotyping with restriction site associated DNA (RAD) sequencing. The genotyping-by-sequencing enhanced the marker density but was met with limited success due to lack of common markers across the genotypes of mapping population. The integrated map has 547 bead-array SNP, 319 RAD-SNP, and 65 simple sequence repeat (SSR) marker loci. We also show here correspondence between our linkage map and published genome pseudomolecules of pigeonpea. The availability of a high-density linkage map will help improve the anchoring of the pigeonpea genome to its chromosomes and the mapping of genes and quantitative trait loci associated with useful agronomic traits. PMID:28654689

Making a chocolate chip: development and evaluation of a 6K SNP array for Theobroma cacao.

USDA-ARS?s Scientific Manuscript database

Theobroma cacao, the key ingredient in chocolate production, is one of the world's most important tree fruit crops, with ~4,000,000 metric tons produced across 50 countries. To move towards gene discovery and marker-assisted breeding in cacao, a single-nucleotide polymorphism (SNP) identification pr...

An evaluation of the genetic-matched pair study design using genome-wide SNP data from the European population.

PubMed

Lu, Timothy Tehua; Lao, Oscar; Nothnagel, Michael; Junge, Olaf; Freitag-Wolf, Sandra; Caliebe, Amke; Balascakova, Miroslava; Bertranpetit, Jaume; Bindoff, Laurence Albert; Comas, David; Holmlund, Gunilla; Kouvatsi, Anastasia; Macek, Milan; Mollet, Isabelle; Nielsen, Finn; Parson, Walther; Palo, Jukka; Ploski, Rafal; Sajantila, Antti; Tagliabracci, Adriano; Gether, Ulrik; Werge, Thomas; Rivadeneira, Fernando; Hofman, Albert; Uitterlinden, André Gerardus; Gieger, Christian; Wichmann, Heinz-Erich; Ruether, Andreas; Schreiber, Stefan; Becker, Christian; Nürnberg, Peter; Nelson, Matthew Roberts; Kayser, Manfred; Krawczak, Michael

2009-07-01

Genetic matching potentially provides a means to alleviate the effects of incomplete Mendelian randomization in population-based gene-disease association studies. We therefore evaluated the genetic-matched pair study design on the basis of genome-wide SNP data (309,790 markers; Affymetrix GeneChip Human Mapping 500K Array) from 2457 individuals, sampled at 23 different recruitment sites across Europe. Using pair-wise identity-by-state (IBS) as a matching criterion, we tried to derive a subset of markers that would allow identification of the best overall matching (BOM) partner for a given individual, based on the IBS status for the subset alone. However, our results suggest that, by following this approach, the prediction accuracy is only notably improved by the first 20 markers selected, and increases proportionally to the marker number thereafter. Furthermore, in a considerable proportion of cases (76.0%), the BOM of a given individual, based on the complete marker set, came from a different recruitment site than the individual itself. A second marker set, specifically selected for ancestry sensitivity using singular value decomposition, performed even more poorly and was no more capable of predicting the BOM than randomly chosen subsets. This leads us to conclude that, at least in Europe, the utility of the genetic-matched pair study design depends critically on the availability of comprehensive genotype information for both cases and controls.

Estimation of linkage disequilibrium and interspecific gene flow in Ficedula flycatchers by a newly developed 50k single-nucleotide polymorphism array

PubMed Central

Kawakami, Takeshi; Backström, Niclas; Burri, Reto; Husby, Arild; Olason, Pall; Rice, Amber M; Ålund, Murielle; Qvarnström, Anna; Ellegren, Hans

2014-01-01

With the access to draft genome sequence assemblies and whole-genome resequencing data from population samples, molecular ecology studies will be able to take truly genome-wide approaches. This now applies to an avian model system in ecological and evolutionary research: Old World flycatchers of the genus Ficedula, for which we recently obtained a 1.1 Gb collared flycatcher genome assembly and identified 13 million single-nucleotide polymorphism (SNP)s in population resequencing of this species and its sister species, pied flycatcher. Here, we developed a custom 50K Illumina iSelect flycatcher SNP array with markers covering 30 autosomes and the Z chromosome. Using a number of selection criteria for inclusion in the array, both genotyping success rate and polymorphism information content (mean marker heterozygosity = 0.41) were high. We used the array to assess linkage disequilibrium (LD) and hybridization in flycatchers. Linkage disequilibrium declined quickly to the background level at an average distance of 17 kb, but the extent of LD varied markedly within the genome and was more than 10-fold higher in ‘genomic islands’ of differentiation than in the rest of the genome. Genetic ancestry analysis identified 33 F1 hybrids but no later-generation hybrids from sympatric populations of collared flycatchers and pied flycatchers, contradicting earlier reports of backcrosses identified from much fewer number of markers. With an estimated divergence time as recently as <1 Ma, this suggests strong selection against F1 hybrids and unusually rapid evolution of reproductive incompatibility in an avian system. PMID:24784959

A Complex 6p25 Rearrangement in a Child With Multiple Epiphyseal Dysplasia

PubMed Central

Bedoyan, Jirair K.; Lesperance, Marci M.; Ackley, Todd; Iyer, Ramaswamy K.; Innis, Jeffrey W.; Misra, Vinod K.

2015-01-01

Genomic rearrangements are increasingly recognized as important contributors to human disease. Here we report on an 11½-year-old child with myopia, Duane retraction syndrome, bilateral mixed hearing loss, skeletal anomalies including multiple epiphyseal dysplasia, and global developmental delay, and a complex 6p25 genomic rearrangement. We have employed oligonucleotide-based comparative genomic hybridization arrays (aCGH) of different resolutions (44 and 244K) as well as a 1 M single nucleotide polymorphism (SNP) array to analyze this complex rearrangement. Our analyses reveal a complex rearrangement involving a ~2.21 Mb interstitial deletion, a ~240 kb terminal deletion, and a 70–80 kb region in between these two deletions that shows maintenance of genomic copy number. The interstitial deletion contains eight known genes, including three Forkhead box containing (FOX) transcription factors (FOXQ1, FOXF2, and FOXC1). The region maintaining genomic copy number partly overlaps the dual specificity protein phosphatase 22 (DUSP22) gene. Array analyses suggest a homozygous loss of genomic material at the 5′ end of DUSP22, which was corroborated using TaqMan® copy number analysis. It is possible that this homozygous genomic loss may render both copies of DUSP22 or its products non-functional. Our analysis suggests a rearrangement mechanism distinct from a previously reported replication-based error-prone mechanism without template switching for a specific 6p25 rearrangement with a 1.22 Mb interstitial deletion. Our study demonstrates the utility and limitations of using oligonucleotide-based aCGH and SNP array technologies of increasing resolutions in order to identify complex DNA rearrangements and gene disruptions. PMID:21204225

Accurate genomic predictions for BCWD resistance in rainbow trout are achieved using low-density SNP panels: Evidence that long-range LD is a major contributing factor.

PubMed

Vallejo, Roger L; Silva, Rafael M O; Evenhuis, Jason P; Gao, Guangtu; Liu, Sixin; Parsons, James E; Martin, Kyle E; Wiens, Gregory D; Lourenco, Daniela A L; Leeds, Timothy D; Palti, Yniv

2018-06-05

Previously accurate genomic predictions for Bacterial cold water disease (BCWD) resistance in rainbow trout were obtained using a medium-density single nucleotide polymorphism (SNP) array. Here, the impact of lower-density SNP panels on the accuracy of genomic predictions was investigated in a commercial rainbow trout breeding population. Using progeny performance data, the accuracy of genomic breeding values (GEBV) using 35K, 10K, 3K, 1K, 500, 300 and 200 SNP panels as well as a panel with 70 quantitative trait loci (QTL)-flanking SNP was compared. The GEBVs were estimated using the Bayesian method BayesB, single-step GBLUP (ssGBLUP) and weighted ssGBLUP (wssGBLUP). The accuracy of GEBVs remained high despite the sharp reductions in SNP density, and even with 500 SNP accuracy was higher than the pedigree-based prediction (0.50-0.56 versus 0.36). Furthermore, the prediction accuracy with the 70 QTL-flanking SNP (0.65-0.72) was similar to the panel with 35K SNP (0.65-0.71). Genomewide linkage disequilibrium (LD) analysis revealed strong LD (r 2  ≥ 0.25) spanning on average over 1 Mb across the rainbow trout genome. This long-range LD likely contributed to the accurate genomic predictions with the low-density SNP panels. Population structure analysis supported the hypothesis that long-range LD in this population may be caused by admixture. Results suggest that lower-cost, low-density SNP panels can be used for implementing genomic selection for BCWD resistance in rainbow trout breeding programs. © 2018 The Authors. This article is a U.S. Government work and is in the public domain in the USA. Journal of Animal Breeding and Genetics published by Blackwell Verlag GmbH.

Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar).

PubMed

Bangera, Rama; Correa, Katharina; Lhorente, Jean P; Figueroa, René; Yáñez, José M

2017-01-31

Salmon Rickettsial Syndrome (SRS) caused by Piscirickettsia salmonis is a major disease affecting the Chilean salmon industry. Genomic selection (GS) is a method wherein genome-wide markers and phenotype information of full-sibs are used to predict genomic EBV (GEBV) of selection candidates and is expected to have increased accuracy and response to selection over traditional pedigree based Best Linear Unbiased Prediction (PBLUP). Widely used GS methods such as genomic BLUP (GBLUP), SNPBLUP, Bayes C and Bayesian Lasso may perform differently with respect to accuracy of GEBV prediction. Our aim was to compare the accuracy, in terms of reliability of genome-enabled prediction, from different GS methods with PBLUP for resistance to SRS in an Atlantic salmon breeding program. Number of days to death (DAYS), binary survival status (STATUS) phenotypes, and 50 K SNP array genotypes were obtained from 2601 smolts challenged with P. salmonis. The reliability of different GS methods at different SNP densities with and without pedigree were compared to PBLUP using a five-fold cross validation scheme. Heritability estimated from GS methods was significantly higher than PBLUP. Pearson's correlation between predicted GEBV from PBLUP and GS models ranged from 0.79 to 0.91 and 0.79-0.95 for DAYS and STATUS, respectively. The relative increase in reliability from different GS methods for DAYS and STATUS with 50 K SNP ranged from 8 to 25% and 27-30%, respectively. All GS methods outperformed PBLUP at all marker densities. DAYS and STATUS showed superior reliability over PBLUP even at the lowest marker density of 3 K and 500 SNP, respectively. 20 K SNP showed close to maximal reliability for both traits with little improvement using higher densities. These results indicate that genomic predictions can accelerate genetic progress for SRS resistance in Atlantic salmon and implementation of this approach will contribute to the control of SRS in Chile. We recommend GBLUP for routine GS evaluation because this method is computationally faster and the results are very similar with other GS methods. The use of lower density SNP or the combination of low density SNP and an imputation strategy may help to reduce genotyping costs without compromising gain in reliability.

A High Density SNP Array for the Domestic Horse and Extant Perissodactyla: Utility for Association Mapping, Genetic Diversity, and Phylogeny Studies

PubMed Central

McCue, Molly E.; Bannasch, Danika L.; Petersen, Jessica L.; Gurr, Jessica; Bailey, Ernie; Binns, Matthew M.; Distl, Ottmar; Guérin, Gérard; Hasegawa, Telhisa; Hill, Emmeline W.; Leeb, Tosso; Lindgren, Gabriella; Penedo, M. Cecilia T.; Røed, Knut H.; Ryder, Oliver A.; Swinburne, June E.; Tozaki, Teruaki; Valberg, Stephanie J.; Vaudin, Mark; Lindblad-Toh, Kerstin

2012-01-01

An equine SNP genotyping array was developed and evaluated on a panel of samples representing 14 domestic horse breeds and 18 evolutionarily related species. More than 54,000 polymorphic SNPs provided an average inter-SNP spacing of ∼43 kb. The mean minor allele frequency across domestic horse breeds was 0.23, and the number of polymorphic SNPs within breeds ranged from 43,287 to 52,085. Genome-wide linkage disequilibrium (LD) in most breeds declined rapidly over the first 50–100 kb and reached background levels within 1–2 Mb. The extent of LD and the level of inbreeding were highest in the Thoroughbred and lowest in the Mongolian and Quarter Horse. Multidimensional scaling (MDS) analyses demonstrated the tight grouping of individuals within most breeds, close proximity of related breeds, and less tight grouping in admixed breeds. The close relationship between the Przewalski's Horse and the domestic horse was demonstrated by pair-wise genetic distance and MDS. Genotyping of other Perissodactyla (zebras, asses, tapirs, and rhinoceros) was variably successful, with call rates and the number of polymorphic loci varying across taxa. Parsimony analysis placed the modern horse as sister taxa to Equus przewalski. The utility of the SNP array in genome-wide association was confirmed by mapping the known recessive chestnut coat color locus (MC1R) and defining a conserved haplotype of ∼750 kb across all breeds. These results demonstrate the high quality of this SNP genotyping resource, its usefulness in diverse genome analyses of the horse, and potential use in related species. PMID:22253606

Genome-Wide SNP Detection, Validation, and Development of an 8K SNP Array for Apple

PubMed Central

Chagné, David; Crowhurst, Ross N.; Troggio, Michela; Davey, Mark W.; Gilmore, Barbara; Lawley, Cindy; Vanderzande, Stijn; Hellens, Roger P.; Kumar, Satish; Cestaro, Alessandro; Velasco, Riccardo; Main, Dorrie; Rees, Jasper D.; Iezzoni, Amy; Mockler, Todd; Wilhelm, Larry; Van de Weg, Eric; Gardiner, Susan E.; Bassil, Nahla; Peace, Cameron

2012-01-01

As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of ‘Golden Delicious’, SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple. PMID:22363718

Whole-Exome Sequencing Study of Thyrotropin-Secreting Pituitary Adenomas.

PubMed

Sapkota, Santosh; Horiguchi, Kazuhiko; Tosaka, Masahiko; Yamada, Syozo; Yamada, Masanobu

2017-02-01

Thyrotropin (TSH)-secreting pituitary adenomas (TSHomas) are a rare cause of hyperthyroidism, and the genetic aberrations responsible remain unknown. To identify somatic genetic abnormalities in TSHomas. A single-nucleotide polymorphism (SNP) array analysis was performed on 8 TSHomas. Four tumors with no allelic losses or limited loss of heterozygosity were selected, and whole-exome sequencing was performed, including their corresponding blood samples. Somatic variants were confirmed by Sanger sequencing. A set of 8 tumors was also assessed to validate candidate genes. Twelve patients with sporadic TSHomas were examined. The overall performance of whole-exome sequencing was good, with an average coverage of each base in the targeted region of 97.6%. Six DNA variants were confirmed as candidate driver mutations, with an average of 1.5 somatic mutations per tumor. No mutations were recurrent. Two of these mutations were found in genes with an established role in malignant tumorigenesis (SMOX and SYTL3), and 4 had unknown roles (ZSCAN23, ASTN2, R3HDM2, and CWH43). Similarly, an SNP array analysis revealed frequent chromosomal regions of copy number gains, including recurrent gains at loci harboring 4 of these 6 genes. Several candidate somatic mutations and changes in copy numbers for TSHomas were identified. The results showed no recurrence of mutations in the tumors studied but a low number of mutations, thereby highlighting their benign nature. Further studies on a larger cohort of TSHomas, along with the use of epigenetic and transcriptomic approaches, may reveal the underlying genetic lesions. Copyright © 2017 by the Endocrine Society

Dandy-Walker malformation and Wisconsin syndrome: novel cases add further insight into the genotype-phenotype correlations of 3q23q25 deletions.

PubMed

Ferraris, Alessandro; Bernardini, Laura; Sabolic Avramovska, Vesna; Zanni, Ginevra; Loddo, Sara; Sukarova-Angelovska, Elena; Parisi, Valentina; Capalbo, Anna; Tumini, Stefano; Travaglini, Lorena; Mancini, Francesca; Duma, Filip; Barresi, Sabina; Novelli, Antonio; Mercuri, Eugenio; Tarani, Luigi; Bertini, Enrico; Dallapiccola, Bruno; Valente, Enza Maria

2013-05-16

The Dandy-Walker malformation (DWM) is one of the commonest congenital cerebellar defects, and can be associated with multiple congenital anomalies and chromosomal syndromes. The occurrence of overlapping 3q deletions including the ZIC1 and ZIC4 genes in few patients, along with data from mouse models, have implicated both genes in the pathogenesis of DWM. Using a SNP-array approach, we recently identified three novel patients carrying heterozygous 3q deletions encompassing ZIC1 and ZIC4. Magnetic resonance imaging showed that only two had a typical DWM, while the third did not present any defect of the DWM spectrum. SNP-array analysis in further eleven children diagnosed with DWM failed to identify deletions of ZIC1-ZIC4. The clinical phenotype of the three 3q deleted patients included multiple congenital anomalies and peculiar facial appearance, related to the localization and extension of each deletion. In particular, phenotypes resulted from the variable combination of three recognizable patterns: DWM (with incomplete penetrance); blepharophimosis, ptosis, and epicanthus inversus syndrome; and Wisconsin syndrome (WS), recently mapped to 3q. Our data indicate that the 3q deletion is a rare defect associated with DWM, and suggest that the hemizygosity of ZIC1-ZIC4 genes is neither necessary nor sufficient per se to cause this condition. Furthermore, based on a detailed comparison of clinical features and molecular data from 3q deleted patients, we propose clinical diagnostic criteria and refine the critical region for WS.

Dandy-Walker malformation and Wisconsin syndrome: novel cases add further insight into the genotype-phenotype correlations of 3q23q25 deletions

PubMed Central

2013-01-01

Background The Dandy-Walker malformation (DWM) is one of the commonest congenital cerebellar defects, and can be associated with multiple congenital anomalies and chromosomal syndromes. The occurrence of overlapping 3q deletions including the ZIC1 and ZIC4 genes in few patients, along with data from mouse models, have implicated both genes in the pathogenesis of DWM. Methods and results Using a SNP-array approach, we recently identified three novel patients carrying heterozygous 3q deletions encompassing ZIC1 and ZIC4. Magnetic resonance imaging showed that only two had a typical DWM, while the third did not present any defect of the DWM spectrum. SNP-array analysis in further eleven children diagnosed with DWM failed to identify deletions of ZIC1-ZIC4. The clinical phenotype of the three 3q deleted patients included multiple congenital anomalies and peculiar facial appearance, related to the localization and extension of each deletion. In particular, phenotypes resulted from the variable combination of three recognizable patterns: DWM (with incomplete penetrance); blepharophimosis, ptosis, and epicanthus inversus syndrome; and Wisconsin syndrome (WS), recently mapped to 3q. Conclusions Our data indicate that the 3q deletion is a rare defect associated with DWM, and suggest that the hemizygosity of ZIC1-ZIC4 genes is neither necessary nor sufficient per se to cause this condition. Furthermore, based on a detailed comparison of clinical features and molecular data from 3q deleted patients, we propose clinical diagnostic criteria and refine the critical region for WS. PMID:23679990

A high density linkage map of the ancestral diploid strawberry F. iinumae using SNP markers from the ISTRAW90 array and GBS

USDA-ARS?s Scientific Manuscript database

Fragaria iinumae is recognized as an ancestor of the octoploid strawberry species, including the cultivated strawberry, Fragaria ×ananassa. Here we report the construction of the first high density linkage map for F. iinumae. The map is based on two high-throughput techniques of single nucleotide p...

Automated tetraploid genotype calling by hierarchical clustering

USDA-ARS?s Scientific Manuscript database

SNP arrays are transforming breeding and genetics research for autotetraploids. To fully utilize these arrays, however, the relationship between signal intensity and allele dosage must be inferred independently for each marker. We developed an improved computational method to automate this process, ...

Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, S; Jaing, C

2012-03-27

The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interimmore » report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.« less

Continuing difficulties in interpreting CNV data: lessons from a genome-wide CNV association study of Australian HNPCC/lynch syndrome patients.

PubMed

Talseth-Palmer, Bente A; Holliday, Elizabeth G; Evans, Tiffany-Jane; McEvoy, Mark; Attia, John; Grice, Desma M; Masson, Amy L; Meldrum, Cliff; Spigelman, Allan; Scott, Rodney J

2013-03-26

Hereditary non-polyposis colorectal cancer (HNPCC)/Lynch syndrome (LS) is a cancer syndrome characterised by early-onset epithelial cancers, especially colorectal cancer (CRC) and endometrial cancer. The aim of the current study was to use SNP-array technology to identify genomic aberrations which could contribute to the increased risk of cancer in HNPCC/LS patients. Individuals diagnosed with HNPCC/LS (100) and healthy controls (384) were genotyped using the Illumina Human610-Quad SNP-arrays. Copy number variation (CNV) calling and association analyses were performed using Nexus software, with significant results validated using QuantiSNP. TaqMan Copy-Number assays were used for verification of CNVs showing significant association with HNPCC/LS identified by both software programs. We detected copy number (CN) gains associated with HNPCC/LS status on chromosome 7q11.21 (28% cases and 0% controls, Nexus; p =3.60E-20 and QuantiSNP; p < 1.00E-16) and 16p11.2 (46% in cases, while a CN loss was observed in 23% of controls, Nexus; p = 4.93E-21 and QuantiSNP; p = 5.00E-06) via in silico analyses. TaqMan Copy-Number assay was used for validation of CNVs showing significant association with HNPCC/LS. In addition, CNV burden (total CNV length, average CNV length and number of observed CNV events) was significantly greater in cases compared to controls. A greater CNV burden was identified in HNPCC/LS cases compared to controls supporting the notion of higher genomic instability in these patients. One intergenic locus on chromosome 7q11.21 is possibly associated with HNPCC/LS and deserves further investigation. The results from this study highlight the complexities of fluorescent based CNV analyses. The inefficiency of both CNV detection methods to reproducibly detect observed CNVs demonstrates the need for sequence data to be considered alongside intensity data to avoid false positive results.

Population-genetic properties of differentiated copy number variations in cattle.

PubMed

Xu, Lingyang; Hou, Yali; Bickhart, Derek M; Zhou, Yang; Hay, El Hamidi Abdel; Song, Jiuzhou; Sonstegard, Tad S; Van Tassell, Curtis P; Liu, George E

2016-03-23

While single nucleotide polymorphism (SNP) is typically the variant of choice for population genetics, copy number variation (CNV) which comprises insertion, deletion and duplication of genomic sequence, is an informative type of genetic variation. CNVs have been shown to be both common in mammals and important for understanding the relationship between genotype and phenotype. However, CNV differentiation, selection and its population genetic properties are not well understood across diverse populations. We performed a population genetics survey based on CNVs derived from the BovineHD SNP array data of eight distinct cattle breeds. We generated high resolution results that show geographical patterns of variations and genome-wide admixture proportions within and among breeds. Similar to the previous SNP-based studies, our CNV-based results displayed a strong correlation of population structure and geographical location. By conducting three pairwise comparisons among European taurine, African taurine, and indicine groups, we further identified 78 unique CNV regions that were highly differentiated, some of which might be due to selection. These CNV regions overlapped with genes involved in traits related to parasite resistance, immunity response, body size, fertility, and milk production. Our results characterize CNV diversity among cattle populations and provide a list of lineage-differentiated CNVs.

Joint genome-wide association study for milk fatty acid traits in Chinese and Danish Holstein populations.

PubMed

Li, X; Buitenhuis, A J; Lund, M S; Li, C; Sun, D; Zhang, Q; Poulsen, N A; Su, G

2015-11-01

The identification of causal genes or genomic regions associated with fatty acids (FA) will enhance our understanding of the pathways underlying FA synthesis and provide opportunities for changing milk fat composition through a genetic approach. The linkage disequilibrium between adjacent markers is highly consistent between the Chinese and Danish Holstein populations, such that a joint genome-wide association study (GWAS) can be performed. In this study, a joint GWAS was performed for 16 milk FA traits based on data of 784 Chinese and 371 Danish Holstein cows genotyped by a high-density bovine single nucleotide polymorphism (SNP) array. A total of 486,464 SNP markers on 29 bovine autosomes were used. Bonferroni corrections were applied to adjust the significance thresholds for multiple testing at the genome- and chromosome-wide levels. According to the analysis of either the Chinese or Danish data individually, the total numbers of overlapping SNP that were significant at the chromosome level were 94 for C14:1, 208 for the C14 index, and 1 for C18:0. Joint analysis using the combined data of the 2 populations detected greater numbers of significant SNP compared with either of the individual populations alone for 7 and 10 traits at the genome- and chromosome-wide significance levels, respectively. Greater numbers of significant SNP were detected for C18:0 and the C18 index in the Chinese population compared with the joint analysis. Sixty-five significant SNP across all traits had significantly different effects in the 2 populations. Ten FA were influenced by a quantitative trait loci (QTL) region including DGAT1. Both C14:1 and the C14 index were influenced by a QTL region including SCD1 in the combined population. Other QTL regions also showed significant associations with the studied FA. A large region (14.9-24.9 Mbp) in BTA26 significantly influenced C14:1 and the C14 index in both populations, mostly likely due to the SNP in SCD1. A QTL region (69.97-73.69 Mbp) on BTA9 showed a significantly different effect on C18:0 between the 2 populations. Detection of these important SNP and the corresponding QTL regions will be helpful for follow-up studies to identify causal mutations and their interaction with environments for milk FA in dairy cattle. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

[Phenotype-genotype correlation analysis of 12 cases with Angelman/Prader-Willi syndrome].

PubMed

Chen, Chen; Peng, Ying; Xia, Yan; Li, Haoxian; Zhu, Huimin; Pan, Qian; Yin, Fei; Wu, Lingqian

2014-12-01

To investigate the genotype-phenotype correlation in patients with Angelman syndrome/Prader-Willi syndrome (AS/PWS) and assess the application value of high-resolution single nucleotide polymorphism microarrays (SNP array) for such diseases. Twelve AS/PWS patients were diagnosed through SNP array, fluorescence in situ hybridization (FISH) and karyotype analysis. Clinical characteristics were analyzed. Deletions ranging from 4.8 Mb to 7.0 Mb on chromosome 15q11.2-13 were detected in 11 patients. Uniparental disomy (UPD) was detected in only 1 patient. Patients with deletions could be divided into 2 groups, including 7 cases with class I and 4 with class II. The two groups however had no significant phenotypic difference. The UPD patient had relatively better development and language ability. Deletions of 6 patients were confirmed by FISH to be of de novo in origin. The risk to their sibs was determined to be less than 1%. The phenotypic differences between AS/PWS patients with class I and class II deletion need to be further studied. SNP array is useful in detecting and distinguishing of patients with deletion or UPD. This method may be applied for studying the genotype-phenotype association and the mechanism underlying AS/PWS.

Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays

PubMed Central

2011-01-01

Background Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs. Results In this study, we introduce a novel method referred to as the wavelet-based identification of focal genomic aberrations (WIFA). The use of the wavelet analysis, because it is a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in broadly aberrant regions. The proposed method integrates multiple cancer samples so that it enables the detection of the consistent aberrations across multiple samples. We then apply this method to glioblastoma multiforme and lung cancer data sets from the SNP microarray platform. Through this process, we confirm the ability to detect previously known cancer related genes from both cancer types with high accuracy. Also, the application of this approach to a lung cancer data set identifies focal amplification regions that contain known oncogenes, though these regions are not reported using a recent CNAs detecting algorithm GISTIC: SMAD7 (chr18q21.1) and FGF10 (chr5p12). Conclusions Our results suggest that WIFA can be used to reveal cancer related genes in various cancer data sets. PMID:21569311

Evaluation of Genomic Instability in the Abnormal Prostate

DTIC Science & Technology

2006-12-01

array CGH maps copy number aberrations relative to the genome sequence by using arrays of BAC or cDNA clones as the hybridization target instead of...data produced from these analyses complicate the interpretation of results . For these reasons, and as outlined by Davies et al., 22 it is desirable...There have been numerous studies of these abnormalities and several techniques, including 9 chromosome painting, array CGH and SNP arrays , have

Incorporation of Personal Single Nucleotide Polymorphism (SNP) Data into a National Level Electronic Health Record for Disease Risk Assessment, Part 2: The Incorporation of SNP into the National Health Information System of Turkey

PubMed Central

Beyan, Timur

2014-01-01

Background A personalized medicine approach provides opportunities for predictive and preventive medicine. Using genomic, clinical, environmental, and behavioral data, the tracking and management of individual wellness is possible. A prolific way to carry this personalized approach into routine practices can be accomplished by integrating clinical interpretations of genomic variations into electronic medical record (EMR)s/electronic health record (EHR)s systems. Today, various central EHR infrastructures have been constituted in many countries of the world, including Turkey. Objective As an initial attempt to develop a sophisticated infrastructure, we have concentrated on incorporating the personal single nucleotide polymorphism (SNP) data into the National Health Information System of Turkey (NHIS-T) for disease risk assessment, and evaluated the performance of various predictive models for prostate cancer cases. We present our work as a miniseries containing three parts: (1) an overview of requirements, (2) the incorporation of SNP into the NHIS-T, and (3) an evaluation of SNP data incorporated into the NHIS-T for prostate cancer. Methods For the second article of this miniseries, we have analyzed the existing NHIS-T and proposed the possible extensional architectures. In light of the literature survey and characteristics of NHIS-T, we have proposed and argued opportunities and obstacles for a SNP incorporated NHIS-T. A prototype with complementary capabilities (knowledge base and end-user applications) for these architectures has been designed and developed. Results In the proposed architectures, the clinically relevant personal SNP (CR-SNP) and clinicogenomic associations are shared between central repositories and end-users via the NHIS-T infrastructure. To produce these files, we need to develop a national level clinicogenomic knowledge base. Regarding clinicogenomic decision support, we planned to complete interpretation of these associations on the end-user applications. This approach gives us the flexibility to add/update envirobehavioral parameters and family health history that will be monitored or collected by end users. Conclusions Our results emphasized that even though the existing NHIS-T messaging infrastructure supports the integration of SNP data and clinicogenomic association, it is critical to develop a national level, accredited knowledge base and better end-user systems for the interpretation of genomic, clinical, and envirobehavioral parameters. PMID:25599817

Incorporation of personal single nucleotide polymorphism (SNP) data into a national level electronic health record for disease risk assessment, part 2: the incorporation of SNP into the national health information system of Turkey.

PubMed

Beyan, Timur; Aydın Son, Yeşim

2014-08-11

A personalized medicine approach provides opportunities for predictive and preventive medicine. Using genomic, clinical, environmental, and behavioral data, the tracking and management of individual wellness is possible. A prolific way to carry this personalized approach into routine practices can be accomplished by integrating clinical interpretations of genomic variations into electronic medical record (EMR)s/electronic health record (EHR)s systems. Today, various central EHR infrastructures have been constituted in many countries of the world, including Turkey. As an initial attempt to develop a sophisticated infrastructure, we have concentrated on incorporating the personal single nucleotide polymorphism (SNP) data into the National Health Information System of Turkey (NHIS-T) for disease risk assessment, and evaluated the performance of various predictive models for prostate cancer cases. We present our work as a miniseries containing three parts: (1) an overview of requirements, (2) the incorporation of SNP into the NHIS-T, and (3) an evaluation of SNP data incorporated into the NHIS-T for prostate cancer. For the second article of this miniseries, we have analyzed the existing NHIS-T and proposed the possible extensional architectures. In light of the literature survey and characteristics of NHIS-T, we have proposed and argued opportunities and obstacles for a SNP incorporated NHIS-T. A prototype with complementary capabilities (knowledge base and end-user applications) for these architectures has been designed and developed. In the proposed architectures, the clinically relevant personal SNP (CR-SNP) and clinicogenomic associations are shared between central repositories and end-users via the NHIS-T infrastructure. To produce these files, we need to develop a national level clinicogenomic knowledge base. Regarding clinicogenomic decision support, we planned to complete interpretation of these associations on the end-user applications. This approach gives us the flexibility to add/update envirobehavioral parameters and family health history that will be monitored or collected by end users. Our results emphasized that even though the existing NHIS-T messaging infrastructure supports the integration of SNP data and clinicogenomic association, it is critical to develop a national level, accredited knowledge base and better end-user systems for the interpretation of genomic, clinical, and envirobehavioral parameters.

Genomic Variation by Whole-Genome SNP Mapping Arrays Predicts Time-to-Event Outcome in Patients with Chronic Lymphocytic Leukemia

PubMed Central

Schweighofer, Carmen D.; Coombes, Kevin R.; Majewski, Tadeusz; Barron, Lynn L.; Lerner, Susan; Sargent, Rachel L.; O'Brien, Susan; Ferrajoli, Alessandra; Wierda, William G.; Czerniak, Bogdan A.; Medeiros, L. Jeffrey; Keating, Michael J.; Abruzzo, Lynne V.

2013-01-01

Genomic abnormalities, such as deletions in 11q22 or 17p13, are associated with poorer prognosis in patients with chronic lymphocytic leukemia (CLL). We hypothesized that unknown regions of copy number variation (CNV) affect clinical outcome and can be detected by array-based single-nucleotide polymorphism (SNP) genotyping. We compared SNP genotypes from 168 untreated patients with CLL with genotypes from 73 white HapMap controls. We identified 322 regions of recurrent CNV, 82 of which occurred significantly more often in CLL than in HapMap (CLL-specific CNV), including regions typically aberrant in CLL: deletions in 6q21, 11q22, 13q14, and 17p13 and trisomy 12. In univariate analyses, 35 of total and 11 of CLL-specific CNVs were associated with unfavorable time-to-event outcomes, including gains or losses in chromosomes 2p, 4p, 4q, 6p, 6q, 7q, 11p, 11q, and 17p. In multivariate analyses, six CNVs (ie, CLL-specific variations in 11p15.1-15.4 or 6q27) predicted time-to-treatment or overall survival independently of established markers of prognosis. Moreover, genotypic complexity (ie, the number of independent CNVs per patient) significantly predicted prognosis, with a median time-to-treatment of 64 months versus 23 months in patients with zero to one versus two or more CNVs, respectively (P = 3.3 × 10−8). In summary, a comparison of SNP genotypes from patients with CLL with HapMap controls allowed us to identify known and unknown recurrent CNVs and to determine regions and rates of CNV that predict poorer prognosis in patients with CLL. PMID:23273604

Dynamic variable selection in SNP genotype autocalling from APEX microarray data.

PubMed

Podder, Mohua; Welch, William J; Zamar, Ruben H; Tebbutt, Scott J

2006-11-30

Single nucleotide polymorphisms (SNPs) are DNA sequence variations, occurring when a single nucleotide--adenine (A), thymine (T), cytosine (C) or guanine (G)--is altered. Arguably, SNPs account for more than 90% of human genetic variation. Our laboratory has developed a highly redundant SNP genotyping assay consisting of multiple probes with signals from multiple channels for a single SNP, based on arrayed primer extension (APEX). This mini-sequencing method is a powerful combination of a highly parallel microarray with distinctive Sanger-based dideoxy terminator sequencing chemistry. Using this microarray platform, our current genotype calling system (known as SNP Chart) is capable of calling single SNP genotypes by manual inspection of the APEX data, which is time-consuming and exposed to user subjectivity bias. Using a set of 32 Coriell DNA samples plus three negative PCR controls as a training data set, we have developed a fully-automated genotyping algorithm based on simple linear discriminant analysis (LDA) using dynamic variable selection. The algorithm combines separate analyses based on the multiple probe sets to give a final posterior probability for each candidate genotype. We have tested our algorithm on a completely independent data set of 270 DNA samples, with validated genotypes, from patients admitted to the intensive care unit (ICU) of St. Paul's Hospital (plus one negative PCR control sample). Our method achieves a concordance rate of 98.9% with a 99.6% call rate for a set of 96 SNPs. By adjusting the threshold value for the final posterior probability of the called genotype, the call rate reduces to 94.9% with a higher concordance rate of 99.6%. We also reversed the two independent data sets in their training and testing roles, achieving a concordance rate up to 99.8%. The strength of this APEX chemistry-based platform is its unique redundancy having multiple probes for a single SNP. Our model-based genotype calling algorithm captures the redundancy in the system considering all the underlying probe features of a particular SNP, automatically down-weighting any 'bad data' corresponding to image artifacts on the microarray slide or failure of a specific chemistry. In this regard, our method is able to automatically select the probes which work well and reduce the effect of other so-called bad performing probes in a sample-specific manner, for any number of SNPs.

[Application of single nucleotide polymorphism-microarray and target gene sequencing in the study of genetic etiology of children with unexplained intellectual disability or developmental delay].

PubMed

Gao, Z J; Jiang, Q; Cheng, D Z; Yan, X X; Chen, Q; Xu, K M

2016-10-02

Objective: To evaluate the application of single nucleotide polymorphism (SNP)-microarray and target gene sequencing technology in the clinical molecular genetic diagnosis of unexplained intellectual disability(ID) or developmental delay (DD). Method: Patients with ID or DD were recruited in the Department of Neurology, Affiliated Children's Hospital of Capital Institute of Pediatrics between September 2015 and February 2016. The intellectual assessment of the patients was performed using 0-6-year-old pediatric examination table of neuropsychological development or Wechsler intelligence scale (>6 years). Patients with a DQ less than 49 or IQ less than 51 were included in this study. The patients were scanned by SNP-array for detection of genomic copy number variations (CNV), and the revealed genomic imbalance was confirmed by quantitative real time-PCR. Candidate gene mutation screening was carried out by target gene sequencing technology.Causal mutations or likely pathogenic variants were verified by polymerase chain reaction and direct sequencing. Result: There were 15 children with ID or DD enrolled, 9 males and 6 females. The age of these patients was 7 months-16 years and 9 months. SNP-array revealed that two of the 15 patients had genomic CNV. Both CNV were de novo micro deletions, one involved 11q24.1q25 and the other micro deletion located on 21q22.2q22.3. Both micro deletions were proved to have a clinical significance due to their association with ID, brain DD, unusual faces etc. by querying Decipher database. Thirteen patients with negative findings in SNP-array were consequently examined with target gene sequencing technology, genotype-phenotype correlation analysis and genetic analysis. Five patients were diagnosed with monogenic disorder, two were diagnosed with suspected genetic disorder and six were still negative. Conclusion: Sequential use of SNP-array and target gene sequencing technology can significantly increase the molecular genetic etiologic diagnosis rate of the patients with unexplained ID or DD. Combined use of these technologies can serve as a useful examinational method in assisting differential diagnosis of children with unexplained ID or DD.

Genome-wide SNP association-based localization of a dwarfism gene in Friesian dwarf horses.

PubMed

Orr, N; Back, W; Gu, J; Leegwater, P; Govindarajan, P; Conroy, J; Ducro, B; Van Arendonk, J A M; MacHugh, D E; Ennis, S; Hill, E W; Brama, P A J

2010-12-01

The recent completion of the horse genome and commercial availability of an equine SNP genotyping array has facilitated the mapping of disease genes. We report putative localization of the gene responsible for dwarfism, a trait in Friesian horses that is thought to have a recessive mode of inheritance, to a 2-MB region of chromosome 14 using just 10 affected animals and 10 controls. We successfully genotyped 34,429 SNPs that were tested for association with dwarfism using chi-square tests. The most significant SNP in our study, BIEC2-239376 (P(2df)=4.54 × 10(-5), P(rec)=7.74 × 10(-6)), is located close to a gene implicated in human dwarfism. Fine-mapping and resequencing analyses did not aid in further localization of the causative variant, and replication of our findings in independent sample sets will be necessary to confirm these results. © 2010 The Authors, Journal compilation © 2010 Stichting International Foundation for Animal Genetics.

Association analysis for feet and legs disorders with whole-genome sequence variants in 3 dairy cattle breeds.

PubMed

Wu, Xiaoping; Guldbrandtsen, Bernt; Lund, Mogens Sandø; Sahana, Goutam

2016-09-01

Identification of genetic variants associated with feet and legs disorders (FLD) will aid in the genetic improvement of these traits by providing knowledge on genes that influence trait variations. In Denmark, FLD in cattle has been recorded since the 1990s. In this report, we used deregressed breeding values as response variables for a genome-wide association study. Bulls (5,334 Danish Holstein, 4,237 Nordic Red Dairy Cattle, and 1,180 Danish Jersey) with deregressed estimated breeding values were genotyped with the Illumina Bovine 54k single nucleotide polymorphism (SNP) genotyping array. Genotypes were imputed to whole-genome sequence variants, and then 22,751,039 SNP on 29 autosomes were used for an association analysis. A modified linear mixed-model approach (efficient mixed-model association eXpedited, EMMAX) and a linear mixed model were used for association analysis. We identified 5 (3,854 SNP), 3 (13,642 SNP), and 0 quantitative trait locus (QTL) regions associated with the FLD index in Danish Holstein, Nordic Red Dairy Cattle, and Danish Jersey populations, respectively. We did not identify any QTL that were common among the 3 breeds. In a meta-analysis of the 3 breeds, 4 QTL regions were significant, but no additional QTL region was identified compared with within-breed analyses. Comparison between top SNP locations within these QTL regions and known genes suggested that RASGRP1, LCORL, MOS, and MITF may be candidate genes for FLD in dairy cattle. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Linkage disequilibrium and signatures of positive selection around LINE-1 retrotransposons in the human genome.

PubMed

Kuhn, Alexandre; Ong, Yao Min; Cheng, Ching-Yu; Wong, Tien Yin; Quake, Stephen R; Burkholder, William F

2014-06-03

Insertions of the human-specific subfamily of LINE-1 (L1) retrotransposon are highly polymorphic across individuals and can critically influence the human transcriptome. We hypothesized that L1 insertions could represent genetic variants determining important human phenotypic traits, and performed an integrated analysis of L1 elements and single nucleotide polymorphisms (SNPs) in several human populations. We found that a large fraction of L1s were in high linkage disequilibrium with their surrounding genomic regions and that they were well tagged by SNPs. However, L1 variants were only partially captured by SNPs on standard SNP arrays, so that their potential phenotypic impact would be frequently missed by SNP array-based genome-wide association studies. We next identified potential phenotypic effects of L1s by looking for signatures of natural selection linked to L1 insertions; significant extended haplotype homozygosity was detected around several L1 insertions. This finding suggests that some of these L1 insertions may have been the target of recent positive selection.

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

USDA-ARS?s Scientific Manuscript database

High-density single nucleotide polymorphism (SNP) genotyping chips are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships among individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array includ...

Comparative Analysis of CNV Calling Algorithms: Literature Survey and a Case Study Using Bovine High-Density SNP Data.

PubMed

Xu, Lingyang; Hou, Yali; Bickhart, Derek M; Song, Jiuzhou; Liu, George E

2013-06-25

Copy number variations (CNVs) are gains and losses of genomic sequence between two individuals of a species when compared to a reference genome. The data from single nucleotide polymorphism (SNP) microarrays are now routinely used for genotyping, but they also can be utilized for copy number detection. Substantial progress has been made in array design and CNV calling algorithms and at least 10 comparison studies in humans have been published to assess them. In this review, we first survey the literature on existing microarray platforms and CNV calling algorithms. We then examine a number of CNV calling tools to evaluate their impacts using bovine high-density SNP data. Large incongruities in the results from different CNV calling tools highlight the need for standardizing array data collection, quality assessment and experimental validation. Only after careful experimental design and rigorous data filtering can the impacts of CNVs on both normal phenotypic variability and disease susceptibility be fully revealed.

Genome-wide SNP scan of pooled DNA reveals nonsense mutation in FGF20 in the scaleless line of featherless chickens

PubMed Central

2012-01-01

Background Scaleless (sc/sc) chickens carry a single recessive mutation that causes a lack of almost all body feathers, as well as foot scales and spurs, due to a failure of skin patterning during embryogenesis. This spontaneous mutant line, first described in the 1950s, has been used extensively to explore the tissue interactions involved in ectodermal appendage formation in embryonic skin. Moreover, the trait is potentially useful in tropical agriculture due to the ability of featherless chickens to tolerate heat, which is at present a major constraint to efficient poultry meat production in hot climates. In the interests of enhancing our understanding of feather placode development, and to provide the poultry industry with a strategy to breed heat-tolerant meat-type chickens (broilers), we mapped and identified the sc mutation. Results Through a cost-effective and labour-efficient SNP array mapping approach using DNA from sc/sc and sc/+ blood sample pools, we map the sc trait to chromosome 4 and show that a nonsense mutation in FGF20 is completely associated with the sc/sc phenotype. This mutation, common to all sc/sc individuals and absent from wild type, is predicted to lead to loss of a highly conserved region of the FGF20 protein important for FGF signalling. In situ hybridisation and quantitative RT-PCR studies reveal that FGF20 is epidermally expressed during the early stages of feather placode patterning. In addition, we describe a dCAPS genotyping assay based on the mutation, developed to facilitate discrimination between wild type and sc alleles. Conclusions This work represents the first loss of function genetic evidence supporting a role for FGF ligand signalling in feather development, and suggests FGF20 as a novel central player in the development of vertebrate skin appendages, including hair follicles and exocrine glands. In addition, this is to our knowledge the first report describing the use of the chicken SNP array to map genes based on genotyping of DNA samples from pooled whole blood. The identification of the sc mutation has important implications for the future breeding of this potentially useful trait for the poultry industry, and our genotyping assay can facilitate its rapid introgression into production lines. PMID:22712610

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction.

PubMed

Brøndum, R F; Su, G; Janss, L; Sahana, G; Guldbrandtsen, B; Boichard, D; Lund, M S

2015-06-01

This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index itself. Depending on the trait's economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage disequilibrium and assaying performance on the array, a total of 1,623 QTL markers were selected for inclusion on the custom chip. Genomic prediction analyses were performed for Nordic and French Holstein and Nordic Red animals using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model including the QTL markers in the analysis, reliability was increased by up to 4 percentage points for production traits in Nordic Holstein animals, up to 3 percentage points for Nordic Reds, and up to 5 percentage points for French Holstein. Smaller gains of up to 1 percentage point was observed for mastitis, but only a 0.5 percentage point increase was seen for fertility. When using a Bayesian model accuracies were generally higher with only 54k data compared with the genomic BLUP approach, but increases in reliability were relatively smaller when QTL markers were included. Results from this study indicate that the reliability of genomic prediction can be increased by including markers significant in genome-wide association studies on whole genome sequence data alongside the 54k SNP set. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A SNP genotyping array for hexaploid oat

USDA-ARS?s Scientific Manuscript database

Recognizing a need in cultivated hexaploid oat (Avena sativa L.) for a reliable set of reference SNPs, we have developed a 6K BeadChip design containing 257 Infinium I and 5,486 Infinium II designs corresponding to 5,743 SNPs. Of those, 4,975 SNPs yielded successful assays after array manufacturing...

Efficient Moment-Based Inference of Admixture Parameters and Sources of Gene Flow

PubMed Central

Levin, Alex; Reich, David; Patterson, Nick; Berger, Bonnie

2013-01-01

The recent explosion in available genetic data has led to significant advances in understanding the demographic histories of and relationships among human populations. It is still a challenge, however, to infer reliable parameter values for complicated models involving many populations. Here, we present MixMapper, an efficient, interactive method for constructing phylogenetic trees including admixture events using single nucleotide polymorphism (SNP) genotype data. MixMapper implements a novel two-phase approach to admixture inference using moment statistics, first building an unadmixed scaffold tree and then adding admixed populations by solving systems of equations that express allele frequency divergences in terms of mixture parameters. Importantly, all features of the model, including topology, sources of gene flow, branch lengths, and mixture proportions, are optimized automatically from the data and include estimates of statistical uncertainty. MixMapper also uses a new method to express branch lengths in easily interpretable drift units. We apply MixMapper to recently published data for Human Genome Diversity Cell Line Panel individuals genotyped on a SNP array designed especially for use in population genetics studies, obtaining confident results for 30 populations, 20 of them admixed. Notably, we confirm a signal of ancient admixture in European populations—including previously undetected admixture in Sardinians and Basques—involving a proportion of 20–40% ancient northern Eurasian ancestry. PMID:23709261

Rapid discovery of SNPs differentiating hatchery steelhead trout from ESA-listed natural-origin steelhead trout using a 57K SNP array

USGS Publications Warehouse

Larson, Wesley; Palti, Yniv; Gao, G.; Warheit, Kenneth I.; Seeb, James E.

2017-01-01

Natural-origin steelhead trout (Oncorhynchus mykiss (Walbaum, 1792)) in the Pacific Northwest, USA, are threatened by a number of factors including habitat destruction, disease, decline in marine survival, and a potential erosion of genetic viability due to introgression from hatchery strains. Our major goal was to use a recently developed SNP array containing ∼57 000 SNPs to identify a subset of SNPs that differentiate hatchery and natural-origin populations. We analyzed 35 765 polymorphic SNPs in nine populations of steelhead trout sampled from Puget Sound, Washington, USA. We then conducted two outlier tests and found 360 loci that were candidates for divergent selection between hatchery and natural-origin populations (mean FCT = 0.29, maximum = 0.65) and 595 SNPs that were candidates for selection among natural-origin populations (mean FST = 0.25, maximum = 0.51). Comparisons with a linkage map revealed that two chromosomes (Omy05 and Omy25) contained significantly more outliers than other chromosomes, suggesting that regions on Omy05 and Omy25 may be of adaptive significance. Our results highlight several advantages of the 57 000 SNP array as a tool for population and conservation genomics studies.

The effect of algorithms on copy number variant detection.

PubMed

Tsuang, Debby W; Millard, Steven P; Ely, Benjamin; Chi, Peter; Wang, Kenneth; Raskind, Wendy H; Kim, Sulgi; Brkanac, Zoran; Yu, Chang-En

2010-12-30

The detection of copy number variants (CNVs) and the results of CNV-disease association studies rely on how CNVs are defined, and because array-based technologies can only infer CNVs, CNV-calling algorithms can produce vastly different findings. Several authors have noted the large-scale variability between CNV-detection methods, as well as the substantial false positive and false negative rates associated with those methods. In this study, we use variations of four common algorithms for CNV detection (PennCNV, QuantiSNP, HMMSeg, and cnvPartition) and two definitions of overlap (any overlap and an overlap of at least 40% of the smaller CNV) to illustrate the effects of varying algorithms and definitions of overlap on CNV discovery. We used a 56 K Illumina genotyping array enriched for CNV regions to generate hybridization intensities and allele frequencies for 48 Caucasian schizophrenia cases and 48 age-, ethnicity-, and gender-matched control subjects. No algorithm found a difference in CNV burden between the two groups. However, the total number of CNVs called ranged from 102 to 3,765 across algorithms. The mean CNV size ranged from 46 kb to 787 kb, and the average number of CNVs per subject ranged from 1 to 39. The number of novel CNVs not previously reported in normal subjects ranged from 0 to 212. Motivated by the availability of multiple publicly available genome-wide SNP arrays, investigators are conducting numerous analyses to identify putative additional CNVs in complex genetic disorders. However, the number of CNVs identified in array-based studies, and whether these CNVs are novel or valid, will depend on the algorithm(s) used. Thus, given the variety of methods used, there will be many false positives and false negatives. Both guidelines for the identification of CNVs inferred from high-density arrays and the establishment of a gold standard for validation of CNVs are needed.

A New Single Nucleotide Polymorphism Database for Rainbow Trout Generated Through Whole Genome Resequencing.

PubMed

Gao, Guangtu; Nome, Torfinn; Pearse, Devon E; Moen, Thomas; Naish, Kerry A; Thorgaard, Gary H; Lien, Sigbjørn; Palti, Yniv

2018-01-01

Single-nucleotide polymorphisms (SNPs) are highly abundant markers, which are broadly distributed in animal genomes. For rainbow trout ( Oncorhynchus mykiss ), SNP discovery has been previously done through sequencing of restriction-site associated DNA (RAD) libraries, reduced representation libraries (RRL) and RNA sequencing. Recently we have performed high coverage whole genome resequencing with 61 unrelated samples, representing a wide range of rainbow trout and steelhead populations, with 49 new samples added to 12 aquaculture samples from AquaGen (Norway) that we previously used for SNP discovery. Of the 49 new samples, 11 were double-haploid lines from Washington State University (WSU) and 38 represented wild and hatchery populations from a wide range of geographic distribution and with divergent migratory phenotypes. We then mapped the sequences to the new rainbow trout reference genome assembly (GCA_002163495.1) which is based on the Swanson YY doubled haploid line. Variant calling was conducted with FreeBayes and SAMtools mpileup , followed by filtering of SNPs based on quality score, sequence complexity, read depth on the locus, and number of genotyped samples. Results from the two variant calling programs were compared and genotypes of the double haploid samples were used for detecting and filtering putative paralogous sequence variants (PSVs) and multi-sequence variants (MSVs). Overall, 30,302,087 SNPs were identified on the rainbow trout genome 29 chromosomes and 1,139,018 on unplaced scaffolds, with 4,042,723 SNPs having high minor allele frequency (MAF > 0.25). The average SNP density on the chromosomes was one SNP per 64 bp, or 15.6 SNPs per 1 kb. Results from the phylogenetic analysis that we conducted indicate that the SNP markers contain enough population-specific polymorphisms for recovering population relationships despite the small sample size used. Intra-Population polymorphism assessment revealed high level of polymorphism and heterozygosity within each population. We also provide functional annotation based on the genome position of each SNP and evaluate the use of clonal lines for filtering of PSVs and MSVs. These SNPs form a new database, which provides an important resource for a new high density SNP array design and for other SNP genotyping platforms used for genetic and genomics studies of this iconic salmonid fish species.

Genotyping of 75 SNPs using arrays for individual identification in five population groups.

PubMed

Hwa, Hsiao-Lin; Wu, Lawrence Shih Hsin; Lin, Chun-Yen; Huang, Tsun-Ying; Yin, Hsiang-I; Tseng, Li-Hui; Lee, James Chun-I

2016-01-01

Single nucleotide polymorphism (SNP) typing offers promise to forensic genetics. Various strategies and panels for analyzing SNP markers for individual identification have been published. However, the best panels with fewer identity SNPs for all major population groups are still under discussion. This study aimed to find more autosomal SNPs with high heterozygosity for individual identification among Asian populations. Ninety-six autosomal SNPs of 502 DNA samples from unrelated individuals of five population groups (208 Taiwanese Han, 83 Filipinos, 62 Thais, 69 Indonesians, and 80 individuals with European, Near Eastern, or South Asian ancestry) were analyzed using arrays in an initial screening, and 75 SNPs (group A, 46 newly selected SNPs; groups B, 29 SNPs based on a previous SNP panel) were selected for further statistical analyses. Some SNPs with high heterozygosity from Asian populations were identified. The combined random match probability of the best 40 and 45 SNPs was between 3.16 × 10(-17) and 7.75 × 10(-17) and between 2.33 × 10(-19) and 7.00 × 10(-19), respectively, in all five populations. These loci offer comparable power to short tandem repeats (STRs) for routine forensic profiling. In this study, we demonstrated the population genetic characteristics and forensic parameters of 75 SNPs with high heterozygosity from five population groups. This SNPs panel can provide valuable genotypic information and can be helpful in forensic casework for individual identification among these populations.

Physical mapping of QTL for tuber yield, starch content and starch yield in tetraploid potato (Solanum tuberosum L.) by means of genome wide genotyping by sequencing and the 8.3 K SolCAP SNP array.

PubMed

Schönhals, Elske Maria; Ding, Jia; Ritter, Enrique; Paulo, Maria João; Cara, Nicolás; Tacke, Ekhard; Hofferbert, Hans-Reinhard; Lübeck, Jens; Strahwald, Josef; Gebhardt, Christiane

2017-08-22

Tuber yield and starch content of the cultivated potato are complex traits of decisive importance for breeding improved varieties. Natural variation of tuber yield and starch content depends on the environment and on multiple, mostly unknown genetic factors. Dissection and molecular identification of the genes and their natural allelic variants controlling these complex traits will lead to the development of diagnostic DNA-based markers, by which precision and efficiency of selection can be increased (precision breeding). Three case-control populations were assembled from tetraploid potato cultivars based on maximizing the differences between high and low tuber yield (TY), starch content (TSC) and starch yield (TSY, arithmetic product of TY and TSC). The case-control populations were genotyped by restriction-site associated DNA sequencing (RADseq) and the 8.3 k SolCAP SNP genotyping array. The allele frequencies of single nucleotide polymorphisms (SNPs) were compared between cases and controls. RADseq identified, depending on data filtering criteria, between 6664 and 450 genes with one or more differential SNPs for one, two or all three traits. Differential SNPs in 275 genes were detected using the SolCAP array. A genome wide association study using the SolCAP array on an independent, unselected population identified SNPs associated with tuber starch content in 117 genes. Physical mapping of the genes containing differential or associated SNPs, and comparisons between the two genome wide genotyping methods and two different populations identified genome segments on all twelve potato chromosomes harboring one or more quantitative trait loci (QTL) for TY, TSC and TSY. Several hundred genes control tuber yield and starch content in potato. They are unequally distributed on all potato chromosomes, forming clusters between 0.5-4 Mbp width. The largest fraction of these genes had unknown function, followed by genes with putative signalling and regulatory functions. The genetic control of tuber yield and starch content is interlinked. Most differential SNPs affecting both traits had antagonistic effects: The allele increasing TY decreased TSC and vice versa. Exceptions were 89 SNP alleles which had synergistic effects on TY, TSC and TSY. These and the corresponding genes are primary targets for developing diagnostic markers.

A Conductometric Indium Oxide Semiconducting Nanoparticle Enzymatic Biosensor Array

PubMed Central

Lee, Dongjin; Ondrake, Janet; Cui, Tianhong

2011-01-01

We report a conductometric nanoparticle biosensor array to address the significant variation of electrical property in nanomaterial biosensors due to the random network nature of nanoparticle thin-film. Indium oxide and silica nanoparticles (SNP) are assembled selectively on the multi-site channel area of the resistors using layer-by-layer self-assembly. To demonstrate enzymatic biosensing capability, glucose oxidase is immobilized on the SNP layer for glucose detection. The packaged sensor chip onto a ceramic pin grid array is tested using syringe pump driven feed and multi-channel I–V measurement system. It is successfully demonstrated that glucose is detected in many different sensing sites within a chip, leading to concentration dependent currents. The sensitivity has been found to be dependent on the channel length of the resistor, 4–12 nA/mM for channel lengths of 5–20 μm, while the apparent Michaelis-Menten constant is 20 mM. By using sensor array, analytical data could be obtained with a single step of sample solution feeding. This work sheds light on the applicability of the developed nanoparticle microsensor array to multi-analyte sensors, novel bioassay platforms, and sensing components in a lab-on-a-chip. PMID:22163696

High-throughput multiplex HLA-typing by ligase detection reaction (LDR) and universal array (UA) approach.

PubMed

Consolandi, Clarissa

2009-01-01

One major goal of genetic research is to understand the role of genetic variation in living systems. In humans, by far the most common type of such variation involves differences in single DNA nucleotides, and is thus termed single nucleotide polymorphism (SNP). The need for improvement in throughput and reliability of traditional techniques makes it necessary to develop new technologies. Thus the past few years have witnessed an extraordinary surge of interest in DNA microarray technology. This new technology offers the first great hope for providing a systematic way to explore the genome. It permits a very rapid analysis of thousands genes for the purpose of gene discovery, sequencing, mapping, expression, and polymorphism detection. We generated a series of analytical tools to address the manufacturing, detection and data analysis components of a microarray experiment. In particular, we set up a universal array approach in combination with a PCR-LDR (polymerase chain reaction-ligation detection reaction) strategy for allele identification in the HLA gene.

Continuing difficulties in interpreting CNV data: lessons from a genome-wide CNV association study of Australian HNPCC/lynch syndrome patients

PubMed Central

2013-01-01

Background Hereditary non-polyposis colorectal cancer (HNPCC)/Lynch syndrome (LS) is a cancer syndrome characterised by early-onset epithelial cancers, especially colorectal cancer (CRC) and endometrial cancer. The aim of the current study was to use SNP-array technology to identify genomic aberrations which could contribute to the increased risk of cancer in HNPCC/LS patients. Methods Individuals diagnosed with HNPCC/LS (100) and healthy controls (384) were genotyped using the Illumina Human610-Quad SNP-arrays. Copy number variation (CNV) calling and association analyses were performed using Nexus software, with significant results validated using QuantiSNP. TaqMan Copy-Number assays were used for verification of CNVs showing significant association with HNPCC/LS identified by both software programs. Results We detected copy number (CN) gains associated with HNPCC/LS status on chromosome 7q11.21 (28% cases and 0% controls, Nexus; p = 3.60E-20 and QuantiSNP; p < 1.00E-16) and 16p11.2 (46% in cases, while a CN loss was observed in 23% of controls, Nexus; p = 4.93E-21 and QuantiSNP; p = 5.00E-06) via in silico analyses. TaqMan Copy-Number assay was used for validation of CNVs showing significant association with HNPCC/LS. In addition, CNV burden (total CNV length, average CNV length and number of observed CNV events) was significantly greater in cases compared to controls. Conclusion A greater CNV burden was identified in HNPCC/LS cases compared to controls supporting the notion of higher genomic instability in these patients. One intergenic locus on chromosome 7q11.21 is possibly associated with HNPCC/LS and deserves further investigation. The results from this study highlight the complexities of fluorescent based CNV analyses. The inefficiency of both CNV detection methods to reproducibly detect observed CNVs demonstrates the need for sequence data to be considered alongside intensity data to avoid false positive results. PMID:23531357

Fine definition of the pedigree haplotypes of closely related rice cultivars by means of genome-wide discovery of single-nucleotide polymorphisms.

PubMed

Yamamoto, Toshio; Nagasaki, Hideki; Yonemaru, Jun-ichi; Ebana, Kaworu; Nakajima, Maiko; Shibaya, Taeko; Yano, Masahiro

2010-04-27

To create useful gene combinations in crop breeding, it is necessary to clarify the dynamics of the genome composition created by breeding practices. A large quantity of single-nucleotide polymorphism (SNP) data is required to permit discrimination of chromosome segments among modern cultivars, which are genetically related. Here, we used a high-throughput sequencer to conduct whole-genome sequencing of an elite Japanese rice cultivar, Koshihikari, which is closely related to Nipponbare, whose genome sequencing has been completed. Then we designed a high-throughput typing array based on the SNP information by comparison of the two sequences. Finally, we applied this array to analyze historical representative rice cultivars to understand the dynamics of their genome composition. The total 5.89-Gb sequence for Koshihikari, equivalent to 15.7 x the entire rice genome, was mapped using the Pseudomolecules 4.0 database for Nipponbare. The resultant Koshihikari genome sequence corresponded to 80.1% of the Nipponbare sequence and led to the identification of 67,051 SNPs. A high-throughput typing array consisting of 1917 SNP sites distributed throughout the genome was designed to genotype 151 representative Japanese cultivars that have been grown during the past 150 years. We could identify the ancestral origin of the pedigree haplotypes in 60.9% of the Koshihikari genome and 18 consensus haplotype blocks which are inherited from traditional landraces to current improved varieties. Moreover, it was predicted that modern breeding practices have generally decreased genetic diversity Detection of genome-wide SNPs by both high-throughput sequencer and typing array made it possible to evaluate genomic composition of genetically related rice varieties. With the aid of their pedigree information, we clarified the dynamics of chromosome recombination during the historical rice breeding process. We also found several genomic regions decreasing genetic diversity which might be caused by a recent human selection in rice breeding. The definition of pedigree haplotypes by means of genome-wide SNPs will facilitate next-generation breeding of rice and other crops.

Discovery of novel variants in genotyping arrays improves genotype retention and reduces ascertainment bias

PubMed Central

2012-01-01

Background High-density genotyping arrays that measure hybridization of genomic DNA fragments to allele-specific oligonucleotide probes are widely used to genotype single nucleotide polymorphisms (SNPs) in genetic studies, including human genome-wide association studies. Hybridization intensities are converted to genotype calls by clustering algorithms that assign each sample to a genotype class at each SNP. Data for SNP probes that do not conform to the expected pattern of clustering are often discarded, contributing to ascertainment bias and resulting in lost information - as much as 50% in a recent genome-wide association study in dogs. Results We identified atypical patterns of hybridization intensities that were highly reproducible and demonstrated that these patterns represent genetic variants that were not accounted for in the design of the array platform. We characterized variable intensity oligonucleotide (VINO) probes that display such patterns and are found in all hybridization-based genotyping platforms, including those developed for human, dog, cattle, and mouse. When recognized and properly interpreted, VINOs recovered a substantial fraction of discarded probes and counteracted SNP ascertainment bias. We developed software (MouseDivGeno) that identifies VINOs and improves the accuracy of genotype calling. MouseDivGeno produced highly concordant genotype calls when compared with other methods but it uniquely identified more than 786000 VINOs in 351 mouse samples. We used whole-genome sequence from 14 mouse strains to confirm the presence of novel variants explaining 28000 VINOs in those strains. We also identified VINOs in human HapMap 3 samples, many of which were specific to an African population. Incorporating VINOs in phylogenetic analyses substantially improved the accuracy of a Mus species tree and local haplotype assignment in laboratory mouse strains. Conclusion The problems of ascertainment bias and missing information due to genotyping errors are widely recognized as limiting factors in genetic studies. We have conducted the first formal analysis of the effect of novel variants on genotyping arrays, and we have shown that these variants account for a large portion of miscalled and uncalled genotypes. Genetic studies will benefit from substantial improvements in the accuracy of their results by incorporating VINOs in their analyses. PMID:22260749

Genomic analysis identified a potential novel molecular mechanism for high-altitude adaptation in sheep at the Himalayas.

PubMed

Gorkhali, Neena Amatya; Dong, Kunzhe; Yang, Min; Song, Shen; Kader, Adiljian; Shrestha, Bhola Shankar; He, Xiaohong; Zhao, Qianjun; Pu, Yabin; Li, Xiangchen; Kijas, James; Guan, Weijun; Han, Jianlin; Jiang, Lin; Ma, Yuehui

2016-07-22

Sheep has successfully adapted to the extreme high-altitude Himalayan region. To identify genes underlying such adaptation, we genotyped genome-wide single nucleotide polymorphisms (SNPs) of four major sheep breeds living at different altitudes in Nepal and downloaded SNP array data from additional Asian and Middle East breeds. Using a di value-based genomic comparison between four high-altitude and eight lowland Asian breeds, we discovered the most differentiated variants at the locus of FGF-7 (Keratinocyte growth factor-7), which was previously reported as a good protective candidate for pulmonary injuries. We further found a SNP upstream of FGF-7 that appears to contribute to the divergence signature. First, the SNP occurred at an extremely conserved site. Second, the SNP showed an increasing allele frequency with the elevated altitude in Nepalese sheep. Third, the electrophoretic mobility shift assays (EMSA) analysis using human lung cancer cells revealed the allele-specific DNA-protein interactions. We thus hypothesized that FGF-7 gene potentially enhances lung function by regulating its expression level in high-altitude sheep through altering its binding of specific transcription factors. Especially, FGF-7 gene was not implicated in previous studies of other high-altitude species, suggesting a potential novel adaptive mechanism to high altitude in sheep at the Himalayas.

Detection of doublecortin domain-containing 2 (DCDC2), a new candidate tumor suppressor gene of hepatocellular carcinoma, by triple combination array analysis

PubMed Central

2013-01-01

Background To detect genes correlated with hepatocellular carcinoma (HCC), we developed a triple combination array consisting of methylation array, gene expression array and single nucleotide polymorphism (SNP) array analysis. Methods A surgical specimen obtained from a 68-year-old female HCC patient was analyzed by triple combination array, which identified doublecortin domain-containing 2 (DCDC2) as a candidate tumor suppressor gene of HCC. Subsequently, samples from 48 HCC patients were evaluated for their DCDC2 methylation and expression status using methylation specific PCR (MSP) and semi-quantitative reverse transcriptase (RT) PCR, respectively. Then, we investigated the relationship between clinicopathological factors and methylation status of DCDC2. Results DCDC2 was revealed to be hypermethylated (methylation value 0.846, range 0–1.0) in cancer tissue, compared with adjacent normal tissue (0.212) by methylation array in the 68-year-old female patient. Expression array showed decreased expression of DCDC2 in cancerous tissue. SNP array showed that the copy number of chromosome 6p22.1, in which DCDC2 resides, was normal. MSP revealed hypermethylation of the promoter region of DCDC2 in 41 of the tumor samples. DCDC2 expression was significantly decreased in the cases with methylation (P = 0.048). Furthermore, the methylated cases revealed worse prognosis for overall survival than unmethylated cases (P = 0.048). Conclusions The present study indicates that triple combination array is an effective method to detect novel genes related to HCC. We propose that DCDC2 is a tumor suppressor gene of HCC. PMID:24034596

RAD tag sequencing as a source of SNP markers in Cynara cardunculus L

PubMed Central

2012-01-01

Background The globe artichoke (Cynara cardunculus L. var. scolymus) genome is relatively poorly explored, especially compared to those of the other major Asteraceae crops sunflower and lettuce. No SNP markers are in the public domain. We have combined the recently developed restriction-site associated DNA (RAD) approach with the Illumina DNA sequencing platform to effect the rapid and mass discovery of SNP markers for C. cardunculus. Results RAD tags were sequenced from the genomic DNA of three C. cardunculus mapping population parents, generating 9.7 million reads, corresponding to ~1 Gbp of sequence. An assembly based on paired ends produced ~6.0 Mbp of genomic sequence, separated into ~19,000 contigs (mean length 312 bp), of which ~21% were fragments of putative coding sequence. The shared sequences allowed for the discovery of ~34,000 SNPs and nearly 800 indels, equivalent to a SNP frequency of 5.6 per 1,000 nt, and an indel frequency of 0.2 per 1,000 nt. A sample of heterozygous SNP loci was mapped by CAPS assays and this exercise provided validation of our mining criteria. The repetitive fraction of the genome had a high representation of retrotransposon sequence, followed by simple repeats, AT-low complexity regions and mobile DNA elements. The genomic k-mers distribution and CpG rate of C. cardunculus, compared with data derived from three whole genome-sequenced dicots species, provided a further evidence of the random representation of the C. cardunculus genome generated by RAD sampling. Conclusion The RAD tag sequencing approach is a cost-effective and rapid method to develop SNP markers in a highly heterozygous species. Our approach permitted to generate a large and robust SNP datasets by the adoption of optimized filtering criteria. PMID:22214349

k-merSNP discovery: Software for alignment-and reference-free scalable SNP discovery, phylogenetics, and annotation for hundreds of microbial genomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

With the flood of whole genome finished and draft microbial sequences, we need faster, more scalable bioinformatics tools for sequence comparison. An algorithm is described to find single nucleotide polymorphisms (SNPs) in whole genome data. It scales to hundreds of bacterial or viral genomes, and can be used for finished and/or draft genomes available as unassembled contigs or raw, unassembled reads. The method is fast to compute, finding SNPs and building a SNP phylogeny in minutes to hours, depending on the size and diversity of the input sequences. The SNP-based trees that result are consistent with known taxonomy and treesmore » determined in other studies. The approach we describe can handle many gigabases of sequence in a single run. The algorithm is based on k-mer analysis.« less

Renal cell carcinoma primary cultures maintain genomic and phenotypic profile of parental tumor tissues.

PubMed

Cifola, Ingrid; Bianchi, Cristina; Mangano, Eleonora; Bombelli, Silvia; Frascati, Fabio; Fasoli, Ester; Ferrero, Stefano; Di Stefano, Vitalba; Zipeto, Maria A; Magni, Fulvio; Signorini, Stefano; Battaglia, Cristina; Perego, Roberto A

2011-06-13

Clear cell renal cell carcinoma (ccRCC) is characterized by recurrent copy number alterations (CNAs) and loss of heterozygosity (LOH), which may have potential diagnostic and prognostic applications. Here, we explored whether ccRCC primary cultures, established from surgical tumor specimens, maintain the DNA profile of parental tumor tissues allowing a more confident CNAs and LOH discrimination with respect to the original tissues. We established a collection of 9 phenotypically well-characterized ccRCC primary cell cultures. Using the Affymetrix SNP array technology, we performed the genome-wide copy number (CN) profiling of both cultures and corresponding tumor tissues. Global concordance for each culture/tissue pair was assayed evaluating the correlations between whole-genome CN profiles and SNP allelic calls. CN analysis was performed using the two CNAG v3.0 and Partek software, and comparing results returned by two different algorithms (Hidden Markov Model and Genomic Segmentation). A very good overlap between the CNAs of each culture and corresponding tissue was observed. The finding, reinforced by high whole-genome CN correlations and SNP call concordances, provided evidence that each culture was derived from its corresponding tissue and maintained the genomic alterations of parental tumor. In addition, primary culture DNA profile remained stable for at least 3 weeks, till to third passage. These cultures showed a greater cell homogeneity and enrichment in tumor component than original tissues, thus enabling a better discrimination of CNAs and LOH. Especially for hemizygous deletions, primary cultures presented more evident CN losses, typically accompanied by LOH; differently, in original tissues the intensity of these deletions was weaken by normal cell contamination and LOH calls were missed. ccRCC primary cultures are a reliable in vitro model, well-reproducing original tumor genetics and phenotype, potentially useful for future functional approaches aimed to study genes or pathways involved in ccRCC etiopathogenesis and to identify novel clinical markers or therapeutic targets. Moreover, SNP array technology proved to be a powerful tool to better define the cell composition and homogeneity of RCC primary cultures. © 2011 Cifola et al; licensee BioMed Central Ltd.

Calling Chromosome Alterations, DNA Methylation Statuses, and Mutations in Tumors by Simple Targeted Next-Generation Sequencing: A Solution for Transferring Integrated Pangenomic Studies into Routine Practice?

PubMed

Garinet, Simon; Néou, Mario; de La Villéon, Bruno; Faillot, Simon; Sakat, Julien; Da Fonseca, Juliana P; Jouinot, Anne; Le Tourneau, Christophe; Kamal, Maud; Luscap-Rondof, Windy; Boeva, Valentina; Gaujoux, Sebastien; Vidaud, Michel; Pasmant, Eric; Letourneur, Franck; Bertherat, Jérôme; Assié, Guillaume

2017-09-01

Pangenomic studies identified distinct molecular classes for many cancers, with major clinical applications. However, routine use requires cost-effective assays. We assessed whether targeted next-generation sequencing (NGS) could call chromosomal alterations and DNA methylation status. A training set of 77 tumors and a validation set of 449 (43 tumor types) were analyzed by targeted NGS and single-nucleotide polymorphism (SNP) arrays. Thirty-two tumors were analyzed by NGS after bisulfite conversion, and compared to methylation array or methylation-specific multiplex ligation-dependent probe amplification. Considering allelic ratios, correlation was strong between targeted NGS and SNP arrays (r = 0.88). In contrast, considering DNA copy number, for variations of one DNA copy, correlation was weaker between read counts and SNP array (r = 0.49). Thus, we generated TARGOMICs, optimized for detecting chromosome alterations by combining allelic ratios and read counts generated by targeted NGS. Sensitivity for calling normal, lost, and gained chromosomes was 89%, 72%, and 31%, respectively. Specificity was 81%, 93%, and 98%, respectively. These results were confirmed in the validation set. Finally, TARGOMICs could efficiently align and compute proportions of methylated cytosines from bisulfite-converted DNA from targeted NGS. In conclusion, beyond calling mutations, targeted NGS efficiently calls chromosome alterations and methylation status in tumors. A single run and minor design/protocol adaptations are sufficient. Optimizing targeted NGS should expand translation of genomics to clinical routine. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Efficient selection of tagging single-nucleotide polymorphisms in multiple populations.

PubMed

Howie, Bryan N; Carlson, Christopher S; Rieder, Mark J; Nickerson, Deborah A

2006-08-01

Common genetic polymorphism may explain a portion of the heritable risk for common diseases, so considerable effort has been devoted to finding and typing common single-nucleotide polymorphisms (SNPs) in the human genome. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), suggesting that only a subset of all SNPs (known as tagging SNPs, or tagSNPs) need to be genotyped for disease association studies. Based on the genetic differences that exist among human populations, most tagSNP sets are defined in a single population and applied only in populations that are closely related. To improve the efficiency of multi-population analyses, we have developed an algorithm called MultiPop-TagSelect that finds a near-minimal union of population-specific tagSNP sets across an arbitrary number of populations. We present this approach as an extension of LD-select, a tagSNP selection method that uses a greedy algorithm to group SNPs into bins based on their pairwise association patterns, although the MultiPop-TagSelect algorithm could be used with any SNP tagging approach that allows choices between nearly equivalent SNPs. We evaluate the algorithm by considering tagSNP selection in candidate-gene resequencing data and lower density whole-chromosome data. Our analysis reveals that an exhaustive search is often intractable, while the developed algorithm can quickly and reliably find near-optimal solutions even for difficult tagSNP selection problems. Using populations of African, Asian, and European ancestry, we also show that an optimal multi-population set of tagSNPs can be substantially smaller (up to 44%) than a typical set obtained through independent or sequential selection.

A High-Resolution SNP Array-Based Linkage Map Anchors a New Domestic Cat Draft Genome Assembly and Provides Detailed Patterns of Recombination.

PubMed

Li, Gang; Hillier, LaDeana W; Grahn, Robert A; Zimin, Aleksey V; David, Victor A; Menotti-Raymond, Marilyn; Middleton, Rondo; Hannah, Steven; Hendrickson, Sher; Makunin, Alex; O'Brien, Stephen J; Minx, Pat; Wilson, Richard K; Lyons, Leslie A; Warren, Wesley C; Murphy, William J

2016-06-01

High-resolution genetic and physical maps are invaluable tools for building accurate genome assemblies, and interpreting results of genome-wide association studies (GWAS). Previous genetic and physical maps anchored good quality draft assemblies of the domestic cat genome, enabling the discovery of numerous genes underlying hereditary disease and phenotypes of interest to the biomedical science and breeding communities. However, these maps lacked sufficient marker density to order thousands of shorter scaffolds in earlier assemblies, which instead relied heavily on comparative mapping with related species. A high-resolution map would aid in validating and ordering chromosome scaffolds from existing and new genome assemblies. Here, we describe a high-resolution genetic linkage map of the domestic cat genome based on genotyping 453 domestic cats from several multi-generational pedigrees on the Illumina 63K SNP array. The final maps include 58,055 SNP markers placed relative to 6637 markers with unique positions, distributed across all autosomes and the X chromosome. Our final sex-averaged maps span a total autosomal length of 4464 cM, the longest described linkage map for any mammal, confirming length estimates from a previous microsatellite-based map. The linkage map was used to order and orient the scaffolds from a substantially more contiguous domestic cat genome assembly (Felis catus v8.0), which incorporated ∼20 × coverage of Illumina fragment reads. The new genome assembly shows substantial improvements in contiguity, with a nearly fourfold increase in N50 scaffold size to 18 Mb. We use this map to report probable structural errors in previous maps and assemblies, and to describe features of the recombination landscape, including a massive (∼50 Mb) recombination desert (of virtually zero recombination) on the X chromosome that parallels a similar desert on the porcine X chromosome in both size and physical location. Copyright © 2016 Li et al.

Restitution and genetic differentiation of salmon populations in the southern Baltic genotyped with the Atlantic salmon 7K SNP array.

PubMed

Poćwierz-Kotus, Anita; Bernaś, Rafał; Kent, Matthew P; Lien, Sigbjørn; Leliűna, Egidijus; Dębowski, Piotr; Wenne, Roman

2015-05-06

Native populations of Atlantic salmon in Poland, from the southern Baltic region, became extinct in the 1980s. Attempts to restitute salmon populations in Poland have been based on a Latvian salmon population from the Daugava river. Releases of hatchery reared smolts started in 1986, but to date, only one population with confirmed natural reproduction has been observed in the Slupia river. Our aim was to investigate the genetic differentiation of salmon populations in the southern Baltic using a 7K SNP (single nucleotide polymorphism) array in order to assess the impact of salmon restitution in Poland. One hundred and forty salmon samples were collected from: the Polish Slupia river including wild salmon and individuals from two hatcheries, the Swedish Morrum river and the Lithuanian Neman river. All samples were genotyped using an Atlantic salmon 7K SNP array. A set of 3218 diagnostic SNPs was used for genetic analyses. Genetic structure analyses indicated that the individuals from the investigated populations were clustered into three groups i.e. one clade that included individuals from both hatcheries and the wild population from the Polish Slupia river, which was clearly separated from the other clades. An assignment test showed that there were no stray fish from the Morrum or Neman rivers in the sample analyzed from the Slupia river. Global FST over polymorphic loci was high (0.177). A strong genetic differentiation was observed between the Lithuanian and Swedish populations (FST = 0.28). Wild juvenile salmon specimens that were sampled from the Slupia river were the progeny of fish released from hatcheries and, most likely, were not progeny of stray fish from Sweden or Lithuania. Strong genetic differences were observed between the salmon populations from the three studied locations. Our recommendation is that future stocking activities that aim at restituting salmon populations in Poland include stocking material from the Lithuanian Neman river because of its closer geographic proximity.

Ultrasoft x-ray imaging system for the National Spherical Torus Experiment

NASA Astrophysics Data System (ADS)

Stutman, D.; Finkenthal, M.; Soukhanovskii, V.; May, M. J.; Moos, H. W.; Kaita, R.

1999-01-01

A spectrally resolved ultrasoft x-ray imaging system, consisting of arrays of high resolution (<2 Å) and throughput (⩾tens of kHz) miniature monochromators, and based on multilayer mirrors and absolute photodiodes, is being designed for the National Spherical Torus Experiment. Initially, three poloidal arrays of diodes filtered for C 1s-np emission will be implemented for fast tomographic imaging of the colder start-up plasmas. Later on, mirrors tuned to the C Lyα emission will be added in order to enable the arrays to "see" the periphery through the hot core and to study magnetohydrodynamic activity and impurity transport in this region. We also discuss possible core diagnostics, based on tomographic imaging of the Lyα emission from the plume of recombined, low Z impurity ions left by neutral beams or fueling pellets. The arrays can also be used for radiated power measurements and to map the distribution of high Z impurities injected for transport studies. The performance of the proposed system is illustrated with results from test channels on the CDX-U spherical torus at Princeton Plasma Physics Laboratory.

Prioritizing causal disease genes using unbiased genomic features.

PubMed

Deo, Rahul C; Musso, Gabriel; Tasan, Murat; Tang, Paul; Poon, Annie; Yuan, Christiana; Felix, Janine F; Vasan, Ramachandran S; Beroukhim, Rameen; De Marco, Teresa; Kwok, Pui-Yan; MacRae, Calum A; Roth, Frederick P

2014-12-03

Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits. To aid in localizing causal genes, we develop a machine learning approach, Objective Prioritization for Enhanced Novelty (OPEN), which quantitatively prioritizes gene-disease associations based on a diverse group of genomic features. This approach uses only unbiased predictive features and thus is not hampered by a preference towards previously well-characterized genes. We demonstrate success in identifying genetic determinants for CVD-related traits, including cholesterol levels, blood pressure, and conduction system and cardiomyopathy phenotypes. Using OPEN, we prioritize genes, including FLNC, for association with increased left ventricular diameter, which is a defining feature of a prevalent cardiovascular disorder, dilated cardiomyopathy or DCM. Using a zebrafish model, we experimentally validate FLNC and identify a novel FLNC splice-site mutation in a patient with severe DCM. Our approach stands to assist interpretation of large-scale genetic studies without compromising their fundamentally unbiased nature.

SNP-array lesions in core binding factor acute myeloid leukemia

PubMed Central

Duployez, Nicolas; Boudry-Labis, Elise; Roumier, Christophe; Boissel, Nicolas; Petit, Arnaud; Geffroy, Sandrine; Helevaut, Nathalie; Celli-Lebras, Karine; Terré, Christine; Fenneteau, Odile; Cuccuini, Wendy; Luquet, Isabelle; Lapillonne, Hélène; Lacombe, Catherine; Cornillet, Pascale; Ifrah, Norbert; Dombret, Hervé; Leverger, Guy; Jourdan, Eric; Preudhomme, Claude

2018-01-01

Acute myeloid leukemia (AML) with t(8;21) and inv(16), together referred as core binding factor (CBF)-AML, are recognized as unique entities. Both rearrangements share a common pathophysiology, the disruption of the CBF, and a relatively good prognosis. Experiments have demonstrated that CBF rearrangements were insufficient to induce leukemia, implying the existence of cooperating events. To explore these aberrations, we performed single nucleotide polymorphism (SNP)-array in a well-annotated cohort of 198 patients with CBF-AML. Excluding breakpoint-associated lesions, the most frequent events included loss of a sex chromosome (53%), deletions at 9q21 (12%) and 7q36 (9%) in patients with t(8;21) compared with trisomy 22 (13%), trisomy 8 (10%) and 7q36 deletions (12%) in patients with inv(16). SNP-array revealed novel recurrent genetic alterations likely to be involved in CBF-AML leukemogenesis. ZBTB7A mutations (20% of t(8;21)-AML) were shown to be a target of copy-neutral losses of heterozygosity (CN-LOH) at chromosome 19p. FOXP1 focal deletions were identified in 5% of inv(16)-AML while sequence analysis revealed that 2% carried FOXP1 truncating mutations. Finally, CCDC26 disruption was found in both subtypes (4.5% of the whole cohort) and possibly highlighted a new lesion associated with aberrant tyrosine kinase signaling in this particular subtype of leukemia. PMID:29464086

SNP-array lesions in core binding factor acute myeloid leukemia.

PubMed

Duployez, Nicolas; Boudry-Labis, Elise; Roumier, Christophe; Boissel, Nicolas; Petit, Arnaud; Geffroy, Sandrine; Helevaut, Nathalie; Celli-Lebras, Karine; Terré, Christine; Fenneteau, Odile; Cuccuini, Wendy; Luquet, Isabelle; Lapillonne, Hélène; Lacombe, Catherine; Cornillet, Pascale; Ifrah, Norbert; Dombret, Hervé; Leverger, Guy; Jourdan, Eric; Preudhomme, Claude

2018-01-19

Acute myeloid leukemia (AML) with t(8;21) and inv(16), together referred as core binding factor (CBF)-AML, are recognized as unique entities. Both rearrangements share a common pathophysiology, the disruption of the CBF, and a relatively good prognosis. Experiments have demonstrated that CBF rearrangements were insufficient to induce leukemia, implying the existence of cooperating events. To explore these aberrations, we performed single nucleotide polymorphism (SNP)-array in a well-annotated cohort of 198 patients with CBF-AML. Excluding breakpoint-associated lesions, the most frequent events included loss of a sex chromosome (53%), deletions at 9q21 (12%) and 7q36 (9%) in patients with t(8;21) compared with trisomy 22 (13%), trisomy 8 (10%) and 7q36 deletions (12%) in patients with inv(16). SNP-array revealed novel recurrent genetic alterations likely to be involved in CBF-AML leukemogenesis. ZBTB7A mutations (20% of t(8;21)-AML) were shown to be a target of copy-neutral losses of heterozygosity (CN-LOH) at chromosome 19p. FOXP1 focal deletions were identified in 5% of inv(16)-AML while sequence analysis revealed that 2% carried FOXP1 truncating mutations. Finally, CCDC26 disruption was found in both subtypes (4.5% of the whole cohort) and possibly highlighted a new lesion associated with aberrant tyrosine kinase signaling in this particular subtype of leukemia.

Microdeletions are a general feature of adult and adolescent acute lymphoblastic leukemia: Unexpected similarities with pediatric disease

PubMed Central

Paulsson, Kajsa; Cazier, Jean-Baptiste; MacDougall, Finlay; Stevens, Jane; Stasevich, Irina; Vrcelj, Nikoletta; Chaplin, Tracy; Lillington, Debra M.; Lister, T. Andrew; Young, Bryan D.

2008-01-01

We present here a genome-wide map of abnormalities found in diagnostic samples from 45 adults and adolescents with acute lymphoblastic leukemia (ALL). A 500K SNP array analysis uncovered frequent genetic abnormalities, with cryptic deletions constituting half of the detected changes, implying that microdeletions are a characteristic feature of this malignancy. Importantly, the pattern of deletions resembled that recently reported in pediatric ALL, suggesting that adult, adolescent, and childhood cases may be more similar on the genetic level than previously thought. Thus, 70% of the cases displayed deletion of one or more of the CDKN2A, PAX5, IKZF1, ETV6, RB1, and EBF1 genes. Furthermore, several genes not previously implicated in the pathogenesis of ALL were identified as possible recurrent targets of deletion. In total, the SNP array analysis identified 367 genetic abnormalities not corresponding to known copy number polymorphisms, with all but two cases (96%) displaying at least one cryptic change. The resolution level of this SNP array study is the highest used to date to investigate a malignant hematologic disorder. Our findings provide insights into the leukemogenic process and may be clinically important in adult and adolescent ALL. Most importantly, we report that microdeletions of key genes appear to be a common, characteristic feature of ALL that is shared among different clinical, morphological, and cytogenetic subgroups. PMID:18458336

Supramolecular Nanoparticles for Molecular Diagnostics and Therapeutics

NASA Astrophysics Data System (ADS)

Chen, Kuan-Ju

Over the past decades, significant efforts have been devoted to explore the use of various nanoparticle-based systems in the field of nanomedicine, including molecular imaging and therapy. Supramolecular synthetic approaches have attracted lots of attention due to their flexibility, convenience, and modularity for producing nanoparticles. In this dissertation, the developmental story of our size-controllable supramolecular nanoparticles (SNPs) will be discussed, as well as their use in specific biomedical applications. To achieve the self-assembly of SNPs, the well-characterized molecular recognition system (i.e., cyclodextrin/adamantane recognition) was employed. The resulting SNPs, which were assembled from three molecular building blocks, possess incredible stability in various physiological conditions, reversible size-controllability and dynamic disassembly that were exploited for various in vitro and in vivo applications. An advantage of using the supramolecular approach is that it enables the convenient incorporation of functional ligands onto SNP surface that confers functionality ( e.g., targeting, cell penetration) to SNPs. We utilized SNPs for molecular imaging such as magnetic resonance imaging (MRI) and positron emission tomography (PET) by introducing reporter systems (i.e., radio-isotopes, MR contrast agents, and fluorophores) into SNPs. On the other hand, the incorporation of various payloads, including drugs, genes and proteins, into SNPs showed improved delivery performance and enhanced therapeutic efficacy for these therapeutic agents. Leveraging the powers of (i) a combinatorial synthetic approach based on supramolecular assembly and (ii) a digital microreactor, a rapid developmental pathway was developed that is capable of screening SNP candidates for the ideal structural and functional properties that deliver optimal performance. Moreover, SNP-based theranostic delivery systems that combine reporter systems and therapeutic payloads into a single SNP for both diagnosis and therapy were generated. The results show that this type of theranostic SNPs may have a great contribution in the optimization of therapeutic efficacy for individual patients in clinical translation in the near future. It is anticipated that our supramolecular synthetic approach could be adopted to assemble various SNP-based delivery agents for molecular diagnostics and therapeutics that pave the way toward personalized medicine.

Development of a 63K SNP array for Gossypium and high-density mapping of intra- and inter-specific populations of cotton (G. hirsutum L.)

USDA-ARS?s Scientific Manuscript database

High-throughput genotyping arrays provide a standardized resource for crop research communities that are useful for a breadth of applications including high-density genetic mapping, genome-wide association studies (GWAS), genomic selection (GS), candidate marker and quantitative trait loci (QTL) ide...

Development and evaluation of the Axiom® IStraw35 384HT array for the allo-octoploid cultivated strawberry Fragaria ×ananassa

USDA-ARS?s Scientific Manuscript database

The Axiom® IStraw90 SNP (single nucleotide polymorphism) array was developed to enable high-throughput genotyping in allo-octoploid cultivated strawberry (Fragaria ×ananassa). However, high cost ($80-105 per sample) limits throughput for certain applications. On average the IStraw90 has yielded 50% ...

Development and evaluation of a high density genotyping 'Axiom_Arachis' array with 58K SNPs for accelerating genetics and breeding in groundnut

USDA-ARS?s Scientific Manuscript database

Single nucleotide polymorphisms (SNPs) are the most abundant DNA sequence variation in the genomes which can be used to associate genotypic variation to the phenotype. Therefore, availability of a high-density SNP array with uniform genome coverage can advance genetic studies and breeding applicatio...

Comprehensive comparison of three commercial human whole-exome capture platforms.

PubMed

Asan; Xu, Yu; Jiang, Hui; Tyler-Smith, Chris; Xue, Yali; Jiang, Tao; Wang, Jiawei; Wu, Mingzhi; Liu, Xiao; Tian, Geng; Wang, Jun; Wang, Jian; Yang, Huangming; Zhang, Xiuqing

2011-09-28

Exome sequencing, which allows the global analysis of protein coding sequences in the human genome, has become an effective and affordable approach to detecting causative genetic mutations in diseases. Currently, there are several commercial human exome capture platforms; however, the relative performances of these have not been characterized sufficiently to know which is best for a particular study. We comprehensively compared three platforms: NimbleGen's Sequence Capture Array and SeqCap EZ, and Agilent's SureSelect. We assessed their performance in a variety of ways, including number of genes covered and capture efficacy. Differences that may impact on the choice of platform were that Agilent SureSelect covered approximately 1,100 more genes, while NimbleGen provided better flanking sequence capture. Although all three platforms achieved similar capture specificity of targeted regions, the NimbleGen platforms showed better uniformity of coverage and greater genotype sensitivity at 30- to 100-fold sequencing depth. All three platforms showed similar power in exome SNP calling, including medically relevant SNPs. Compared with genotyping and whole-genome sequencing data, the three platforms achieved a similar accuracy of genotype assignment and SNP detection. Importantly, all three platforms showed similar levels of reproducibility, GC bias and reference allele bias. We demonstrate key differences between the three platforms, particularly advantages of solutions over array capture and the importance of a large gene target set.

Sunflower Hybrid Breeding: From Markers to Genomic Selection

PubMed Central

Dimitrijevic, Aleksandra; Horn, Renate

2018-01-01

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches combining omic technologies (genomics, transcriptomics, proteomics, metabolomics and phenomics) using bioinformatic tools will facilitate the identification of target genes and markers for complex traits and will give a better insight into the mechanisms behind the traits. PMID:29387071

[Phenotypic and genetic analysis of a patient presented with Tietz/Waardenburg type II a syndrome].

PubMed

Wang, Huanhuan; Tang, Lifang; Zhang, Jingmin; Hu, Qin; Chen, Yingwei; Xiao, Bing

2015-08-01

To determine the genetic cause for a patient featuring decreased pigmentation of the skin and iris, hearing loss and multiple congenital anomalies. Routine chromosomal banding was performed to analyze the karyotype of the patient and his parents. Single nucleotide polymorphism array (SNP array) was employed to identify cryptic chromosome aberrations, and quantitative real-time PCR was used to confirm the results. Karyotype analysis has revealed no obvious anomaly for the patient and his parents. SNP array analysis of the patient has demonstrated a 3.9 Mb deletion encompassing 3p13p14.1, which caused loss of entire MITF gene. The deletion was confirmed by quantitative real-time PCR. Clinical features of the patient have included severe bilateral hearing loss, decreased pigmentation of the skin and iris and multiple congenital anomalies. The patient, carrying a 3p13p14.1 deletion, has features of Tietz syndrome/Waardenburg syndrome type IIa. This case may provide additional data for the study of genotype-phenotype correlation of this disease.

Development of a rapid SNP-typing assay to differentiate Bifidobacterium animalis ssp. lactis strains used in probiotic-supplemented dairy products.

PubMed

Lomonaco, Sara; Furumoto, Emily J; Loquasto, Joseph R; Morra, Patrizia; Grassi, Ausilia; Roberts, Robert F

2015-02-01

Identification at the genus, species, and strain levels is desirable when a probiotic microorganism is added to foods. Strains of Bifidobacterium animalis ssp. lactis (BAL) are commonly used worldwide in dairy products supplemented with probiotic strains. However, strain discrimination is difficult because of the high degree of genome identity (99.975%) between different genomes of this subspecies. Typing of monomorphic species can be carried out efficiently by targeting informative single nucleotide polymorphisms (SNP). Findings from a previous study analyzing both reference and commercial strains of BAL identified SNP that could be used to discriminate common strains into 8 groups. This paper describes development of a minisequencing assay based on the primer extension reaction (PER) targeting multiple SNP that can allow strain differentiation of BAL. Based on previous data, 6 informative SNP were selected for further testing, and a multiplex preliminary PCR was optimized to amplify the DNA regions containing the selected SNP. Extension primers (EP) annealing immediately adjacent to the selected SNP were developed and tested in simplex and multiplex PER to evaluate their performance. Twenty-five strains belonging to 9 distinct genomic clusters of B. animalis ssp. lactis were selected and analyzed using the developed minisequencing assay, simultaneously targeting the 6 selected SNP. Fragment analysis was subsequently carried out in duplicate and demonstrated that the assay yielded 8 specific profiles separating the most commonly used commercial strains. This novel multiplex PER approach provides a simple, rapid, flexible SNP-based subtyping method for proper characterization and identification of commercial probiotic strains of BAL from fermented dairy products. To assess the usefulness of this method, DNA was extracted from yogurt manufactured with and without the addition of B. animalis ssp. lactis BB-12. Extracted DNA was then subjected to the minisequencing protocol, resulting in a SNP profile matching the profile for the strain BB-12. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Extensive population structure in San, Khoe, and mixed ancestry populations from southern Africa revealed by 44 short 5-SNP haplotypes.

PubMed

Schlebusch, Carina M; Soodyall, Himlya

2012-12-01

The San and Khoe people currently represent remnant groups of a much larger and widely distributed population of hunter-gatherers and pastoralists who had exclusive occupation of southern Africa before the arrival of Bantu-speaking groups in the past 1,200 years and sea-borne immigrants within the last 350 years. Genetic studies [mitochondrial deoxyribonucleic acid (DNA) and Y-chromosome] conducted on San and Khoe groups revealed that they harbor some of the most divergent lineages found in living peoples throughout the world. Recently, high-density, autosomal, single-nucleotide polymorphism (SNP)-array studies confirmed the early divergence of Khoe-San population groups from all other human populations. The present study made use of 220 autosomal SNP markers (in the format of both haplotypes and genotypes) to examine the population structure of various San and Khoe groups and their relationship to other neighboring groups. Whereas analyses based on the genotypic SNP data only supported the division of the included populations into three main groups-Khoe-San, Bantu-speakers, and non-African populations-haplotype analyses revealed finer structure within Khoe-San populations. By the use of only 44 short SNP haplotypes (compiled from a total of 220 SNPs), most of the Khoe-San groups could be resolved as separate groups by applying STRUCTURE analyses. Therefore, by carefully selecting a few SNPs and combining them into haplotypes, we were able to achieve the same level of population distinction that was achieved previously in high-density SNP studies on the same population groups. Using haplotypes proved to be a very efficient and cost-effective way to study population structure. Copyright © 2013 Wayne State University Press, Detroit, Michigan 48201-1309.

SNPchiMp: a database to disentangle the SNPchip jungle in bovine livestock.

PubMed

Nicolazzi, Ezequiel Luis; Picciolini, Matteo; Strozzi, Francesco; Schnabel, Robert David; Lawley, Cindy; Pirani, Ali; Brew, Fiona; Stella, Alessandra

2014-02-11

Currently, six commercial whole-genome SNP chips are available for cattle genotyping, produced by two different genotyping platforms. Technical issues need to be addressed to combine data that originates from the different platforms, or different versions of the same array generated by the manufacturer. For example: i) genome coordinates for SNPs may refer to different genome assemblies; ii) reference genome sequences are updated over time changing the positions, or even removing sequences which contain SNPs; iii) not all commercial SNP ID's are searchable within public databases; iv) SNPs can be coded using different formats and referencing different strands (e.g. A/B or A/C/T/G alleles, referencing forward/reverse, top/bottom or plus/minus strand); v) Due to new information being discovered, higher density chips do not necessarily include all the SNPs present in the lower density chips; and, vi) SNP IDs may not be consistent across chips and platforms. Most researchers and breed associations manage SNP data in real-time and thus require tools to standardise data in a user-friendly manner. Here we present SNPchiMp, a MySQL database linked to an open access web-based interface. Features of this interface include, but are not limited to, the following functions: 1) referencing the SNP mapping information to the latest genome assembly, 2) extraction of information contained in dbSNP for SNPs present in all commercially available bovine chips, and 3) identification of SNPs in common between two or more bovine chips (e.g. for SNP imputation from lower to higher density). In addition, SNPchiMp can retrieve this information on subsets of SNPs, accessing such data either via physical position on a supported assembly, or by a list of SNP IDs, rs or ss identifiers. This tool combines many different sources of information, that otherwise are time consuming to obtain and difficult to integrate. The SNPchiMp not only provides the information in a user-friendly format, but also enables researchers to perform a large number of operations with a few clicks of the mouse. This significantly reduces the time needed to execute the large number of operations required to manage SNP data.

A graphene-based platform for single nucleotide polymorphism (SNP) genotyping.

PubMed

Liu, Meng; Zhao, Huimin; Chen, Shuo; Yu, Hongtao; Zhang, Yaobin; Quan, Xie

2011-06-15

A facile, rapid, stable and sensitive approach for fluorescent detection of single nucleotide polymorphism (SNP) is designed based on DNA ligase reaction and π-stacking between the graphene and the nucleotide bases. In the presence of perfectly matched DNA, DNA ligase can catalyze the linkage of fluorescein amidite-labeled single-stranded DNA (ssDNA) and a phosphorylated ssDNA, and thus the formation of a stable duplex in high yield. However, the catalytic reaction cannot effectively carry out with one-base mismatched DNA target. In this case, we add graphene to the system in order to produce different quenching signals due to its different adsorption affinity for ssDNA and double-stranded DNA. Taking advantage of the unique surface property of graphene and the high discriminability of DNA ligase, the proposed protocol exhibits good performance in SNP genotyping. The results indicate that it is possible to accurately determine SNP with frequency as low as 2.6% within 40 min. Furthermore, the presented flexible strategy facilitates the development of other biosensing applications in the future. Copyright © 2011 Elsevier B.V. All rights reserved.

Combined sequence and sequence-structure-based methods for analyzing RAAS gene SNPs: a computational approach.

PubMed

Singh, Kh Dhanachandra; Karthikeyan, Muthusamy

2014-12-01

The renin-angiotensin-aldosterone system (RAAS) plays a key role in the regulation of blood pressure (BP). Mutations on the genes that encode components of the RAAS have played a significant role in genetic susceptibility to hypertension and have been intensively scrutinized. The identification of such probably causal mutations not only provides insight into the RAAS but may also serve as antihypertensive therapeutic targets and diagnostic markers. The methods for analyzing the SNPs from the huge dataset of SNPs, containing both functional and neutral SNPs is challenging by the experimental approach on every SNPs to determine their biological significance. To explore the functional significance of genetic mutation (SNPs), we adopted combined sequence and sequence-structure-based SNP analysis algorithm. Out of 3864 SNPs reported in dbSNP, we found 108 missense SNPs in the coding region and remaining in the non-coding region. In this study, we are reporting only those SNPs in coding region to be deleterious when three or more tools are predicted to be deleterious and which have high RMSD from the native structure. Based on these analyses, we have identified two SNPs of REN gene, eight SNPs of AGT gene, three SNPs of ACE gene, two SNPs of AT1R gene, three SNPs of CYP11B2 gene and three SNPs of CMA1 gene in the coding region were found to be deleterious. Further this type of study will be helpful in reducing the cost and time for identification of potential SNP and also helpful in selecting potential SNP for experimental study out of SNP pool.

Efficient SNP Discovery by Combining Microarray and Lab-on-a-Chip Data for Animal Breeding and Selection

PubMed Central

Huang, Chao-Wei; Lin, Yu-Tsung; Ding, Shih-Torng; Lo, Ling-Ling; Wang, Pei-Hwa; Lin, En-Chung; Liu, Fang-Wei; Lu, Yen-Wen

2015-01-01

The genetic markers associated with economic traits have been widely explored for animal breeding. Among these markers, single-nucleotide polymorphism (SNPs) are gradually becoming a prevalent and effective evaluation tool. Since SNPs only focus on the genetic sequences of interest, it thereby reduces the evaluation time and cost. Compared to traditional approaches, SNP genotyping techniques incorporate informative genetic background, improve the breeding prediction accuracy and acquiesce breeding quality on the farm. This article therefore reviews the typical procedures of animal breeding using SNPs and the current status of related techniques. The associated SNP information and genotyping techniques, including microarray and Lab-on-a-Chip based platforms, along with their potential are highlighted. Examples in pig and poultry with different SNP loci linked to high economic trait values are given. The recommendations for utilizing SNP genotyping in nimal breeding are summarized. PMID:27600241

Seven newly identified loci for autoimmune thyroid disease.

PubMed

Cooper, Jason D; Simmonds, Matthew J; Walker, Neil M; Burren, Oliver; Brand, Oliver J; Guo, Hui; Wallace, Chris; Stevens, Helen; Coleman, Gillian; Franklyn, Jayne A; Todd, John A; Gough, Stephen C L

2012-12-01

Autoimmune thyroid disease (AITD), including Graves' disease (GD) and Hashimoto's thyroiditis (HT), is one of the most common of the immune-mediated diseases. To further investigate the genetic determinants of AITD, we conducted an association study using a custom-made single-nucleotide polymorphism (SNP) array, the ImmunoChip. The SNP array contains all known and genotype-able SNPs across 186 distinct susceptibility loci associated with one or more immune-mediated diseases. After stringent quality control, we analysed 103 875 common SNPs (minor allele frequency >0.05) in 2285 GD and 462 HT patients and 9364 controls. We found evidence for seven new AITD risk loci (P < 1.12 × 10(-6); a permutation test derived significance threshold), five at locations previously associated and two at locations awaiting confirmation, with other immune-mediated diseases.

A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses

PubMed Central

2010-01-01

Background Thoroughbred horses have been selected for traits contributing to speed and stamina for centuries. It is widely recognized that inherited variation in physical and physiological characteristics is responsible for variation in individual aptitude for race distance, and that muscle phenotypes in particular are important. Results A genome-wide SNP-association study for optimum racing distance was performed using the EquineSNP50 Bead Chip genotyping array in a cohort of n = 118 elite Thoroughbred racehorses divergent for race distance aptitude. In a cohort-based association test we evaluated genotypic variation at 40,977 SNPs between horses suited to short distance (≤ 8 f) and middle-long distance (> 8 f) races. The most significant SNP was located on chromosome 18: BIEC2-417495 ~690 kb from the gene encoding myostatin (MSTN) [Punadj. = 6.96 × 10-6]. Considering best race distance as a quantitative phenotype, a peak of association on chromosome 18 (chr18:65809482-67545806) comprising eight SNPs encompassing a 1.7 Mb region was observed. Again, similar to the cohort-based analysis, the most significant SNP was BIEC2-417495 (Punadj. = 1.61 × 10-9; PBonf. = 6.58 × 10-5). In a candidate gene study we have previously reported a SNP (g.66493737C>T) in MSTN associated with best race distance in Thoroughbreds; however, its functional and genome-wide relevance were uncertain. Additional re-sequencing in the flanking regions of the MSTN gene revealed four novel 3' UTR SNPs and a 227 bp SINE insertion polymorphism in the 5' UTR promoter sequence. Linkage disequilibrium was highest between g.66493737C>T and BIEC2-417495 (r2 = 0.86). Conclusions Comparative association tests consistently demonstrated the g.66493737C>T SNP as the superior variant in the prediction of distance aptitude in racehorses (g.66493737C>T, P = 1.02 × 10-10; BIEC2-417495, Punadj. = 1.61 × 10-9). Functional investigations will be required to determine whether this polymorphism affects putative transcription-factor binding and gives rise to variation in gene and protein expression. Nonetheless, this study demonstrates that the g.66493737C>T SNP provides the most powerful genetic marker for prediction of race distance aptitude in Thoroughbreds. PMID:20932346

A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses.

PubMed

Hill, Emmeline W; McGivney, Beatrice A; Gu, Jingjing; Whiston, Ronan; Machugh, David E

2010-10-11

Thoroughbred horses have been selected for traits contributing to speed and stamina for centuries. It is widely recognized that inherited variation in physical and physiological characteristics is responsible for variation in individual aptitude for race distance, and that muscle phenotypes in particular are important. A genome-wide SNP-association study for optimum racing distance was performed using the EquineSNP50 Bead Chip genotyping array in a cohort of n = 118 elite Thoroughbred racehorses divergent for race distance aptitude. In a cohort-based association test we evaluated genotypic variation at 40,977 SNPs between horses suited to short distance (≤ 8 f) and middle-long distance (> 8 f) races. The most significant SNP was located on chromosome 18: BIEC2-417495 ~690 kb from the gene encoding myostatin (MSTN) [P(unadj.) = 6.96 x 10⁻⁶]. Considering best race distance as a quantitative phenotype, a peak of association on chromosome 18 (chr18:65809482-67545806) comprising eight SNPs encompassing a 1.7 Mb region was observed. Again, similar to the cohort-based analysis, the most significant SNP was BIEC2-417495 (P(unadj.) = 1.61 x 10⁻⁹; P(Bonf.) = 6.58 x 10⁻⁵). In a candidate gene study we have previously reported a SNP (g.66493737C>T) in MSTN associated with best race distance in Thoroughbreds; however, its functional and genome-wide relevance were uncertain. Additional re-sequencing in the flanking regions of the MSTN gene revealed four novel 3' UTR SNPs and a 227 bp SINE insertion polymorphism in the 5' UTR promoter sequence. Linkage disequilibrium was highest between g.66493737C>T and BIEC2-417495 (r² = 0.86). Comparative association tests consistently demonstrated the g.66493737C>T SNP as the superior variant in the prediction of distance aptitude in racehorses (g.66493737C>T, P = 1.02 x 10⁻¹⁰; BIEC2-417495, P(unadj.) = 1.61 x 10⁻⁹). Functional investigations will be required to determine whether this polymorphism affects putative transcription-factor binding and gives rise to variation in gene and protein expression. Nonetheless, this study demonstrates that the g.66493737C>T SNP provides the most powerful genetic marker for prediction of race distance aptitude in Thoroughbreds.

Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls.

PubMed

Craddock, Nick; Hurles, Matthew E; Cardin, Niall; Pearson, Richard D; Plagnol, Vincent; Robson, Samuel; Vukcevic, Damjan; Barnes, Chris; Conrad, Donald F; Giannoulatou, Eleni; Holmes, Chris; Marchini, Jonathan L; Stirrups, Kathy; Tobin, Martin D; Wain, Louise V; Yau, Chris; Aerts, Jan; Ahmad, Tariq; Andrews, T Daniel; Arbury, Hazel; Attwood, Anthony; Auton, Adam; Ball, Stephen G; Balmforth, Anthony J; Barrett, Jeffrey C; Barroso, Inês; Barton, Anne; Bennett, Amanda J; Bhaskar, Sanjeev; Blaszczyk, Katarzyna; Bowes, John; Brand, Oliver J; Braund, Peter S; Bredin, Francesca; Breen, Gerome; Brown, Morris J; Bruce, Ian N; Bull, Jaswinder; Burren, Oliver S; Burton, John; Byrnes, Jake; Caesar, Sian; Clee, Chris M; Coffey, Alison J; Connell, John M C; Cooper, Jason D; Dominiczak, Anna F; Downes, Kate; Drummond, Hazel E; Dudakia, Darshna; Dunham, Andrew; Ebbs, Bernadette; Eccles, Diana; Edkins, Sarah; Edwards, Cathryn; Elliot, Anna; Emery, Paul; Evans, David M; Evans, Gareth; Eyre, Steve; Farmer, Anne; Ferrier, I Nicol; Feuk, Lars; Fitzgerald, Tomas; Flynn, Edward; Forbes, Alistair; Forty, Liz; Franklyn, Jayne A; Freathy, Rachel M; Gibbs, Polly; Gilbert, Paul; Gokumen, Omer; Gordon-Smith, Katherine; Gray, Emma; Green, Elaine; Groves, Chris J; Grozeva, Detelina; Gwilliam, Rhian; Hall, Anita; Hammond, Naomi; Hardy, Matt; Harrison, Pile; Hassanali, Neelam; Hebaishi, Husam; Hines, Sarah; Hinks, Anne; Hitman, Graham A; Hocking, Lynne; Howard, Eleanor; Howard, Philip; Howson, Joanna M M; Hughes, Debbie; Hunt, Sarah; Isaacs, John D; Jain, Mahim; Jewell, Derek P; Johnson, Toby; Jolley, Jennifer D; Jones, Ian R; Jones, Lisa A; Kirov, George; Langford, Cordelia F; Lango-Allen, Hana; Lathrop, G Mark; Lee, James; Lee, Kate L; Lees, Charlie; Lewis, Kevin; Lindgren, Cecilia M; Maisuria-Armer, Meeta; Maller, Julian; Mansfield, John; Martin, Paul; Massey, Dunecan C O; McArdle, Wendy L; McGuffin, Peter; McLay, Kirsten E; Mentzer, Alex; Mimmack, Michael L; Morgan, Ann E; Morris, Andrew P; Mowat, Craig; Myers, Simon; Newman, William; Nimmo, Elaine R; O'Donovan, Michael C; Onipinla, Abiodun; Onyiah, Ifejinelo; Ovington, Nigel R; Owen, Michael J; Palin, Kimmo; Parnell, Kirstie; Pernet, David; Perry, John R B; Phillips, Anne; Pinto, Dalila; Prescott, Natalie J; Prokopenko, Inga; Quail, Michael A; Rafelt, Suzanne; Rayner, Nigel W; Redon, Richard; Reid, David M; Renwick; Ring, Susan M; Robertson, Neil; Russell, Ellie; St Clair, David; Sambrook, Jennifer G; Sanderson, Jeremy D; Schuilenburg, Helen; Scott, Carol E; Scott, Richard; Seal, Sheila; Shaw-Hawkins, Sue; Shields, Beverley M; Simmonds, Matthew J; Smyth, Debbie J; Somaskantharajah, Elilan; Spanova, Katarina; Steer, Sophia; Stephens, Jonathan; Stevens, Helen E; Stone, Millicent A; Su, Zhan; Symmons, Deborah P M; Thompson, John R; Thomson, Wendy; Travers, Mary E; Turnbull, Clare; Valsesia, Armand; Walker, Mark; Walker, Neil M; Wallace, Chris; Warren-Perry, Margaret; Watkins, Nicholas A; Webster, John; Weedon, Michael N; Wilson, Anthony G; Woodburn, Matthew; Wordsworth, B Paul; Young, Allan H; Zeggini, Eleftheria; Carter, Nigel P; Frayling, Timothy M; Lee, Charles; McVean, Gil; Munroe, Patricia B; Palotie, Aarno; Sawcer, Stephen J; Scherer, Stephen W; Strachan, David P; Tyler-Smith, Chris; Brown, Matthew A; Burton, Paul R; Caulfield, Mark J; Compston, Alastair; Farrall, Martin; Gough, Stephen C L; Hall, Alistair S; Hattersley, Andrew T; Hill, Adrian V S; Mathew, Christopher G; Pembrey, Marcus; Satsangi, Jack; Stratton, Michael R; Worthington, Jane; Deloukas, Panos; Duncanson, Audrey; Kwiatkowski, Dominic P; McCarthy, Mark I; Ouwehand, Willem; Parkes, Miles; Rahman, Nazneen; Todd, John A; Samani, Nilesh J; Donnelly, Peter

2010-04-01

Copy number variants (CNVs) account for a major proportion of human genetic polymorphism and have been predicted to have an important role in genetic susceptibility to common disease. To address this we undertook a large, direct genome-wide study of association between CNVs and eight common human diseases. Using a purpose-designed array we typed approximately 19,000 individuals into distinct copy-number classes at 3,432 polymorphic CNVs, including an estimated approximately 50% of all common CNVs larger than 500 base pairs. We identified several biological artefacts that lead to false-positive associations, including systematic CNV differences between DNAs derived from blood and cell lines. Association testing and follow-up replication analyses confirmed three loci where CNVs were associated with disease-IRGM for Crohn's disease, HLA for Crohn's disease, rheumatoid arthritis and type 1 diabetes, and TSPAN8 for type 2 diabetes-although in each case the locus had previously been identified in single nucleotide polymorphism (SNP)-based studies, reflecting our observation that most common CNVs that are well-typed on our array are well tagged by SNPs and so have been indirectly explored through SNP studies. We conclude that common CNVs that can be typed on existing platforms are unlikely to contribute greatly to the genetic basis of common human diseases.

Incorporation of Personal Single Nucleotide Polymorphism (SNP) Data into a National Level Electronic Health Record for Disease Risk Assessment, Part 3: An Evaluation of SNP Incorporated National Health Information System of Turkey for Prostate Cancer

PubMed Central

Beyan, Timur

2014-01-01

Background A personalized medicine approach provides opportunities for predictive and preventive medicine. Using genomic, clinical, environmental, and behavioral data, the tracking and management of individual wellness is possible. A prolific way to carry this personalized approach into routine practices can be accomplished by integrating clinical interpretations of genomic variations into electronic medical records (EMRs)/electronic health records (EHRs). Today, various central EHR infrastructures have been constituted in many countries of the world, including Turkey. Objective As an initial attempt to develop a sophisticated infrastructure, we have concentrated on incorporating the personal single nucleotide polymorphism (SNP) data into the National Health Information System of Turkey (NHIS-T) for disease risk assessment, and evaluated the performance of various predictive models for prostate cancer cases. We present our work as a three part miniseries: (1) an overview of requirements, (2) the incorporation of SNP data into the NHIS-T, and (3) an evaluation of SNP data incorporated into the NHIS-T for prostate cancer. Methods In the third article of this miniseries, we have evaluated the proposed complementary capabilities (ie, knowledge base and end-user application) with real data. Before the evaluation phase, clinicogenomic associations about increased prostate cancer risk were extracted from knowledge sources, and published predictive genomic models assessing individual prostate cancer risk were collected. To evaluate complementary capabilities, we also gathered personal SNP data of four prostate cancer cases and fifteen controls. Using these data files, we compared various independent and model-based, prostate cancer risk assessment approaches. Results Through the extraction and selection processes of SNP-prostate cancer risk associations, we collected 209 independent associations for increased risk of prostate cancer from the studied knowledge sources. Also, we gathered six cumulative models and two probabilistic models. Cumulative models and assessment of independent associations did not have impressive results. There was one of the probabilistic, model-based interpretation that was successful compared to the others. In envirobehavioral and clinical evaluations, we found that some of the comorbidities, especially, would be useful to evaluate disease risk. Even though we had a very limited dataset, a comparison of performances of different disease models and their implementation with real data as use case scenarios helped us to gain deeper insight into the proposed architecture. Conclusions In order to benefit from genomic variation data, existing EHR/EMR systems must be constructed with the capability of tracking and monitoring all aspects of personal health status (genomic, clinical, environmental, etc) in 24/7 situations, and also with the capability of suggesting evidence-based recommendations. A national-level, accredited knowledge base is a top requirement for improved end-user systems interpreting these parameters. Finally, categorization using similar, individual characteristics (SNP patterns, exposure history, etc) may be an effective way to predict disease risks, but this approach needs to be concretized and supported with new studies. PMID:25600087

A multi-SNP association test for complex diseases incorporating an optimal P-value threshold algorithm in nuclear families.

PubMed

Wang, Yi-Ting; Sung, Pei-Yuan; Lin, Peng-Lin; Yu, Ya-Wen; Chung, Ren-Hua

2015-05-15

Genome-wide association studies (GWAS) have become a common approach to identifying single nucleotide polymorphisms (SNPs) associated with complex diseases. As complex diseases are caused by the joint effects of multiple genes, while the effect of individual gene or SNP is modest, a method considering the joint effects of multiple SNPs can be more powerful than testing individual SNPs. The multi-SNP analysis aims to test association based on a SNP set, usually defined based on biological knowledge such as gene or pathway, which may contain only a portion of SNPs with effects on the disease. Therefore, a challenge for the multi-SNP analysis is how to effectively select a subset of SNPs with promising association signals from the SNP set. We developed the Optimal P-value Threshold Pedigree Disequilibrium Test (OPTPDT). The OPTPDT uses general nuclear families. A variable p-value threshold algorithm is used to determine an optimal p-value threshold for selecting a subset of SNPs. A permutation procedure is used to assess the significance of the test. We used simulations to verify that the OPTPDT has correct type I error rates. Our power studies showed that the OPTPDT can be more powerful than the set-based test in PLINK, the multi-SNP FBAT test, and the p-value based test GATES. We applied the OPTPDT to a family-based autism GWAS dataset for gene-based association analysis and identified MACROD2-AS1 with genome-wide significance (p-value=2.5×10(-6)). Our simulation results suggested that the OPTPDT is a valid and powerful test. The OPTPDT will be helpful for gene-based or pathway association analysis. The method is ideal for the secondary analysis of existing GWAS datasets, which may identify a set of SNPs with joint effects on the disease.

Resolving incomplete single nucleotide polymorphism tagging of HLA-DQ2.2 for coeliac disease genotyping using digital droplet PCR.

PubMed

Hardy, M Y; Ontiveros, N; Varney, M D; Tye-Din, J A

2018-04-01

A hallmark of coeliac disease (CD) is the exceptionally strong genetic association with HLA-DQ2.5, DQ8, and DQ2.2. HLA typing provides information on CD risk important to both clinicians and researchers. A method that enables simple and fast detection of all CD risk genotypes is particularly desirable for the study of large populations. Single nucleotide polymorphism (SNP)-based HLA typing can detect the CD risk genotypes by detecting a combination of six SNPs but this approach can struggle to resolve HLA-DQ2.2, seen in 4% of European CD patients, because of the low resolution of one negatively predicting SNP. We sought to optimise SNP-based HLA typing by harnessing the additional resolution of digital droplet PCR to resolve HLA-DQ2.2. Here we test this two-step approach in an unselected sample of Mexican DNA and compare its accuracy to DNA typed using traditional exon detection. The addition of digital droplet PCR for samples requiring negative prediction of HLA-DQ2.2 enabled HLA-DQ2.2 to be accurately typed. This technique is a simple addition to a SNP-based typing strategy and enables comprehensive definition of all at-risk HLA genotypes in CD in a timely and cost-effective manner. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Uniparental disomy and prenatal phenotype

PubMed Central

Li, Xiaofei; Liu, Yan; Yue, Song; Wang, Li; Zhang, Tiejuan; Guo, Cuixia; Hu, Wenjie; Kagan, Karl-Oliver; Wu, Qingqing

2017-01-01

Abstract Rationale: Uniparental disomy (UPD) gives a description of the inheritance of both homologues of a chromosome pair from the same parent. The consequences of UPD depend on the specific chromosome/segment involved and its parental origin. Patient concerns: We report prenatal phenotypes of 2 rare cases of UPD. Diagnoses: The prenatal phenotype of case 1 included sonographic markers such as enlarged nuchal translucency (NT), absent nasal bone, short femur and humerus length, and several structural malformations involving Dandy–Walker malformation and congenital heart defects. The prenatal phenotype of Case 2 are sonographic markers, including enlarged NT, thickened nuchal fold, ascites, and polyhydramnios without apparent structural malformations. Interventions: Conventional G-band karyotype appears normal in case 1, while it shows normal chromosomes with a small supernumerary marker chromosome (sSMC) in case 2. Genetic etiology was left unknown until single-nucleotide polymorphism-based array (SNP-array) was performed, and segmental paternal UPD 22 was identified in case 1 and segmental paternal UPD 14 was found in case 2. Outcomes: The parents of case 1 chose termination of pregnancy. The neonate of case 2 was born prematurely with a bellshaped small thorax and died within a day. Lessons: UPD cases are rare and the phenotypes are different, which depend on the origin and affected chromosomal part. If a fetus shows multiple anomalies that cannot be attributed to a common aneuploidy or a genetic syndrome, or manifests some features possibly related to an UPD syndrome, such as detection of sSMC, SNP-array should be considered. PMID:29137034

Uniparental disomy and prenatal phenotype: Two case reports and review.

PubMed

Li, Xiaofei; Liu, Yan; Yue, Song; Wang, Li; Zhang, Tiejuan; Guo, Cuixia; Hu, Wenjie; Kagan, Karl-Oliver; Wu, Qingqing

2017-11-01

Uniparental disomy (UPD) gives a description of the inheritance of both homologues of a chromosome pair from the same parent. The consequences of UPD depend on the specific chromosome/segment involved and its parental origin. We report prenatal phenotypes of 2 rare cases of UPD. The prenatal phenotype of case 1 included sonographic markers such as enlarged nuchal translucency (NT), absent nasal bone, short femur and humerus length, and several structural malformations involving Dandy-Walker malformation and congenital heart defects. The prenatal phenotype of Case 2 are sonographic markers, including enlarged NT, thickened nuchal fold, ascites, and polyhydramnios without apparent structural malformations. Conventional G-band karyotype appears normal in case 1, while it shows normal chromosomes with a small supernumerary marker chromosome (sSMC) in case 2. Genetic etiology was left unknown until single-nucleotide polymorphism-based array (SNP-array) was performed, and segmental paternal UPD 22 was identified in case 1 and segmental paternal UPD 14 was found in case 2. The parents of case 1 chose termination of pregnancy. The neonate of case 2 was born prematurely with a bellshaped small thorax and died within a day. UPD cases are rare and the phenotypes are different, which depend on the origin and affected chromosomal part. If a fetus shows multiple anomalies that cannot be attributed to a common aneuploidy or a genetic syndrome, or manifests some features possibly related to an UPD syndrome, such as detection of sSMC, SNP-array should be considered.

Integrating Milk Metabolite Profile Information for the Prediction of Traditional Milk Traits Based on SNP Information for Holstein Cows

PubMed Central

Melzer, Nina; Wittenburg, Dörte; Repsilber, Dirk

2013-01-01

In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs) enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach). To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL) were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317) SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype). PMID:23990900

High-density fiber optic biosensor arrays

NASA Astrophysics Data System (ADS)

Epstein, Jason R.; Walt, David R.

2002-02-01

Novel approaches are required to coordinate the immense amounts of information derived from diverse genomes. This concept has influenced the expanded role of high-throughput DNA detection and analysis in the biological sciences. A high-density fiber optic DNA biosensor was developed consisting of oligonucleotide-functionalized, 3.1 mm diameter microspheres deposited into the etched wells on the distal face of a 500 micrometers imaging fiber bundle. Imaging fiber bundles containing thousands of optical fibers, each associated with a unique oligonucleotide probe sequence, were the foundation for an optically connected, individually addressable DNA detection platform. Different oligonucleotide-functionalized microspheres were combined in a stock solution, and randomly dispersed into the etched wells. Microsphere positions were registered from optical dyes incorporated onto the microspheres. The distribution process provided an inherent redundancy that increases the signal-to-noise ratio as the square root of the number of sensors examined. The representative amount of each probe-type in the array was dependent on their initial stock solution concentration, and as other sequences of interest arise, new microsphere elements can be added to arrays without altering the existing detection capabilities. The oligonucleotide probe sequences hybridize to fluorescently-labeled, complementary DNA target solutions. Fiber optic DNA microarray research has included DNA-protein interaction profiles, microbial strain differentiation, non-labeled target interrogation with molecular beacons, and single cell-based assays. This biosensor array is proficient in DNA detection linked to specific disease states, single nucleotide polymorphism (SNP's) discrimination, and gene expression analysis. This array platform permits multiple detection formats, provides smaller feature sizes, and enables sensor design flexibility. High-density fiber optic microarray biosensors provide a fast, reversible format with the detection limit of a few hundred molecules.

Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study.

PubMed

Lane, William J; Westhoff, Connie M; Gleadall, Nicholas S; Aguad, Maria; Smeland-Wagman, Robin; Vege, Sunitha; Simmons, Daimon P; Mah, Helen H; Lebo, Matthew S; Walter, Klaudia; Soranzo, Nicole; Di Angelantonio, Emanuele; Danesh, John; Roberts, David J; Watkins, Nick A; Ouwehand, Willem H; Butterworth, Adam S; Kaufman, Richard M; Rehm, Heidi L; Silberstein, Leslie E; Green, Robert C

2018-06-01

There are more than 300 known red blood cell (RBC) antigens and 33 platelet antigens that differ between individuals. Sensitisation to antigens is a serious complication that can occur in prenatal medicine and after blood transfusion, particularly for patients who require multiple transfusions. Although pre-transfusion compatibility testing largely relies on serological methods, reagents are not available for many antigens. Methods based on single-nucleotide polymorphism (SNP) arrays have been used, but typing for ABO and Rh-the most important blood groups-cannot be done with SNP typing alone. We aimed to develop a novel method based on whole-genome sequencing to identify RBC and platelet antigens. This whole-genome sequencing study is a subanalysis of data from patients in the whole-genome sequencing arm of the MedSeq Project randomised controlled trial (NCT01736566) with no measured patient outcomes. We created a database of molecular changes in RBC and platelet antigens and developed an automated antigen-typing algorithm based on whole-genome sequencing (bloodTyper). This algorithm was iteratively improved to address cis-trans haplotype ambiguities and homologous gene alignments. Whole-genome sequencing data from 110 MedSeq participants (30 × depth) were used to initially validate bloodTyper through comparison with conventional serology and SNP methods for typing of 38 RBC antigens in 12 blood-group systems and 22 human platelet antigens. bloodTyper was further validated with whole-genome sequencing data from 200 INTERVAL trial participants (15 × depth) with serological comparisons. We iteratively improved bloodTyper by comparing its typing results with conventional serological and SNP typing in three rounds of testing. The initial whole-genome sequencing typing algorithm was 99·5% concordant across the first 20 MedSeq genomes. Addressing discordances led to development of an improved algorithm that was 99·8% concordant for the remaining 90 MedSeq genomes. Additional modifications led to the final algorithm, which was 99·2% concordant across 200 INTERVAL genomes (or 99·9% after adjustment for the lower depth of coverage). By enabling more precise antigen-matching of patients with blood donors, antigen typing based on whole-genome sequencing provides a novel approach to improve transfusion outcomes with the potential to transform the practice of transfusion medicine. National Human Genome Research Institute, Doris Duke Charitable Foundation, National Health Service Blood and Transplant, National Institute for Health Research, and Wellcome Trust. Copyright © 2018 Elsevier Ltd. All rights reserved.

Application of Nexus copy number software for CNV detection and analysis.

PubMed

Darvishi, Katayoon

2010-04-01

Among human structural genomic variation, copy number variants (CNVs) are the most frequently known component, comprised of gains/losses of DNA segments that are generally 1 kb in length or longer. Array-based comparative genomic hybridization (aCGH) has emerged as a powerful tool for detecting genomic copy number variants (CNVs). With the rapid increase in the density of array technology and with the adaptation of new high-throughput technology, a reliable and computationally scalable method for accurate mapping of recurring DNA copy number aberrations has become a main focus in research. Here we introduce Nexus Copy Number software, a platform-independent tool, to analyze the output files of all types of commercial and custom-made comparative genomic hybridization (CGH) and single-nucleotide polymorphism (SNP) arrays, such as those manufactured by Affymetrix, Agilent Technologies, Illumina, and Roche NimbleGen. It also supports data generated by various array image-analysis software tools such as GenePix, ImaGene, and BlueFuse. (c) 2010 by John Wiley & Sons, Inc.

Phenotype variations affect genetic association studies of degenerative disc disease: conclusions of analysis of genetic association of 58 single nucleotide polymorphisms with highly specific phenotypes for disc degeneration in 332 subjects.

PubMed

Rajasekaran, S; Kanna, Rishi Mugesh; Senthil, Natesan; Raveendran, Muthuraja; Cheung, Kenneth M C; Chan, Danny; Subramaniam, Sakthikanal; Shetty, Ajoy Prasad

2013-10-01

Although the influence of genetics on the process of disc degeneration is well recognized, in recently published studies, there is a wide variation in the race and selection criteria for such study populations. More importantly, the radiographic features of disc degeneration that are selected to represent the disc degeneration phenotype are variable in these studies. The study presented here evaluates the association between single nucleotide polymorphisms (SNPs) of candidate genes and three distinct radiographic features that can be defined as the degenerative disc disease (DDD) phenotype. The study objectives were to examine the allelic diversity of 58 SNPs related to 35 candidate genes related to lumbar DDD, to evaluate the association in a hitherto unevaluated ethnic Indian population that represents more than one-sixth of the world population, and to analyze how genetic associations can vary in the same study subjects with the choice of phenotype. A cross-sectional, case-control study of an ethnic Indian population was carried out. Fifty-eight SNPs in 35 potential candidate genes were evaluated in 342 subjects and the associations were analyzed against three highly specific markers for DDD, namely disc degeneration by Pfirrmann grading, end-plate damage evaluated by total end-plate damage score, and annular tears evaluated by disc herniations and hyperintense zones. Genotyping of cases and controls was performed on a genome-wide SNP array to identify potential associated disease loci. The results from the genome-wide SNP array were then used to facilitate SNP selection and genotype validation was conducted using Sequenom-based genotyping. Eleven of the 58 SNPs provided evidence of association with one of the phenotypes. For annular tears, rs1042631 SNP of AGC1 and rs467691 SNP of ADAMTS5 were highly significantly associated (p<.01) and SNPs in NGFB, IL1B, IL18RAP, and MMP10 were also significantly associated (p<.05). The rs4076018 SNP of NGFB was highly significant (p<.01) and rs2292657 SNP of GLI1 was significantly (p<.05) correlated to disc degeneration. For end-plate damage, the rs2252070 SNP of MMP 13 showed a significant association (p<.05). Previously associated genes such as COL 9, SKT, CHST 3, CILP, IGFR, SOXp, BMP, MMP 2-12, ADH2, IL1RN, and COX2 were not significantly associated and new associations (NGFB and GLI1) were identified. The validity of all the associations was found to be phenotype dependent. For the first time, genetic associations with DDD have been performed in an Indian population. Apart from identifying new associations, the highlight of the study was that in the same study population with DDD, SNP associations completely changed when different radiographic features were used to define the DDD phenotype. Our study results therefore indicate that standardization of the phenotypes chosen to study the genetics of disc degeneration is essential and should be strongly considered before planning genetic association studies. Copyright © 2013 Elsevier Inc. All rights reserved.

Clinical impact of gene mutations and lesions detected by SNP-array karyotyping in acute myeloid leukemia patients in the context of gemtuzumab ozogamicin treatment: Results of the ALFA-0701 trial

PubMed Central

Chevret, Sylvie; Nibourel, Olivier; Cheok, Meyling; Pautas, Cécile; Duléry, Rémy; Boyer, Thomas; Cayuela, Jean-Michel; Hayette, Sandrine; Raffoux, Emmanuel; Farhat, Hassan; Boissel, Nicolas; Terre, Christine

2014-01-01

We recently showed that the addition of fractionated doses of gemtuzumab ozogamicin (GO) to standard chemotherapy improves clinical outcome of acute myeloid leukemia (AML) patients. In the present study, we performed mutational analysis of 11 genes (FLT3, NPM1, CEBPA, MLL, WT1, IDH1/2, RUNX1, ASXL1, TET2, DNMT3A), EVI1 overexpression screening, and 6.0 single-nucleotide polymorphism array (SNP-A) analysis in diagnostic samples of the 278 AML patients enrolled in the ALFA-0701 trial. In cytogenetically normal (CN) AML (n = 146), 38% of the patients had at least 1 SNP-A lesion and 89% of the patients had at least 1 molecular alteration. In multivariate analysis, the independent predictors of higher cumulative incidence of relapse were unfavorable karyotype (P = 0.013) and randomization in the control arm (P = 0.007) in the whole cohort, and MLL partial tandem duplications (P = 0.014) and DNMT3A mutations (P = 0.010) in CN-AML. The independent predictors of shorter overall survival (OS) were unfavorable karyotype (P < 0.001) and SNP-A lesion(s) (P = 0.001) in the whole cohort, and SNP-A lesion(s) (P = 0.006), DNMT3A mutations (P = 0.042) and randomization in the control arm (P = 0.043) in CN-AML. Interestingly, CN-AML patients benefited preferentially more from GO treatment as compared to AML patients with abnormal cytogenetics (hazard ratio for death, 0.52 versus 1.14; test for interaction, P = 0.04). Although the interaction test was not statistically significant, the OS benefit associated with GO treatment appeared also more pronounced in FLT3 internal tandem duplication positive than in negative patients. PMID:24659740

Clinical impact of gene mutations and lesions detected by SNP-array karyotyping in acute myeloid leukemia patients in the context of gemtuzumab ozogamicin treatment: results of the ALFA-0701 trial.

PubMed

Renneville, Aline; Abdelali, Raouf Ben; Chevret, Sylvie; Nibourel, Olivier; Cheok, Meyling; Pautas, Cécile; Duléry, Rémy; Boyer, Thomas; Cayuela, Jean-Michel; Hayette, Sandrine; Raffoux, Emmanuel; Farhat, Hassan; Boissel, Nicolas; Terre, Christine; Dombret, Hervé; Castaigne, Sylvie; Preudhomme, Claude

2014-02-28

We recently showed that the addition of fractionated doses of gemtuzumab ozogamicin (GO) to standard chemotherapy improves clinical outcome of acute myeloid leukemia (AML) patients. In the present study, we performed mutational analysis of 11 genes (FLT3, NPM1, CEBPA, MLL, WT1, IDH1/2, RUNX1, ASXL1, TET2, DNMT3A), EVI1 overexpression screening, and 6.0 single-nucleotide polymorphism array (SNP-A) analysis in diagnostic samples of the 278 AML patients enrolled in the ALFA-0701 trial. In cytogenetically normal (CN) AML (n=146), 38% of the patients had at least 1 SNP-A lesion and 89% of the patients had at least 1 molecular alteration. In multivariate analysis, the independent predictors of higher cumulative incidence of relapse were unfavorable karyotype (P = 0.013) and randomization in the control arm (P = 0.007) in the whole cohort, and MLL partial tandem duplications (P = 0.014) and DNMT3A mutations (P = 0.010) in CN-AML. The independent predictors of shorter overall survival (OS) were unfavorable karyotype (P <0.001) and SNP-A lesion(s) (P = 0.001) in the whole cohort, and SNP-A lesion(s) (P = 0.006), DNMT3A mutations (P = 0.042) and randomization in the control arm (P = 0.043) in CN-AML. Interestingly, CN-AML patients benefited preferentially more from GO treatment as compared to AML patients with abnormal cytogenetics (hazard ratio for death, 0.52 versus 1.14; test for interaction, P = 0.04). Although the interaction test was not statistically significant, the OS benefit associated with GO treatment appeared also more pronounced in FLT3 internal tandem duplication positive than in negative patients.

Development and Evaluation of a Genome-Wide 6K SNP Array for Diploid Sweet Cherry and Tetraploid Sour Cherry

PubMed Central

Peace, Cameron; Bassil, Nahla; Main, Dorrie; Ficklin, Stephen; Rosyara, Umesh R.; Stegmeir, Travis; Sebolt, Audrey; Gilmore, Barbara; Lawley, Cindy; Mockler, Todd C.; Bryant, Douglas W.; Wilhelm, Larry; Iezzoni, Amy

2012-01-01

High-throughput genome scans are important tools for genetic studies and breeding applications. Here, a 6K SNP array for use with the Illumina Infinium® system was developed for diploid sweet cherry (Prunus avium) and allotetraploid sour cherry (P. cerasus). This effort was led by RosBREED, a community initiative to enable marker-assisted breeding for rosaceous crops. Next-generation sequencing in diverse breeding germplasm provided 25 billion basepairs (Gb) of cherry DNA sequence from which were identified genome-wide SNPs for sweet cherry and for the two sour cherry subgenomes derived from sweet cherry (avium subgenome) and P. fruticosa (fruticosa subgenome). Anchoring to the peach genome sequence, recently released by the International Peach Genome Initiative, predicted relative physical locations of the 1.9 million putative SNPs detected, preliminarily filtered to 368,943 SNPs. Further filtering was guided by results of a 144-SNP subset examined with the Illumina GoldenGate® assay on 160 accessions. A 6K Infinium® II array was designed with SNPs evenly spaced genetically across the sweet and sour cherry genomes. SNPs were developed for each sour cherry subgenome by using minor allele frequency in the sour cherry detection panel to enrich for subgenome-specific SNPs followed by targeting to either subgenome according to alleles observed in sweet cherry. The array was evaluated using panels of sweet (n = 269) and sour (n = 330) cherry breeding germplasm. Approximately one third of array SNPs were informative for each crop. A total of 1825 polymorphic SNPs were verified in sweet cherry, 13% of these originally developed for sour cherry. Allele dosage was resolved for 2058 polymorphic SNPs in sour cherry, one third of these being originally developed for sweet cherry. This publicly available genomics resource represents a significant advance in cherry genome-scanning capability that will accelerate marker-locus-trait association discovery, genome structure investigation, and genetic diversity assessment in this diploid-tetraploid crop group. PMID:23284615

Activity study of biogenic spherical silver nanoparticles towards microbes and oxidants

NASA Astrophysics Data System (ADS)

Hoskote Anand, Kiran Kumar; Mandal, Badal Kumar

2015-01-01

The eco-friendly approach for the green synthesis of silver nanoparticles (SNP) using Terminalia bellirica (T. bellirica) fruit extract is reported herein. Initially formation of SNP was noticed through visual color change from yellow to reddish brown and further analyzed by surface plasmonic resonance (SPR) band at 429 nm using UV-Vis spectroscopy. Identification of different polyphenols present in T. bellirica extract was done using High Pressure Liquid Chromatography (HPLC). Aqueous T. bellirica extract contains high amount of gallic acid which is major secondary metabolite responsible for the reduction and stabilization process. It was established by analyses of extracts before and after reduction using HPLC. Formation of spherical SNP was characterized by Transmission Electron Microscopy (TEM) analysis. X-ray Diffraction (XRD) study revealed crystalline nature of SNP. Presence of different functional groups on the surface of SNP was evidenced by Fourier Transform Infrared Spectroscopy (FTIR) study. A plausible mechanism of reduction and stabilization processes involved in the synthesis of stable SNP was also explained based on HPLC and FTIR data. In addition, the synthesized SNP was tested for antibacterial and antioxidant activities. SNP showed good antimicrobial activity against both gram positive (S. aureus) and gram negative (E. coli) bacteria. It also showed good antioxidant activity compared to ascorbic acid as standard antioxidant by using standard DPPH method.

A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46 450 cases and 42 461 controls from the breast cancer association consortium

PubMed Central

Milne, Roger L.; Herranz, Jesús; Michailidou, Kyriaki; Dennis, Joe; Tyrer, Jonathan P.; Zamora, M. Pilar; Arias-Perez, José Ignacio; González-Neira, Anna; Pita, Guillermo; Alonso, M. Rosario; Wang, Qin; Bolla, Manjeet K.; Czene, Kamila; Eriksson, Mikael; Humphreys, Keith; Darabi, Hatef; Li, Jingmei; Anton-Culver, Hoda; Neuhausen, Susan L.; Ziogas, Argyrios; Clarke, Christina A.; Hopper, John L.; Dite, Gillian S.; Apicella, Carmel; Southey, Melissa C.; Chenevix-Trench, Georgia; Swerdlow, Anthony; Ashworth, Alan; Orr, Nicholas; Schoemaker, Minouk; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Mulligan, Anna Marie; Bojesen, Stig E.; Nordestgaard, Børge G.; Flyger, Henrik; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Wang, Xianshu; Olson, Janet E.; Vachon, Celine; Purrington, Kristen; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Dunning, Alison M.; Shah, Mitul; Guénel, Pascal; Truong, Thérèse; Sanchez, Marie; Mulot, Claire; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Lindblom, Annika; Margolin, Sara; Hooning, Maartje J.; Hollestelle, Antoinette; Collée, J. Margriet; Jager, Agnes; Cox, Angela; Brock, Ian W.; Reed, Malcolm W.R.; Devilee, Peter; Tollenaar, Robert A.E.M.; Seynaeve, Caroline; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Dumont, Martine; Soucy, Penny; Dörk, Thilo; Bogdanova, Natalia V.; Hamann, Ute; Försti, Asta; Rüdiger, Thomas; Ulmer, Hans-Ulrich; Fasching, Peter A.; Häberle, Lothar; Ekici, Arif B.; Beckmann, Matthias W.; Fletcher, Olivia; Johnson, Nichola; dos Santos Silva, Isabel; Peto, Julian; Radice, Paolo; Peterlongo, Paolo; Peissel, Bernard; Mariani, Paolo; Giles, Graham G.; Severi, Gianluca; Baglietto, Laura; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Miller, Nicola; Marme, Federik; Burwinkel, Barbara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Lambrechts, Diether; Yesilyurt, Betul T.; Floris, Giuseppe; Leunen, Karin; Alnæs, Grethe Grenaker; Kristensen, Vessela; Børresen-Dale, Anne-Lise; García-Closas, Montserrat; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Schmidt, Marjanka K.; Broeks, Annegien; Verhoef, Senno; Rutgers, Emiel J.; Brauch, Hiltrud; Brüning, Thomas; Ko, Yon-Dschun; Couch, Fergus J.; Toland, Amanda E.; Yannoukakos, Drakoulis; Pharoah, Paul D.P.; Hall, Per; Benítez, Javier; Malats, Núria; Easton, Douglas F.

2014-01-01

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70 917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46 450 breast cancer cases and 42 461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10−4) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10−8. Results from the second analytic approach were consistent with those from the first (P > 10−10). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome. PMID:24242184

A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium.

PubMed

Milne, Roger L; Herranz, Jesús; Michailidou, Kyriaki; Dennis, Joe; Tyrer, Jonathan P; Zamora, M Pilar; Arias-Perez, José Ignacio; González-Neira, Anna; Pita, Guillermo; Alonso, M Rosario; Wang, Qin; Bolla, Manjeet K; Czene, Kamila; Eriksson, Mikael; Humphreys, Keith; Darabi, Hatef; Li, Jingmei; Anton-Culver, Hoda; Neuhausen, Susan L; Ziogas, Argyrios; Clarke, Christina A; Hopper, John L; Dite, Gillian S; Apicella, Carmel; Southey, Melissa C; Chenevix-Trench, Georgia; Swerdlow, Anthony; Ashworth, Alan; Orr, Nicholas; Schoemaker, Minouk; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Bojesen, Stig E; Nordestgaard, Børge G; Flyger, Henrik; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Wang, Xianshu; Olson, Janet E; Vachon, Celine; Purrington, Kristen; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Dunning, Alison M; Shah, Mitul; Guénel, Pascal; Truong, Thérèse; Sanchez, Marie; Mulot, Claire; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Lindblom, Annika; Margolin, Sara; Hooning, Maartje J; Hollestelle, Antoinette; Collée, J Margriet; Jager, Agnes; Cox, Angela; Brock, Ian W; Reed, Malcolm W R; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline; Haiman, Christopher A; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Dumont, Martine; Soucy, Penny; Dörk, Thilo; Bogdanova, Natalia V; Hamann, Ute; Försti, Asta; Rüdiger, Thomas; Ulmer, Hans-Ulrich; Fasching, Peter A; Häberle, Lothar; Ekici, Arif B; Beckmann, Matthias W; Fletcher, Olivia; Johnson, Nichola; dos Santos Silva, Isabel; Peto, Julian; Radice, Paolo; Peterlongo, Paolo; Peissel, Bernard; Mariani, Paolo; Giles, Graham G; Severi, Gianluca; Baglietto, Laura; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Miller, Nicola; Marme, Federik; Burwinkel, Barbara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Lambrechts, Diether; Yesilyurt, Betul T; Floris, Giuseppe; Leunen, Karin; Alnæs, Grethe Grenaker; Kristensen, Vessela; Børresen-Dale, Anne-Lise; García-Closas, Montserrat; Chanock, Stephen J; Lissowska, Jolanta; Figueroa, Jonine D; Schmidt, Marjanka K; Broeks, Annegien; Verhoef, Senno; Rutgers, Emiel J; Brauch, Hiltrud; Brüning, Thomas; Ko, Yon-Dschun; Couch, Fergus J; Toland, Amanda E; Yannoukakos, Drakoulis; Pharoah, Paul D P; Hall, Per; Benítez, Javier; Malats, Núria; Easton, Douglas F

2014-04-01

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

Robust optimization-based DC optimal power flow for managing wind generation uncertainty

NASA Astrophysics Data System (ADS)

Boonchuay, Chanwit; Tomsovic, Kevin; Li, Fangxing; Ongsakul, Weerakorn

2012-11-01

Integrating wind generation into the wider grid causes a number of challenges to traditional power system operation. Given the relatively large wind forecast errors, congestion management tools based on optimal power flow (OPF) need to be improved. In this paper, a robust optimization (RO)-based DCOPF is proposed to determine the optimal generation dispatch and locational marginal prices (LMPs) for a day-ahead competitive electricity market considering the risk of dispatch cost variation. The basic concept is to use the dispatch to hedge against the possibility of reduced or increased wind generation. The proposed RO-based DCOPF is compared with a stochastic non-linear programming (SNP) approach on a modified PJM 5-bus system. Primary test results show that the proposed DCOPF model can provide lower dispatch cost than the SNP approach.

A Large Maize (Zea mays L.) SNP Genotyping Array: Development and Germplasm Genotyping, and Genetic Mapping to Compare with the B73 Reference Genome

PubMed Central

Ganal, Martin W.; Durstewitz, Gregor; Polley, Andreas; Bérard, Aurélie; Buckler, Edward S.; Charcosset, Alain; Clarke, Joseph D.; Graner, Eva-Maria; Hansen, Mark; Joets, Johann; Le Paslier, Marie-Christine; McMullen, Michael D.; Montalent, Pierre; Rose, Mark; Schön, Chris-Carolin; Sun, Qi; Walter, Hildrun; Martin, Olivier C.; Falque, Matthieu

2011-01-01

SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations – IBM (B73×Mo17) and LHRF (F2×F252) – were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding. PMID:22174790

A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145.

PubMed

Rueda, Oscar M; Diaz-Uriarte, Ramon

2007-10-16

Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state. We rerun the analysis in Yu et al. using appropriate settings for both the Markov Chain Monte Carlo iterations and the reference level. Additionally, to show how easy it is to obtain answers to additional specific questions, we have added a new analysis targeted specifically to the detection of breakpoints. The reanalysis shows that the performance of our method is comparable to that of the other methods analyzed. In addition, we can provide probabilities of a given spot being a breakpoint, something unique among the methods examined. Markov Chain Monte Carlo methods require using a sufficient number of iterations before they can be assumed to yield samples from the distribution of interest. Running our method with too small a number of iterations cannot be representative of its performance. Moreover, our analysis shows how our original approach can be easily adapted to answer specific additional questions (e.g., identify edges).

The genome-wide structure of two economically important indigenous Sicilian cattle breeds.

PubMed

Mastrangelo, S; Saura, M; Tolone, M; Salces-Ortiz, J; Di Gerlando, R; Bertolini, F; Fontanesi, L; Sardina, M T; Serrano, M; Portolano, B

2014-11-01

Genomic technologies, such as high-throughput genotyping based on SNP arrays, provided background information concerning genome structure in domestic animals. The aim of this work was to investigate the genetic structure, the genome-wide estimates of inbreeding, coancestry, effective population size (Ne), and the patterns of linkage disequilibrium (LD) in 2 economically important Sicilian local cattle breeds, Cinisara (CIN) and Modicana (MOD), using the Illumina Bovine SNP50K v2 BeadChip. To understand the genetic relationship and to place both Sicilian breeds in a global context, genotypes from 134 other domesticated bovid breeds were used. Principal component analysis showed that the Sicilian cattle breeds were closer to individuals of Bos taurus taurus from Eurasia and formed nonoverlapping clusters with other breeds. Between the Sicilian cattle breeds, MOD was the most differentiated, whereas the animals belonging to the CIN breed showed a lower value of assignment, the presence of substructure, and genetic links with the MOD breed. The average molecular inbreeding and coancestry coefficients were moderately high, and the current estimates of Ne were low in both breeds. These values indicated a low genetic variability. Considering levels of LD between adjacent markers, the average r(2) in the MOD breed was comparable to those reported for others cattle breeds, whereas CIN showed a lower value. Therefore, these results support the need of more dense SNP arrays for a high-power association mapping and genomic selection efficiency, particularly for the CIN cattle breed. Controlling molecular inbreeding and coancestry would restrict inbreeding depression, the probability of losing beneficial rare alleles, and therefore the risk of extinction. The results generated from this study have important implications for the development of conservation and/or selection breeding programs in these 2 local cattle breeds.

UPD detection using homozygosity profiling with a SNP genotyping microarray.

PubMed

Papenhausen, Peter; Schwartz, Stuart; Risheg, Hiba; Keitges, Elisabeth; Gadi, Inder; Burnside, Rachel D; Jaswaney, Vikram; Pappas, John; Pasion, Romela; Friedman, Kenneth; Tepperberg, James

2011-04-01

Single nucleotide polymorphism (SNP) based chromosome microarrays provide both a high-density whole genome analysis of copy number and genotype. In the past 21 months we have analyzed over 13,000 samples primarily referred for developmental delay using the Affymetrix SNP/CN 6.0 version array platform. In addition to copy number, we have focused on the relative distribution of allele homozygosity (HZ) throughout the genome to confirm a strong association of uniparental disomy (UPD) with regions of isoallelism found in most confirmed cases of UPD. We sought to determine whether a long contiguous stretch of HZ (LCSH) greater than a threshold value found only in a single chromosome would correlate with UPD of that chromosome. Nine confirmed UPD cases were retrospectively analyzed with the array in the study, each showing the anticipated LCSH with the smallest 13.5 Mb in length. This length is well above the average longest run of HZ in a set of control patients and was then set as the prospective threshold for reporting possible UPD correlation. Ninety-two cases qualified at that threshold, 46 of those had molecular UPD testing and 29 were positive. Including retrospective cases, 16 showed complete HZ across the chromosome, consistent with total isoUPD. The average size LCSH in the 19 cases that were not completely HZ was 46.3 Mb with a range of 13.5-127.8 Mb. Three patients showed only segmental UPD. Both the size and location of the LCSH are relevant to correlation with UPD. Further studies will continue to delineate an optimal threshold for LCSH/UPD correlation. Copyright © 2011 Wiley-Liss, Inc.

EvoSNP-DB: A database of genetic diversity in East Asian populations.

PubMed

Kim, Young Uk; Kim, Young Jin; Lee, Jong-Young; Park, Kiejung

2013-08-01

Genome-wide association studies (GWAS) have become popular as an approach for the identification of large numbers of phenotype-associated variants. However, differences in genetic architecture and environmental factors mean that the effect of variants can vary across populations. Understanding population genetic diversity is valuable for the investigation of possible population specific and independent effects of variants. EvoSNP-DB aims to provide information regarding genetic diversity among East Asian populations, including Chinese, Japanese, and Korean. Non-redundant SNPs (1.6 million) were genotyped in 54 Korean trios (162 samples) and were compared with 4 million SNPs from HapMap phase II populations. EvoSNP-DB provides two user interfaces for data query and visualization, and integrates scores of genetic diversity (Fst and VarLD) at the level of SNPs, genes, and chromosome regions. EvoSNP-DB is a web-based application that allows users to navigate and visualize measurements of population genetic differences in an interactive manner, and is available online at [http://biomi.cdc.go.kr/EvoSNP/].

The Role of Constitutional Copy Number Variants in Breast Cancer

PubMed Central

Walker, Logan C.; Wiggins, George A.R.; Pearson, John F.

2015-01-01

Constitutional copy number variants (CNVs) include inherited and de novo deviations from a diploid state at a defined genomic region. These variants contribute significantly to genetic variation and disease in humans, including breast cancer susceptibility. Identification of genetic risk factors for breast cancer in recent years has been dominated by the use of genome-wide technologies, such as single nucleotide polymorphism (SNP)-arrays, with a significant focus on single nucleotide variants. To date, these large datasets have been underutilised for generating genome-wide CNV profiles despite offering a massive resource for assessing the contribution of these structural variants to breast cancer risk. Technical challenges remain in determining the location and distribution of CNVs across the human genome due to the accuracy of computational prediction algorithms and resolution of the array data. Moreover, better methods are required for interpreting the functional effect of newly discovered CNVs. In this review, we explore current and future application of SNP array technology to assess rare and common CNVs in association with breast cancer risk in humans. PMID:27600231

Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds.

PubMed

Bertolini, F; Galimberti, G; Schiavo, G; Mastrangelo, S; Di Gerlando, R; Strillacci, M G; Bagnato, A; Portolano, B; Fontanesi, L

2018-01-01

Commercial single nucleotide polymorphism (SNP) arrays have been recently developed for several species and can be used to identify informative markers to differentiate breeds or populations for several downstream applications. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this work, we compared several methods of SNPs preselection (Delta, F st and principal component analyses (PCA)) in addition to Random Forest classifications to analyse SNP data from six dairy cattle breeds, including cosmopolitan (Holstein, Brown and Simmental) and autochthonous Italian breeds raised in two different regions and subjected to limited or no breeding programmes (Cinisara, Modicana, raised only in Sicily and Reggiana, raised only in Emilia Romagna). From these classifications, two panels of 96 and 48 SNPs that contain the most discriminant SNPs were created for each preselection method. These panels were evaluated in terms of the ability to discriminate as a whole and breed-by-breed, as well as linkage disequilibrium within each panel. The obtained results showed that for the 48-SNP panel, the error rate increased mainly for autochthonous breeds, probably as a consequence of their admixed origin lower selection pressure and by ascertaining bias in the construction of the SNP chip. The 96-SNP panels were generally more able to discriminate all breeds. The panel derived by PCA-chrom (obtained by a preselection chromosome by chromosome) could identify informative SNPs that were particularly useful for the assignment of minor breeds that reached the lowest value of Out Of Bag error even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Several selected SNPs are located nearby genes affecting breed-specific phenotypic traits (coat colour and stature) or associated with production traits. In general, our results demonstrated the usefulness of Random Forest in combination to other reduction techniques to identify population informative SNPs.

A SNP resource for Douglas-fir: de novo transcriptome assembly and SNP detection and validation

PubMed Central

2013-01-01

Background Douglas-fir (Pseudotsuga menziesii), one of the most economically and ecologically important tree species in the world, also has one of the largest tree breeding programs. Although the coastal and interior varieties of Douglas-fir (vars. menziesii and glauca) are native to North America, the coastal variety is also widely planted for timber production in Europe, New Zealand, Australia, and Chile. Our main goal was to develop a SNP resource large enough to facilitate genomic selection in Douglas-fir breeding programs. To accomplish this, we developed a 454-based reference transcriptome for coastal Douglas-fir, annotated and evaluated the quality of the reference, identified putative SNPs, and then validated a sample of those SNPs using the Illumina Infinium genotyping platform. Results We assembled a reference transcriptome consisting of 25,002 isogroups (unique gene models) and 102,623 singletons from 2.76 million 454 and Sanger cDNA sequences from coastal Douglas-fir. We identified 278,979 unique SNPs by mapping the 454 and Sanger sequences to the reference, and by mapping four datasets of Illumina cDNA sequences from multiple seed sources, genotypes, and tissues. The Illumina datasets represented coastal Douglas-fir (64.00 and 13.41 million reads), interior Douglas-fir (80.45 million reads), and a Yakima population similar to interior Douglas-fir (8.99 million reads). We assayed 8067 SNPs on 260 trees using an Illumina Infinium SNP genotyping array. Of these SNPs, 5847 (72.5%) were called successfully and were polymorphic. Conclusions Based on our validation efficiency, our SNP database may contain as many as ~200,000 true SNPs, and as many as ~69,000 SNPs that could be genotyped at ~20,000 gene loci using an Infinium II array—more SNPs than are needed to use genomic selection in tree breeding programs. Ultimately, these genomic resources will enhance Douglas-fir breeding and allow us to better understand landscape-scale patterns of genetic variation and potential responses to climate change. PMID:23445355

Assumption-free estimation of the genetic contribution to refractive error across childhood.

PubMed

Guggenheim, Jeremy A; St Pourcain, Beate; McMahon, George; Timpson, Nicholas J; Evans, David M; Williams, Cathy

2015-01-01

Studies in relatives have generally yielded high heritability estimates for refractive error: twins 75-90%, families 15-70%. However, because related individuals often share a common environment, these estimates are inflated (via misallocation of unique/common environment variance). We calculated a lower-bound heritability estimate for refractive error free from such bias. Between the ages 7 and 15 years, participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) underwent non-cycloplegic autorefraction at regular research clinics. At each age, an estimate of the variance in refractive error explained by single nucleotide polymorphism (SNP) genetic variants was calculated using genome-wide complex trait analysis (GCTA) using high-density genome-wide SNP genotype information (minimum N at each age=3,404). The variance in refractive error explained by the SNPs ("SNP heritability") was stable over childhood: Across age 7-15 years, SNP heritability averaged 0.28 (SE=0.08, p<0.001). The genetic correlation for refractive error between visits varied from 0.77 to 1.00 (all p<0.001) demonstrating that a common set of SNPs was responsible for the genetic contribution to refractive error across this period of childhood. Simulations suggested lack of cycloplegia during autorefraction led to a small underestimation of SNP heritability (adjusted SNP heritability=0.35; SE=0.09). To put these results in context, the variance in refractive error explained (or predicted) by the time participants spent outdoors was <0.005 and by the time spent reading was <0.01, based on a parental questionnaire completed when the child was aged 8-9 years old. Genetic variation captured by common SNPs explained approximately 35% of the variation in refractive error between unrelated subjects. This value sets an upper limit for predicting refractive error using existing SNP genotyping arrays, although higher-density genotyping in larger samples and inclusion of interaction effects is expected to raise this figure toward twin- and family-based heritability estimates. The same SNPs influenced refractive error across much of childhood. Notwithstanding the strong evidence of association between time outdoors and myopia, and time reading and myopia, less than 1% of the variance in myopia at age 15 was explained by crude measures of these two risk factors, indicating that their effects may be limited, at least when averaged over the whole population.

Multifaceted Genomic Risk for Brain Function in Schizophrenia

PubMed Central

Chen, Jiayu; Calhoun, Vince D.; Pearlson, Godfrey D.; Ehrlich, Stefan; Turner, Jessica A.; Ho, Beng-Choon; Wassink, Thomas H.; Michael, Andrew M; Liu, Jingyu

2012-01-01

Recently, deriving candidate endophenotypes from brain imaging data has become a valuable approach to study genetic influences on schizophrenia (SZ), whose pathophysiology remains unclear. In this work we utilized a multivariate approach, parallel independent component analysis, to identify genomic risk components associated with brain function abnormalities in SZ. 5157 candidate single nucleotide polymorphisms (SNPs) were derived from genome-wide array based on their possible connections with SZ and further investigated for their associations with brain activations captured with functional magnetic resonance imaging (fMRI) during a sensorimotor task. Using data from 92 SZ patients and 116 healthy controls, we detected a significant correlation (r= 0.29; p= 2.41×10−5) between one fMRI component and one SNP component, both of which significantly differentiated patients from controls. The fMRI component mainly consisted of precentral and postcentral gyri, the major activated regions in the motor task. On average, higher activation in these regions was observed in participants with higher loadings of the linked SNP component, predominantly contributed to by 253 SNPs. 138 identified SNPs were from known coding regions of 100 unique genes. 31 identified SNPs did not differ between groups, but moderately correlated with some other group-discriminating SNPs, indicating interactions among alleles contributing towards elevated SZ susceptibility. The genes associated with the identified SNPs participated in four neurotransmitter pathways: GABA receptor signaling, dopamine receptor signaling, neuregulin signaling and glutamate receptor signaling. In summary, our work provides further evidence for the complexity of genomic risk to the functional brain abnormality in SZ and suggests a pathological role of interactions between SNPs, genes and multiple neurotransmitter pathways. PMID:22440650

Prioritizing individual genetic variants after kernel machine testing using variable selection.

PubMed

He, Qianchuan; Cai, Tianxi; Liu, Yang; Zhao, Ni; Harmon, Quaker E; Almli, Lynn M; Binder, Elisabeth B; Engel, Stephanie M; Ressler, Kerry J; Conneely, Karen N; Lin, Xihong; Wu, Michael C

2016-12-01

Kernel machine learning methods, such as the SNP-set kernel association test (SKAT), have been widely used to test associations between traits and genetic polymorphisms. In contrast to traditional single-SNP analysis methods, these methods are designed to examine the joint effect of a set of related SNPs (such as a group of SNPs within a gene or a pathway) and are able to identify sets of SNPs that are associated with the trait of interest. However, as with many multi-SNP testing approaches, kernel machine testing can draw conclusion only at the SNP-set level, and does not directly inform on which one(s) of the identified SNP set is actually driving the associations. A recently proposed procedure, KerNel Iterative Feature Extraction (KNIFE), provides a general framework for incorporating variable selection into kernel machine methods. In this article, we focus on quantitative traits and relatively common SNPs, and adapt the KNIFE procedure to genetic association studies and propose an approach to identify driver SNPs after the application of SKAT to gene set analysis. Our approach accommodates several kernels that are widely used in SNP analysis, such as the linear kernel and the Identity by State (IBS) kernel. The proposed approach provides practically useful utilities to prioritize SNPs, and fills the gap between SNP set analysis and biological functional studies. Both simulation studies and real data application are used to demonstrate the proposed approach. © 2016 WILEY PERIODICALS, INC.

Sample-to-SNP kit: a reliable, easy and fast tool for the detection of HFE p.H63D and p.C282Y variations associated to hereditary hemochromatosis.

PubMed

Nielsen, Peter B; Petersen, Maja S; Ystaas, Viviana; Andersen, Rolf V; Hansen, Karin M; Blaabjerg, Vibeke; Refstrup, Mette

2012-10-01

Classical hereditary hemochromatosis involves the HFE-gene and diagnostic analysis of the DNA variants HFE p.C282Y (c.845G>A; rs1800562) and HFE p.H63D (c.187C>G; rs1799945). The affected protein alters the iron homeostasis resulting in iron overload in various tissues. The aim of this study was to validate the TaqMan-based Sample-to-SNP protocol for the analysis of the HFE-p.C282Y and p.H63D variants with regard to accuracy, usefulness and reproducibility compared to an existing SNP protocol. The Sample-to-SNP protocol uses an approach where the DNA template is made accessible from a cell lysate followed by TaqMan analysis. Besides the HFE-SNPs other eight SNPs were used as well. These SNPs were: Coagulation factor II-gene F2 c.20210G>A, Coagulation factor V-gene F5 p.R506Q (c.1517G>A; rs121917732), Mitochondria SNP: mt7028 G>A, Mitochondria SNP: mt12308 A>G, Proprotein convertase subtilisin/kexin type 9-gene PCSK9 p.R46L (c.137G>T), Plutathione S-transferase pi 1-gene GSTP1 p.I105V (c313A>G; rs1695), LXR g.-171 A>G, ZNF202 g.-118 G>T. In conclusion the Sample-to-SNP kit proved to be an accurate, reliable, robust, easy to use and rapid TaqMan-based SNP detection protocol, which could be quickly implemented in a routine diagnostic or research facility. Copyright © 2012. Published by Elsevier B.V.

Dissimilarity based Partial Least Squares (DPLS) for genomic prediction from SNPs.

PubMed

Singh, Priyanka; Engel, Jasper; Jansen, Jeroen; de Haan, Jorn; Buydens, Lutgarde Maria Celina

2016-05-04

Genomic prediction (GP) allows breeders to select plants and animals based on their breeding potential for desirable traits, without lengthy and expensive field trials or progeny testing. We have proposed to use Dissimilarity-based Partial Least Squares (DPLS) for GP. As a case study, we use the DPLS approach to predict Bacterial wilt (BW) in tomatoes using SNPs as predictors. The DPLS approach was compared with the Genomic Best-Linear Unbiased Prediction (GBLUP) and single-SNP regression with SNP as a fixed effect to assess the performance of DPLS. Eight genomic distance measures were used to quantify relationships between the tomato accessions from the SNPs. Subsequently, each of these distance measures was used to predict the BW using the DPLS prediction model. The DPLS model was found to be robust to the choice of distance measures; similar prediction performances were obtained for each distance measure. DPLS greatly outperformed the single-SNP regression approach, showing that BW is a comprehensive trait dependent on several loci. Next, the performance of the DPLS model was compared to that of GBLUP. Although GBLUP and DPLS are conceptually very different, the prediction quality (PQ) measured by DPLS models were similar to the prediction statistics obtained from GBLUP. A considerable advantage of DPLS is that the genotype-phenotype relationship can easily be visualized in a 2-D scatter plot. This so-called score-plot provides breeders an insight to select candidates for their future breeding program. DPLS is a highly appropriate method for GP. The model prediction performance was similar to the GBLUP and far better than the single-SNP approach. The proposed method can be used in combination with a wide range of genomic dissimilarity measures and genotype representations such as allele-count, haplotypes or allele-intensity values. Additionally, the data can be insightfully visualized by the DPLS model, allowing for selection of desirable candidates from the breeding experiments. In this study, we have assessed the DPLS performance on a single trait.

Cohort analysis of a single nucleotide polymorphism on DNA chips.

PubMed

Schwonbeck, Susanne; Krause-Griep, Andrea; Gajovic-Eichelmann, Nenad; Ehrentreich-Förster, Eva; Meinl, Walter; Glatt, Hansrüdi; Bier, Frank F

2004-11-15

A method has been developed to determine SNPs on DNA chips by applying a flow-through bioscanner. As a practical application we demonstrated the fast and simple SNP analysis of 24 genotypes in an array of 96 spots with a single hybridisation and dissociation experiment. The main advantage of this methodical concept is the parallel and fast analysis without any need of enzymatic digestion. Additionally, the DNA chip format used is appropriate for parallel analysis up to 400 spots. The polymorphism in the gene of the human phenol sulfotransferase SULT1A1 was studied as a model SNP. Biotinylated PCR products containing the SNP (The SNP summary web site: ) (mutant) and those containing no mutation (wild-type) were brought onto the chips coated with NeutrAvidin using non-contact spotting. This was followed by an analysis which was carried out in a flow-through biochip scanner while constantly rinsing with buffer. After removing the non-biotinylated strand a fluorescent probe was hybridised, which is complementary to the wild-type sequence. If this probe binds to a mutant sequence, then one single base is not fully matching. Thereby, the mismatched hybrid (mutant) is less stable than the full-matched hybrid (wild-type). The final step after hybridisation on the chip involves rinsing with a buffer to start dissociation of the fluorescent probe from the immobilised DNA strand. The online measurement of the fluorescence intensity by the biochip scanner provides the possibility to follow the kinetics of the hybridisation and dissociation processes. According to the different stability of the full-match and the mismatch, either visual discrimination or kinetic analysis is possible to distinguish SNP-containing sequence from the wild-type sequence.

New generation pharmacogenomic tools: a SNP linkage disequilibrium Map, validated SNP assay resource, and high-throughput instrumentation system for large-scale genetic studies.

PubMed

De La Vega, Francisco M; Dailey, David; Ziegle, Janet; Williams, Julie; Madden, Dawn; Gilbert, Dennis A

2002-06-01

Since public and private efforts announced the first draft of the human genome last year, researchers have reported great numbers of single nucleotide polymorphisms (SNPs). We believe that the availability of well-mapped, quality SNP markers constitutes the gateway to a revolution in genetics and personalized medicine that will lead to better diagnosis and treatment of common complex disorders. A new generation of tools and public SNP resources for pharmacogenomic and genetic studies--specifically for candidate-gene, candidate-region, and whole-genome association studies--will form part of the new scientific landscape. This will only be possible through the greater accessibility of SNP resources and superior high-throughput instrumentation-assay systems that enable affordable, highly productive large-scale genetic studies. We are contributing to this effort by developing a high-quality linkage disequilibrium SNP marker map and an accompanying set of ready-to-use, validated SNP assays across every gene in the human genome. This effort incorporates both the public sequence and SNP data sources, and Celera Genomics' human genome assembly and enormous resource ofphysically mapped SNPs (approximately 4,000,000 unique records). This article discusses our approach and methodology for designing the map, choosing quality SNPs, designing and validating these assays, and obtaining population frequency ofthe polymorphisms. We also discuss an advanced, high-performance SNP assay chemisty--a new generation of the TaqMan probe-based, 5' nuclease assay-and high-throughput instrumentation-software system for large-scale genotyping. We provide the new SNP map and validation information, validated SNP assays and reagents, and instrumentation systems as a novel resource for genetic discoveries.

High-density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool.

PubMed

Winfield, Mark O; Allen, Alexandra M; Burridge, Amanda J; Barker, Gary L A; Benbow, Harriet R; Wilkinson, Paul A; Coghill, Jane; Waterfall, Christy; Davassi, Alessandro; Scopes, Geoff; Pirani, Ali; Webster, Teresa; Brew, Fiona; Bloor, Claire; King, Julie; West, Claire; Griffiths, Simon; King, Ian; Bentley, Alison R; Edwards, Keith J

2016-05-01

In wheat, a lack of genetic diversity between breeding lines has been recognized as a significant block to future yield increases. Species belonging to bread wheat's secondary and tertiary gene pools harbour a much greater level of genetic variability, and are an important source of genes to broaden its genetic base. Introgression of novel genes from progenitors and related species has been widely employed to improve the agronomic characteristics of hexaploid wheat, but this approach has been hampered by a lack of markers that can be used to track introduced chromosome segments. Here, we describe the identification of a large number of single nucleotide polymorphisms that can be used to genotype hexaploid wheat and to identify and track introgressions from a variety of sources. We have validated these markers using an ultra-high-density Axiom(®) genotyping array to characterize a range of diploid, tetraploid and hexaploid wheat accessions and wheat relatives. To facilitate the use of these, both the markers and the associated sequence and genotype information have been made available through an interactive web site. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

A consensus genetic map of cowpea [Vigna unguiculata (L) Walp.] and synteny based on EST-derived SNPs.

PubMed

Muchero, Wellington; Diop, Ndeye N; Bhat, Prasanna R; Fenton, Raymond D; Wanamaker, Steve; Pottorff, Marti; Hearne, Sarah; Cisse, Ndiaga; Fatokun, Christian; Ehlers, Jeffrey D; Roberts, Philip A; Close, Timothy J

2009-10-27

Consensus genetic linkage maps provide a genomic framework for quantitative trait loci identification, map-based cloning, assessment of genetic diversity, association mapping, and applied breeding in marker-assisted selection schemes. Among "orphan crops" with limited genomic resources such as cowpea [Vigna unguiculata (L.) Walp.] (2n = 2x = 22), the use of transcript-derived SNPs in genetic maps provides opportunities for automated genotyping and estimation of genome structure based on synteny analysis. Here, we report the development and validation of a high-throughput EST-derived SNP assay for cowpea, its application in consensus map building, and determination of synteny to reference genomes. SNP mining from 183,118 ESTs sequenced from 17 cDNA libraries yielded approximately 10,000 high-confidence SNPs from which an Illumina 1,536-SNP GoldenGate genotyping array was developed and applied to 741 recombinant inbred lines from six mapping populations. Approximately 90% of the SNPs were technically successful, providing 1,375 dependable markers. Of these, 928 were incorporated into a consensus genetic map spanning 680 cM with 11 linkage groups and an average marker distance of 0.73 cM. Comparison of this cowpea genetic map to reference legumes, soybean (Glycine max) and Medicago truncatula, revealed extensive macrosynteny encompassing 85 and 82%, respectively, of the cowpea map. Regions of soybean genome duplication were evident relative to the simpler diploid cowpea. Comparison with Arabidopsis revealed extensive genomic rearrangement with some conserved microsynteny. These results support evolutionary closeness between cowpea and soybean and identify regions for synteny-based functional genomics studies in legumes.

Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification

PubMed Central

Faye, Laura L.; Machiela, Mitchell J.; Kraft, Peter; Bull, Shelley B.; Sun, Lei

2013-01-01

Next generation sequencing has dramatically increased our ability to localize disease-causing variants by providing base-pair level information at costs increasingly feasible for the large sample sizes required to detect complex-trait associations. Yet, identification of causal variants within an established region of association remains a challenge. Counter-intuitively, certain factors that increase power to detect an associated region can decrease power to localize the causal variant. First, combining GWAS with imputation or low coverage sequencing to achieve the large sample sizes required for high power can have the unintended effect of producing differential genotyping error among SNPs. This tends to bias the relative evidence for association toward better genotyped SNPs. Second, re-use of GWAS data for fine-mapping exploits previous findings to ensure genome-wide significance in GWAS-associated regions. However, using GWAS findings to inform fine-mapping analysis can bias evidence away from the causal SNP toward the tag SNP and SNPs in high LD with the tag. Together these factors can reduce power to localize the causal SNP by more than half. Other strategies commonly employed to increase power to detect association, namely increasing sample size and using higher density genotyping arrays, can, in certain common scenarios, actually exacerbate these effects and further decrease power to localize causal variants. We develop a re-ranking procedure that accounts for these adverse effects and substantially improves the accuracy of causal SNP identification, often doubling the probability that the causal SNP is top-ranked. Application to the NCI BPC3 aggressive prostate cancer GWAS with imputation meta-analysis identified a new top SNP at 2 of 3 associated loci and several additional possible causal SNPs at these loci that may have otherwise been overlooked. This method is simple to implement using R scripts provided on the author's website. PMID:23950724

Family-Based Benchmarking of Copy Number Variation Detection Software.

PubMed

Nutsua, Marcel Elie; Fischer, Annegret; Nebel, Almut; Hofmann, Sylvia; Schreiber, Stefan; Krawczak, Michael; Nothnagel, Michael

2015-01-01

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

Genome-wide association study for milking speed in French Holstein cows.

PubMed

Marete, Andrew; Sahana, Goutam; Fritz, Sébastien; Lefebvre, Rachel; Barbat, Anne; Lund, Mogens Sandø; Guldbrandtsen, Bernt; Boichard, Didier

2018-04-25

Using a combination of data from the BovineSNP50 BeadChip SNP array (Illumina, San Diego, CA) and a EuroGenomics (Amsterdam, the Netherlands) custom single nucleotide polymorphism (SNP) chip with SNP pre-selected from whole genome sequence data, we carried out an association study of milking speed in 32,491 French Holstein dairy cows. Milking speed was measured by a score given by the farmer. Phenotypes were yield deviations as obtained from the French evaluation system. They were analyzed with a linear mixed model for association studies. We identified SNP on 22 chromosomes significantly associated with milking speed. As clinical mastitis and somatic cell score have an unfavorable genetic correlation with milking speed, we tested whether the most significant SNP on these 22 chromosomes associated with milking speed were also associated with clinical mastitis or somatic cell score. Nine hundred seventy-one genome-wide significant SNP were associated with milking speed. Of these, 86 were associated with clinical mastitis and 198 with somatic cell score. The most significant association signals for milking speed were observed on chromosomes 7, 8, 10, 14, and 18. The most significant signal was located on chromosome 14 (ZFAT gene). Eleven novel milking speed quantitative trait loci (QTL) were observed on chromosomes 7, 10, 11, 14, 18, 25, and 26. Twelve candidate SNP for milking speed mapped directly within genes. Of these 10 were QTL lead SNP, which mapped within the genes HMHA1, POLR2E, GNB5, KLHL29, ZFAT, KCNB2, CEACAM18, CCL24, and LHPP. Limited pleiotropy was observed between milking speed QTL and clinical mastitis. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

BAC-end sequence-based SNPs and Bin mapping for rapid integration of physical and genetic maps in apple.

PubMed

Han, Yuepeng; Chagné, David; Gasic, Ksenija; Rikkerink, Erik H A; Beever, Jonathan E; Gardiner, Susan E; Korban, Schuyler S

2009-03-01

A genome-wide BAC physical map of the apple, Malus x domestica Borkh., has been recently developed. Here, we report on integrating the physical and genetic maps of the apple using a SNP-based approach in conjunction with bin mapping. Briefly, BAC clones located at ends of BAC contigs were selected, and sequenced at both ends. The BAC end sequences (BESs) were used to identify candidate SNPs. Subsequently, these candidate SNPs were genetically mapped using a bin mapping strategy for the purpose of mapping the physical onto the genetic map. Using this approach, 52 (23%) out of 228 BESs tested were successfully exploited to develop SNPs. These SNPs anchored 51 contigs, spanning approximately 37 Mb in cumulative physical length, onto 14 linkage groups. The reliability of the integration of the physical and genetic maps using this SNP-based strategy is described, and the results confirm the feasibility of this approach to construct an integrated physical and genetic maps for apple.

The Genetic Architecture of Adaptations to High Altitude in Ethiopia

PubMed Central

Alkorta-Aranburu, Gorka; Beall, Cynthia M.; Witonsky, David B.; Gebremedhin, Amha; Pritchard, Jonathan K.; Di Rienzo, Anna

2012-01-01

Although hypoxia is a major stress on physiological processes, several human populations have survived for millennia at high altitudes, suggesting that they have adapted to hypoxic conditions. This hypothesis was recently corroborated by studies of Tibetan highlanders, which showed that polymorphisms in candidate genes show signatures of natural selection as well as well-replicated association signals for variation in hemoglobin levels. We extended genomic analysis to two Ethiopian ethnic groups: Amhara and Oromo. For each ethnic group, we sampled low and high altitude residents, thus allowing genetic and phenotypic comparisons across altitudes and across ethnic groups. Genome-wide SNP genotype data were collected in these samples by using Illumina arrays. We find that variants associated with hemoglobin variation among Tibetans or other variants at the same loci do not influence the trait in Ethiopians. However, in the Amhara, SNP rs10803083 is associated with hemoglobin levels at genome-wide levels of significance. No significant genotype association was observed for oxygen saturation levels in either ethnic group. Approaches based on allele frequency divergence did not detect outliers in candidate hypoxia genes, but the most differentiated variants between high- and lowlanders have a clear role in pathogen defense. Interestingly, a significant excess of allele frequency divergence was consistently detected for genes involved in cell cycle control and DNA damage and repair, thus pointing to new pathways for high altitude adaptations. Finally, a comparison of CpG methylation levels between high- and lowlanders found several significant signals at individual genes in the Oromo. PMID:23236293

MMP9 polymorphisms and breast cancer risk: a report from the Shanghai Breast Cancer Genetics Study.

PubMed

Beeghly-Fadiel, Alicia; Lu, Wei; Shu, Xiao-Ou; Long, Jirong; Cai, Qiuyin; Xiang, Yongbin; Gao, Yu-Tang; Zheng, Wei

2011-04-01

In addition to tumor invasion and angiogenesis, matrix metalloproteinase (MMP)9 also contributes to carcinogenesis and tumor growth. Genetic variation that may influence MMP9 expression was evaluated among participants of the Shanghai Breast Cancer Genetics Study (SBCGS) for associations with breast cancer susceptibility. In stage 1, 11 MMP9 single nucleotide polymorphisms (SNPs) were genotyped by the Affymetrix Targeted Genotyping System and/or the Affymetrix Genome-Wide Human SNP Array 6.0 among 4,227 SBCGS participants. One SNP was further genotyped using the Sequenom iPLEX MassARRAY platform among an additional 6,270 SBCGS participants. Associations with breast cancer risk were evaluated by odds ratios (OR) and 95% confidence intervals (CI) from logistic regression models that included adjustment for age, education, and genotyping stage when appropriate. In Stage 1, rare allele homozygotes for a promoter SNP (rs3918241) or a non-synonymous SNP (rs2274756, R668Q) tended to occur more frequently among breast cancer cases (P value = 0.116 and 0.056, respectively). Given their high linkage disequilibrium (D' = 1.0, r (2) = 0.97), one (rs3918241) was selected for additional analysis. An association with breast cancer risk was not supported by additional Stage 2 genotyping. In combined analysis, no elevated risk of breast cancer among homozygotes was found (OR: 1.2, 95% CI: 0.8-1.8). Common genetic variation in MMP9 was not found to be significantly associated with breast cancer susceptibility among participants of the Shanghai Breast Cancer Genetics Study.

Construction and Annotation of a High Density SNP Linkage Map of the Atlantic Salmon (Salmo salar) Genome.

PubMed

Tsai, Hsin Y; Robledo, Diego; Lowe, Natalie R; Bekaert, Michael; Taggart, John B; Bron, James E; Houston, Ross D

2016-07-07

High density linkage maps are useful tools for fine-scale mapping of quantitative trait loci, and characterization of the recombination landscape of a species' genome. Genomic resources for Atlantic salmon (Salmo salar) include a well-assembled reference genome, and high density single nucleotide polymorphism (SNP) arrays. Our aim was to create a high density linkage map, and to align it with the reference genome assembly. Over 96,000 SNPs were mapped and ordered on the 29 salmon linkage groups using a pedigreed population comprising 622 fish from 60 nuclear families, all genotyped with the 'ssalar01' high density SNP array. The number of SNPs per group showed a high positive correlation with physical chromosome length (r = 0.95). While the order of markers on the genetic and physical maps was generally consistent, areas of discrepancy were identified. Approximately 6.5% of the previously unmapped reference genome sequence was assigned to chromosomes using the linkage map. Male recombination rate was lower than females across the vast majority of the genome, but with a notable peak in subtelomeric regions. Finally, using RNA-Seq data to annotate the reference genome, the mapped SNPs were categorized according to their predicted function, including annotation of ∼2500 putative nonsynonymous variants. The highest density SNP linkage map for any salmonid species has been created, annotated, and integrated with the Atlantic salmon reference genome assembly. This map highlights the marked heterochiasmy of salmon, and provides a useful resource for salmonid genetics and genomics research. Copyright © 2016 Tsai et al.

Three clinical experiences with SNP array results consistent with parental incest: a narrative with lessons learned.

PubMed

Helm, Benjamin M; Langley, Katherine; Spangler, Brooke; Vergano, Samantha

2014-08-01

Single nucleotide polymorphism microarrays have the ability to reveal parental consanguinity which may or may not be known to healthcare providers. Consanguinity can have significant implications for the health of patients and for individual and family psychosocial well-being. These results often present ethical and legal dilemmas that can have important ramifications. Unexpected consanguinity can be confounding to healthcare professionals who may be unprepared to handle these results or to communicate them to families or other appropriate representatives. There are few published accounts of experiences with consanguinity and SNP arrays. In this paper we discuss three cases where molecular evidence of parental incest was identified by SNP microarray. We hope to further highlight consanguinity as a potential incidental finding, how the cases were handled by the clinical team, and what resources were found to be most helpful. This paper aims to contribute further to professional discourse on incidental findings with genomic technology and how they were addressed clinically. These experiences may provide some guidance on how others can prepare for these findings and help improve practice. As genetic and genomic testing is utilized more by non-genetics providers, we also hope to inform about the importance of engaging with geneticists and genetic counselors when addressing these findings.

Analysis of LDLR mutations in familial hypercholesterolemia patients in Greece by use of the NanoChip microelectronic array technology.

PubMed

Laios, Eleftheria; Drogari, Euridiki

2006-12-01

Three mutations in the low density lipoprotein receptor (LDLR) gene account for 49% of familial hypercholesterolemia (FH) cases in Greece. We used the microelectronic array technology of the NanoChip Molecular Biology Workstation to develop a multiplex method to analyze these single-nucleotide polymorphisms (SNPs). Primer pairs amplified the region encompassing each SNP. The biotinylated PCR amplicon was electronically addressed to streptavidin-coated microarray sites. Allele-specific fluorescently labeled oligonucleotide reporters were designed and used for detection of wild-type and SNP sequences. Genotypes were compared to PCR-restriction fragment length polymorphism (PCR-RFLP). We developed three monoplex assays (1 SNP/site) and an optimized multiplex assay (3SNPs/site). We performed 92 Greece II, 100 Genoa, and 98 Afrikaner-2 NanoChip monoplex assays (addressed to duplicate sites and analyzed separately). Of the 580 monoplex genotypings (290 samples), 579 agreed with RFLP. Duplicate sites of one sample were not in agreement with each other. Of the 580 multiplex genotypings, 576 agreed with the monoplex results. Duplicate sites of three samples were not in agreement with each other, indicating requirement for repetition upon which discrepancies were resolved. The multiplex assay detects common LDLR mutations in Greek FH patients and can be extended to accommodate additional mutations.

Evaluation of SNP Data from the Malus Infinium Array Identifies Challenges for Genetic Analysis of Complex Genomes of Polyploid Origin.

PubMed

Troggio, Michela; Surbanovski, Nada; Bianco, Luca; Moretto, Marco; Giongo, Lara; Banchi, Elisa; Viola, Roberto; Fernández, Felicdad Fernández; Costa, Fabrizio; Velasco, Riccardo; Cestaro, Alessandro; Sargent, Daniel James

2013-01-01

High throughput arrays for the simultaneous genotyping of thousands of single-nucleotide polymorphisms (SNPs) have made the rapid genetic characterisation of plant genomes and the development of saturated linkage maps a realistic prospect for many plant species of agronomic importance. However, the correct calling of SNP genotypes in divergent polyploid genomes using array technology can be problematic due to paralogy, and to divergence in probe sequences causing changes in probe binding efficiencies. An Illumina Infinium II whole-genome genotyping array was recently developed for the cultivated apple and used to develop a molecular linkage map for an apple rootstock progeny (M432), but a large proportion of segregating SNPs were not mapped in the progeny, due to unexpected genotype clustering patterns. To investigate the causes of this unexpected clustering we performed BLAST analysis of all probe sequences against the 'Golden Delicious' genome sequence and discovered evidence for paralogous annealing sites and probe sequence divergence for a high proportion of probes contained on the array. Following visual re-evaluation of the genotyping data generated for 8,788 SNPs for the M432 progeny using the array, we manually re-scored genotypes at 818 loci and mapped a further 797 markers to the M432 linkage map. The newly mapped markers included the majority of those that could not be mapped previously, as well as loci that were previously scored as monomorphic, but which segregated due to divergence leading to heterozygosity in probe annealing sites. An evaluation of the 8,788 probes in a diverse collection of Malus germplasm showed that more than half the probes returned genotype clustering patterns that were difficult or impossible to interpret reliably, highlighting implications for the use of the array in genome-wide association studies.

Linear reduction methods for tag SNP selection.

PubMed

He, Jingwu; Zelikovsky, Alex

2004-01-01

It is widely hoped that constructing a complete human haplotype map will help to associate complex diseases with certain SNP's. Unfortunately, the number of SNP's is huge and it is very costly to sequence many individuals. Therefore, it is desirable to reduce the number of SNP's that should be sequenced to considerably small number of informative representatives, so called tag SNP's. In this paper, we propose a new linear algebra based method for selecting and using tag SNP's. Our method is purely combinatorial and can be combined with linkage disequilibrium (LD) and block based methods. We measure the quality of our tag SNP selection algorithm by comparing actual SNP's with SNP's linearly predicted from linearly chosen tag SNP's. We obtain an extremely good compression and prediction rates. For example, for long haplotypes (>25000 SNP's), knowing only 0.4% of all SNP's we predict the entire unknown haplotype with 2% accuracy while the prediction method is based on a 10% sample of the population.

Genome-wide association study in discordant sibships identifies multiple inherited susceptibility alleles linked to lung cancer.

PubMed

Galvan, Antonella; Falvella, Felicia S; Frullanti, Elisa; Spinola, Monica; Incarbone, Matteo; Nosotti, Mario; Santambrogio, Luigi; Conti, Barbara; Pastorino, Ugo; Gonzalez-Neira, Anna; Dragani, Tommaso A

2010-03-01

We analyzed a series of young (median age = 52 years) non-smoker lung cancer patients and their unaffected siblings as controls, using a genome-wide 620 901 single-nucleotide polymorphism (SNP) array analysis and a case-control DNA pooling approach. We identified 82 putatively associated SNPs that were retested by individual genotyping followed by use of the sib transmission disequilibrium test, pointing to 36 SNPs associated with lung cancer risk in the discordant sibs series. Analysis of these 36 SNPs in a polygenic model characterized by additive and interchangeable effects of rare alleles revealed a highly statistically significant dosage-dependent association between risk allele carrier status and proportion of cancer cases. Replication of the same 36 SNPs in a population-based series confirmed the association with lung cancer for three SNPs, suggesting that phenocopies and genetic heterogeneity can play a major role in the complex genetics of lung cancer risk in the general population.

SUSCEPTIBILITY LOCI FOR UMBILICAL HERNIA IN SWINE DETECTED BY GENOME-WIDE ASSOCIATION.

PubMed

Liao, X J; Lia, L; Zhang, Z Y; Long, Y; Yang, B; Ruan, G R; Su, Y; Ai, H S; Zhang, W C; Deng, W Y; Xiao, S J; Ren, J; Ding, N S; Huang, L S

2015-10-01

Umbilical hernia (UH) is a complex disorder caused by both genetic and environmental factors. UH brings animal welfare problems and severe economic loss to the pig industry. Until now, the genetic basis of UH is poorly understood. The high-density 60K porcine SNP array enables the rapid application of genome-wide association study (GWAS) to identify genetic loci for phenotypic traits at genome wide scale in pigs. The objective of this research was to identify susceptibility loci for swine umbilical hernia using the GWAS approach. We genotyped 478 piglets from 142 families representing three Western commercial breeds with the Illumina PorcineSNP60 BeadChip. Then significant SNPs were detected by GWAS using ROADTRIPS (Robust Association-Detection Test for Related Individuals with Population Substructure) software base on a Bonferroni corrected threshold (P = 1.67E-06) or suggestive threshold (P = 3.34E-05) and false discovery rate (FDR = 0.05). After quality control, 29,924 qualified SNPs and 472 piglets were used for GWAS. Two suggestive loci predisposing to pig UH were identified at 44.25MB on SSC2 (rs81358018, P = 3.34E-06, FDR = 0.049933) and at 45.90MB on SSC17 (rs81479278, P = 3.30E-06, FDR = 0.049933) in Duroc population, respectively. And no SNP was detected to be associated with pig UH at significant level in neither Landrace nor Large White population. Furthermore, we carried out a meta-analysis in the combined pure-breed population containing all the 472 piglets. rs81479278 (P = 1.16E-06, FDR = 0.022475) was identified to associate with pig UH at genome-wide significant level. SRC was characterized as plausible candidate gene for susceptibility to pig UH according to its genomic position and biological functions. To our knowledge, this study gives the first description of GWAS identifying susceptibility loci for umbilical hernia in pigs. Our findings provide deeper insights to the genetic architecture of umbilical hernia in pigs.

Tag SNP selection via a genetic algorithm.

PubMed

Mahdevar, Ghasem; Zahiri, Javad; Sadeghi, Mehdi; Nowzari-Dalini, Abbas; Ahrabian, Hayedeh

2010-10-01

Single Nucleotide Polymorphisms (SNPs) provide valuable information on human evolutionary history and may lead us to identify genetic variants responsible for human complex diseases. Unfortunately, molecular haplotyping methods are costly, laborious, and time consuming; therefore, algorithms for constructing full haplotype patterns from small available data through computational methods, Tag SNP selection problem, are convenient and attractive. This problem is proved to be an NP-hard problem, so heuristic methods may be useful. In this paper we present a heuristic method based on genetic algorithm to find reasonable solution within acceptable time. The algorithm was tested on a variety of simulated and experimental data. In comparison with the exact algorithm, based on brute force approach, results show that our method can obtain optimal solutions in almost all cases and runs much faster than exact algorithm when the number of SNP sites is large. Our software is available upon request to the corresponding author.

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour.

PubMed

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E; Kayser, Manfred

2017-02-27

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing.

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour

PubMed Central

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H.; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R.; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E.; Kayser, Manfred

2017-01-01

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing. PMID:28240252

Tomato breeding in the genomics era: insights from a SNP array.

PubMed

Víquez-Zamora, Marcela; Vosman, Ben; van de Geest, Henri; Bovy, Arnaud; Visser, Richard G F; Finkers, Richard; van Heusden, Adriaan W

2013-05-27

The major bottle neck in genetic and linkage studies in tomato has been the lack of a sufficient number of molecular markers. This has radically changed with the application of next generation sequencing and high throughput genotyping. A set of 6000 SNPs was identified and 5528 of them were used to evaluate tomato germplasm at the level of species, varieties and segregating populations. From the 5528 SNPs, 1980 originated from 454-sequencing, 3495 from Illumina Solexa sequencing and 53 were additional known markers. Genotyping different tomato samples allowed the evaluation of the level of heterozygosity and introgressions among commercial varieties. Cherry tomatoes were especially different from round/beefs in chromosomes 4, 5 and 12. We were able to identify a set of 750 unique markers distinguishing S. lycopersicum 'Moneymaker' from all its distantly related wild relatives. Clustering and neighbour joining analysis among varieties and species showed expected grouping patterns, with S. pimpinellifolium as the most closely related to commercial tomatoes earlier results. Our results show that a SNP search in only a few breeding lines already provides generally applicable markers in tomato and its wild relatives. It also shows that the Illumina bead array generated data are highly reproducible. Our SNPs can roughly be divided in two categories: SNPs of which both forms are present in the wild relatives and in domesticated tomatoes (originating from common ancestors) and SNPs unique for the domesticated tomato (originating from after the domestication event). The SNPs can be used for genotyping, identification of varieties, comparison of genetic and physical linkage maps and to confirm (phylogenetic) relations. In the SNPs used for the array there is hardly any overlap with the SolCAP array and it is strongly recommended to combine both SNP sets and to select a core collection of robust SNPs completely covering the entire tomato genome.

High-density genetic map construction and comparative genome analysis in asparagus bean.

PubMed

Huang, Haitao; Tan, Huaqiang; Xu, Dongmei; Tang, Yi; Niu, Yisong; Lai, Yunsong; Tie, Manman; Li, Huanxiu

2018-03-19

Genetic maps are a prerequisite for quantitative trait locus (QTL) analysis, marker-assisted selection (MAS), fine gene mapping, and assembly of genome sequences. So far, several asparagus bean linkage maps have been established using various kinds of molecular markers. However, these maps were all constructed by gel- or array-based markers. No maps based on sequencing method have been reported. In this study, an NGS-based strategy, SLAF-seq, was applied to create a high-density genetic map for asparagus bean. Through SLAF library construction and Illumina sequencing of two parents and 100 F2 individuals, a total of 55,437 polymorphic SLAF markers were developed and mined for SNP markers. The map consisted of 5,225 SNP markers in 11 LGs, spanning a total distance of 1,850.81 cM, with an average distance between markers of 0.35 cM. Comparative genome analysis with four other legume species, soybean, common bean, mung bean and adzuki bean showed that asparagus bean is genetically more related to adzuki bean. The results will provide a foundation for future genomic research, such as QTL fine mapping, comparative mapping in pulses, and offer support for assembling asparagus bean genome sequence.

The iSelect 9 K SNP analysis revealed polyploidization induced revolutionary changes and intense human selection causing strong haplotype blocks in wheat.

PubMed

Hao, Chenyang; Wang, Yuquan; Chao, Shiaoman; Li, Tian; Liu, Hongxia; Wang, Lanfen; Zhang, Xueyong

2017-01-30

A Chinese wheat mini core collection was genotyped using the wheat 9 K iSelect SNP array. Total 2420 and 2396 polymorphic SNPs were detected on the A and the B genome chromosomes, which formed 878 haplotype blocks. There were more blocks in the B genome, but the average block size was significantly (P < 0.05) smaller than those in the A genome. Intense selection (domestication and breeding) had a stronger effect on the A than on the B genome chromosomes. Based on the genetic pedigrees, many blocks can be traced back to a well-known Strampelli cross, which was made one century ago. Furthermore, polyploidization of wheat (both tetraploidization and hexaploidization) induced revolutionary changes in both the A and the B genomes, with a greater increase of gene diversity compared to their diploid ancestors. Modern breeding has dramatically increased diversity in the gene coding regions, though obvious blocks were formed on most of the chromosomes in both tetraploid and hexaploid wheats. Tag-SNP markers identified in this study can be used for marker assisted selection using haplotype blocks as a wheat breeding strategy. This strategy can also be employed to facilitate genome selection in other self-pollinating crop species.

Development and application of a novel genome-wide SNP array reveals domestication history in soybean

PubMed Central

Wang, Jiao; Chu, Shanshan; Zhang, Huairen; Zhu, Ying; Cheng, Hao; Yu, Deyue

2016-01-01

Domestication of soybeans occurred under the intense human-directed selections aimed at developing high-yielding lines. Tracing the domestication history and identifying the genes underlying soybean domestication require further exploration. Here, we developed a high-throughput NJAU 355 K SoySNP array and used this array to study the genetic variation patterns in 367 soybean accessions, including 105 wild soybeans and 262 cultivated soybeans. The population genetic analysis suggests that cultivated soybeans have tended to originate from northern and central China, from where they spread to other regions, accompanied with a gradual increase in seed weight. Genome-wide scanning for evidence of artificial selection revealed signs of selective sweeps involving genes controlling domestication-related agronomic traits including seed weight. To further identify genomic regions related to seed weight, a genome-wide association study (GWAS) was conducted across multiple environments in wild and cultivated soybeans. As a result, a strong linkage disequilibrium region on chromosome 20 was found to be significantly correlated with seed weight in cultivated soybeans. Collectively, these findings should provide an important basis for genomic-enabled breeding and advance the study of functional genomics in soybean. PMID:26856884

Development and application of a novel genome-wide SNP array reveals domestication history in soybean.

PubMed

Wang, Jiao; Chu, Shanshan; Zhang, Huairen; Zhu, Ying; Cheng, Hao; Yu, Deyue

2016-02-09

Domestication of soybeans occurred under the intense human-directed selections aimed at developing high-yielding lines. Tracing the domestication history and identifying the genes underlying soybean domestication require further exploration. Here, we developed a high-throughput NJAU 355 K SoySNP array and used this array to study the genetic variation patterns in 367 soybean accessions, including 105 wild soybeans and 262 cultivated soybeans. The population genetic analysis suggests that cultivated soybeans have tended to originate from northern and central China, from where they spread to other regions, accompanied with a gradual increase in seed weight. Genome-wide scanning for evidence of artificial selection revealed signs of selective sweeps involving genes controlling domestication-related agronomic traits including seed weight. To further identify genomic regions related to seed weight, a genome-wide association study (GWAS) was conducted across multiple environments in wild and cultivated soybeans. As a result, a strong linkage disequilibrium region on chromosome 20 was found to be significantly correlated with seed weight in cultivated soybeans. Collectively, these findings should provide an important basis for genomic-enabled breeding and advance the study of functional genomics in soybean.

Comparing CNV detection methods for SNP arrays.

PubMed

Winchester, Laura; Yau, Christopher; Ragoussis, Jiannis

2009-09-01

Data from whole genome association studies can now be used for dual purposes, genotyping and copy number detection. In this review we discuss some of the methods for using SNP data to detect copy number events. We examine a number of algorithms designed to detect copy number changes through the use of signal-intensity data and consider methods to evaluate the changes found. We describe the use of several statistical models in copy number detection in germline samples. We also present a comparison of data using these methods to assess accuracy of prediction and detection of changes in copy number.

Single-Nucleotide Polymorphism Array-Based Karyotyping of Acute Promyelocytic Leukemia

PubMed Central

Gómez-Seguí, Inés; Sánchez-Izquierdo, Dolors; Barragán, Eva; Such, Esperanza; Luna, Irene; López-Pavía, María; Ibáñez, Mariam; Villamón, Eva; Alonso, Carmen; Martín, Iván; Llop, Marta; Dolz, Sandra; Fuster, Óscar; Montesinos, Pau; Cañigral, Carolina; Boluda, Blanca; Salazar, Claudia

2014-01-01

Acute promyelocytic leukemia (APL) is characterized by the t(15;17)(q22;q21), but additional chromosomal abnormalities (ACA) and other rearrangements can contribute in the development of the whole leukemic phenotype. We hypothesized that some ACA not detected by conventional techniques may be informative of the onset of APL. We performed the high-resolution SNP array (SNP-A) 6.0 (Affymetrix) in 48 patients diagnosed with APL on matched diagnosis and remission sample. Forty-six abnormalities were found as an acquired event in 23 patients (48%): 22 duplications, 23 deletions and 1 Copy-Neutral Loss of Heterozygocity (CN-LOH), being a duplication of 8(q24) (23%) and a deletion of 7(q33-qter) (6%) the most frequent copy-number abnormalities (CNA). Four patients (8%) showed CNAs adjacent to the breakpoints of the translocation. We compared our results with other APL series and found that, except for dup(8q24) and del(7q33-qter), ACA were infrequent (≤3%) but most of them recurrent (70%). Interestingly, having CNA or FLT3 mutation were mutually exclusive events. Neither the number of CNA, nor any specific CNA was associated significantly with prognosis. This study has delineated recurrent abnormalities in addition to t(15;17) that may act as secondary events and could explain leukemogenesis in up to 40% of APL cases with no ACA by conventional cytogenetics. PMID:24959826

Single-nucleotide polymorphism array-based karyotyping of acute promyelocytic leukemia.

PubMed

Gómez-Seguí, Inés; Sánchez-Izquierdo, Dolors; Barragán, Eva; Such, Esperanza; Luna, Irene; López-Pavía, María; Ibáñez, Mariam; Villamón, Eva; Alonso, Carmen; Martín, Iván; Llop, Marta; Dolz, Sandra; Fuster, Oscar; Montesinos, Pau; Cañigral, Carolina; Boluda, Blanca; Salazar, Claudia; Cervera, Jose; Sanz, Miguel A

2014-01-01

Acute promyelocytic leukemia (APL) is characterized by the t(15;17)(q22;q21), but additional chromosomal abnormalities (ACA) and other rearrangements can contribute in the development of the whole leukemic phenotype. We hypothesized that some ACA not detected by conventional techniques may be informative of the onset of APL. We performed the high-resolution SNP array (SNP-A) 6.0 (Affymetrix) in 48 patients diagnosed with APL on matched diagnosis and remission sample. Forty-six abnormalities were found as an acquired event in 23 patients (48%): 22 duplications, 23 deletions and 1 Copy-Neutral Loss of Heterozygocity (CN-LOH), being a duplication of 8(q24) (23%) and a deletion of 7(q33-qter) (6%) the most frequent copy-number abnormalities (CNA). Four patients (8%) showed CNAs adjacent to the breakpoints of the translocation. We compared our results with other APL series and found that, except for dup(8q24) and del(7q33-qter), ACA were infrequent (≤3%) but most of them recurrent (70%). Interestingly, having CNA or FLT3 mutation were mutually exclusive events. Neither the number of CNA, nor any specific CNA was associated significantly with prognosis. This study has delineated recurrent abnormalities in addition to t(15;17) that may act as secondary events and could explain leukemogenesis in up to 40% of APL cases with no ACA by conventional cytogenetics.

Clarifying sub-genomic positions of QTLs for flowering habit and fruit quality in U.S. strawberry (Fragaria×ananassa) breeding populations using pedigree-based QTL analysis

PubMed Central

Verma, Sujeet; Zurn, Jason D; Salinas, Natalia; Mathey, Megan M; Denoyes, Beatrice; Hancock, James F; Finn, Chad E; Bassil, Nahla V; Whitaker, Vance M

2017-01-01

The cultivated strawberry (Fragaria×ananassa) is consumed worldwide for its flavor and nutritional benefits. Genetic analysis of commercially important traits in strawberry are important for the development of breeding methods and tools for this species. Although several quantitative trait loci (QTL) have been previously detected for fruit quality and flowering traits using low-density genetic maps, clarity on the sub-genomic locations of these QTLs was missing. Recent discoveries in allo-octoploid strawberry genomics led to the development of the IStraw90 single-nucleotide polymorphism (SNP) array, enabling high-density genetic maps and finer resolution QTL analysis. In this study, breeder-specified traits were evaluated in the Eastern (Michigan) and Western (Oregon) United States for a common set of breeding populations during 2 years. Several QTLs were validated for soluble solids content (SSC), fruit weight (FWT), pH and titratable acidity (TA) using a pedigree-based QTL analysis approach. For fruit quality, a QTL for SSC on linkage group (LG) 6A, a QTL for FWT on LG 2BII, a QTL for pH on LG 4CII and two QTLs for TA on LGs 2A and 5B were detected. In addition, a large-effect QTL for flowering was detected at the distal end of LG 4A, coinciding with the FaPFRU locus. Marker haplotype analysis in the FaPFRU region indicated that the homozygous recessive genotype was highly predictive of seasonal flowering. SNP probes in the FaPFRU region may help facilitate marker-assisted selection for this trait. PMID:29138689

Clarifying sub-genomic positions of QTLs for flowering habit and fruit quality in U.S. strawberry (Fragaria×ananassa) breeding populations using pedigree-based QTL analysis.

PubMed

Verma, Sujeet; Zurn, Jason D; Salinas, Natalia; Mathey, Megan M; Denoyes, Beatrice; Hancock, James F; Finn, Chad E; Bassil, Nahla V; Whitaker, Vance M

2017-01-01

The cultivated strawberry ( Fragaria × ananassa ) is consumed worldwide for its flavor and nutritional benefits. Genetic analysis of commercially important traits in strawberry are important for the development of breeding methods and tools for this species. Although several quantitative trait loci (QTL) have been previously detected for fruit quality and flowering traits using low-density genetic maps, clarity on the sub-genomic locations of these QTLs was missing. Recent discoveries in allo-octoploid strawberry genomics led to the development of the IStraw90 single-nucleotide polymorphism (SNP) array, enabling high-density genetic maps and finer resolution QTL analysis. In this study, breeder-specified traits were evaluated in the Eastern (Michigan) and Western (Oregon) United States for a common set of breeding populations during 2 years. Several QTLs were validated for soluble solids content (SSC), fruit weight (FWT), pH and titratable acidity (TA) using a pedigree-based QTL analysis approach. For fruit quality, a QTL for SSC on linkage group (LG) 6A, a QTL for FWT on LG 2BII, a QTL for pH on LG 4CII and two QTLs for TA on LGs 2A and 5B were detected. In addition, a large-effect QTL for flowering was detected at the distal end of LG 4A, coinciding with the FaPFRU locus. Marker haplotype analysis in the FaPFRU region indicated that the homozygous recessive genotype was highly predictive of seasonal flowering. SNP probes in the FaPFRU region may help facilitate marker-assisted selection for this trait.

RNA sequencing to study gene expression and SNP variations associated with growth in zebrafish fed a plant protein-based diet.

PubMed

Ulloa, Pilar E; Rincón, Gonzalo; Islas-Trejo, Alma; Araneda, Cristian; Iturra, Patricia; Neira, Roberto; Medrano, Juan F

2015-06-01

The objectives of this study were to measure gene expression in zebrafish and then identify SNP to be used as potential markers in a growth association study. We developed an approach where muscle samples collected from low- and high-growth fish were analyzed using RNA-Sequencing (RNA-seq), and SNP were chosen from the genes that were differentially expressed between the low and high groups. A population of 24 families was fed a plant protein-based diet from the larval to adult stages. From a total of 440 males, 5 % of the fish from both tails of the weight gain distribution were selected. Total RNA was extracted from individual muscle of 8 low-growth and 8 high-growth fish. Two pooled RNA-Seq libraries were prepared for each phenotype using 4 fish per library. Libraries were sequenced using the Illumina GAII Sequencer and analyzed using the CLCBio genomic workbench software. One hundred and twenty-four genes were differentially expressed between phenotypes (p value < 0.05 and FDR < 0.2). From these genes, 164 SNP were selected and genotyped in 240 fish samples. Marker-trait analysis revealed 5 SNP associated with growth in key genes (Nars, Lmod2b, Cuzd1, Acta1b, and Plac8l1). These genes are good candidates for further growth studies in fish and to consider for identification of potential SNPs associated with different growth rates in response to a plant protein-based diet.

Genome-wide association study (GWAS) for growth rate and age at sexual maturation in Atlantic salmon (Salmo salar).

PubMed

Gutierrez, Alejandro P; Yáñez, José M; Fukui, Steve; Swift, Bruce; Davidson, William S

2015-01-01

Early sexual maturation is considered a serious drawback for Atlantic salmon aquaculture as it retards growth, increases production times and affects flesh quality. Although both growth and sexual maturation are thought to be complex processes controlled by several genetic and environmental factors, selection for these traits has been continuously accomplished since the beginning of Atlantic salmon selective breeding programs. In this genome-wide association study (GWAS) we used a 6.5K single-nucleotide polymorphism (SNP) array to genotype ∼ 480 individuals from the Cermaq Canada broodstock program and search for SNPs associated with growth and age at sexual maturation. Using a mixed model approach we identified markers showing a significant association with growth, grilsing (early sexual maturation) and late sexual maturation. The most significant associations were found for grilsing, with markers located in Ssa10, Ssa02, Ssa13, Ssa25 and Ssa12, and for late maturation with markers located in Ssa28, Ssa01 and Ssa21. A lower level of association was detected with growth on Ssa13. Candidate genes, which were linked to these genetic markers, were identified and some of them show a direct relationship with developmental processes, especially for those in association with sexual maturation. However, the relatively low power to detect genetic markers associated with growth (days to 5 kg) in this GWAS indicates the need to use a higher density SNP array in order to overcome the low levels of linkage disequilibrium observed in Atlantic salmon before the information can be incorporated into a selective breeding program.

FISH Oracle: a web server for flexible visualization of DNA copy number data in a genomic context.

PubMed

Mader, Malte; Simon, Ronald; Steinbiss, Sascha; Kurtz, Stefan

2011-07-28

The rapidly growing amount of array CGH data requires improved visualization software supporting the process of identifying candidate cancer genes. Optimally, such software should work across multiple microarray platforms, should be able to cope with data from different sources and should be easy to operate. We have developed a web-based software FISH Oracle to visualize data from multiple array CGH experiments in a genomic context. Its fast visualization engine and advanced web and database technology supports highly interactive use. FISH Oracle comes with a convenient data import mechanism, powerful search options for genomic elements (e.g. gene names or karyobands), quick navigation and zooming into interesting regions, and mechanisms to export the visualization into different high quality formats. These features make the software especially suitable for the needs of life scientists. FISH Oracle offers a fast and easy to use visualization tool for array CGH and SNP array data. It allows for the identification of genomic regions representing minimal common changes based on data from one or more experiments. FISH Oracle will be instrumental to identify candidate onco and tumor suppressor genes based on the frequency and genomic position of DNA copy number changes. The FISH Oracle application and an installed demo web server are available at http://www.zbh.uni-hamburg.de/fishoracle.

FISH Oracle: a web server for flexible visualization of DNA copy number data in a genomic context

PubMed Central

2011-01-01

Background The rapidly growing amount of array CGH data requires improved visualization software supporting the process of identifying candidate cancer genes. Optimally, such software should work across multiple microarray platforms, should be able to cope with data from different sources and should be easy to operate. Results We have developed a web-based software FISH Oracle to visualize data from multiple array CGH experiments in a genomic context. Its fast visualization engine and advanced web and database technology supports highly interactive use. FISH Oracle comes with a convenient data import mechanism, powerful search options for genomic elements (e.g. gene names or karyobands), quick navigation and zooming into interesting regions, and mechanisms to export the visualization into different high quality formats. These features make the software especially suitable for the needs of life scientists. Conclusions FISH Oracle offers a fast and easy to use visualization tool for array CGH and SNP array data. It allows for the identification of genomic regions representing minimal common changes based on data from one or more experiments. FISH Oracle will be instrumental to identify candidate onco and tumor suppressor genes based on the frequency and genomic position of DNA copy number changes. The FISH Oracle application and an installed demo web server are available at http://www.zbh.uni-hamburg.de/fishoracle. PMID:21884636

Accuracy of CNV Detection from GWAS Data.

PubMed

Zhang, Dandan; Qian, Yudong; Akula, Nirmala; Alliey-Rodriguez, Ney; Tang, Jinsong; Gershon, Elliot S; Liu, Chunyu

2011-01-13

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites--Birdsuite, Partek, HelixTree, and PennCNV-Affy--in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two "gold standards," the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a "gold standard" for detection of CNVs remains to be established.

High-density linkage mapping in a pine tree reveals a genomic region associated with inbreeding depression and provides clues to the extent and distribution of meiotic recombination

PubMed Central

2013-01-01

Background The availability of a large expressed sequence tags (EST) resource and recent advances in high-throughput genotyping technology have made it possible to develop highly multiplexed SNP arrays for multi-objective genetic applications, including the construction of meiotic maps. Such approaches are particularly useful in species with a large genome size, precluding the use of whole-genome shotgun assembly with current technologies. Results In this study, a 12 k-SNP genotyping array was developed for maritime pine from an extensive EST resource assembled into a unigene set. The offspring of three-generation outbred and inbred mapping pedigrees were then genotyped. The inbred pedigree consisted of a classical F2 population resulting from the selfing of a single inter-provenance (Landes x Corsica) hybrid tree, whereas the outbred pedigree (G2) resulted from a controlled cross of two intra-provenance (Landes x Landes) hybrid trees. This resulted in the generation of three linkage maps based on SNP markers: one from the parental genotype of the F2 population (1,131 markers in 1,708 centimorgan (cM)), and one for each parent of the G2 population (1,015 and 1,110 markers in 1,447 and 1,425 cM for the female and male parents, respectively). A comparison of segregation patterns in the progeny obtained from the two types of mating (inbreeding and outbreeding) led to the identification of a chromosomal region carrying an embryo viability locus with a semi-lethal allele. Following selfing and segregation, zygote mortality resulted in a deficit of Corsican homozygous genotypes in the F2 population. This dataset was also used to study the extent and distribution of meiotic recombination along the length of the chromosomes and the effect of sex and/or genetic background on recombination. The genetic background of trees in which meiotic recombination occurred was found to have a significant effect on the frequency of recombination. Furthermore, only a small proportion of the recombination hot- and cold-spots were common to all three genotypes, suggesting that the spatial pattern of recombination was genetically variable. Conclusion This study led to the development of classical genomic tools for this ecologically and economically important species. It also identified a chromosomal region bearing a semi-lethal recessive allele and demonstrated the genetic variability of recombination rate over the genome. PMID:23597128

Increased Frequency of De Novo Copy Number Variations in Congenital Heart Disease by Integrative Analysis of SNP Array and Exome Sequence Data

PubMed Central

Rodriguez-Murillo, Laura; Fromer, Menachem; Mazaika, Erica; Vardarajan, Badri; Italia, Michael; Leipzig, Jeremy; DePalma, Steven R.; Golhar, Ryan; Sanders, Stephan J.; Yamrom, Boris; Ronemus, Michael; Iossifov, Ivan; Willsey, A. Jeremy; State, Matthew W.; Kaltman, Jonathan R.; White, Peter S.; Shen, Yufeng; Warburton, Dorothy; Brueckner, Martina; Seidman, Christine; Goldmuntz, Elizabeth; Gelb, Bruce D.; Lifton, Richard; Seidman, Jonathan; Hakonarson, Hakon; Chung, Wendy K.

2014-01-01

Rationale Congenital heart disease (CHD) is among the most common birth defects. Most cases are of unknown etiology. Objective To determine the contribution of de novo copy number variants (CNVs) in the etiology of sporadic CHD. Methods and Results We studied 538 CHD trios using genome-wide dense single nucleotide polymorphism (SNP) arrays and/or whole exome sequencing (WES). Results were experimentally validated using digital droplet PCR. We compared validated CNVs in CHD cases to CNVs in 1,301 healthy control trios. The two complementary high-resolution technologies identified 63 validated de novo CNVs in 51 CHD cases. A significant increase in CNV burden was observed when comparing CHD trios with healthy trios, using either SNP array (p=7x10−5, Odds Ratio (OR)=4.6) or WES data (p=6x10−4, OR=3.5) and remained after removing 16% of de novo CNV loci previously reported as pathogenic (p=0.02, OR=2.7). We observed recurrent de novo CNVs on 15q11.2 encompassing CYFIP1, NIPA1, and NIPA2 and single de novo CNVs encompassing DUSP1, JUN, JUP, MED15, MED9, PTPRE SREBF1, TOP2A, and ZEB2, genes that interact with established CHD proteins NKX2-5 and GATA4. Integrating de novo variants in WES and CNV data suggests that ETS1 is the pathogenic gene altered by 11q24.2-q25 deletions in Jacobsen syndrome and that CTBP2 is the pathogenic gene in 10q sub-telomeric deletions. Conclusions We demonstrate a significantly increased frequency of rare de novo CNVs in CHD patients compared with healthy controls and suggest several novel genetic loci for CHD. PMID:25205790

Similar Genetic Architecture with Shared and Unique Quantitative Trait Loci for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations

PubMed Central

Vallejo, Roger L.; Liu, Sixin; Gao, Guangtu; Fragomeni, Breno O.; Hernandez, Alvaro G.; Leeds, Timothy D.; Parsons, James E.; Martin, Kyle E.; Evenhuis, Jason P.; Welch, Timothy J.; Wiens, Gregory D.; Palti, Yniv

2017-01-01

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect quantitative trait loci (QTL) for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57 K SNP array and a reference genome assembly have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57 K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57 K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered. PMID:29109734

Similar Genetic Architecture with Shared and Unique Quantitative Trait Loci for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations.

PubMed

Vallejo, Roger L; Liu, Sixin; Gao, Guangtu; Fragomeni, Breno O; Hernandez, Alvaro G; Leeds, Timothy D; Parsons, James E; Martin, Kyle E; Evenhuis, Jason P; Welch, Timothy J; Wiens, Gregory D; Palti, Yniv

2017-01-01

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect quantitative trait loci (QTL) for BCWD resistance in rainbow trout ( Oncorhynchus mykiss ). However, the recent availability of a 57 K SNP array and a reference genome assembly have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57 K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57 K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.

Genome-wide association analysis reveals loci associated with resistance against Piscirickettsia salmonis in two Atlantic salmon (Salmo salar L.) chromosomes.

PubMed

Correa, Katharina; Lhorente, Jean P; López, María E; Bassini, Liane; Naswa, Sudhir; Deeb, Nader; Di Genova, Alex; Maass, Alejandro; Davidson, William S; Yáñez, José M

2015-10-24

Pisciricketssia salmonis is the causal agent of Salmon Rickettsial Syndrome (SRS), which affects salmon species and causes severe economic losses. Selective breeding for disease resistance represents one approach for controlling SRS in farmed Atlantic salmon. Knowledge concerning the architecture of the resistance trait is needed before deciding on the most appropriate approach to enhance artificial selection for P. salmonis resistance in Atlantic salmon. The purpose of the study was to dissect the genetic variation in the resistance to this pathogen in Atlantic salmon. 2,601 Atlantic salmon smolts were experimentally challenged against P. salmonis by means of intra-peritoneal injection. These smolts were the progeny of 40 sires and 118 dams from a Chilean breeding population. Mortalities were recorded daily and the experiment ended at day 40 post-inoculation. Fish were genotyped using a 50K Affymetrix® Axiom® myDesignTM Single Nucleotide Polymorphism (SNP) Genotyping Array. A Genome Wide Association Analysis was performed on data from the challenged fish. Linear regression and logistic regression models were tested. Genome Wide Association Analysis indicated that resistance to P. salmonis is a moderately polygenic trait. There were five SNPs in chromosomes Ssa01 and Ssa17 significantly associated with the traits analysed. The proportion of the phenotypic variance explained by each marker is small, ranging from 0.007 to 0.045. Candidate genes including interleukin receptors and fucosyltransferase have been found to be physically linked with these genetic markers and may play an important role in the differential immune response against this pathogen. Due to the small amount of variance explained by each significant marker we conclude that genetic resistance to this pathogen can be more efficiently improved with the implementation of genetic evaluations incorporating genotype information from a dense SNP array.

Developing 100K Affymetrix Axiom SNP Array for Polyploid Sugarcane

USDA-ARS?s Scientific Manuscript database

Sugarcane genotyping or fingerprinting has long been a daunting task due to its high polyploidy level with large number of chromosomes. Single nucleotide polymorphisms (SNPs) are very abundant DNA sequence variations in the genomes. With the advance of next generation sequencing (NGS) technologies, ...

Population sequencing reveals breed and sub-species specific CNVs in cattle

USDA-ARS?s Scientific Manuscript database

Individualized copy number variation (CNV) maps have highlighted the need for population surveys of cattle to detect rare and common variants. While SNP and comparative genomic hybridization (CGH) arrays have provided preliminary data, next-generation sequence (NGS) data analysis offers an increased...

QTL mapping of potato chip color and tuber traits within an autotetraploid family

USDA-ARS?s Scientific Manuscript database

Cultivated potato (Solanum tuberosum L.) is a highly heterozygous autotetraploid crop species, and this presents challenges for traditional line development and molecular breeding. Recent availability of a single nucleotide polymorphism (SNP) array with 8303 features and software packages for linkag...

Development and characterization of a microheater array device for real-time DNA mutation detection

NASA Astrophysics Data System (ADS)

Williams, Layne; Okandan, Murat; Chagovetz, Alex; Blair, Steve

2008-04-01

DNA analysis, specifically single nucleotide polymorphism (SNP) detection, is becoming increasingly important in rapid diagnostics and disease detection. Temperature is often controlled to help speed reaction rates and perform melting of hybridized oligonucleotides. The difference in melting temperatures, Tm, between wild-type and SNP sequences, respectively, to a given probe oligonucleotide, is indicative of the specificity of the reaction. We have characterized Tm's in solution and on a solid substrate of three sequences from known mutations associated with Cystic Fibrosis. Taking advantage of Tm differences, a microheater array device was designed to enable individual temperature control of up to 18 specific hybridization events. The device was fabricated at Sandia National Laboratories using surface micromachining techniques. The microheaters have been characterized using an IR camera at Sandia and show individual temperature control with minimal thermal cross talk. Development of the device as a real-time DNA detection platform, including surface chemistry and associated microfluidics, is described.

Development and characterization of a microheater array device for real-time DNA mutation detection

NASA Astrophysics Data System (ADS)

Williams, Layne; Okandan, Murat; Chagovetz, Alex; Blair, Steve

2008-02-01

DNA analysis, specifically single nucleotide polymorphism (SNP) detection, is becoming increasingly important in rapid diagnostics and disease detection. Temperature is often controlled to help speed reaction rates and perform melting of hybridized oligonucleotides. The difference in melting temperatures, Tm, between wild-type and SNP sequences, respectively, to a given probe oligonucleotide, is indicative of the specificity of the reaction. We have characterized Tm's in solution and on a solid substrate of three sequences from known mutations associated with Cystic Fibrosis. Taking advantage of Tm differences, a microheater array device was designed to enable individual temperature control of up to 18 specific hybridization events. The device was fabricated at Sandia National Laboratories using surface micromachining techniques. The microheaters have been characterized using an IR camera at Sandia and show individual temperature control with minimal thermal cross talk. Development of the device as a real-time DNA detection platform, including surface chemistry and associated microfluidics, is described.

Novel SNP array analysis and exome sequencing detect a homozygous exon 7 deletion of MEGF10 causing early onset myopathy, areflexia, respiratory distress and dysphagia (EMARDD)

PubMed Central

Pierson, Tyler Mark; Markello, Thomas; Accardi, John; Wolfe, Lynne; Adams, David; Sincan, Murat; Tarazi, Noor M.; Fajardo, Karin Fuentes; Cherukuri, Praveen F.; Bajraktari, Ilda; Meilleur, Katy G.; Donkervoort, Sandra; Jain, Mina; Hu, Ying; Lehky, Tanya J.; Cruz, Pedro; Mullikin, James C.; Bonnemann, Carsten; Gahl, William A.; Boerkoel, Cornelius F.; Tifft, Cynthia J.

2013-01-01

Early-onset myopathy, areflexia, respiratory distress and dysphagia (EMARDD) is a myopathic disorder associated with mutations in MEGF10. By novel analysis of SNP array hybridization and exome sequence coverage, we diagnosed a 10-year old girl with EMARDD following identification of a novel homozygous deletion of exon 7 in MEGF10. In contrast to previously reported EMARDD patients, her weakness was more prominent proximally than distally, and involved her legs more than her arms. MRI of her pelvis and thighs showed muscle atrophy and fatty replacement. Ultrasound of several muscle groups revealed dense homogenous increases in echogenicity. Cloning and sequencing of the deletion breakpoint identified features suggesting the mutation arose by fork stalling and template switching. These findings constitute the first genomic deletion causing EMARDD, expand the clinical phenotype, and provide new insight into the pattern and histology of its muscular pathology. PMID:23453856

DNA-mounted self-assembly: new approaches for genomic analysis and SNP detection.

PubMed

Bichenkova, Elena V; Lang, Zhaolei; Yu, Xuan; Rogert, Candelaria; Douglas, Kenneth T

2011-01-01

This article presents an overview of new emerging approaches for nucleic acid detection via hybridization techniques that can potentially be applied to genomic analysis and SNP identification in clinical diagnostics. Despite the availability of a diverse variety of SNP genotyping technologies on the diagnostic market, none has truly succeeded in dominating its competitors thus far. Having been designed for specific diagnostic purposes or clinical applications, each of the existing bio-assay systems (briefly outlined here) is usually limited to a relatively narrow aspect or format of nucleic acid detection, and thus cannot entirely satisfy all the varieties of commercial requirements and clinical demands. This drives the diagnostic sector to pursue novel, cost-effective approaches to ensure rapid and reliable identification of pathogenic or hereditary human diseases. Hence, the purpose of this review is to highlight some new strategic directions in DNA detection technologies in order to inspire development of novel molecular diagnostic tools and bio-assay systems with superior reliability, reproducibility, robustness, accuracy and sensitivity at lower assay cost. One approach to improving the sensitivity of an assay to confidently discriminate between single point mutations is based on the use of target assembled, split-probe systems, which constitutes the main focus of this review. Copyright © 2010 Elsevier B.V. All rights reserved.

TotalReCaller: improved accuracy and performance via integrated alignment and base-calling.

PubMed

Menges, Fabian; Narzisi, Giuseppe; Mishra, Bud

2011-09-01

Currently, re-sequencing approaches use multiple modules serially to interpret raw sequencing data from next-generation sequencing platforms, while remaining oblivious to the genomic information until the final alignment step. Such approaches fail to exploit the full information from both raw sequencing data and the reference genome that can yield better quality sequence reads, SNP-calls, variant detection, as well as an alignment at the best possible location in the reference genome. Thus, there is a need for novel reference-guided bioinformatics algorithms for interpreting analog signals representing sequences of the bases ({A, C, G, T}), while simultaneously aligning possible sequence reads to a source reference genome whenever available. Here, we propose a new base-calling algorithm, TotalReCaller, to achieve improved performance. A linear error model for the raw intensity data and Burrows-Wheeler transform (BWT) based alignment are combined utilizing a Bayesian score function, which is then globally optimized over all possible genomic locations using an efficient branch-and-bound approach. The algorithm has been implemented in soft- and hardware [field-programmable gate array (FPGA)] to achieve real-time performance. Empirical results on real high-throughput Illumina data were used to evaluate TotalReCaller's performance relative to its peers-Bustard, BayesCall, Ibis and Rolexa-based on several criteria, particularly those important in clinical and scientific applications. Namely, it was evaluated for (i) its base-calling speed and throughput, (ii) its read accuracy and (iii) its specificity and sensitivity in variant calling. A software implementation of TotalReCaller as well as additional information, is available at: http://bioinformatics.nyu.edu/wordpress/projects/totalrecaller/ fabian.menges@nyu.edu.

High-Resolution Mapping of Structural Mutations in Prostate Cancer with Single Nucleotide Polymorphism Arrays

DTIC Science & Technology

2006-11-01

study of the NCI60 panel of cancer cell lines [39]. More recently, amplifications of NOTCH3 were noted in ovarian tumors by an SNP array analysis...and the functional role of NOTCH3 was suggested by the ability to suppress cell proliferation by inhibiting NOTCH3 [40]. Allele-specific copy...Identified and functionally validated the oncogene MITF. 40 Park JT, Li M, Nakayama K, et al. Notch3 gene amplification in ovarian cancer. Cancer Res

Single Nucleotide Polymorphism (SNP)-Based Loss of Heterozygosity (LOH) Testing by Real Time PCR in Patients Suspect of Myeloproliferative Disease

PubMed Central

Huijsmans, Cornelis J. J.; Poodt, Jeroen; Damen, Jan; van der Linden, Johannes C.; Savelkoul, Paul H. M.; Pruijt, Johannes F. M.; Hilbink, Mirrian; Hermans, Mirjam H. A.

2012-01-01

During tumor development, loss of heterozygosity (LOH) often occurs. When LOH is preceded by an oncogene activating mutation, the mutant allele may be further potentiated if the wild-type allele is lost or inactivated. In myeloproliferative neoplasms (MPN) somatic acquisition of JAK2V617F may be followed by LOH resulting in loss of the wild type allele. The occurrence of LOH in MPN and other proliferative diseases may lead to a further potentiating the mutant allele and thereby increasing morbidity. A real time PCR based SNP profiling assay was developed and validated for LOH detection of the JAK2 region (JAK2LOH). Blood of a cohort of 12 JAK2V617F-positive patients (n = 6 25–50% and n = 6>50% JAK2V617F) and a cohort of 81 patients suspected of MPN was stored with EDTA and subsequently used for validation. To generate germ-line profiles, non-neoplastic formalin-fixed paraffin-embedded tissue from each patient was analyzed. Results of the SNP assay were compared to those of an established Short Tandem Repeat (STR) assay. Both assays revealed JAK2LOH in 1/6 patients with 25–50% JAK2V617F. In patients with >50% JAK2V617F, JAK2LOH was detected in 6/6 by the SNP assay and 5/6 patients by the STR assay. Of the 81 patients suspected of MPN, 18 patients carried JAK2V617F. Both the SNP and STR assay demonstrated the occurrence of JAK2LOH in 5 of them. In the 63 JAK2V617F-negative patients, no JAK2LOH was observed by SNP and STR analyses. The presented SNP assay reliably detects JAK2LOH and is a fast and easy to perform alternative for STR analyses. We therefore anticipate the SNP approach as a proof of principle for the development of LOH SNP-assays for other clinically relevant LOH loci. PMID:22768290

Identification and association analysis of several hundred single nucleotide polymorphisms within candidate genes for back fat thickness in Italian Large White pigs using a selective genotyping approach.

PubMed

Fontanesi, L; Galimberti, G; Calò, D G; Fronza, R; Martelli, P L; Scotti, E; Colombo, M; Schiavo, G; Casadio, R; Buttazzoni, L; Russo, V

2012-08-01

Combining different approaches (resequencing of portions of 54 obesity candidate genes, literature mining for pig markers associated with fat deposition or related traits in 77 genes, and in silico mining of porcine expressed sequence tags and other sequences available in databases), we identified and analyzed 736 SNP within candidate genes to identify markers associated with back fat thickness (BFT) in Italian Large White sows. Animals were chosen using a selective genotyping approach according to their EBV for BFT (276 with most negative and 279 with most positive EBV) within a population of ≈ 12,000 pigs. Association analysis between the SNP and BFT has been carried out using the MAX test proposed for case-control studies. The designed assays were successful for 656 SNP: 370 were excluded (low call rate or minor allele frequency <5%), whereas the remaining 286 in 212 genes were taken for subsequent analyses, among which 64 showed a P(nominal) value <0.1. To deal with the multiple testing problem in a candidate gene approach, we applied the proportion of false positives (PFP) method. Thirty-eight SNP were significant (P(PFP) < 0.20). The most significant SNP was the IGF2 intron3-g.3072G>A polymorphism (P(nominal) < 1.0E-50). The second most significant SNP was the MC4R c.1426A>G polymorphism (P(nominal) = 8.0E-05). The third top SNP (P(nominal) = 6.2E-04) was the intronic TBC1D1 g.219G>A polymorphic site, in agreement with our previous results obtained in an independent study. The list of significant markers also included SNP in additional genes (ABHD16A, ABHD5, ACP2, ALMS1, APOA2, ATP1A2, CALR, COL14A1, CTSF, DARS, DECR1, ENPP1, ESR1, GH1, GHRL, GNMT, IKBKB, JAK3, MTTP, NFKBIA, NT5E, PLAT, PPARG, PPP2R5D, PRLR, RRAGD, RFC2, SDHD, SERPINF1, UBE2H, VCAM1, and WAT). Functional relationships between genes were obtained using the Ingenuity Pathway Analysis (IPA) Knowledge Base. The top scoring pathway included 19 genes with a P(nominal) < 0.1, 2 of which (IKBKB and NFKBIA) are involved in the hypothalamic IKKβ/NFκB program that could represent a key axis to affect fat deposition traits in pigs. These results represent a starting point to plan marker-assisted selection in Italian Large White nuclei for BFT. Because of similarities between humans and pigs, this study might also provide useful clues to investigate genetic factors affecting human obesity.

Population sequencing reveals breed and sub-species specific CNVs in cattle

USDA-ARS?s Scientific Manuscript database

Individualized copy number variation (CNV) maps have highlighted the need for population surveys of cattle to detect the rare and common variants. While SNP and comparative genomic hybridization (CGH) arrays have provided preliminary data, next-generation sequence (NGS) data analysis offers an incre...

Development and utilization of 100K SNP array in Saccharum Spp.

USDA-ARS?s Scientific Manuscript database

Sugarcane genotyping or fingerprinting has long been a daunting task due to its high polyploidy level with large number of chromosomes. Single nucleotide polymorphisms (SNPs) are very abundant DNA sequence variations in the genome. With the advance of next generation sequencing (NGS) technologies, m...

Pathway-based analyses.

PubMed

Kent, Jack W

2016-02-03

New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

Whole genome sequences are required to fully resolve the linkage disequilibrium structure of human populations.

PubMed

Pengelly, Reuben J; Tapper, William; Gibson, Jane; Knut, Marcin; Tearle, Rick; Collins, Andrew; Ennis, Sarah

2015-09-03

An understanding of linkage disequilibrium (LD) structures in the human genome underpins much of medical genetics and provides a basis for disease gene mapping and investigating biological mechanisms such as recombination and selection. Whole genome sequencing (WGS) provides the opportunity to determine LD structures at maximal resolution. We compare LD maps constructed from WGS data with LD maps produced from the array-based HapMap dataset, for representative European and African populations. WGS provides up to 5.7-fold greater SNP density than array-based data and achieves much greater resolution of LD structure, allowing for identification of up to 2.8-fold more regions of intense recombination. The absence of ascertainment bias in variant genotyping improves the population representativeness of the WGS maps, and highlights the extent of uncaptured variation using array genotyping methodologies. The complete capture of LD patterns using WGS allows for higher genome-wide association study (GWAS) power compared to array-based GWAS, with WGS also allowing for the analysis of rare variation. The impact of marker ascertainment issues in arrays has been greatest for Sub-Saharan African populations where larger sample sizes and substantially higher marker densities are required to fully resolve the LD structure. WGS provides the best possible resource for LD mapping due to the maximal marker density and lack of ascertainment bias. WGS LD maps provide a rich resource for medical and population genetics studies. The increasing availability of WGS data for large populations will allow for improved research utilising LD, such as GWAS and recombination biology studies.

Sequence-Based Genotyping for Marker Discovery and Co-Dominant Scoring in Germplasm and Populations

PubMed Central

Truong, Hoa T.; Ramos, A. Marcos; Yalcin, Feyruz; de Ruiter, Marjo; van der Poel, Hein J. A.; Huvenaars, Koen H. J.; Hogers, René C. J.; van Enckevort, Leonora. J. G.; Janssen, Antoine; van Orsouw, Nathalie J.; van Eijk, Michiel J. T.

2012-01-01

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n = 222 samples) and lettuce (n = 87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike. PMID:22662172

Systems Genetics Identifies a Novel Regulatory Domain of Amylose Synthesis1[OPEN

PubMed Central

Parween, Sabiha; Samson, Irene; de Guzman, Krishna; Alhambra, Crisline Mae; Misra, Gopal

2017-01-01

A deeper understanding of the regulation of starch biosynthesis in rice (Oryza sativa) endosperm is crucial in tailoring digestibility without sacrificing grain quality. In this study, significant association peaks on chromosomes 6 and 7 were identified through a genomewide association study (GWAS) of debranched starch structure from grains of a 320 indica rice diversity panel using genotyping data from the high-density rice array. A systems genetics approach that interrelates starch structure data from GWAS to functional pathways from a gene regulatory network identified known genes with high correlation to the proportion of amylose and amylopectin. An SNP in the promoter region of Granule Bound Starch Synthase I was identified along with seven other SNPs to form haplotypes that discriminate samples into different phenotypic ranges of amylose. A GWAS peak on chromosome 7 between LOC_Os07g11020 and LOC_Os07g11520 indexed by a nonsynonymous SNP mutation on exon 5 of a bHLH transcription factor was found to elevate the proportion of amylose at the expense of reduced short-chain amylopectin. Linking starch structure with starch digestibility by determining the kinetics of cooked grain amylolysis of selected haplotypes revealed strong association of starch structure with estimated digestibility kinetics. Combining all results from grain quality genomics, systems genetics, and digestibility phenotyping, we propose target haplotypes for fine-tuning starch structure in rice through marker-assisted breeding that can be used to alter the digestibility of rice grain, thus offering rice consumers a new diet-based intervention to mitigate the impact of nutrition-related noncommunicable diseases. PMID:27881726

A reduced number of mtSNPs saturates mitochondrial DNA haplotype diversity of worldwide population groups.

PubMed

Salas, Antonio; Amigo, Jorge

2010-05-03

The high levels of variation characterising the mitochondrial DNA (mtDNA) molecule are due ultimately to its high average mutation rate; moreover, mtDNA variation is deeply structured in different populations and ethnic groups. There is growing interest in selecting a reduced number of mtDNA single nucleotide polymorphisms (mtSNPs) that account for the maximum level of discrimination power in a given population. Applications of the selected mtSNP panel range from anthropologic and medical studies to forensic genetic casework. This study proposes a new simulation-based method that explores the ability of different mtSNP panels to yield the maximum levels of discrimination power. The method explores subsets of mtSNPs of different sizes randomly chosen from a preselected panel of mtSNPs based on frequency. More than 2,000 complete genomes representing three main continental human population groups (Africa, Europe, and Asia) and two admixed populations ("African-Americans" and "Hispanics") were collected from GenBank and the literature, and were used as training sets. Haplotype diversity was measured for each combination of mtSNP and compared with existing mtSNP panels available in the literature. The data indicates that only a reduced number of mtSNPs ranging from six to 22 are needed to account for 95% of the maximum haplotype diversity of a given population sample. However, only a small proportion of the best mtSNPs are shared between populations, indicating that there is not a perfect set of "universal" mtSNPs suitable for all population contexts. The discrimination power provided by these mtSNPs is much higher than the power of the mtSNP panels proposed in the literature to date. Some mtSNP combinations also yield high diversity values in admixed populations. The proposed computational approach for exploring combinations of mtSNPs that optimise the discrimination power of a given set of mtSNPs is more efficient than previous empirical approaches. In contrast to precedent findings, the results seem to indicate that only few mtSNPs are needed to reach high levels of discrimination power in a population, independently of its ancestral background.

A Reduced Number of mtSNPs Saturates Mitochondrial DNA Haplotype Diversity of Worldwide Population Groups

PubMed Central

Salas, Antonio; Amigo, Jorge

2010-01-01

Background The high levels of variation characterising the mitochondrial DNA (mtDNA) molecule are due ultimately to its high average mutation rate; moreover, mtDNA variation is deeply structured in different populations and ethnic groups. There is growing interest in selecting a reduced number of mtDNA single nucleotide polymorphisms (mtSNPs) that account for the maximum level of discrimination power in a given population. Applications of the selected mtSNP panel range from anthropologic and medical studies to forensic genetic casework. Methodology/Principal Findings This study proposes a new simulation-based method that explores the ability of different mtSNP panels to yield the maximum levels of discrimination power. The method explores subsets of mtSNPs of different sizes randomly chosen from a preselected panel of mtSNPs based on frequency. More than 2,000 complete genomes representing three main continental human population groups (Africa, Europe, and Asia) and two admixed populations (“African-Americans” and “Hispanics”) were collected from GenBank and the literature, and were used as training sets. Haplotype diversity was measured for each combination of mtSNP and compared with existing mtSNP panels available in the literature. The data indicates that only a reduced number of mtSNPs ranging from six to 22 are needed to account for 95% of the maximum haplotype diversity of a given population sample. However, only a small proportion of the best mtSNPs are shared between populations, indicating that there is not a perfect set of “universal” mtSNPs suitable for all population contexts. The discrimination power provided by these mtSNPs is much higher than the power of the mtSNP panels proposed in the literature to date. Some mtSNP combinations also yield high diversity values in admixed populations. Conclusions/Significance The proposed computational approach for exploring combinations of mtSNPs that optimise the discrimination power of a given set of mtSNPs is more efficient than previous empirical approaches. In contrast to precedent findings, the results seem to indicate that only few mtSNPs are needed to reach high levels of discrimination power in a population, independently of its ancestral background. PMID:20454657

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks.

PubMed

Guo, Liyuan; Wang, Jing

2018-01-04

Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks

PubMed Central

2018-01-01

Abstract Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element–target gene pairs (E–G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. PMID:29140525

Development and implementation of a highly-multiplexed SNP array for genetic mapping in maritime pine and comparative mapping with loblolly pine

PubMed Central

2011-01-01

Background Single nucleotide polymorphisms (SNPs) are the most abundant source of genetic variation among individuals of a species. New genotyping technologies allow examining hundreds to thousands of SNPs in a single reaction for a wide range of applications such as genetic diversity analysis, linkage mapping, fine QTL mapping, association studies, marker-assisted or genome-wide selection. In this paper, we evaluated the potential of highly-multiplexed SNP genotyping for genetic mapping in maritime pine (Pinus pinaster Ait.), the main conifer used for commercial plantation in southwestern Europe. Results We designed a custom GoldenGate assay for 1,536 SNPs detected through the resequencing of gene fragments (707 in vitro SNPs/Indels) and from Sanger-derived Expressed Sequenced Tags assembled into a unigene set (829 in silico SNPs/Indels). Offspring from three-generation outbred (G2) and inbred (F2) pedigrees were genotyped. The success rate of the assay was 63.6% and 74.8% for in silico and in vitro SNPs, respectively. A genotyping error rate of 0.4% was further estimated from segregating data of SNPs belonging to the same gene. Overall, 394 SNPs were available for mapping. A total of 287 SNPs were integrated with previously mapped markers in the G2 parental maps, while 179 SNPs were localized on the map generated from the analysis of the F2 progeny. Based on 98 markers segregating in both pedigrees, we were able to generate a consensus map comprising 357 SNPs from 292 different loci. Finally, the analysis of sequence homology between mapped markers and their orthologs in a Pinus taeda linkage map, made it possible to align the 12 linkage groups of both species. Conclusions Our results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in maritime pine, a conifer species that has a genome seven times the size of the human genome. This SNP-array will be extended thanks to recent sequencing effort using new generation sequencing technologies and will include SNPs from comparative orthologous sequences that were identified in the present study, providing a wider collection of anchor points for comparative genomics among the conifers. PMID:21767361

Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies

PubMed Central

Zhang, Yu; Liu, Jun S.

2011-01-01

Genome-wide association studies commonly involve simultaneous tests of millions of single nucleotide polymorphisms (SNP) for disease association. The SNPs in nearby genomic regions, however, are often highly correlated due to linkage disequilibrium (LD, a genetic term for correlation). Simple Bonferonni correction for multiple comparisons is therefore too conservative. Permutation tests, which are often employed in practice, are both computationally expensive for genome-wide studies and limited in their scopes. We present an accurate and computationally efficient method, based on Poisson de-clumping heuristics, for approximating genome-wide significance of SNP associations. Compared with permutation tests and other multiple comparison adjustment approaches, our method computes the most accurate and robust p-value adjustments for millions of correlated comparisons within seconds. We demonstrate analytically that the accuracy and the efficiency of our method are nearly independent of the sample size, the number of SNPs, and the scale of p-values to be adjusted. In addition, our method can be easily adopted to estimate false discovery rate. When applied to genome-wide SNP datasets, we observed highly variable p-value adjustment results evaluated from different genomic regions. The variation in adjustments along the genome, however, are well conserved between the European and the African populations. The p-value adjustments are significantly correlated with LD among SNPs, recombination rates, and SNP densities. Given the large variability of sequence features in the genome, we further discuss a novel approach of using SNP-specific (local) thresholds to detect genome-wide significant associations. This article has supplementary material online. PMID:22140288

A self-assembled deoxyribonucleic acid concatemer for sensitive detection of single nucleotide polymorphism.

PubMed

Wu, Wei; Chen, Junhua; Fang, Zhiyuan; Ge, Chenchen; Xiang, Zhicheng; Ouyang, Chuanyan; Lie, Puchang; Xiao, Zhuo; Yu, Luxin; Wang, Lin; Zeng, Lingwen

2013-12-04

Polymerase-free and label-free strategies for DNA detection have shown excellent sensitivity and specificity in various biological samples. Herein, we propose a method for single nucleotide polymorphism (SNP) detection by using self-assembled DNA concatemers. Capture probes, bound to magnetic beads, can joint mediator probes by T4 DNA ligase in the presence of target DNA that is complementary to the capture probe and mediator probe. The mediator probes trigger self-assembly of two auxiliary probes on magnetic beads to form DNA concatemers. Separated by a magnetic rack, the double-stranded concatemers on beads can recruit a great amount of SYBR Green I and eventually result in amplified fluorescent signals. In comparison with reported methods for SNP detection, the concatemer-based approach has significant advantages of low background, simplicity, and ultrasensitivity, making it as a convenient platform for clinical applications. As a proof of concept, BRAF(T1799A) oncogene mutation, a SNP involved in diverse human cancers, was used as a model target. The developed approach using a fluorescent intercalator can detect as low as 0.1 fM target BRAF(T1799A) DNA, which is better than those previously published methods for SNP detection. This method is robust and can be used directly to measure the BRAF(T1799A) DNA in complex human serum with excellent recovery (94-103%). It is expected that this assay principle can be directed toward other SNP genes by simply changing the mediator probe and auxiliary probes. Copyright © 2013 Elsevier B.V. All rights reserved.

Oligonucleotide-arrayed TFT photosensor applicable for DNA chip technology.

PubMed

Tanaka, Tsuyoshi; Hatakeyama, Keiichi; Sawaguchi, Masahiro; Iwadate, Akihito; Mizutani, Yasushi; Sasaki, Kazuhiro; Tateishi, Naofumi; Takeyama, Haruko; Matsunaga, Tadashi

2006-09-05

A thin film transistor (TFT) photosensor fabricated by semiconductor integrated circuit (IC) technology was applied to DNA chip technology. The surface of the TFT photosensor was coated with TiO2 using a vapor deposition technique for the fabrication of optical filters. The immobilization of thiolated oligonucleotide probes onto a TiO2-coated TFT photosensor using gamma-aminopropyltriethoxysilane (APTES) and N-(gamma-maleimidobutyloxy) sulfosuccinimide ester (GMBS) was optimized. The coverage value of immobilized oligonucleotides reached a plateau at 33.7 pmol/cm2, which was similar to a previous analysis using radioisotope-labeled oligonucleotides. The lowest detection limits were 0.05 pmol/cm2 for quantum dot and 2.1 pmol/cm2 for Alexa Fluor 350. Furthermore, single nucleotide polymorphism (SNP) detection was examined using the oligonucleotide-arrayed TFT photosensor. A SNP present in the aldehyde dehydrogenase 2 (ALDH2) gene was used as a target. The SNPs in ALDH2*1 and ALDH2*2 target DNA were detected successfully using the TFT photosensor. DNA hybridization in the presence of both ALDH2*1 and ALDH2*2 target DNA was observed using both ALDH2*1 and ALDH2*2 detection oligonucleotides-arrayed TFT photosensor. Use of the TFT photosensor will allow the development of a disposable photodetecting device for DNA chip systems. (c) 2006 Wiley Periodicals, Inc.

Genome-wide SNP scan in a porcine Large White×Minzhu intercross population reveals a locus influencing muscle mass on chromosome 2.

PubMed

Liu, Xin; Wang, Li Gang; Luo, Wei Zhen; Li, Yong; Liang, Jing; Yan, Hua; Zhao, Ke Bin; Wang, Li Xian; Zhang, Long Chao

2014-12-01

A high-density single nucleotide polymorphism (SNP) array containing 62 163 markers was employed for a genome-wide association study (GWAS) to identify variants associated with lean meat in ham (LMH, %) and lean meat percentage (LMP, %) within a porcine Large White×Minzhu intercross population. For each individual, LMH and LMP were measured after slaughter at the age of 240±7 days. A total of 557 F2 animals were genotyped. The GWAS revealed that 21 SNPs showed significant genome-wide or chromosome-wide associations with LMH and LMP by the Genome-wide Rapid Association using Mixed Model and Regression-Genomic Control approach. Nineteen significant genome-wide SNPs were mapped to the distal end of Sus Scrofa Chromosome (SSC) 2, where a major known gene responsible for muscle mass, IGF2 is located. A conditioned analysis, in which the genotype of the strongest associated SNP is included as a fixed effect in the model, showed that those significant SNPs on SSC2 were derived from a single quantitative trait locus. The two chromosome-wide association SNPs on SSC1 disappeared after conditioned analysis suggested the association signal is a false association derived from using a F2 population. The present result is expected to lead to novel insights into muscle mass in different pig breeds and lays a preliminary foundation for follow-up studies for identification of causal mutations for subsequent application in marker-assisted selection programs for improving muscle mass in pigs. © 2014 Japanese Society of Animal Science.

DNA abasic site-directed formation of fluorescent silver nanoclusters for selective nucleobase recognition

NASA Astrophysics Data System (ADS)

Ma, Kun; Cui, Qinghua; Liu, Guiying; Wu, Fei; Xu, Shujuan; Shao, Yong

2011-07-01

DNA single-nucleotide polymorphism (SNP) detection has attracted much attention due to mutation related diseases. Various methods for SNP detection have been proposed and many are already in use. Here, we find that the abasic site (AP site) in the DNA duplex can be developed as a capping scaffold for the generation of fluorescent silver nanoclusters (Ag NCs). As a proof of concept, the DNA sequences from fragments near codon 177 of cancer supression gene p53 were used as a model for SNP detection by in situ formed Ag NCs. The formation of fluorescent Ag NCs in the AP site-containing DNA duplex is highly selective for cytosine facing the AP site and guanines flanking the site and can be employed in situ as readout for SNP detection. The fluorescent signal-on sensing for SNP based on this inorganic fluorophore is substantially advantageous over the previously reported signal-off responses using low-molecular-weight organic ligands. The strong dependence of fluorescent Ag NC formation on the sequences surrounding the AP site was successfully used to identify mutations in codon 177 of cancer supression gene p53. We anticipate that this approach will be employed to develop a practical SNP detection method by locating an AP site toward the midway cytosine in a target strand containing more than three consecutive cytosines.

The use of population-scale sequencing to identify CNVs impacting productive traits in different cattle breeds

USDA-ARS?s Scientific Manuscript database

Individualized copy number variation (CNV) maps have highlighted the need for population surveys of cattle to detect rare and common variants. While SNP and comparative genomic hybridization (CGH) arrays have provided preliminary data, next-generation sequence (NGS) data analysis offers an increased...

CIDR

Science.gov Websites

variety of arrays appropriate for a wide breadth of study design needs. Genomic coverage of many of the chromosomal anomalies are services offered at NO ADDITIONAL COST to study investigators with GWAS projects be submitted for both the initial GWAS study as well as replication using our custom SNP service

Evaluation of SNP Data from the Malus Infinium Array Identifies Challenges for Genetic Analysis of Complex Genomes of Polyploid Origin

PubMed Central

Troggio, Michela; Šurbanovski, Nada; Bianco, Luca; Moretto, Marco; Giongo, Lara; Banchi, Elisa; Viola, Roberto; Fernández, Felicdad Fernández; Costa, Fabrizio; Velasco, Riccardo; Cestaro, Alessandro; Sargent, Daniel James

2013-01-01

High throughput arrays for the simultaneous genotyping of thousands of single-nucleotide polymorphisms (SNPs) have made the rapid genetic characterisation of plant genomes and the development of saturated linkage maps a realistic prospect for many plant species of agronomic importance. However, the correct calling of SNP genotypes in divergent polyploid genomes using array technology can be problematic due to paralogy, and to divergence in probe sequences causing changes in probe binding efficiencies. An Illumina Infinium II whole-genome genotyping array was recently developed for the cultivated apple and used to develop a molecular linkage map for an apple rootstock progeny (M432), but a large proportion of segregating SNPs were not mapped in the progeny, due to unexpected genotype clustering patterns. To investigate the causes of this unexpected clustering we performed BLAST analysis of all probe sequences against the ‘Golden Delicious’ genome sequence and discovered evidence for paralogous annealing sites and probe sequence divergence for a high proportion of probes contained on the array. Following visual re-evaluation of the genotyping data generated for 8,788 SNPs for the M432 progeny using the array, we manually re-scored genotypes at 818 loci and mapped a further 797 markers to the M432 linkage map. The newly mapped markers included the majority of those that could not be mapped previously, as well as loci that were previously scored as monomorphic, but which segregated due to divergence leading to heterozygosity in probe annealing sites. An evaluation of the 8,788 probes in a diverse collection of Malus germplasm showed that more than half the probes returned genotype clustering patterns that were difficult or impossible to interpret reliably, highlighting implications for the use of the array in genome-wide association studies. PMID:23826289

Genome-Wide Association of Stem Water Soluble Carbohydrates in Bread Wheat.

PubMed

Dong, Yan; Liu, Jindong; Zhang, Yan; Geng, Hongwei; Rasheed, Awais; Xiao, Yonggui; Cao, Shuanghe; Fu, Luping; Yan, Jun; Wen, Weie; Zhang, Yong; Jing, Ruilian; Xia, Xianchun; He, Zhonghu

2016-01-01

Water soluble carbohydrates (WSC) in stems play an important role in buffering grain yield in wheat against biotic and abiotic stresses; however, knowledge of genes controlling WSC is very limited. We conducted a genome-wide association study (GWAS) using a high-density 90K SNP array to better understand the genetic basis underlying WSC, and to explore marker-based breeding approaches. WSC was evaluated in an association panel comprising 166 Chinese bread wheat cultivars planted in four environments. Fifty two marker-trait associations (MTAs) distributed across 23 loci were identified for phenotypic best linear unbiased estimates (BLUEs), and 11 MTAs were identified in two or more environments. Liner regression showed a clear dependence of WSC BLUE scores on numbers of favorable (increasing WSC content) and unfavorable alleles (decreasing WSC), indicating that genotypes with higher numbers of favorable or lower numbers of unfavorable alleles had higher WSC content. In silico analysis of flanking sequences of trait-associated SNPs revealed eight candidate genes related to WSC content grouped into two categories based on the type of encoding proteins, namely, defense response proteins and proteins triggered by environmental stresses. The identified SNPs and candidate genes related to WSC provide opportunities for breeding higher WSC wheat cultivars.

LS-CAP: an algorithm for identifying cytogenetic aberrations in hepatocellular carcinoma using microarray data.

PubMed

He, Xianmin; Wei, Qing; Sun, Meiqian; Fu, Xuping; Fan, Sichang; Li, Yao

2006-05-01

Biological techniques such as Array-Comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH) and affymetrix single nucleotide pleomorphism (SNP) array have been used to detect cytogenetic aberrations. However, on genomic scale, these techniques are labor intensive and time consuming. Comparative genomic microarray analysis (CGMA) has been used to identify cytogenetic changes in hepatocellular carcinoma (HCC) using gene expression microarray data. However, CGMA algorithm can not give precise localization of aberrations, fails to identify small cytogenetic changes, and exhibits false negatives and positives. Locally un-weighted smoothing cytogenetic aberrations prediction (LS-CAP) based on local smoothing and binomial distribution can be expected to address these problems. LS-CAP algorithm was built and used on HCC microarray profiles. Eighteen cytogenetic abnormalities were identified, among them 5 were reported previously, and 12 were proven by CGH studies. LS-CAP effectively reduced the false negatives and positives, and precisely located small fragments with cytogenetic aberrations.

High-throughput SNP genotyping in the highly heterozygous genome of Eucalyptus: assay success, polymorphism and transferability across species

PubMed Central

2011-01-01

Background High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes. When nucleotide diversity is high, a refined diagnosis of the target SNP sequence context is needed to convert queried SNPs into high-quality genotypes using the Golden Gate Genotyping Technology (GGGT). This issue becomes exacerbated when attempting to transfer SNPs across species, a scarcely explored topic in plants, and likely to become significant for population genomics and inter specific breeding applications in less domesticated and less funded plant genera. Results We have successfully developed the first set of 768 SNPs assayed by the GGGT for the highly heterozygous genome of Eucalyptus from a mixed Sanger/454 database with 1,164,695 ESTs and the preliminary 4.5X draft genome sequence for E. grandis. A systematic assessment of in silico SNP filtering requirements showed that stringent constraints on the SNP surrounding sequences have a significant impact on SNP genotyping performance and polymorphism. SNP assay success was high for the 288 SNPs selected with more rigorous in silico constraints; 93% of them provided high quality genotype calls and 71% of them were polymorphic in a diverse panel of 96 individuals of five different species. SNP reliability was high across nine Eucalyptus species belonging to three sections within subgenus Symphomyrtus and still satisfactory across species of two additional subgenera, although polymorphism declined as phylogenetic distance increased. Conclusions This study indicates that the GGGT performs well both within and across species of Eucalyptus notwithstanding its nucleotide diversity ≥2%. The development of a much larger array of informative SNPs across multiple Eucalyptus species is feasible, although strongly dependent on having a representative and sufficiently deep collection of sequences from many individuals of each target species. A higher density SNP platform will be instrumental to undertake genome-wide phylogenetic and population genomics studies and to implement molecular breeding by Genomic Selection in Eucalyptus. PMID:21492434

Combined Targeted DNA Sequencing in Non-Small Cell Lung Cancer (NSCLC) Using UNCseq and NGScopy, and RNA Sequencing Using UNCqeR for the Detection of Genetic Aberrations in NSCLC

PubMed Central

Walter, Vonn; Patel, Nirali M.; Eberhard, David A.; Hayward, Michele C.; Salazar, Ashley H.; Jo, Heejoon; Soloway, Matthew G.; Wilkerson, Matthew D.; Parker, Joel S.; Yin, Xiaoying; Zhang, Guosheng; Siegel, Marni B.; Rosson, Gary B.; Earp, H. Shelton; Sharpless, Norman E.; Gulley, Margaret L.; Weck, Karen E.

2015-01-01

The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07–0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11–1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion. PMID:26076459

Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars.

PubMed

Cavanagh, Colin R; Chao, Shiaoman; Wang, Shichen; Huang, Bevan Emma; Stephen, Stuart; Kiani, Seifollah; Forrest, Kerrie; Saintenac, Cyrille; Brown-Guedira, Gina L; Akhunova, Alina; See, Deven; Bai, Guihua; Pumphrey, Michael; Tomar, Luxmi; Wong, Debbie; Kong, Stephan; Reynolds, Matthew; da Silva, Marta Lopez; Bockelman, Harold; Talbert, Luther; Anderson, James A; Dreisigacker, Susanne; Baenziger, Stephen; Carter, Arron; Korzun, Viktor; Morrell, Peter Laurent; Dubcovsky, Jorge; Morell, Matthew K; Sorrells, Mark E; Hayden, Matthew J; Akhunov, Eduard

2013-05-14

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat.

Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars

PubMed Central

Cavanagh, Colin R.; Chao, Shiaoman; Wang, Shichen; Huang, Bevan Emma; Stephen, Stuart; Kiani, Seifollah; Forrest, Kerrie; Saintenac, Cyrille; Brown-Guedira, Gina L.; Akhunova, Alina; See, Deven; Bai, Guihua; Pumphrey, Michael; Tomar, Luxmi; Wong, Debbie; Kong, Stephan; Reynolds, Matthew; da Silva, Marta Lopez; Bockelman, Harold; Talbert, Luther; Anderson, James A.; Dreisigacker, Susanne; Baenziger, Stephen; Carter, Arron; Korzun, Viktor; Morrell, Peter Laurent; Dubcovsky, Jorge; Morell, Matthew K.; Sorrells, Mark E.; Hayden, Matthew J.; Akhunov, Eduard

2013-01-01

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat. PMID:23630259

Association of single-nucleotide polymorphisms of the tau gene with late-onset Parkinson disease.

PubMed

Martin, E R; Scott, W K; Nance, M A; Watts, R L; Hubble, J P; Koller, W C; Lyons, K; Pahwa, R; Stern, M B; Colcher, A; Hiner, B C; Jankovic, J; Ondo, W G; Allen, F H; Goetz, C G; Small, G W; Masterman, D; Mastaglia, F; Laing, N G; Stajich, J M; Ribble, R C; Booze, M W; Rogala, A; Hauser, M A; Zhang, F; Gibson, R A; Middleton, L T; Roses, A D; Haines, J L; Scott, B L; Pericak-Vance, M A; Vance, J M

2001-11-14

The human tau gene, which promotes assembly of neuronal microtubules, has been associated with several rare neurologic diseases that clinically include parkinsonian features. We recently observed linkage in idiopathic Parkinson disease (PD) to a region on chromosome 17q21 that contains the tau gene. These factors make tau a good candidate for investigation as a susceptibility gene for idiopathic PD, the most common form of the disease. To investigate whether the tau gene is involved in idiopathic PD. Among a sample of 1056 individuals from 235 families selected from 13 clinical centers in the United States and Australia and from a family ascertainment core center, we tested 5 single-nucleotide polymorphisms (SNPs) within the tau gene for association with PD, using family-based tests of association. Both affected (n = 426) and unaffected (n = 579) family members were included; 51 individuals had unclear PD status. Analyses were conducted to test individual SNPs and SNP haplotypes within the tau gene. Family-based tests of association, calculated using asymptotic distributions. Analysis of association between the SNPs and PD yielded significant evidence of association for 3 of the 5 SNPs tested: SNP 3, P =.03; SNP 9i, P =.04; and SNP 11, P =.04. The 2 other SNPs did not show evidence of significant association (SNP 9ii, P =.11, and SNP 9iii, P =.87). Strong evidence of association was found with haplotype analysis, with a positive association with one haplotype (P =.009) and a negative association with another haplotype (P =.007). Substantial linkage disequilibrium (P<.001) was detected between 4 of the 5 SNPs (SNPs 3, 9i, 9ii, and 11). This integrated approach of genetic linkage and positional association analyses implicates tau as a susceptibility gene for idiopathic PD.

A Bayesian antedependence model for whole genome prediction.

PubMed

Yang, Wenzhao; Tempelman, Robert J

2012-04-01

Hierarchical mixed effects models have been demonstrated to be powerful for predicting genomic merit of livestock and plants, on the basis of high-density single-nucleotide polymorphism (SNP) marker panels, and their use is being increasingly advocated for genomic predictions in human health. Two particularly popular approaches, labeled BayesA and BayesB, are based on specifying all SNP-associated effects to be independent of each other. BayesB extends BayesA by allowing a large proportion of SNP markers to be associated with null effects. We further extend these two models to specify SNP effects as being spatially correlated due to the chromosomally proximal effects of causal variants. These two models, that we respectively dub as ante-BayesA and ante-BayesB, are based on a first-order nonstationary antedependence specification between SNP effects. In a simulation study involving 20 replicate data sets, each analyzed at six different SNP marker densities with average LD levels ranging from r(2) = 0.15 to 0.31, the antedependence methods had significantly (P < 0.01) higher accuracies than their corresponding classical counterparts at higher LD levels (r(2) > 0. 24) with differences exceeding 3%. A cross-validation study was also conducted on the heterogeneous stock mice data resource (http://mus.well.ox.ac.uk/mouse/HS/) using 6-week body weights as the phenotype. The antedependence methods increased cross-validation prediction accuracies by up to 3.6% compared to their classical counterparts (P < 0.001). Finally, we applied our method to other benchmark data sets and demonstrated that the antedependence methods were more accurate than their classical counterparts for genomic predictions, even for individuals several generations beyond the training data.

ARTS: a web-based tool for the set-up of high-throughput genome-wide mapping panels for the SNP genotyping of mouse mutants.

PubMed

Klaften, Matthias; Hrabé de Angelis, Martin

2005-07-01

Genome-wide mapping in the identification of novel candidate genes has always been the standard method in genetics and genomics to correlate a clinically interesting phenotypic trait with a genotype. However, the performance of a mapping experiment using classical microsatellite approaches can be very time consuming. The high-throughput analysis of single-nucleotide polymorphisms (SNPs) has the potential of being the successor of microsatellite analysis routinely used for these mapping approaches, where one of the major obstacles is the design of the appropriate SNP marker set itself. Here we report on ARTS, an advanced retrieval tool for SNPs, which allows researchers to comb freely the public mouse dbSNP database for multiple reference and test strains. Several filters can be applied in order to improve the sensitivity and the specificity of the search results. By employing the panel generator function of this program, it is possible to abbreviate the extraction of reliable sequence data for a large marker panel including several different mouse strains from days to minutes. The concept of ARTS is easily adaptable to other species for which SNP databases are available, making it a versatile tool for the use of SNPs as markers for genotyping. The web interface is accessible at http://andromeda.gsf.de/arts.

Genomic analyses of tropical beef cattle fertility based on genotyping pools of Brahman cows with unknown pedigree.

PubMed

Reverter, A; Porto-Neto, L R; Fortes, M R S; McCulloch, R; Lyons, R E; Moore, S; Nicol, D; Henshall, J; Lehnert, S A

2016-10-01

We introduce an innovative approach to lowering the overall cost of obtaining genomic EBV (GEBV) and encourage their use in commercial extensive herds of Brahman beef cattle. In our approach, the DNA genotyping of cow herds from 2 independent properties was performed using a high-density bovine SNP chip on DNA from pooled blood samples, grouped according to the result of a pregnancy test following their first and second joining opportunities. For the DNA pooling strategy, 15 to 28 blood samples from the same phenotype and contemporary group were allocated to pools. Across the 2 properties, a total of 183 pools were created representing 4,164 cows. In addition, blood samples from 309 bulls from the same properties were also taken. After genotyping and quality control, 74,584 remaining SNP were used for analyses. Pools and individual DNA samples were related by means of a "hybrid" genomic relationship matrix. The pooled genotyping analysis of 2 large and independent commercial populations of tropical beef cattle was able to recover significant and plausible associations between SNP and pregnancy test outcome. We discuss 24 SNP with significant association ( < 1.0 × 10) and mapped within 40 kb of an annotated gene. We have established a method to estimate the GEBV in young herd bulls for a trait that is currently unable to be predicted at all. In summary, our novel approach allowed us to conduct genomic analyses of fertility in 2 large commercial Brahman herds managed under extensive pastoral conditions.

Association of Long Runs of Homozygosity With Alzheimer Disease Among African American Individuals

PubMed Central

Ghani, Mahdi; Reitz, Christiane; Cheng, Rong; Vardarajan, Badri Narayan; Jun, Gyungah; Sato, Christine; Naj, Adam; Rajbhandary, Ruchita; Wang, Li-San; Valladares, Otto; Lin, Chiao-Feng; Larson, Eric B.; Graff-Radford, Neill R.; Evans, Denis; De Jager, Philip L.; Crane, Paul K.; Buxbaum, Joseph D.; Murrell, Jill R.; Raj, Towfique; Ertekin-Taner, Nilufer; Logue, Mark; Baldwin, Clinton T.; Green, Robert C.; Barnes, Lisa L.; Cantwell, Laura B.; Fallin, M. Daniele; Go, Rodney C. P.; Griffith, Patrick A.; Obisesan, Thomas O.; Manly, Jennifer J.; Lunetta, Kathryn L.; Kamboh, M. Ilyas; Lopez, Oscar L.; Bennett, David A.; Hendrie, Hugh; Hall, Kathleen S.; Goate, Alison M.; Byrd, Goldie S.; Kukull, Walter A.; Foroud, Tatiana M.; Haines, Jonathan L.; Farrer, Lindsay A.; Pericak-Vance, Margaret A.; Lee, Joseph H.; Schellenberg, Gerard D.; St. George-Hyslop, Peter; Mayeux, Richard; Rogaeva, Ekaterina

2015-01-01

IMPORTANCE Mutations in known causal Alzheimer disease (AD) genes account for only 1% to 3% of patients and almost all are dominantly inherited. Recessive inheritance of complex phenotypes can be linked to long (>1-megabase [Mb]) runs of homozygosity (ROHs) detectable by single-nucleotide polymorphism (SNP) arrays. OBJECTIVE To evaluate the association between ROHs and AD in an African American population known to have a risk for AD up to 3 times higher than white individuals. DESIGN, SETTING, AND PARTICIPANTS Case-control study of a large African American data set previously genotyped on different genome-wide SNP arrays conducted from December 2013 to January 2015. Global and locus-based ROH measurements were analyzed using raw or imputed genotype data. We studied the raw genotypes from 2 case-control subsets grouped based on SNP array: Alzheimer’s Disease Genetics Consortium data set (871 cases and 1620 control individuals) and Chicago Health and Aging Project–Indianapolis Ibadan Dementia Study data set (279 cases and 1367 control individuals). We then examined the entire data set using imputed genotypes from 1917 cases and 3858 control individuals. MAIN OUTCOMES AND MEASURES The ROHs larger than 1 Mb, 2 Mb, or 3 Mb were investigated separately for global burden evaluation, consensus regions, and gene-based analyses. RESULTS The African American cohort had a low degree of inbreeding (F ~ 0.006). In the Alzheimer’s Disease Genetics Consortium data set, we detected a significantly higher proportion of cases with ROHs greater than 2 Mb (P = .004) or greater than 3 Mb (P = .02), as well as a significant 114-kilobase consensus region on chr4q31.3 (empirical P value 2 = .04; ROHs >2 Mb). In the Chicago Health and Aging Project–Indianapolis Ibadan Dementia Study data set, we identified a significant 202-kilobase consensus region on Chr15q24.1 (empirical P value 2 = .02; ROHs >1 Mb) and a cluster of 13 significant genes on Chr3p21.31 (empirical P value 2 = .03; ROHs >3 Mb). A total of 43 of 49 nominally significant genes common for both data sets also mapped to Chr3p21.31. Analyses of imputed SNP data from the entire data set confirmed the association of AD with global ROH measurements (12.38 ROHs >1 Mb in cases vs 12.11 in controls; 2.986 Mb average size of ROHs >2 Mb in cases vs 2.889 Mb in controls; and 22% of cases with ROHs >3 Mb vs 19% of controls) and a gene-cluster on Chr3p21.31 (empirical P value 2 = .006-.04; ROHs >3 Mb). Also, we detected a significant association between AD and CLDN17 (empirical P value 2 = .01; ROHs >1 Mb), encoding a protein from the Claudin family, members of which were previously suggested as AD biomarkers. CONCLUSIONS AND RELEVANCE To our knowledge, we discovered the first evidence of increased burden of ROHs among patients with AD from an outbred African American population, which could reflect either the cumulative effect of multiple ROHs to AD or the contribution of specific loci harboring recessive mutations and risk haplotypes in a subset of patients. Sequencing is required to uncover AD variants in these individuals. PMID:26366463

Tin phosphide-based anodes for sodium-ion batteries: synthesis via solvothermal transformation of Sn metal and phase-dependent Na storage performance

PubMed Central

Shin, Hyun-Seop; Jung, Kyu-Nam; Jo, Yong Nam; Park, Min-Sik; Kim, Hansung; Lee, Jong-Won

2016-01-01

There is a great deal of current interest in the development of rechargeable sodium (Na)-ion batteries (SIBs) for low-cost, large-scale stationary energy storage systems. For the commercial success of this technology, significant progress should be made in developing robust anode (negative electrode) materials with high capacity and long cycle life. Sn-P compounds are considered promising anode materials that have considerable potential to meet the required performance of SIBs, and they have been typically prepared by high-energy mechanical milling. Here, we report Sn-P-based anodes synthesised through solvothermal transformation of Sn metal and their electrochemical Na storage properties. The temperature and time period used for solvothermal treatment play a crucial role in determining the phase, microstructure, and composition of the Sn-P compound and thus its electrochemical performance. The Sn-P compound prepared under an optimised solvothermal condition shows excellent electrochemical performance as an SIB anode, as evidenced by a high reversible capacity of ~560 mAh g−1 at a current density of 100 mA g−1 and cycling stability for 100 cycles. The solvothermal route provides an effective approach to synthesising Sn-P anodes with controlled phases and compositions, thus tailoring their Na storage behaviour. PMID:27189834

Proper joint analysis of summary association statistics requires the adjustment of heterogeneity in SNP coverage pattern.

PubMed

Zhang, Han; Wheeler, William; Song, Lei; Yu, Kai

2017-07-07

As meta-analysis results published by consortia of genome-wide association studies (GWASs) become increasingly available, many association summary statistics-based multi-locus tests have been developed to jointly evaluate multiple single-nucleotide polymorphisms (SNPs) to reveal novel genetic architectures of various complex traits. The validity of these approaches relies on the accurate estimate of z-score correlations at considered SNPs, which in turn requires knowledge on the set of SNPs assessed by each study participating in the meta-analysis. However, this exact SNP coverage information is usually unavailable from the meta-analysis results published by GWAS consortia. In the absence of the coverage information, researchers typically estimate the z-score correlations by making oversimplified coverage assumptions. We show through real studies that such a practice can generate highly inflated type I errors, and we demonstrate the proper way to incorporate correct coverage information into multi-locus analyses. We advocate that consortia should make SNP coverage information available when posting their meta-analysis results, and that investigators who develop analytic tools for joint analyses based on summary data should pay attention to the variation in SNP coverage and adjust for it appropriately. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

Assignment of Streptococcus agalactiae isolates to clonal complexes using a small set of single nucleotide polymorphisms.

PubMed

Honsa, Erin; Fricke, Thomas; Stephens, Alex J; Ko, Danny; Kong, Fanrong; Gilbert, Gwendolyn L; Huygens, Flavia; Giffard, Philip M

2008-08-19

Streptococcus agalactiae (Group B Streptococcus (GBS)) is an important human pathogen, particularly of newborns. Emerging evidence for a relationship between genotype and virulence has accentuated the need for efficient and well-defined typing methods. The objective of this study was to develop a single nucleotide polymorphism (SNP) based method for assigning GBS isolates to multilocus sequence typing (MLST)-defined clonal complexes. It was found that a SNP set derived from the MLST database on the basis of maximization of Simpsons Index of Diversity provided poor resolution and did not define groups concordant with the population structure as defined by eBURST analysis of the MLST database. This was interpreted as being a consequence of low diversity and high frequency horizontal gene transfer. Accordingly, a different approach to SNP identification was developed. This entailed use of the "Not-N" bioinformatic algorithm that identifies SNPs diagnostic for groups of known sequence variants, together with an empirical process of SNP testing. This yielded a four member SNP set that divides GBS into 10 groups that are concordant with the population structure. A fifth SNP was identified that increased the sensitivity for the clinically significant clonal complex 17 to 100%. Kinetic PCR methods for the interrogation of these SNPs were developed, and used to genotype 116 well characterized isolates. A five SNP method for dividing GBS into biologically valid groups has been developed. These SNPs are ideal for high throughput surveillance activities, and combining with more rapidly evolving loci when additional resolution is required.

Assignment of Streptococcus agalactiae isolates to clonal complexes using a small set of single nucleotide polymorphisms

PubMed Central

Honsa, Erin; Fricke, Thomas; Stephens, Alex J; Ko, Danny; Kong, Fanrong; Gilbert, Gwendolyn L; Huygens, Flavia; Giffard, Philip M

2008-01-01

Background Streptococcus agalactiae (Group B Streptococcus (GBS)) is an important human pathogen, particularly of newborns. Emerging evidence for a relationship between genotype and virulence has accentuated the need for efficient and well-defined typing methods. The objective of this study was to develop a single nucleotide polymorphism (SNP) based method for assigning GBS isolates to multilocus sequence typing (MLST)-defined clonal complexes. Results It was found that a SNP set derived from the MLST database on the basis of maximisation of Simpsons Index of Diversity provided poor resolution and did not define groups concordant with the population structure as defined by eBURST analysis of the MLST database. This was interpreted as being a consequence of low diversity and high frequency horizontal gene transfer. Accordingly, a different approach to SNP identification was developed. This entailed use of the "Not-N" bioinformatic algorithm that identifies SNPs diagnostic for groups of known sequence variants, together with an empirical process of SNP testing. This yielded a four member SNP set that divides GBS into 10 groups that are concordant with the population structure. A fifth SNP was identified that increased the sensitivity for the clinically significant clonal complex 17 to 100%. Kinetic PCR methods for the interrogation of these SNPs were developed, and used to genotype 116 well characterized isolates. Conclusion A five SNP method for dividing GBS into biologically valid groups has been developed. These SNPs are ideal for high throughput surveillance activities, and combining with more rapidly evolving loci when additional resolution is required. PMID:18710585

The genetic component of human longevity: New insights from the analysis of pathway-based SNP-SNP interactions.

PubMed

Dato, Serena; Soerensen, Mette; De Rango, Francesco; Rose, Giuseppina; Christensen, Kaare; Christiansen, Lene; Passarino, Giuseppe

2018-06-01

In human longevity studies, single nucleotide polymorphism (SNP) analysis identified a large number of genetic variants with small effects, yet not easily replicable in different populations. New insights may come from the combined analysis of different SNPs, especially when grouped by metabolic pathway. We applied this approach to study the joint effect on longevity of SNPs belonging to three candidate pathways, the insulin/insulin-like growth factor signalling (IIS), DNA repair and pro/antioxidant. We analysed data from 1,058 tagging SNPs in 140 genes, collected in 1825 subjects (1,089 unrelated nonagenarians from the Danish 1905 Birth Cohort Study and 736 Danish controls aged 46-55 years) for evaluating synergic interactions by SNPsyn. Synergies were further tested by the multidimensional reduction (MDR) approach, both intra- and interpathways. The best combinations (FDR<0.0001) resulted those encompassing IGF1R-rs12437963 and PTPN1-rs6067484, TP53-rs2078486 and ERCC2-rs50871, TXNRD1-rs17202060 and TP53-rs2078486, the latter two supporting a central role of TP53 in mediating the concerted activation of the DNA repair and pro-antioxidant pathways in human longevity. Results were consistently replicated with both approaches, as well as a significant effect on longevity was found for the GHSR gene, which also interacts with partners belonging to both IIS and DNA repair pathways (PAPPA, PTPN1, PARK7, MRE11A). The combination GHSR-MREA11, positively associated with longevity by MDR, was further found influencing longitudinal survival in nonagenarian females (p = .026). Results here presented highlight the validity of SNP-SNP interactions analyses for investigating the genetics of human longevity, confirming previously identified markers but also pointing to novel genes as central nodes of additional networks involved in human longevity. © 2018 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Parentage Reconstruction in Eucalyptus nitens Using SNPs and Microsatellite Markers: A Comparative Analysis of Marker Data Power and Robustness.

PubMed

Telfer, Emily J; Stovold, Grahame T; Li, Yongjun; Silva-Junior, Orzenil B; Grattapaglia, Dario G; Dungey, Heidi S

2015-01-01

Pedigree reconstruction using molecular markers enables efficient management of inbreeding in open-pollinated breeding strategies, replacing expensive and time-consuming controlled pollination. This is particularly useful in preferentially outcrossed, insect pollinated Eucalypts known to suffer considerable inbreeding depression from related matings. A single nucleotide polymorphism (SNP) marker panel consisting of 106 markers was selected for pedigree reconstruction from the recently developed high-density Eucalyptus Infinium SNP chip (EuCHIP60K). The performance of this SNP panel for pedigree reconstruction in open-pollinated progenies of two Eucalyptus nitens seed orchards was compared with that of two microsatellite panels with 13 and 16 markers respectively. The SNP marker panel out-performed one of the microsatellite panels in the resolution power to reconstruct pedigrees and out-performed both panels with respect to data quality. Parentage of all but one offspring in each clonal seed orchard was correctly matched to the expected seed parent using the SNP marker panel, whereas parentage assignment to less than a third of the expected seed parents were supported using the 13-microsatellite panel. The 16-microsatellite panel supported all but one of the recorded seed parents, one better than the SNP panel, although there was still a considerable level of missing and inconsistent data. SNP marker data was considerably superior to microsatellite data in accuracy, reproducibility and robustness. Although microsatellites and SNPs data provide equivalent resolution for pedigree reconstruction, microsatellite analysis requires more time and experience to deal with the uncertainties of allele calling and faces challenges for data transferability across labs and over time. While microsatellite analysis will continue to be useful for some breeding tasks due to the high information content, existing infrastructure and low operating costs, the multi-species SNP resource available with the EuCHIP60k, opens a whole new array of opportunities for high-throughput, genome-wide or targeted genotyping in species of Eucalyptus.

Microarray Technology for the Diagnosis of Fetal Chromosomal Aberrations: Which Platform Should We Use?

PubMed Central

Karampetsou, Evangelia; Morrogh, Deborah; Chitty, Lyn

2014-01-01

The advantage of microarray (array) over conventional karyotype for the diagnosis of fetal pathogenic chromosomal anomalies has prompted the use of microarrays in prenatal diagnostics. In this review we compare the performance of different array platforms (BAC, oligonucleotide CGH, SNP) and designs (targeted, whole genome, whole genome, and targeted, custom) and discuss their advantages and disadvantages in relation to prenatal testing. We also discuss the factors to consider when implementing a microarray testing service for the diagnosis of fetal chromosomal aberrations. PMID:26237396

Nested association mapping for dissecting complex traits using Peanut 58K SNP array

USDA-ARS?s Scientific Manuscript database

Genome-wide association studies (GWAS) and linkage mapping have been the two most predominant strategies to dissect complex traits, but are limited by the occurrence of false positives reported for GWAS, and low resolution in the case of linkage analysis. This has led to the development of a joint a...

Genome-wide association studies identify 25 genetic loci associated with resistance to Bacterial Cold Water Disease in rainbow trout

USDA-ARS?s Scientific Manuscript database

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonids aquaculture. In previous studies we have identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a high density SNP array and...

Design of a bovine low-density SNP array optimized for imputation

USDA-ARS?s Scientific Manuscript database

The Illumina BovineLD BeadChip was designed to support imputation to higher density genotypes in dairy and beef breeds by including single-nucleotide polymorphisms (SNPs) that had a high minor allele frequency as well as uniform spacing across the genome except at the ends of the chromosome where de...

Determination of Metastatic Potential in Breast Tumors by Global Molecular Characterization Using Multiple Modalities

DTIC Science & Technology

2010-10-01

5 Results ...to disease prognosis and in determining the course of treatment for the patient (2) . Breast cancer is a highly heterogeneous and complex disease...progression is a challenge. Introduction of high density single nucleotide polymorphism (SNP) genotyping arrays has helped not only for whole genome

Genome-wide associations for water-soluble carbohydrate concentration and relative maturity in wheat using SNP and DArT marker arrays

USDA-ARS?s Scientific Manuscript database

Improving water-use efficiency by incorporating drought avoidance traits into new wheat varieties is an important objective for wheat breeding in water-limited environments. This study uses genome wide association studies (GWAS) to identify candidate loci for water-soluble carbohydrate accumulation,...

Comparison of Constitutional and Replication Stress-Induced Genome Structural Variation by SNP Array and Mate-Pair Sequencing

PubMed Central

Arlt, Martin F.; Ozdemir, Alev Cagla; Birkeland, Shanda R.; Lyons, Robert H.; Glover, Thomas W.; Wilson, Thomas E.

2011-01-01

Copy-number variants (CNVs) are a major source of genetic variation in human health and disease. Previous studies have implicated replication stress as a causative factor in CNV formation. However, existing data are technically limited in the quality of comparisons that can be made between human CNVs and experimentally induced variants. Here, we used two high-resolution strategies—single nucleotide polymorphism (SNP) arrays and mate-pair sequencing—to compare CNVs that occur constitutionally to those that arise following aphidicolin-induced DNA replication stress in the same human cells. Although the optimized methods provided complementary information, sequencing was more sensitive to small variants and provided superior structural descriptions. The majority of constitutional and all aphidicolin-induced CNVs appear to be formed via homology-independent mechanisms, while aphidicolin-induced CNVs were of a larger median size than constitutional events even when mate-pair data were considered. Aphidicolin thus appears to stimulate formation of CNVs that closely resemble human pathogenic CNVs and the subset of larger nonhomologous constitutional CNVs. PMID:21212237

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.

PubMed

Eyre, Steve; Bowes, John; Diogo, Dorothée; Lee, Annette; Barton, Anne; Martin, Paul; Zhernakova, Alexandra; Stahl, Eli; Viatte, Sebastien; McAllister, Kate; Amos, Christopher I; Padyukov, Leonid; Toes, Rene E M; Huizinga, Tom W J; Wijmenga, Cisca; Trynka, Gosia; Franke, Lude; Westra, Harm-Jan; Alfredsson, Lars; Hu, Xinli; Sandor, Cynthia; de Bakker, Paul I W; Davila, Sonia; Khor, Chiea Chuen; Heng, Khai Koon; Andrews, Robert; Edkins, Sarah; Hunt, Sarah E; Langford, Cordelia; Symmons, Deborah; Concannon, Pat; Onengut-Gumuscu, Suna; Rich, Stephen S; Deloukas, Panos; Gonzalez-Gay, Miguel A; Rodriguez-Rodriguez, Luis; Ärlsetig, Lisbeth; Martin, Javier; Rantapää-Dahlqvist, Solbritt; Plenge, Robert M; Raychaudhuri, Soumya; Klareskog, Lars; Gregersen, Peter K; Worthington, Jane

2012-12-01

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

High density genetic mapping identifies new susceptibility loci for rheumatoid arthritis

PubMed Central

Eyre, Steve; Bowes, John; Diogo, Dorothée; Lee, Annette; Barton, Anne; Martin, Paul; Zhernakova, Alexandra; Stahl, Eli; Viatte, Sebastien; McAllister, Kate; Amos, Christopher I.; Padyukov, Leonid; Toes, Rene E.M.; Huizinga, Tom W.J.; Wijmenga, Cisca; Trynka, Gosia; Franke, Lude; Westra, Harm-Jan; Alfredsson, Lars; Hu, Xinli; Sandor, Cynthia; de Bakker, Paul I.W.; Davila, Sonia; Khor, Chiea Chuen; Heng, Khai Koon; Andrews, Robert; Edkins, Sarah; Hunt, Sarah E; Langford, Cordelia; Symmons, Deborah; Concannon, Pat; Onengut-Gumuscu, Suna; Rich, Stephen S; Deloukas, Panos; Gonzalez-Gay, Miguel A.; Rodriguez-Rodriguez, Luis; Ärlsetig, Lisbeth; Martin, Javier; Rantapää-Dahlqvist, Solbritt; Plenge, Robert; Raychaudhuri, Soumya; Klareskog, Lars; Gregersen, Peter K; Worthington, Jane

2012-01-01

Summary Using the Immunochip custom single nucleotide polymorphism (SNP) array, designed for dense genotyping of 186 genome wide association study (GWAS) confirmed loci we analysed 11,475 rheumatoid arthritis cases of European ancestry and 15,870 controls for 129,464 markers. The data were combined in meta-analysis with GWAS data from additional independent cases (n=2,363) and controls (n=17,872). We identified fourteen novel loci; nine were associated with rheumatoid arthritis overall and 5 specifically in anti-citrillunated peptide antibody positive disease, bringing the number of confirmed European ancestry rheumatoid arthritis loci to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at six loci and association to low frequency variants (minor allele frequency <0.05) at 4 loci. Bioinformatic analysis of the data generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations. PMID:23143596

Association Mapping of the High-Grade Myopia MYP3 Locus Reveals Novel Candidates UHRF1BP1L, PTPRR, and PPFIA2

PubMed Central

Hawthorne, Felicia; Feng, Sheng; Metlapally, Ravikanth; Li, Yi-Ju; Tran-Viet, Khanh-Nhat; Guggenheim, Jeremy A.; Malecaze, Francois; Calvas, Patrick; Rosenberg, Thomas; Mackey, David A.; Venturini, Cristina; Hysi, Pirro G.; Hammond, Christopher J.; Young, Terri L.

2013-01-01

Purpose. Myopia, or nearsightedness, is a common ocular genetic disease for which over 20 candidate genomic loci have been identified. The high-grade myopia locus, MYP3, has been reported on chromosome 12q21–23 by four independent linkage studies. Methods. We performed a genetic association study of the MYP3 locus in a family-based high-grade myopia cohort (n = 82) by genotyping 768 single-nucleotide polymorphisms (SNPs) within the linkage region. Qualitative testing for high-grade myopia (sphere ≤ −5 D affected, > −0.5 D unaffected) and quantitative testing on the average dioptric sphere were performed. Results. Several genetic markers were nominally significantly associated with high-grade myopia in qualitative testing, including rs3803036, a missense mutation in PTPRR (P = 9.1 × 10−4) and rs4764971, an intronic SNP in UHRF1BP1L (P = 6.1 × 10−4). Quantitative testing determined statistically significant SNPs rs4764971, also found by qualitative testing (P = 3.1 × 10−6); rs7134216, in the 3′ untranslated region (UTR) of DEPDC4 (P = 5.4 × 10−7); and rs17306116, an intronic SNP within PPFIA2 (P < 9 × 10−4). Independently conducted whole genome expression array analyses identified protein tyrosine phosphatase genes PTPRR and PPFIA2, which are in the same gene family, as differentially expressed in normal rapidly growing fetal relative to normal adult ocular tissue (confirmed by RT-qPCR). Conclusions. In an independent high-grade myopia cohort, an intronic SNP in UHRF1BP1L, rs4764971, was validated for quantitative association, and SNPs within PTPRR (quantitative) and PPFIA2 (qualitative and quantitative) approached significance. Three genes identified by our association study and supported by ocular expression and/or replication, UHRF1BP1L, PTPRR, and PPFIA2, are novel candidates for myopic development within the MYP3 locus that should be further studied. PMID:23422819

Small cell ovarian carcinoma: genomic stability and responsiveness to therapeutics.

PubMed

Gamwell, Lisa F; Gambaro, Karen; Merziotis, Maria; Crane, Colleen; Arcand, Suzanna L; Bourada, Valerie; Davis, Christopher; Squire, Jeremy A; Huntsman, David G; Tonin, Patricia N; Vanderhyden, Barbara C

2013-02-21

The biology of small cell ovarian carcinoma of the hypercalcemic type (SCCOHT), which is a rare and aggressive form of ovarian cancer, is poorly understood. Tumourigenicity, in vitro growth characteristics, genetic and genomic anomalies, and sensitivity to standard and novel chemotherapeutic treatments were investigated in the unique SCCOHT cell line, BIN-67, to provide further insight in the biology of this rare type of ovarian cancer. The tumourigenic potential of BIN-67 cells was determined and the tumours formed in a xenograft model was compared to human SCCOHT. DNA sequencing, spectral karyotyping and high density SNP array analysis was performed. The sensitivity of the BIN-67 cells to standard chemotherapeutic agents and to vesicular stomatitis virus (VSV) and the JX-594 vaccinia virus was tested. BIN-67 cells were capable of forming spheroids in hanging drop cultures. When xenografted into immunodeficient mice, BIN-67 cells developed into tumours that reflected the hypercalcemia and histology of human SCCOHT, notably intense expression of WT-1 and vimentin, and lack of expression of inhibin. Somatic mutations in TP53 and the most common activating mutations in KRAS and BRAF were not found in BIN-67 cells by DNA sequencing. Spectral karyotyping revealed a largely normal diploid karyotype (in greater than 95% of cells) with a visibly shorter chromosome 20 contig. High density SNP array analysis also revealed few genomic anomalies in BIN-67 cells, which included loss of heterozygosity of an estimated 16.7 Mb interval on chromosome 20. SNP array analyses of four SCCOHT samples also indicated a low frequency of genomic anomalies in the majority of cases. Although resistant to platinum chemotherapeutic drugs, BIN-67 cell viability in vitro was reduced by > 75% after infection with oncolytic viruses. These results show that SCCOHT differs from high-grade serous carcinomas by exhibiting few chromosomal anomalies and lacking TP53 mutations. Although BIN-67 cells are resistant to standard chemotherapeutic agents, their sensitivity to oncolytic viruses suggests that their therapeutic use in SCCOHT should be considered.

Genome-wide single-nucleotide polymorphism arrays demonstrate high fidelity of multiple displacement-based whole-genome amplification.

PubMed

Tzvetkov, Mladen V; Becker, Christian; Kulle, Bettina; Nürnberg, Peter; Brockmöller, Jürgen; Wojnowski, Leszek

2005-02-01

Whole-genome DNA amplification by multiple displacement (MD-WGA) is a promising tool to obtain sufficient DNA amounts from samples of limited quantity. Using Affymetrix' GeneChip Human Mapping 10K Arrays, we investigated the accuracy and allele amplification bias in DNA samples subjected to MD-WGA. We observed an excellent concordance (99.95%) between single-nucleotide polymorphisms (SNPs) called both in the nonamplified and the corresponding amplified DNA. This concordance was only 0.01% lower than the intra-assay reproducibility of the genotyping technique used. However, MD-WGA failed to amplify an estimated 7% of polymorphic loci. Due to the algorithm used to call genotypes, this was detected only for heterozygous loci. We achieved a 4.3-fold reduction of noncalled SNPs by combining the results from two independent MD-WGA reactions. This indicated that inter-reaction variations rather than specific chromosomal loci reduced the efficiency of MD-WGA. Consistently, we detected no regions of reduced amplification, with the exception of several SNPs located near chromosomal ends. Altogether, despite a substantial loss of polymorphic sites, MD-WGA appears to be the current method of choice to amplify genomic DNA for array-based SNP analyses. The number of nonamplified loci can be substantially reduced by amplifying each DNA sample in duplicate.

Genome-wide Target Enrichment-aided Chip Design: a 66 K SNP Chip for Cashmere Goat.

PubMed

Qiao, Xian; Su, Rui; Wang, Yang; Wang, Ruijun; Yang, Ting; Li, Xiaokai; Chen, Wei; He, Shiyang; Jiang, Yu; Xu, Qiwu; Wan, Wenting; Zhang, Yaolei; Zhang, Wenguang; Chen, Jiang; Liu, Bin; Liu, Xin; Fan, Yixing; Chen, Duoyuan; Jiang, Huaizhi; Fang, Dongming; Liu, Zhihong; Wang, Xiaowen; Zhang, Yanjun; Mao, Danqing; Wang, Zhiying; Di, Ran; Zhao, Qianjun; Zhong, Tao; Yang, Huanming; Wang, Jian; Wang, Wen; Dong, Yang; Chen, Xiaoli; Xu, Xun; Li, Jinquan

2017-08-17

Compared with the commercially available single nucleotide polymorphism (SNP) chip based on the Bead Chip technology, the solution hybrid selection (SHS)-based target enrichment SNP chip is not only design-flexible, but also cost-effective for genotype sequencing. In this study, we propose to design an animal SNP chip using the SHS-based target enrichment strategy for the first time. As an update to the international collaboration on goat research, a 66 K SNP chip for cashmere goat was created from the whole-genome sequencing data of 73 individuals. Verification of this 66 K SNP chip with the whole-genome sequencing data of 436 cashmere goats showed that the SNP call rates was between 95.3% and 99.8%. The average sequencing depth for target SNPs were 40X. The capture regions were shown to be 200 bp that flank target SNPs. This chip was further tested in a genome-wide association analysis of cashmere fineness (fiber diameter). Several top hit loci were found marginally associated with signaling pathways involved in hair growth. These results demonstrate that the 66 K SNP chip is a useful tool in the genomic analyses of cashmere goats. The successful chip design shows that the SHS-based target enrichment strategy could be applied to SNP chip design in other species.

A novel approach to exploring potential interactions among single-nucleotide polymorphisms of inflammation genes in gliomagenesis: an exploratory case-only study.

PubMed

Amirian, E Susan; Scheurer, Michael E; Liu, Yanhong; D'Amelio, Anthony M; Houlston, Richard S; Etzel, Carol J; Shete, Sanjay; Swerdlow, Anthony J; Schoemaker, Minouk J; McKinney, Patricia A; Fleming, Sarah J; Muir, Kenneth R; Lophatananon, Artitaya; Bondy, Melissa L

2011-08-01

Despite extensive research on the topic, glioma etiology remains largely unknown. Exploration of potential interactions between single-nucleotide polymorphisms (SNP) of immune genes is a promising new area of glioma research. The case-only study design is a powerful and efficient design for exploring possible multiplicative interactions between factors that are independent of one another. The purpose of our study was to use this exploratory design to identify potential pair wise SNP-SNP interactions from genes involved in several different immune-related pathways for investigation in future studies. The study population consisted of two case groups: 1,224 histologic confirmed, non-Hispanic white glioma cases from the United States and a validation population of 634 glioma cases from the United Kingdom. Polytomous logistic regression, in which one SNP was coded as the outcome and the other SNP was included as the exposure, was utilized to calculate the ORs of the likelihood of cases simultaneously having the variant alleles of two different SNPs. Potential interactions were examined only between SNPs located in different genes or chromosomes. Using this data mining strategy, we found 396 significant SNP-SNP interactions among polymorphisms of immune-related genes that were present in both the U.S. and U.K. study populations. This exploratory study was conducted for the purpose of hypothesis generation, and thus has provided several new hypotheses that can be tested using traditional case-control study designs to obtain estimates of risk. This is the first study, to our knowledge, to take this novel approach to identifying SNP-SNP interactions relevant to glioma etiology. ©2011 AACR.

A 2-Stage Genome-Wide Association Study to Identify Single Nucleotide Polymorphisms Associated With Development of Erectile Dysfunction Following Radiation Therapy for Prostate Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kerns, Sarah L.; Departments of Pathology and Genetics, Albert Einstein College of Medicine, Bronx, New York; Stock, Richard

2013-01-01

Purpose: To identify single nucleotide polymorphisms (SNPs) associated with development of erectile dysfunction (ED) among prostate cancer patients treated with radiation therapy. Methods and Materials: A 2-stage genome-wide association study was performed. Patients were split randomly into a stage I discovery cohort (132 cases, 103 controls) and a stage II replication cohort (128 cases, 102 controls). The discovery cohort was genotyped using Affymetrix 6.0 genome-wide arrays. The 940 top ranking SNPs selected from the discovery cohort were genotyped in the replication cohort using Illumina iSelect custom SNP arrays. Results: Twelve SNPs identified in the discovery cohort and validated in themore » replication cohort were associated with development of ED following radiation therapy (Fisher combined P values 2.1 Multiplication-Sign 10{sup -5} to 6.2 Multiplication-Sign 10{sup -4}). Notably, these 12 SNPs lie in or near genes involved in erectile function or other normal cellular functions (adhesion and signaling) rather than DNA damage repair. In a multivariable model including nongenetic risk factors, the odds ratios for these SNPs ranged from 1.6 to 5.6 in the pooled cohort. There was a striking relationship between the cumulative number of SNP risk alleles an individual possessed and ED status (Sommers' D P value = 1.7 Multiplication-Sign 10{sup -29}). A 1-allele increase in cumulative SNP score increased the odds for developing ED by a factor of 2.2 (P value = 2.1 Multiplication-Sign 10{sup -19}). The cumulative SNP score model had a sensitivity of 84% and specificity of 75% for prediction of developing ED at the radiation therapy planning stage. Conclusions: This genome-wide association study identified a set of SNPs that are associated with development of ED following radiation therapy. These candidate genetic predictors warrant more definitive validation in an independent cohort.« less

High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies.

PubMed

Goudey, Benjamin; Abedini, Mani; Hopper, John L; Inouye, Michael; Makalic, Enes; Schmidt, Daniel F; Wagner, John; Zhou, Zeyu; Zobel, Justin; Reumann, Matthias

2015-01-01

Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucleotide polymorphisms (SNPs) which are associated with a given disease. Univariate analysis approaches commonly employed may miss important SNP associations that only appear through multivariate analysis in complex diseases. However, multivariate SNP analysis is currently limited by its inherent computational complexity. In this work, we present a computational framework that harnesses supercomputers. Based on our results, we estimate a three-way interaction analysis on 1.1 million SNP GWAS data requiring over 5.8 years on the full "Avoca" IBM Blue Gene/Q installation at the Victorian Life Sciences Computation Initiative. This is hundreds of times faster than estimates for other CPU based methods and four times faster than runtimes estimated for GPU methods, indicating how the improvement in the level of hardware applied to interaction analysis may alter the types of analysis that can be performed. Furthermore, the same analysis would take under 3 months on the currently largest IBM Blue Gene/Q supercomputer "Sequoia" at the Lawrence Livermore National Laboratory assuming linear scaling is maintained as our results suggest. Given that the implementation used in this study can be further optimised, this runtime means it is becoming feasible to carry out exhaustive analysis of higher order interaction studies on large modern GWAS.

Viability of in-house datamarting approaches for population genetics analysis of SNP genotypes

PubMed Central

Amigo, Jorge; Phillips, Christopher; Salas, Antonio; Carracedo, Ángel

2009-01-01

Background Databases containing very large amounts of SNP (Single Nucleotide Polymorphism) data are now freely available for researchers interested in medical and/or population genetics applications. While many of these SNP repositories have implemented data retrieval tools for general-purpose mining, these alone cannot cover the broad spectrum of needs of most medical and population genetics studies. Results To address this limitation, we have built in-house customized data marts from the raw data provided by the largest public databases. In particular, for population genetics analysis based on genotypes we have built a set of data processing scripts that deal with raw data coming from the major SNP variation databases (e.g. HapMap, Perlegen), stripping them into single genotypes and then grouping them into populations, then merged with additional complementary descriptive information extracted from dbSNP. This allows not only in-house standardization and normalization of the genotyping data retrieved from different repositories, but also the calculation of statistical indices from simple allele frequency estimates to more elaborate genetic differentiation tests within populations, together with the ability to combine population samples from different databases. Conclusion The present study demonstrates the viability of implementing scripts for handling extensive datasets of SNP genotypes with low computational costs, dealing with certain complex issues that arise from the divergent nature and configuration of the most popular SNP repositories. The information contained in these databases can also be enriched with additional information obtained from other complementary databases, in order to build a dedicated data mart. Updating the data structure is straightforward, as well as permitting easy implementation of new external data and the computation of supplementary statistical indices of interest. PMID:19344481

Viability of in-house datamarting approaches for population genetics analysis of SNP genotypes.

PubMed

Amigo, Jorge; Phillips, Christopher; Salas, Antonio; Carracedo, Angel

2009-03-19

Databases containing very large amounts of SNP (Single Nucleotide Polymorphism) data are now freely available for researchers interested in medical and/or population genetics applications. While many of these SNP repositories have implemented data retrieval tools for general-purpose mining, these alone cannot cover the broad spectrum of needs of most medical and population genetics studies. To address this limitation, we have built in-house customized data marts from the raw data provided by the largest public databases. In particular, for population genetics analysis based on genotypes we have built a set of data processing scripts that deal with raw data coming from the major SNP variation databases (e.g. HapMap, Perlegen), stripping them into single genotypes and then grouping them into populations, then merged with additional complementary descriptive information extracted from dbSNP. This allows not only in-house standardization and normalization of the genotyping data retrieved from different repositories, but also the calculation of statistical indices from simple allele frequency estimates to more elaborate genetic differentiation tests within populations, together with the ability to combine population samples from different databases. The present study demonstrates the viability of implementing scripts for handling extensive datasets of SNP genotypes with low computational costs, dealing with certain complex issues that arise from the divergent nature and configuration of the most popular SNP repositories. The information contained in these databases can also be enriched with additional information obtained from other complementary databases, in order to build a dedicated data mart. Updating the data structure is straightforward, as well as permitting easy implementation of new external data and the computation of supplementary statistical indices of interest.

Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-05-12

A better understanding of the genetic architecture of complex traits can contribute to improve genomic prediction. We hypothesized that genomic variants associated with mastitis and milk production traits in dairy cattle are enriched in hepatic transcriptomic regions that are responsive to intra-mammary infection (IMI). Genomic markers [e.g. single nucleotide polymorphisms (SNPs)] from those regions, if included, may improve the predictive ability of a genomic model. We applied a genomic feature best linear unbiased prediction model (GFBLUP) to implement the above strategy by considering the hepatic transcriptomic regions responsive to IMI as genomic features. GFBLUP, an extension of GBLUP, includes a separate genomic effect of SNPs within a genomic feature, and allows differential weighting of the individual marker relationships in the prediction equation. Since GFBLUP is computationally intensive, we investigated whether a SNP set test could be a computationally fast way to preselect predictive genomic features. The SNP set test assesses the association between a genomic feature and a trait based on single-SNP genome-wide association studies. We applied these two approaches to mastitis and milk production traits (milk, fat and protein yield) in Holstein (HOL, n = 5056) and Jersey (JER, n = 1231) cattle. We observed that a majority of genomic features were enriched in genomic variants that were associated with mastitis and milk production traits. Compared to GBLUP, the accuracy of genomic prediction with GFBLUP was marginally improved (3.2 to 3.9%) in within-breed prediction. The highest increase (164.4%) in prediction accuracy was observed in across-breed prediction. The significance of genomic features based on the SNP set test were correlated with changes in prediction accuracy of GFBLUP (P < 0.05). GFBLUP provides a framework for integrating multiple layers of biological knowledge to provide novel insights into the biological basis of complex traits, and to improve the accuracy of genomic prediction. The SNP set test might be used as a first-step to improve GFBLUP models. Approaches like GFBLUP and SNP set test will become increasingly useful, as the functional annotations of genomes keep accumulating for a range of species and traits.

Extended diversity analysis of cultivated grapevine Vitis vinifera with 10K genome-wide SNPs.

PubMed

Laucou, Valérie; Launay, Amandine; Bacilieri, Roberto; Lacombe, Thierry; Adam-Blondon, Anne-Françoise; Bérard, Aurélie; Chauveau, Aurélie; de Andrés, Maria Teresa; Hausmann, Ludger; Ibáñez, Javier; Le Paslier, Marie-Christine; Maghradze, David; Martinez-Zapater, José Miguel; Maul, Erika; Ponnaiah, Maharajah; Töpfer, Reinhard; Péros, Jean-Pierre; Boursiquot, Jean-Michel

2018-01-01

Grapevine is a very important crop species that is mainly cultivated worldwide for fruits, wine and juice. Identification of the genetic bases of performance traits through association mapping studies requires a precise knowledge of the available diversity and how this diversity is structured and varies across the whole genome. An 18k SNP genotyping array was evaluated on a panel of Vitis vinifera cultivars and we obtained a data set with no missing values for a total of 10207 SNPs and 783 different genotypes. The average inter-SNP spacing was ~47 kbp, the mean minor allele frequency (MAF) was 0.23 and the genetic diversity in the sample was high (He = 0.32). Fourteen SNPs, chosen from those with the highest MAF values, were sufficient to identify each genotype in the sample. Parentage analysis revealed 118 full parentages and 490 parent-offspring duos, thus confirming the close pedigree relationships within the cultivated grapevine. Structure analyses also confirmed the main divisions due to an eastern-western gradient and human usage (table vs. wine). Using a multivariate approach, we refined the structure and identified a total of eight clusters. Both the genetic diversity (He, 0.26-0.32) and linkage disequilibrium (LD, 28.8-58.2 kbp) varied between clusters. Despite the short span LD, we also identified some non-recombining haplotype blocks that may complicate association mapping. Finally, we performed a genome-wide association study that confirmed previous works and also identified new regions for important performance traits such as acidity. Taken together, all the results contribute to a better knowledge of the genetics of the cultivated grapevine.

Extended diversity analysis of cultivated grapevine Vitis vinifera with 10K genome-wide SNPs

PubMed Central

Launay, Amandine; Bacilieri, Roberto; Lacombe, Thierry; Adam-Blondon, Anne-Françoise; Bérard, Aurélie; Chauveau, Aurélie; de Andrés, Maria Teresa; Maghradze, David; Maul, Erika; Ponnaiah, Maharajah; Töpfer, Reinhard; Péros, Jean-Pierre; Boursiquot, Jean-Michel

2018-01-01

Grapevine is a very important crop species that is mainly cultivated worldwide for fruits, wine and juice. Identification of the genetic bases of performance traits through association mapping studies requires a precise knowledge of the available diversity and how this diversity is structured and varies across the whole genome. An 18k SNP genotyping array was evaluated on a panel of Vitis vinifera cultivars and we obtained a data set with no missing values for a total of 10207 SNPs and 783 different genotypes. The average inter-SNP spacing was ~47 kbp, the mean minor allele frequency (MAF) was 0.23 and the genetic diversity in the sample was high (He = 0.32). Fourteen SNPs, chosen from those with the highest MAF values, were sufficient to identify each genotype in the sample. Parentage analysis revealed 118 full parentages and 490 parent-offspring duos, thus confirming the close pedigree relationships within the cultivated grapevine. Structure analyses also confirmed the main divisions due to an eastern-western gradient and human usage (table vs. wine). Using a multivariate approach, we refined the structure and identified a total of eight clusters. Both the genetic diversity (He, 0.26–0.32) and linkage disequilibrium (LD, 28.8–58.2 kbp) varied between clusters. Despite the short span LD, we also identified some non-recombining haplotype blocks that may complicate association mapping. Finally, we performed a genome-wide association study that confirmed previous works and also identified new regions for important performance traits such as acidity. Taken together, all the results contribute to a better knowledge of the genetics of the cultivated grapevine. PMID:29420602

Incorporating Functional Genomic Information in Genetic Association Studies Using an Empirical Bayes Approach.

PubMed

Spencer, Amy V; Cox, Angela; Lin, Wei-Yu; Easton, Douglas F; Michailidou, Kyriaki; Walters, Kevin

2016-04-01

There is a large amount of functional genetic data available, which can be used to inform fine-mapping association studies (in diseases with well-characterised disease pathways). Single nucleotide polymorphism (SNP) prioritization via Bayes factors is attractive because prior information can inform the effect size or the prior probability of causal association. This approach requires the specification of the effect size. If the information needed to estimate a priori the probability density for the effect sizes for causal SNPs in a genomic region isn't consistent or isn't available, then specifying a prior variance for the effect sizes is challenging. We propose both an empirical method to estimate this prior variance, and a coherent approach to using SNP-level functional data, to inform the prior probability of causal association. Through simulation we show that when ranking SNPs by our empirical Bayes factor in a fine-mapping study, the causal SNP rank is generally as high or higher than the rank using Bayes factors with other plausible values of the prior variance. Importantly, we also show that assigning SNP-specific prior probabilities of association based on expert prior functional knowledge of the disease mechanism can lead to improved causal SNPs ranks compared to ranking with identical prior probabilities of association. We demonstrate the use of our methods by applying the methods to the fine mapping of the CASP8 region of chromosome 2 using genotype data from the Collaborative Oncological Gene-Environment Study (COGS) Consortium. The data we analysed included approximately 46,000 breast cancer case and 43,000 healthy control samples. © 2016 The Authors. *Genetic Epidemiology published by Wiley Periodicals, Inc.

High-resolution melting PCR analysis for rapid genotyping of Burkholderia mallei.

PubMed

Girault, G; Wattiau, P; Saqib, M; Martin, B; Vorimore, F; Singha, H; Engelsma, M; Roest, H J; Spicic, S; Grunow, R; Vicari, N; De Keersmaecker, S C J; Roosens, N H C; Fabbi, M; Tripathi, B N; Zientara, S; Madani, N; Laroucau, K

2018-05-08

Burkholderia (B.) mallei is the causative agent of glanders. A previous work conducted on single-nucleotide polymorphisms (SNP) extracted from the whole genome sequences of 45 B. mallei isolates identified 3 lineages for this species. In this study, we designed a high-resolution melting (HRM) method for the screening of 15 phylogenetically informative SNPs within the genome of B. mallei that subtype the species into 3 lineages and 12 branches/sub-branches/groups. The present results demonstrate that SNP-based genotyping represent an interesting approach for the molecular epidemiology analysis of B. mallei. Copyright © 2018 Elsevier B.V. All rights reserved.

Semi-nonparametric VaR forecasts for hedge funds during the recent crisis

NASA Astrophysics Data System (ADS)

Del Brio, Esther B.; Mora-Valencia, Andrés; Perote, Javier

2014-05-01

The need to provide accurate value-at-risk (VaR) forecasting measures has triggered an important literature in econophysics. Although these accurate VaR models and methodologies are particularly demanded for hedge fund managers, there exist few articles specifically devoted to implement new techniques in hedge fund returns VaR forecasting. This article advances in these issues by comparing the performance of risk measures based on parametric distributions (the normal, Student’s t and skewed-t), semi-nonparametric (SNP) methodologies based on Gram-Charlier (GC) series and the extreme value theory (EVT) approach. Our results show that normal-, Student’s t- and Skewed t- based methodologies fail to forecast hedge fund VaR, whilst SNP and EVT approaches accurately success on it. We extend these results to the multivariate framework by providing an explicit formula for the GC copula and its density that encompasses the Gaussian copula and accounts for non-linear dependences. We show that the VaR obtained by the meta GC accurately captures portfolio risk and outperforms regulatory VaR estimates obtained through the meta Gaussian and Student’s t distributions.

Uneven recombination rate and linkage disequilibrium across a reference SNP map for common bean (Phaseolus vulgaris L.)

PubMed Central

Farmer, Andrew D.; Huang, Wei; Ambachew, Daniel; Penmetsa, R. Varma; Carrasquilla-Garcia, Noelia; Assefa, Teshale; Cannon, Steven B.

2018-01-01

Recombination (R) rate and linkage disequilibrium (LD) analyses are the basis for plant breeding. These vary by breeding system, by generation of inbreeding or outcrossing and by region in the chromosome. Common bean (Phaseolus vulgaris L.) is a favored food legume with a small sequenced genome (514 Mb) and n = 11 chromosomes. The goal of this study was to describe R and LD in the common bean genome using a 768-marker array of single nucleotide polymorphisms (SNP) based on Trans-legume Orthologous Group (TOG) genes along with an advanced-generation Recombinant Inbred Line reference mapping population (BAT93 x Jalo EEP558) and an internationally available diversity panel. A whole genome genetic map was created that covered all eleven linkage groups (LG). The LGs were linked to the physical map by sequence data of the TOGs compared to each chromosome sequence of common bean. The genetic map length in total was smaller than for previous maps reflecting the precision of allele calling and mapping with SNP technology as well as the use of gene-based markers. A total of 91.4% of TOG markers had singleton hits with annotated Pv genes and all mapped outside of regions of resistance gene clusters. LD levels were found to be stronger within the Mesoamerican genepool and decay more rapidly within the Andean genepool. The recombination rate across the genome was 2.13 cM / Mb but R was found to be highly repressed around centromeres and frequent outside peri-centromeric regions. These results have important implications for association and genetic mapping or crop improvement in common bean. PMID:29522524

Rapid discovery of SNPs differentiating hatchery steelhead trout from ESA-listed wild steelhead trout using a 57K SNP array

USDA-ARS?s Scientific Manuscript database

Natural-origin steelhead in the Pacific Northwest USA are threatened by a number of factors including habitat destruction, disease, decline in marine survival and a potential erosion of genetic viability due to introgression from hatchery strains. The major goal of this study was to use a recently ...

Discovery of 20,000 RAD-SNPs and development of a 52-SNP array for monitoring river otters

Treesearch

Jeffrey B. Stetz; Seth Smith; Michael A. Sawaya; Alan B. Ramsey; Stephen J. Amish; Michael K. Schwartz; Gordon Luikart

2016-01-01

Many North American river otter (Lontra canadensis) populations are threatened or recovering but are difficult to study because they occur at low densities, it is difficult to visually identify individuals, and they inhabit aquatic environments that accelerate degradation of biological samples. Single nucleotide polymorphisms (SNPs) can improve our ability to...

Development of a 690K SNP array in catfish and its application for genetic mapping and validation of the reference genome sequence

USDA-ARS?s Scientific Manuscript database

Single nucleotide polymorphisms (SNPs) are capable of providing the highest level of genome coverage for genomic and genetic analysis because of their abundance and relatively even distribution in the genome. Such a capacity, however, cannot be achieved without an efficient genotyping platform such ...

Similar genetic architecture with shared and unique quantitative trait loci for bacterial cold water disease resistance in two rainbow trout breeding populations

USDA-ARS?s Scientific Manuscript database

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57K SNP array and a genome phys...

Meta-analysis diagnostic accuracy of SNP-based pathogenicity detection tools: a case of UTG1A1 gene mutations.

PubMed

Galehdari, Hamid; Saki, Najmaldin; Mohammadi-Asl, Javad; Rahim, Fakher

2013-01-01

Crigler-Najjar syndrome (CNS) type I and type II are usually inherited as autosomal recessive conditions that result from mutations in the UGT1A1 gene. The main objective of the present review is to summarize results of all available evidence on the accuracy of SNP-based pathogenicity detection tools compared to published clinical result for the prediction of in nsSNPs that leads to disease using prediction performance method. A comprehensive search was performed to find all mutations related to CNS. Database searches included dbSNP, SNPdbe, HGMD, Swissvar, ensemble, and OMIM. All the mutation related to CNS was extracted. The pathogenicity prediction was done using SNP-based pathogenicity detection tools include SIFT, PHD-SNP, PolyPhen2, fathmm, Provean, and Mutpred. Overall, 59 different SNPs related to missense mutations in the UGT1A1 gene, were reviewed. Comparing the diagnostic OR, PolyPhen2 and Mutpred have the highest detection 4.983 (95% CI: 1.24 - 20.02) in both, following by SIFT (diagnostic OR: 3.25, 95% CI: 1.07 - 9.83). The highest MCC of SNP-based pathogenicity detection tools, was belong to SIFT (34.19%) followed by Provean, PolyPhen2, and Mutpred (29.99%, 29.89%, and 29.89%, respectively). Hence the highest SNP-based pathogenicity detection tools ACC, was fit to SIFT (62.71%) followed by PolyPhen2, and Mutpred (61.02%, in both). Our results suggest that some of the well-established SNP-based pathogenicity detection tools can appropriately reflect the role of a disease-associated SNP in both local and global structures.

Rare De Novo Copy Number Variants in Patients with Congenital Pulmonary Atresia

PubMed Central

Xie, Li; Chen, Jin-Lan; Zhang, Wei-Zhi; Wang, Shou-Zheng; Zhao, Tian-Li; Huang, Can; Wang, Jian; Yang, Jin-Fu; Yang, Yi-Feng; Tan, Zhi-Ping

2014-01-01

Background Ongoing studies using genomic microarrays and next-generation sequencing have demonstrated that the genetic contributions to cardiovascular diseases have been significantly ignored in the past. The aim of this study was to identify rare copy number variants in individuals with congenital pulmonary atresia (PA). Methods and Results Based on the hypothesis that rare structural variants encompassing key genes play an important role in heart development in PA patients, we performed high-resolution genome-wide microarrays for copy number variations (CNVs) in 82 PA patient-parent trios and 189 controls with an Illumina SNP array platform. CNVs were identified in 17/82 patients (20.7%), and eight of these CNVs (9.8%) are considered potentially pathogenic. Five de novo CNVs occurred at two known congenital heart disease (CHD) loci (16p13.1 and 22q11.2). Two de novo CNVs that may affect folate and vitamin B12 metabolism were identified for the first time. A de novo 1-Mb deletion at 17p13.2 may represent a rare genomic disorder that involves mild intellectual disability and associated facial features. Conclusions Rare CNVs contribute to the pathogenesis of PA (9.8%), suggesting that the causes of PA are heterogeneous and pleiotropic. Together with previous data from animal models, our results might help identify a link between CHD and folate-mediated one-carbon metabolism (FOCM). With the accumulation of high-resolution SNP array data, these previously undescribed rare CNVs may help reveal critical gene(s) in CHD and may provide novel insights about CHD pathogenesis. PMID:24826987

Rare de novo copy number variants in patients with congenital pulmonary atresia.

PubMed

Xie, Li; Chen, Jin-Lan; Zhang, Wei-Zhi; Wang, Shou-Zheng; Zhao, Tian-Li; Huang, Can; Wang, Jian; Yang, Jin-Fu; Yang, Yi-Feng; Tan, Zhi-Ping

2014-01-01

Ongoing studies using genomic microarrays and next-generation sequencing have demonstrated that the genetic contributions to cardiovascular diseases have been significantly ignored in the past. The aim of this study was to identify rare copy number variants in individuals with congenital pulmonary atresia (PA). Based on the hypothesis that rare structural variants encompassing key genes play an important role in heart development in PA patients, we performed high-resolution genome-wide microarrays for copy number variations (CNVs) in 82 PA patient-parent trios and 189 controls with an Illumina SNP array platform. CNVs were identified in 17/82 patients (20.7%), and eight of these CNVs (9.8%) are considered potentially pathogenic. Five de novo CNVs occurred at two known congenital heart disease (CHD) loci (16p13.1 and 22q11.2). Two de novo CNVs that may affect folate and vitamin B12 metabolism were identified for the first time. A de novo 1-Mb deletion at 17p13.2 may represent a rare genomic disorder that involves mild intellectual disability and associated facial features. Rare CNVs contribute to the pathogenesis of PA (9.8%), suggesting that the causes of PA are heterogeneous and pleiotropic. Together with previous data from animal models, our results might help identify a link between CHD and folate-mediated one-carbon metabolism (FOCM). With the accumulation of high-resolution SNP array data, these previously undescribed rare CNVs may help reveal critical gene(s) in CHD and may provide novel insights about CHD pathogenesis.

Localization of canine brachycephaly using an across breed mapping approach.

PubMed

Bannasch, Danika; Young, Amy; Myers, Jeffrey; Truvé, Katarina; Dickinson, Peter; Gregg, Jeffrey; Davis, Ryan; Bongcam-Rudloff, Eric; Webster, Matthew T; Lindblad-Toh, Kerstin; Pedersen, Niels

2010-03-10

The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10-30) and control (20-60) samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.

Loss-of-function DNA sequence variant in the CLCNKA chloride channel implicates the cardio-renal axis in interindividual heart failure risk variation.

PubMed

Cappola, Thomas P; Matkovich, Scot J; Wang, Wei; van Booven, Derek; Li, Mingyao; Wang, Xuexia; Qu, Liming; Sweitzer, Nancy K; Fang, James C; Reilly, Muredach P; Hakonarson, Hakon; Nerbonne, Jeanne M; Dorn, Gerald W

2011-02-08

Common heart failure has a strong undefined heritable component. Two recent independent cardiovascular SNP array studies identified a common SNP at 1p36 in intron 2 of the HSPB7 gene as being associated with heart failure. HSPB7 resequencing identified other risk alleles but no functional gene variants. Here, we further show no effect of the HSPB7 SNP on cardiac HSPB7 mRNA levels or splicing, suggesting that the SNP marks the position of a functional variant in another gene. Accordingly, we used massively parallel platforms to resequence all coding exons of the adjacent CLCNKA gene, which encodes the K(a) renal chloride channel (ClC-K(a)). Of 51 exonic CLCNKA variants identified, one SNP (rs10927887, encoding Arg83Gly) was common, in linkage disequilibrium with the heart failure risk SNP in HSPB7, and associated with heart failure in two independent Caucasian referral populations (n = 2,606 and 1,168; combined P = 2.25 × 10(-6)). Individual genotyping of rs10927887 in the two study populations and a third independent heart failure cohort (combined n = 5,489) revealed an additive allele effect on heart failure risk that is independent of age, sex, and prior hypertension (odds ratio = 1.27 per allele copy; P = 8.3 × 10(-7)). Functional characterization of recombinant wild-type Arg83 and variant Gly83 ClC-K(a) chloride channel currents revealed ≈ 50% loss-of-function of the variant channel. These findings identify a common, functionally significant genetic risk factor for Caucasian heart failure. The variant CLCNKA risk allele, telegraphed by linked variants in the adjacent HSPB7 gene, uncovers a previously overlooked genetic mechanism affecting the cardio-renal axis.

The Minnesota Center for Twin and Family Research Genome-Wide Association Study

PubMed Central

Miller, Michael B.; Basu, Saonli; Cunningham, Julie; Eskin, Eleazar; Malone, Steven M.; Oetting, William S.; Schork, Nicholas; Sul, Jae Hoon; Iacono, William G.; Mcgue, Matt

2012-01-01

As part of the Genes, Environment and Development Initiative (GEDI), the Minnesota Center for Twin and Family Research (MCTFR) undertook a genome-wide association study (GWAS), which we describe here. A total of 8405 research participants, clustered in 4-member families, have been successfully genotyped on 527,829 single nucleotide polymorphism (SNP) markers using Illumina’s Human660W-Quad array. Quality control screening of samples and markers as well as SNP imputation procedures are described. We also describe methods for ancestry control and how the familial clustering of the MCTFR sample can be accounted for in the analysis using a Rapid Feasible Generalized Least Squares algorithm. The rich longitudinal MCTFR assessments provide numerous opportunities for collaboration. PMID:23363460

Predicting the disease of Alzheimer with SNP biomarkers and clinical data using data mining classification approach: decision tree.

PubMed

Erdoğan, Onur; Aydin Son, Yeşim

2014-01-01

Single Nucleotide Polymorphisms (SNPs) are the most common genomic variations where only a single nucleotide differs between individuals. Individual SNPs and SNP profiles associated with diseases can be utilized as biological markers. But there is a need to determine the SNP subsets and patients' clinical data which is informative for the diagnosis. Data mining approaches have the highest potential for extracting the knowledge from genomic datasets and selecting the representative SNPs as well as most effective and informative clinical features for the clinical diagnosis of the diseases. In this study, we have applied one of the widely used data mining classification methodology: "decision tree" for associating the SNP biomarkers and significant clinical data with the Alzheimer's disease (AD), which is the most common form of "dementia". Different tree construction parameters have been compared for the optimization, and the most accurate tree for predicting the AD is presented.

Molecular inversion probe assay for allelic quantitation

PubMed Central

Ji, Hanlee; Welch, Katrina

2010-01-01

Molecular inversion probe (MIP) technology has been demonstrated to be a robust platform for large-scale dual genotyping and copy number analysis. Applications in human genomic and genetic studies include the possibility of running dual germline genotyping and combined copy number variation ascertainment. MIPs analyze large numbers of specific genetic target sequences in parallel, relying on interrogation of a barcode tag, rather than direct hybridization of genomic DNA to an array. The MIP approach does not replace, but is complementary to many of the copy number technologies being performed today. Some specific advantages of MIP technology include: Less DNA required (37 ng vs. 250 ng), DNA quality less important, more dynamic range (amplifications detected up to copy number 60), allele specific information “cleaner” (less SNP crosstalk/contamination), and quality of markers better (fewer individual MIPs versus SNPs needed to identify copy number changes). MIPs can be considered a candidate gene (targeted whole genome) approach and can find specific areas of interest that otherwise may be missed with other methods. PMID:19488872

Quantitative analysis of low-density SNP data for parentage assignment and estimation of family contributions to pooled samples.

PubMed

Henshall, John M; Dierens, Leanne; Sellars, Melony J

2014-09-02

While much attention has focused on the development of high-density single nucleotide polymorphism (SNP) assays, the costs of developing and running low-density assays have fallen dramatically. This makes it feasible to develop and apply SNP assays for agricultural species beyond the major livestock species. Although low-cost low-density assays may not have the accuracy of the high-density assays widely used in human and livestock species, we show that when combined with statistical analysis approaches that use quantitative instead of discrete genotypes, their utility may be improved. The data used in this study are from a 63-SNP marker Sequenom® iPLEX Platinum panel for the Black Tiger shrimp, for which high-density SNP assays are not currently available. For quantitative genotypes that could be estimated, in 5% of cases the most likely genotype for an individual at a SNP had a probability of less than 0.99. Matrix formulations of maximum likelihood equations for parentage assignment were developed for the quantitative genotypes and also for discrete genotypes perturbed by an assumed error term. Assignment rates that were based on maximum likelihood with quantitative genotypes were similar to those based on maximum likelihood with perturbed genotypes but, for more than 50% of cases, the two methods resulted in individuals being assigned to different families. Treating genotypes as quantitative values allows the same analysis framework to be used for pooled samples of DNA from multiple individuals. Resulting correlations between allele frequency estimates from pooled DNA and individual samples were consistently greater than 0.90, and as high as 0.97 for some pools. Estimates of family contributions to the pools based on quantitative genotypes in pooled DNA had a correlation of 0.85 with estimates of contributions from DNA-derived pedigree. Even with low numbers of SNPs of variable quality, parentage testing and family assignment from pooled samples are sufficiently accurate to provide useful information for a breeding program. Treating genotypes as quantitative values is an alternative to perturbing genotypes using an assumed error distribution, but can produce very different results. An understanding of the distribution of the error is required for SNP genotyping platforms.

Association of Single-Nucleotide Polymorphisms of the Tau Gene With Late-Onset Parkinson Disease

PubMed Central

Martin, Eden R.; Scott, William K.; Nance, Martha A.; Watts, Ray L.; Hubble, Jean P.; Koller, William C.; Lyons, Kelly; Pahwa, Rajesh; Stern, Matthew B.; Colcher, Amy; Hiner, Bradley C.; Jankovic, Joseph; Ondo, William G.; Allen, Fred H.; Goetz, Christopher G.; Small, Gary W.; Masterman, Donna; Mastaglia, Frank; Laing, Nigel G.; Stajich, Jeffrey M.; Ribble, Robert C.; Booze, Michael W.; Rogala, Allison; Hauser, Michael A.; Zhang, Fengyu; Gibson, Rachel A.; Middleton, Lefkos T.; Roses, Allen D.; Haines, Jonathan L.; Scott, Burton L.; Pericak-Vance, Margaret A.; Vance, Jeffery M.

2013-01-01

Context The human tau gene, which promotes assembly of neuronal microtubules, has been associated with several rare neurologic diseases that clinically include parkinsonian features. We recently observed linkage in idiopathic Parkinson disease (PD) to a region on chromosome 17q21 that contains the tau gene. These factors make tau a good candidate for investigation as a susceptibility gene for idiopathic PD, the most common form of the disease. Objective To investigate whether the tau gene is involved in idiopathic PD. Design, Setting, and Participants Among a sample of 1056 individuals from 235 families selected from 13 clinical centers in the United States and Australia and from a family ascertainment core center, we tested 5 single-nucleotide polymorphisms (SNPs) within the tau gene for association with PD, using family-based tests of association. Both affected (n = 426) and unaffected (n = 579) family members were included; 51 individuals had unclear PD status. Analyses were conducted to test individual SNPs and SNP haplotypes within the tau gene. Main Outcome Measure Family-based tests of association, calculated using asymptotic distributions. Results Analysis of association between the SNPs and PD yielded significant evidence of association for 3 of the 5 SNPs tested: SNP 3, P = .03; SNP 9i, P = .04; and SNP 11, P = .04. The 2 other SNPs did not show evidence of significant association (SNP 9ii, P = .11, and SNP 9iii, P = .87). Strong evidence of association was found with haplotype analysis, with a positive association with one haplotype (P = .009) and a negative association with another haplotype (P = .007). Substantial linkage disequilibrium (P<.001) was detected between 4 of the 5 SNPs (SNPs 3,9i, 9ii, and 11). Conclusions This integrated approach of genetic linkage and positional association analyses implicates tau as a susceptibility gene for idiopathic PD. PMID:11710889

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association

PubMed Central

Di Guardo, Mario; Bink, Marco C.A.M.; Guerra, Walter; Letschka, Thomas; Lozano, Lidia; Busatto, Nicola; Poles, Lara; Tadiello, Alice; Bianco, Luca; Visser, Richard G.F.; van de Weg, Eric

2017-01-01

Abstract Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer’s appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties. PMID:28338805

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association.

PubMed

Di Guardo, Mario; Bink, Marco C A M; Guerra, Walter; Letschka, Thomas; Lozano, Lidia; Busatto, Nicola; Poles, Lara; Tadiello, Alice; Bianco, Luca; Visser, Richard G F; van de Weg, Eric; Costa, Fabrizio

2017-03-01

Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer's appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Detection of genetic association and functional polymorphisms of UGDH affecting milk production trait in Chinese Holstein cattle.

PubMed

Xu, Qing; Mei, Gui; Sun, Dongxiao; Zhang, Qin; Zhang, Yuan; Yin, Cengceng; Chen, Huiyong; Ding, Xiangdong; Liu, Jianfeng

2012-11-02

We previously localized a quantitative trait locus (QTL) on bovine chromosome 6 affecting milk production traits to a 1.5-Mb region between BMS483 and MNB-209 via genome scanning followed by fine mapping. Totally 15 genes were mapped within such linkage region through bioinformatic analysis of the cattle-human comparative map and bovine genome assembly. Of them, the UDP-glucose dehydrogenase (UGDH) was suggested as a potential positional candidate gene for milk production traits based on its corresponding physiological and biochemical functions and genetic effects. By sequencing all the coding exons and the untranslated regions in UGDH with pooled DNA of 8 sires represented the separated families detected in our previous studies, a total of ten SNPs were identified and genotyped in 1417 Holstein cows of 8 separation families. Individual SNP-based association analysis revealed 4 significant associations of SNP Ex1-1, SNP Int3-1, SNP Int5-1, and SNP Ex12-3 with milk yield (P < 0.05), and 2 significant associations of SNP Ex1-1 and SNP Ex12-3 with protein yield (P < 0.05). Furthermore, our haplotype-based association analyses indicated that haplotypes G-C-C, formed by SNP Ex12-2-SNP Int11-1-SNP Ex11-1, T-G, formed by SNP Int9-3-SNP Int9-2, and C-C, formed by SNP Int5-1-SNP Int3-1, are significantly associated with protein percentage (F=4.15; P=0.0418) and fat percentage (F=5.18~7.25; P=0.0072~0.0231). Finally, by using an in vitro expression assay, we demonstrated that the A allele of SNP Ex1-1 and T allele of SNP Ex11-1of UGDH significantly decreases the expression of UGDH by 68.0% at the RNA, and 50.1% at the protein level, suggesting that SNP Ex1-1 and Ex11-1 represent two functional polymorphisms affecting expression of UGDH and may partly contributed to the observed association of the gene with milk production traits in our samples. Taken together, our findings strongly indicate that UGDH gene could be involved in genetic variation underlying the QTL for milk production traits.

SNP-Based Typing: A Useful Tool to Study Bordetella pertussis Populations

PubMed Central

van der Heide, Han G. J.; Heuvelman, Kees J.; Kallonen, Teemu; He, Qiushui; Mertsola, Jussi; Advani, Abdolreza; Hallander, Hans O.; Janssens, Koen; Hermans, Peter W.; Mooi, Frits R.

2011-01-01

To monitor changes in Bordetella pertussis populations, mainly two typing methods are used; Pulsed-Field Gel Electrophoresis (PFGE) and Multiple-Locus Variable-Number Tandem Repeat Analysis (MLVA). In this study, a single nucleotide polymorphism (SNP) typing method, based on 87 SNPs, was developed and compared with PFGE and MLVA. The discriminatory indices of SNP typing, PFGE and MLVA were found to be 0.85, 0.95 and 0.83, respectively. Phylogenetic analysis, using SNP typing as Gold Standard, revealed false homoplasies in the PFGE and MLVA trees. Further, in contrast to the SNP-based tree, the PFGE- and MLVA-based trees did not reveal a positive correlation between root-to-tip distance and the isolation year of strains. Thus PFGE and MLVA do not allow an estimation of the relative age of the selected strains. In conclusion, SNP typing was found to be phylogenetically more informative than PFGE and more discriminative than MLVA. Further, in contrast to PFGE, it is readily standardized allowing interlaboratory comparisons. We applied SNP typing to study strains with a novel allele for the pertussis toxin promoter, ptxP3, which have a worldwide distribution and which have replaced the resident ptxP1 strains in the last 20 years. Previously, we showed that ptxP3 strains showed increased pertussis toxin expression and that their emergence was associated with increased notification in the Netherlands. SNP typing showed that the ptxP3 strains isolated in the Americas, Asia, Australia and Europe formed a monophyletic branch which recently diverged from ptxP1 strains. Two predominant ptxP3 SNP types were identified which spread worldwide. The widespread use of SNP typing will enhance our understanding of the evolution and global epidemiology of B. pertussis. PMID:21647370

Particle-Based Microarrays of Oligonucleotides and Oligopeptides.

PubMed

Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F Ralf; Breitling, Frank; Loeffler, Felix F

2014-10-28

In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches.

Particle-Based Microarrays of Oligonucleotides and Oligopeptides

PubMed Central

Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K.; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F. Ralf; Breitling, Frank; Loeffler, Felix F.

2014-01-01

In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches. PMID:27600347

Accurate HLA type inference using a weighted similarity graph.

PubMed

Xie, Minzhu; Li, Jing; Jiang, Tao

2010-12-14

The human leukocyte antigen system (HLA) contains many highly variable genes. HLA genes play an important role in the human immune system, and HLA gene matching is crucial for the success of human organ transplantations. Numerous studies have demonstrated that variation in HLA genes is associated with many autoimmune, inflammatory and infectious diseases. However, typing HLA genes by serology or PCR is time consuming and expensive, which limits large-scale studies involving HLA genes. Since it is much easier and cheaper to obtain single nucleotide polymorphism (SNP) genotype data, accurate computational algorithms to infer HLA gene types from SNP genotype data are in need. To infer HLA types from SNP genotypes, the first step is to infer SNP haplotypes from genotypes. However, for the same SNP genotype data set, the haplotype configurations inferred by different methods are usually inconsistent, and it is often difficult to decide which one is true. In this paper, we design an accurate HLA gene type inference algorithm by utilizing SNP genotype data from pedigrees, known HLA gene types of some individuals and the relationship between inferred SNP haplotypes and HLA gene types. Given a set of haplotypes inferred from the genotypes of a population consisting of many pedigrees, the algorithm first constructs a weighted similarity graph based on a new haplotype similarity measure and derives constraint edges from known HLA gene types. Based on the principle that different HLA gene alleles should have different background haplotypes, the algorithm searches for an optimal labeling of all the haplotypes with unknown HLA gene types such that the total weight among the same HLA gene types is maximized. To deal with ambiguous haplotype solutions, we use a genetic algorithm to select haplotype configurations that tend to maximize the same optimization criterion. Our experiments on a previously typed subset of the HapMap data show that the algorithm is highly accurate, achieving an accuracy of 96% for gene HLA-A, 95% for HLA-B, 97% for HLA-C, 84% for HLA-DRB1, 98% for HLA-DQA1 and 97% for HLA-DQB1 in a leave-one-out test. Our algorithm can infer HLA gene types from neighboring SNP genotype data accurately. Compared with a recent approach on the same input data, our algorithm achieved a higher accuracy. The code of our algorithm is available to the public for free upon request to the corresponding authors.

SSGP: SNP-set based genomic prediction to incorporate biological information

USDA-ARS?s Scientific Manuscript database

Genomic prediction has emerged as an effective approach in plant and animal breeding and in precision medicine. Much research has been devoted to an improved accuracy in genomic prediction, and one of the potential ways is to incorporate biological information. Due to the statistical and computation...

Brief Overview of a Decade of Genome-Wide Association Studies on Primary Hypertension.

PubMed

Azam, Afifah Binti; Azizan, Elena Aisha Binti

2018-01-01

Primary hypertension is widely believed to be a complex polygenic disorder with the manifestation influenced by the interactions of genomic and environmental factors making identification of susceptibility genes a major challenge. With major advancement in high-throughput genotyping technology, genome-wide association study (GWAS) has become a powerful tool for researchers studying genetically complex diseases. GWASs work through revealing links between DNA sequence variation and a disease or trait with biomedical importance. The human genome is a very long DNA sequence which consists of billions of nucleotides arranged in a unique way. A single base-pair change in the DNA sequence is known as a single nucleotide polymorphism (SNP). With the help of modern genotyping techniques such as chip-based genotyping arrays, thousands of SNPs can be genotyped easily. Large-scale GWASs, in which more than half a million of common SNPs are genotyped and analyzed for disease association in hundreds of thousands of cases and controls, have been broadly successful in identifying SNPs associated with heart diseases, diabetes, autoimmune diseases, and psychiatric disorders. It is however still debatable whether GWAS is the best approach for hypertension. The following is a brief overview on the outcomes of a decade of GWASs on primary hypertension.

Estrogen pathway polymorphisms in relation to primary open angle glaucoma: An analysis accounting for gender from the United States

PubMed Central

Loomis, Stephanie J.; Weinreb, Robert N.; Kang, Jae H.; Yaspan, Brian L.; Bailey, Jessica Cooke; Gaasterland, Douglas; Gaasterland, Terry; Lee, Richard K.; Scott, William K.; Lichter, Paul R.; Budenz, Donald L.; Liu, Yutao; Realini, Tony; Friedman, David S.; McCarty, Catherine A.; Moroi, Sayoko E.; Olson, Lana; Schuman, Joel S.; Singh, Kuldev; Vollrath, Douglas; Wollstein, Gadi; Zack, Donald J.; Brilliant, Murray; Sit, Arthur J.; Christen, William G.; Fingert, John; Kraft, Peter; Zhang, Kang; Allingham, R. Rand; Pericak-Vance, Margaret A.; Richards, Julia E.; Hauser, Michael A.; Haines, Jonathan L.; Wiggs, Janey L.

2013-01-01

Purpose Circulating estrogen levels are relevant in glaucoma phenotypic traits. We assessed the association between an estrogen metabolism single nucleotide polymorphism (SNP) panel in relation to primary open angle glaucoma (POAG), accounting for gender. Methods We included 3,108 POAG cases and 3,430 controls of both genders from the Glaucoma Genes and Environment (GLAUGEN) study and the National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) consortium genotyped on the Illumina 660W-Quad platform. We assessed the relation between the SNP panels representative of estrogen metabolism and POAG using pathway- and gene-based approaches with the Pathway Analysis by Randomization Incorporating Structure (PARIS) software. PARIS executes a permutation algorithm to assess statistical significance relative to the pathways and genes of comparable genetic architecture. These analyses were performed using the meta-analyzed results from the GLAUGEN and NEIGHBOR data sets. We evaluated POAG overall as well as two subtypes of POAG defined as intraocular pressure (IOP) ≥22 mmHg (high-pressure glaucoma [HPG]) or IOP <22 mmHg (normal pressure glaucoma [NPG]) at diagnosis. We conducted these analyses for each gender separately and then jointly in men and women. Results Among women, the estrogen SNP pathway was associated with POAG overall (permuted p=0.006) and HPG (permuted p<0.001) but not NPG (permuted p=0.09). Interestingly, there was no relation between the estrogen SNP pathway and POAG when men were considered alone (permuted p>0.99). Among women, gene-based analyses revealed that the catechol-O-methyltransferase gene showed strong associations with HTG (permuted gene p≤0.001) and NPG (permuted gene p=0.01). Conclusions The estrogen SNP pathway was associated with POAG among women. PMID:23869166

SEURAT: visual analytics for the integrated analysis of microarray data.

PubMed

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

Next-Generation Sequencing Approaches in Genome-Wide Discovery of Single Nucleotide Polymorphism Markers Associated with Pungency and Disease Resistance in Pepper.

PubMed

Manivannan, Abinaya; Kim, Jin-Hee; Yang, Eun-Young; Ahn, Yul-Kyun; Lee, Eun-Su; Choi, Sena; Kim, Do-Sun

2018-01-01

Pepper is an economically important horticultural plant that has been widely used for its pungency and spicy taste in worldwide cuisines. Therefore, the domestication of pepper has been carried out since antiquity. Owing to meet the growing demand for pepper with high quality, organoleptic property, nutraceutical contents, and disease tolerance, genomics assisted breeding techniques can be incorporated to develop novel pepper varieties with desired traits. The application of next-generation sequencing (NGS) approaches has reformed the plant breeding technology especially in the area of molecular marker assisted breeding. The availability of genomic information aids in the deeper understanding of several molecular mechanisms behind the vital physiological processes. In addition, the NGS methods facilitate the genome-wide discovery of DNA based markers linked to key genes involved in important biological phenomenon. Among the molecular markers, single nucleotide polymorphism (SNP) indulges various benefits in comparison with other existing DNA based markers. The present review concentrates on the impact of NGS approaches in the discovery of useful SNP markers associated with pungency and disease resistance in pepper. The information provided in the current endeavor can be utilized for the betterment of pepper breeding in future.

A kernel regression approach to gene-gene interaction detection for case-control studies.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

A novel single neuron perceptron with universal approximation and XOR computation properties.

PubMed

Lotfi, Ehsan; Akbarzadeh-T, M-R

2014-01-01

We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous system. The resulting architecture of SNP can be trained by supervised excitatory and inhibitory online learning rules. The main features of proposed single layer perceptron are universal approximation property and low computational complexity. The method is tested on 6 UCI (University of California, Irvine) pattern recognition and classification datasets. Various comparisons with multilayer perceptron (MLP) with gradient decent backpropagation (GDBP) learning algorithm indicate the superiority of the approach in terms of higher accuracy, lower time, and spatial complexity, as well as faster training. Hence, we believe the proposed approach can be generally applicable to various problems such as in pattern recognition and classification.

Novel Single Nucleotide Polymorphism-Based Assay for Genotyping Mycobacterium avium subsp. paratuberculosis

PubMed Central

Goldstone, Robert J.; McLuckie, Joyce; Smith, David G. E.

2015-01-01

Typing of Mycobacterium avium subspecies paratuberculosis strains presents a challenge, since they are genetically monomorphic and traditional molecular techniques have limited discriminatory power. The recent advances and availability of whole-genome sequencing have extended possibilities for the characterization of Mycobacterium avium subspecies paratuberculosis, and whole-genome sequencing can provide a phylogenetic context to facilitate global epidemiology studies. In this study, we developed a single nucleotide polymorphism (SNP) assay based on PCR and restriction enzyme digestion or sequencing of the amplified product. The SNP analysis was performed using genome sequence data from 133 Mycobacterium avium subspecies paratuberculosis isolates with different genotypes from 8 different host species and 17 distinct geographic regions around the world. A total of 28,402 SNPs were identified among all of the isolates. The minimum number of SNPs required to distinguish between all of the 133 genomes was 93 and between only the type C isolates was 41. To reduce the number of SNPs and PCRs required, we adopted an approach based on sequential detection of SNPs and a decision tree. By the analysis of 14 SNPs Mycobacterium avium subspecies paratuberculosis isolates can be characterized within 14 phylogenetic groups with a higher discriminatory power than mycobacterial interspersed repetitive unit–variable number tandem repeat assay and other typing methods. Continuous updating of genome sequences is needed in order to better characterize new phylogenetic groups and SNP profiles. The novel SNP assay is a discriminative, simple, reproducible method and requires only basic laboratory equipment for the large-scale global typing of Mycobacterium avium subspecies paratuberculosis isolates. PMID:26677250

Diagnosis of intrachromosomal amplification of chromosome 21 (iAMP21) by molecular cytogenetics in pediatric acute lymphoblastic leukemia.

PubMed

Duployez, Nicolas; Boudry-Labis, Elise; Decool, Gauthier; Grzych, Guillaume; Grardel, Nathalie; Abou Chahla, Wadih; Preudhomme, Claude; Roche-Lestienne, Catherine

2015-10-01

Intrachromosomal amplification of chromosome 21 (iAMP21) defines a distinct cytogenetic subgroup of B-cell precursor acute lymphoblastic leukemia (BCP-ALL) with poor prognosis that should be investigated in routine practice. Single-nucleotide polymorphism (SNP)-array provides a useful method to detect such cases showing a highly characteristic profile.

Canonical single nucleotide polymorphisms (SNPs) for high-resolution subtyping of Shiga-toxin producing Escherichia coli (STEC) O157:H7

USDA-ARS?s Scientific Manuscript database

The objective of this study was to develop a canonical SNP panel for subtyping of Shiga-toxin producing Escherichia coli (STEC). To this purpose, 906 putative SNPs were identified using resequencing tiling arrays. A subset of 391 SNPs was further screened using high-throughput TaqMan PCR against a d...

Development and preliminary evaluation of a 90K Axiom® SNP array for the allo-octoploid cultivated strawberry Fragaria ×ananassa

USDA-ARS?s Scientific Manuscript database

A high-throughput genotyping platform is needed to enable marker-assisted breeding in the allo-octoploid cultivated strawberry Fragaria ×ananassa. Short-read sequences from one diploid and 19 octoploid accessions were aligned to the diploid Fragaria vesca ‘Hawaii 4’ reference genome to identify sing...

Software for optimization of SNP and PCR-RFLP genotyping to discriminate many genomes with the fewest assays

PubMed Central

Gardner, Shea N; Wagner, Mark C

2005-01-01

Background Microbial forensics is important in tracking the source of a pathogen, whether the disease is a naturally occurring outbreak or part of a criminal investigation. Results A method and SPR Opt (SNP and PCR-RFLP Optimization) software to perform a comprehensive, whole-genome analysis to forensically discriminate multiple sequences is presented. Tools for the optimization of forensic typing using Single Nucleotide Polymorphism (SNP) and PCR-Restriction Fragment Length Polymorphism (PCR-RFLP) analyses across multiple isolate sequences of a species are described. The PCR-RFLP analysis includes prediction and selection of optimal primers and restriction enzymes to enable maximum isolate discrimination based on sequence information. SPR Opt calculates all SNP or PCR-RFLP variations present in the sequences, groups them into haplotypes according to their co-segregation across those sequences, and performs combinatoric analyses to determine which sets of haplotypes provide maximal discrimination among all the input sequences. Those set combinations requiring that membership in the fewest haplotypes be queried (i.e. the fewest assays be performed) are found. These analyses highlight variable regions based on existing sequence data. These markers may be heterogeneous among unsequenced isolates as well, and thus may be useful for characterizing the relationships among unsequenced as well as sequenced isolates. The predictions are multi-locus. Analyses of mumps and SARS viruses are summarized. Phylogenetic trees created based on SNPs, PCR-RFLPs, and full genomes are compared for SARS virus, illustrating that purported phylogenies based only on SNP or PCR-RFLP variations do not match those based on multiple sequence alignment of the full genomes. Conclusion This is the first software to optimize the selection of forensic markers to maximize information gained from the fewest assays, accepting whole or partial genome sequence data as input. As more sequence data becomes available for multiple strains and isolates of a species, automated, computational approaches such as those described here will be essential to make sense of large amounts of information, and to guide and optimize efforts in the laboratory. The software and source code for SPR Opt is publicly available and free for non-profit use at . PMID:15904493

Clear cell papillary renal cell carcinoma: a chromosomal microarray analysis of two cases using a novel Molecular Inversion Probe (MIP) technology.

PubMed

Alexiev, Borislav A; Zou, Ying S

2014-12-01

Chromosomal microarray analysis using novel Molecular Inversion Probe (MIP) technology demonstrated 2,570 kb copy neutral LOH of 10q11.22 in two clear cell papillary renal cell carcinomas. In addition, one of the tumors had a big 29,784 kb deletion of 13q11-q14.2. There were two variants of unknown significance, a 2,509 kb gain of Xp22.33 and a 257 kb homozygous deletion of 8p11.22. The somatic mutation panel containing 74 mutations in nine genes did not reveal any mutations. Besides identification of submicroscopic duplications or deletions, SNP microarrays can reveal abnormal allelic imbalances including LOH and copy neutral LOH, which cannot be recognized by chromosome, FISH, and non-SNP microarray arrays. To the best of our knowledge, this is the first study demonstrating copy neutral LOH of 10q11.22 in clear cell papillary renal cell carcinomas using the new MIP SNP OncoScan FFPE Assay Kit on formalin-fixed paraffin-embedded tumor samples. Copyright © 2014 Elsevier GmbH. All rights reserved.

The G72/G30 gene complex and cognitive abnormalities in schizophrenia.

PubMed

Goldberg, Terry E; Straub, Richard E; Callicott, Joseph H; Hariri, Ahmad; Mattay, Venkata S; Bigelow, Llewellyn; Coppola, Richard; Egan, Michael F; Weinberger, Daniel R

2006-09-01

A recently discovered gene complex, G72/G30 (hereafter G72, but now termed DAOA), was found to be associated with schizophrenia and with bipolar disorder, possibly because of an indirect effect on NMDA neurotransmission. In principle, if G72 increases risk for psychosis by this mechanism, it might impact with greater penetrance those cortically based cognitive and neurophysiological functions associated with NMDA signaling. We performed two independent family-based association studies (one sample contained more than 200 families and the other more than 65) of multiple SNPs in the G72 region and of multiple SNPs in the gene for D-amino acid oxidase (DAAO), which may be modulated by G72. We examined the relationship between select cognitive measures in attention, working memory, and episodic memory and a restricted set of G72 SNPs in over 600 normal controls, schizophrenic patients, and their nonpsychotic siblings using mixed model ANOVAs. We also determined genotype effects on neurophysiology measures in normal controls using the fMRI BOLD response obtained during activation procedures involving either episodic memory or working memory. There were no significant single G72 SNP associations and clinical diagnosis in either sample, though one approached significance (p=0.06). Diagnosis by genotype interaction effects for G72 SNP 10 were significant for cognitive variables assessing working memory and attention (p=0.05), and at the trend level for episodic memory, such that in the schizophrenia group an exaggerated allele load effect in the predicted directions was observed. In the fMRI paradigms, a strong effect of G72 SNP 10 genotype was observed on BOLD activation in the hippocampus during the episodic memory paradigm. Tests of association with DAAO were consistently nonsignificant. We present evidence that SNP variations in the G72 gene region increase risk of cognitive impairment in schizophrenia. SNP variations were not strongly associated with clinical diagnosis in family-based analyses.

A genome-wide detection of copy number variation using SNP genotyping arrays in Beijing-You chickens.

PubMed

Zhou, Wei; Liu, Ranran; Zhang, Jingjing; Zheng, Maiqing; Li, Peng; Chang, Guobin; Wen, Jie; Zhao, Guiping

2014-10-01

Copy number variation (CNV) has been recently examined in many species and is recognized as being a source of genetic variability, especially for disease-related phenotypes. In this study, the PennCNV software, a genome-wide CNV detection system based on the 60 K SNP BeadChip was used on a total sample size of 1,310 Beijing-You chickens (a Chinese local breed). After quality control, 137 high confidence CNVRs covering 27.31 Mb of the chicken genome and corresponding to 2.61 % of the whole chicken genome. Within these regions, 131 known genes or coding sequences were involved. Q-PCR was applied to verify some of the genes related to disease development. Results showed that copy number of genes such as, phosphatidylinositol-5-phosphate 4-kinase II alpha, PHD finger protein 14, RHACD8 (a CD8α- like messenger RNA), MHC B-G, zinc finger protein, sarcosine dehydrogenase and ficolin 2 varied between individual chickens, which also supports the reliability of chip-detection of the CNVs. As one source of genomic variation, CNVs may provide new insight into the relationship between the genome and phenotypic characteristics.

Heritability of Individual Psychotic Experiences Captured by Common Genetic Variants in a Community Sample of Adolescents.

PubMed

Sieradzka, Dominika; Power, Robert A; Freeman, Daniel; Cardno, Alastair G; Dudbridge, Frank; Ronald, Angelica

2015-09-01

Occurrence of psychotic experiences is common amongst adolescents in the general population. Twin studies suggest that a third to a half of variance in adolescent psychotic experiences is explained by genetic influences. Here we test the extent to which common genetic variants account for some of the twin-based heritability. Psychotic experiences were assessed with the Specific Psychotic Experiences Questionnaire in a community sample of 2152 16-year-olds. Self-reported measures of Paranoia, Hallucinations, Cognitive Disorganization, Grandiosity, Anhedonia, and Parent-rated Negative Symptoms were obtained. Estimates of SNP heritability were derived and compared to the twin heritability estimates from the same sample. Three approaches to genome-wide restricted maximum likelihood (GREML) analyses were compared: (1) standard GREML performed on full genome-wide data; (2) GREML stratified by minor allele frequency (MAF); and (3) GREML performed on pruned data. The standard GREML revealed a significant SNP heritability of 20 % for Anhedonia (SE = 0.12; p < 0.046) and an estimate of 19 % for Cognitive Disorganization, which was close to significant (SE = 0.13; p < 0.059). Grandiosity and Paranoia showed modest SNP heritability estimates (17 %; SE = 0.13 and 14 %; SE = 0.13, respectively, both n.s.), and zero estimates were found for Hallucinations and Negative Symptoms. The estimates for Anhedonia, Cognitive Disorganization and Grandiosity accounted for approximately half the previously reported twin heritability. SNP heritability estimates from the MAF-stratified approach were mostly consistent with the standard estimates and offered additional information about the distribution of heritability across the MAF range of the SNPs. In contrast, the estimates derived from the pruned data were for the most part not consistent with the other two approaches. It is likely that the difference seen in the pruned estimates was driven by the loss of tagged causal variants, an issue fundamental to this approach. The current results suggest that common genetic variants play a role in the etiology of some adolescent psychotic experiences, however further research on larger samples is desired and the use of MAF-stratified approach recommended.

Characterization of a Wheat Breeders' Array suitable for high-throughput SNP genotyping of global accessions of hexaploid bread wheat (Triticum aestivum).

PubMed

Allen, Alexandra M; Winfield, Mark O; Burridge, Amanda J; Downie, Rowena C; Benbow, Harriet R; Barker, Gary L A; Wilkinson, Paul A; Coghill, Jane; Waterfall, Christy; Davassi, Alessandro; Scopes, Geoff; Pirani, Ali; Webster, Teresa; Brew, Fiona; Bloor, Claire; Griffiths, Simon; Bentley, Alison R; Alda, Mark; Jack, Peter; Phillips, Andrew L; Edwards, Keith J

2017-03-01

Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism-based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high-density Affymetrix Axiom ® genotyping array (the Wheat Breeders' Array), in a high-throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders' Array is also suitable for generating high-density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site 'CerealsDB'. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs)

PubMed Central

Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Moradi Marjaneh, Mahdi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Fues Wahl, Hanna; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Alonso, M. Rosario; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Benitez, Javier; Bogdanova, Natalia V.; Bojesen, Stig E.; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M.; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Easton, Douglas F.; Fasching, Peter A.; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G.; Goldberg, Mark S.; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A.; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L.; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; McKay, James; Meindl, Alfons; Milne, Roger L.; Muir, Kenneth; Neuhausen, Susan L.; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkäs, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C.; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H.; Tessier, Daniel C.; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine M.; Vincent, Daniel; Winqvist, Robert; Wu, Anna H.; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D. P.; Hall, Per; Edwards, Stacey L.; Simard, Jacques; French, Juliet D.; Chenevix-Trench, Georgia; Dunning, Alison M.

2016-01-01

Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90–0.94; P = 8.96 × 10−15)) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10−09, r2 = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10−11, r2 = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus. PMID:27600471

Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs).

PubMed

Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Moradi Marjaneh, Mahdi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Fues Wahl, Hanna; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Alonso, M Rosario; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Benitez, Javier; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Easton, Douglas F; Fasching, Peter A; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G; Goldberg, Mark S; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; McKay, James; Meindl, Alfons; Milne, Roger L; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkäs, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C; Stram, Daniel O; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H; Tessier, Daniel C; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine M; Vincent, Daniel; Winqvist, Robert; Wu, Anna H; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D P; Hall, Per; Edwards, Stacey L; Simard, Jacques; French, Juliet D; Chenevix-Trench, Georgia; Dunning, Alison M

2016-09-07

Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 × 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10(-09), r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.

DNA methylation data analysis and its application to cancer research

PubMed Central

Ma, Xiaotu; Wang, Yi-Wei; Zhang, Michael Q; Gazdar, Adi F

2013-01-01

With the rapid development of genome-wide high-throughput technologies, including expression arrays, SNP arrays and next-generation sequencing platforms, enormous amounts of molecular data have been generated and deposited in the public domain. The application of computational approaches is required to yield biological insights from this enormous, ever-growing resource. A particularly interesting subset of these resources is related to epigenetic regulation, with DNA methylation being the most abundant data type. In this paper, we will focus on the analysis of DNA methylation data and its application to cancer studies. We first briefly review the molecular techniques that generate such data, much of which has been obtained with the use of the most recent version of Infinium HumanMethylation450 BeadChip® technology (Illumina, CA, USA). We describe the coverage of the methylome by this technique. Several examples of data mining are provided. However, it should be understood that reliance on a single aspect of epigenetics has its limitations. In the not too distant future, these defects may be rectified, providing scientists with previously unavailable opportunities to explore in detail the role of epigenetics in cancer and other disease states. PMID:23750645

Genetic diversity and trait genomic prediction in a pea diversity panel.

PubMed

Burstin, Judith; Salloignon, Pauline; Chabert-Martinello, Marianne; Magnin-Robert, Jean-Bernard; Siol, Mathieu; Jacquin, Françoise; Chauveau, Aurélie; Pont, Caroline; Aubert, Grégoire; Delaitre, Catherine; Truntzer, Caroline; Duc, Gérard

2015-02-21

Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more efficient methods of selection and better take advantage of the large genetic diversity present in the Pisum sativum genepool. Diversity studies conducted so far in pea used Simple Sequence Repeat (SSR) and Retrotransposon Based Insertion Polymorphism (RBIP) markers. Recently, SNP marker panels have been developed that will be useful for genetic diversity assessment and marker-assisted selection. A collection of diverse pea accessions, including landraces and cultivars of garden, field or fodder peas as well as wild peas was characterised at the molecular level using newly developed SNP markers, as well as SSR markers and RBIP markers. The three types of markers were used to describe the structure of the collection and revealed different pictures of the genetic diversity among the collection. SSR showed the fastest rate of evolution and RBIP the slowest rate of evolution, pointing to their contrasted mode of evolution. SNP markers were then used to predict phenotypes -the date of flowering (BegFlo), the number of seeds per plant (Nseed) and thousand seed weight (TSW)- that were recorded for the collection. Different statistical methods were tested including the LASSO (Least Absolute Shrinkage ans Selection Operator), PLS (Partial Least Squares), SPLS (Sparse Partial Least Squares), Bayes A, Bayes B and GBLUP (Genomic Best Linear Unbiased Prediction) methods and the structure of the collection was taken into account in the prediction. Despite a limited number of 331 markers used for prediction, TSW was reliably predicted. The development of marker assisted selection has not reached its full potential in pea until now. This paper shows that the high-throughput SNP arrays that are being developed will most probably allow for a more efficient selection in this species.

Single tube genotyping of sickle cell anaemia using PCR-based SNP analysis.

PubMed

Waterfall, C M; Cobb, B D

2001-12-01

Allele-specific amplification (ASA) is a generally applicable technique for the detection of known single nucleotide polymorphisms (SNPs), deletions, insertions and other sequence variations. Conventionally, two reactions are required to determine the zygosity of DNA in a two-allele system, along with significant upstream optimisation to define the specific test conditions. Here, we combine single tube bi-directional ASA with a 'matrix-based' optimisation strategy, speeding up the whole process in a reduced reaction set. We use sickle cell anaemia as our model SNP system, a genetic disease that is currently screened using ASA methods. Discriminatory conditions were rapidly optimised enabling the unambiguous identification of DNA from homozygous sickle cell patients (HbS/S), heterozygous carriers (HbA/S) or normal DNA in a single tube. Simple downstream mathematical analyses based on product yield across the optimisation set allow an insight into the important aspects of priming competition and component interactions in this competitive PCR. This strategy can be applied to any polymorphism, defining specific conditions using a multifactorial approach. The inherent simplicity and low cost of this PCR-based method validates bi-directional ASA as an effective tool in future clinical screening and pharmacogenomic research where more expensive fluorescence-based approaches may not be desirable.

Loss of Dermatan-4-Sulfotransferase 1 Function Results in Adducted Thumb-Clubfoot Syndrome

PubMed Central

Dündar, Munis; Müller, Thomas; Zhang, Qi; Pan, Jing; Steinmann, Beat; Vodopiutz, Julia; Gruber, Robert; Sonoda, Tohru; Krabichler, Birgit; Utermann, Gerd; Baenziger, Jacques U.; Zhang, Lijuan; Janecke, Andreas R.

2009-01-01

Adducted thumb-clubfoot syndrome is an autosomal-recessive disorder characterized by typical facial appearance, wasted build, thin and translucent skin, congenital contractures of thumbs and feet, joint instability, facial clefting, and coagulopathy, as well as heart, kidney, or intestinal defects. We elucidated the molecular basis of the disease by using a SNP array-based genome-wide linkage approach that identified distinct homozygous nonsense and missense mutations in CHST14 in each of four consanguineous families with this disease. The CHST14 gene encodes N-acetylgalactosamine 4-O-sulfotransferase 1 (D4ST1), which catalyzes 4-O sulfation of N-acetylgalactosamine in the repeating iduronic acid-α1,3-N-acetylgalactosamine disaccharide sequence to form dermatan sulfate. Mass spectrometry of glycosaminoglycans from a patient's fibroblasts revealed absence of dermatan sulfate and excess of chondroitin sulfate, showing that 4-O sulfation by CHST14 is essential for dermatan sulfate formation in vivo. Our results indicate that adducted thumb-clubfoot syndrome is a disorder resulting from a defect specific to dermatan sulfate biosynthesis and emphasize roles for dermatan sulfate in human development and extracellular-matrix maintenance. PMID:20004762

Gene-Based Single Nucleotide Polymorphism Markers for Genetic and Association Mapping in Common Bean

PubMed Central

2012-01-01

Background In common bean, expressed sequence tags (ESTs) are an underestimated source of gene-based markers such as insertion-deletions (Indels) or single-nucleotide polymorphisms (SNPs). However, due to the nature of these conserved sequences, detection of markers is difficult and portrays low levels of polymorphism. Therefore, development of intron-spanning EST-SNP markers can be a valuable resource for genetic experiments such as genetic mapping and association studies. Results In this study, a total of 313 new gene-based markers were developed at target genes. Intronic variation was deeply explored in order to capture more polymorphism. Introns were putatively identified after comparing the common bean ESTs with the soybean genome, and the primers were designed over intron-flanking regions. The intronic regions were evaluated for parental polymorphisms using the single strand conformational polymorphism (SSCP) technique and Sequenom MassARRAY system. A total of 53 new marker loci were placed on an integrated molecular map in the DOR364 × G19833 recombinant inbred line (RIL) population. The new linkage map was used to build a consensus map, merging the linkage maps of the BAT93 × JALO EEP558 and DOR364 × BAT477 populations. A total of 1,060 markers were mapped, with a total map length of 2,041 cM across 11 linkage groups. As a second application of the generated resource, a diversity panel with 93 genotypes was evaluated with 173 SNP markers using the MassARRAY-platform and KASPar technology. These results were coupled with previous SSR evaluations and drought tolerance assays carried out on the same individuals. This agglomerative dataset was examined, in order to discover marker-trait associations, using general linear model (GLM) and mixed linear model (MLM). Some significant associations with yield components were identified, and were consistent with previous findings. Conclusions In short, this study illustrates the power of intron-based markers for linkage and association mapping in common bean. The utility of these markers is discussed in relation with the usefulness of microsatellites, the molecular markers by excellence in this crop. PMID:22734675

Beyond the Labor Market Paradigm: A Social Network Perspective on Teacher Recruitment and Retention

ERIC Educational Resources Information Center

Baker-Doyle, Kira

2010-01-01

This article identifies limits of the dominant labor market perspective (LMP) in research on teacher recruitment and retention and describes how research that incorporates a social network perspective (SNP) can contribute to the knowledge base and development of teacher education, staffing, and professional development approaches. A discussion of…

A Genome-Wide Association Study for the Incidence of Persistent Bovine Viral Diarrhea Virus Infection in Cattle.

USDA-ARS?s Scientific Manuscript database

Bovine Viral Diarrhea Virus (BVDV) is a diverse group of viruses causing disease in ruminants. The objective was to determine genomic regions harboring single nucleotide polymorphisms (SNP) associated with presence or absence of persistent BVDV infections. A genome wide association approach based on...

SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate

USGS Publications Warehouse

Roffler, Gretchen H.; Amish, Stephen J.; Smith, Seth; Cosart, Ted F.; Kardos, Marty; Schwartz, Michael K.; Luikart, Gordon

2016-01-01

Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding and nearby 5′ and 3′ untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis aries v. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR-based SNP chip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositan and bayescan), we detected 28 SNP loci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease-regulating functions (e.g. Ovar-DRA, APC, BATF2, MAGEB18), cell regulation signalling pathways (e.g. KRIT1, PI3K, ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene-targeted SNP discovery and subsequent SNP chip genotyping using low-quality samples in a nonmodel species.

Polymorphisms in the promoter region of the bovine lactoferrin gene influence milk somatic cell score and milk production traits in Chinese Holstein cows.

PubMed

Mao, Yongjiang; Zhu, Xiaorui; Xing, Shiyu; Zhang, Meirong; Zhang, Huimin; Wang, Xiaolong; Karrow, Niel; Yang, Liguo; Yang, Zhangping

2015-12-01

Lactoferrin is an iron-binding protein found in cow's milk that plays an important role in preventing mastitis caused by intramammary infection. In this study, 20 Chinese Holstein cows were selected randomly for PCR amplification and sequencing of the bovine lactoferrin gene promoter region and used for SNP discovery in the region between nucleotide positions -461 to -132. Three SNPs (-270T>C, -190G>A and -156A>G) were identified in bovine lactoferrin, then Chinese Holstein cows (n=866) were genotyped using Sequenom MassARRAY (Sequenom Inc., San Diego, CA) based on the previous SNP information in this study, and the associations between SNPs or haplotype and milk somatic cell score (SCS) and production traits were analyzed by the least squares method in the GLM procedure of SAS. SNPs -270T>C and -156A>G showed close linkage disequilibrium (r(2)=0.76). The SNP -190G>A showed a significant association with SCS, and individuals with genotype GG had higher SCS than genotypes AG and AA. Associations were found between the SNPs -270T>C and -190G>A with SCS and the milk composition. The software MatInspector revealed that these SNPs were located within several potential transcription factor binding sites, including NF-κB p50, KLF7 and SP1, and may alter gene expression, but further investigation will be required to elucidate the biological and practical relevance of these SNPs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Variation in Recombination Rate and Its Genetic Determinism in Sheep Populations

PubMed Central

Petit, Morgane; Astruc, Jean-Michel; Sarry, Julien; Drouilhet, Laurence; Fabre, Stéphane; Moreno, Carole R.; Servin, Bertrand

2017-01-01

Recombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and data sets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified ∼50,000 crossover hotspots on the genome, and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting interindividual variation in recombination rate in Lacaune, including the RNF212 and HEI10 genes and possibly two other loci of smaller effects including the KCNJ15 and FSHR genes. The comparison of these new results to those obtained previously in a distantly related population of domestic sheep (the Soay) revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome. The two data sets were thus combined to create more precise male meiotic recombination maps in Sheep. However, despite their similar recombination maps, Soay and Lacaune males were found to exhibit different heritabilities and QTL effects for interindividual variation in genome-wide recombination rates. This highlights the robustness of recombination patterns to underlying variation in their genetic determinism. PMID:28978774

Molecular Breeding of Rice Restorer Lines and Hybrids for Brown Planthopper (BPH) Resistance Using the Bph14 and Bph15 Genes.

PubMed

Wang, Hongbo; Ye, Shengtuo; Mou, Tongmin

2016-12-01

The development of hybrid rice is a practical approach for increasing rice production. However, the brown planthopper (BPH), Nilaparvata lugens Stål, causes severe yield loss of rice (Oryza sativa L.) and can threaten food security. Therefore, breeding hybrid rice resistant to BPH is the most effective and economical strategy to maintain high and stable production. Fortunately, numerous BPH resistance genes have been identified, and abundant linkage markers are available for molecular marker-assisted selection (MAS) in breeding programs. Hence, we pyramided two BPH resistance genes, Bph14 and Bph15, into a susceptive CMS restorer line Huahui938 and its derived hybrids using MAS to improve the BPH resistance of hybrid rice. Three near-isogenic lines (NILs) with pyramided Bph14 and Bph15 were obtained by molecular marker-assisted backcross (MAB) and phenotypic selection. The genomic components of these NILs were detected using the whole-genome SNP (Single nucleotide polymorphism) array, RICE6K, suggesting that the recurrent parent genome (RPG) recovery of the NILs was 87.88, 87.70 and 86.62 %, respectively. BPH bioassays showed that the improved NILs and their derived hybrids carrying homozygous Bph14 and Bph15 were resistant to BPH. However, the hybrids with heterozygous Bph14 and Bph15 remained susceptible to BPH. The developed NILs showed no significant differences in major agronomic traits and rice qualities compared with the recurrent parent. Moreover, the improved hybrids derived from the NILs exhibited better agronomic performance and rice quality compared with the controls under natural field conditions. This study demonstrates that it is essential to stack Bph14 and Bph15 into both the maternal and paternal parents for developing BPH-resistant hybrid rice varieties. The SNP array with abundant DNA markers is an efficient tool for analyzing the RPG recovery of progenies and can be used to monitor the donor segments in NILs, thus being extremely important for rice molecular breeding.

Variation in Recombination Rate and Its Genetic Determinism in Sheep Populations.

PubMed

Petit, Morgane; Astruc, Jean-Michel; Sarry, Julien; Drouilhet, Laurence; Fabre, Stéphane; Moreno, Carole R; Servin, Bertrand

2017-10-01

Recombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and data sets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified ∼50,000 crossover hotspots on the genome, and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting interindividual variation in recombination rate in Lacaune, including the RNF212 and HEI10 genes and possibly two other loci of smaller effects including the KCNJ15 and FSHR genes. The comparison of these new results to those obtained previously in a distantly related population of domestic sheep (the Soay) revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome. The two data sets were thus combined to create more precise male meiotic recombination maps in Sheep. However, despite their similar recombination maps, Soay and Lacaune males were found to exhibit different heritabilities and QTL effects for interindividual variation in genome-wide recombination rates. This highlights the robustness of recombination patterns to underlying variation in their genetic determinism. Copyright © 2017 by the Genetics Society of America.

Loss of heterozygosity at D8S262: an early genetic event of hepatocarcinogenesis.

PubMed

Zhu, Qiao; Gong, Li; Liu, Xiaoyan; Wang, Jun; Ren, Pin; Zhang, Wendong; Yao, Li; Han, Xiujuan; Zhu, Shaojun; Lan, Miao; Li, Yanhong; Zhang, Wei

2015-06-16

Hepatocellular carcinoma (HCC) is a multi-factor, multi-step, multi-gene and complicated process resulting from the accumulation of sequential genetic and epigenetic alterations. An important change among them is from precancerous lesions to HCC. However, only few studies have been reported about the sequential genetic changes during hepatocarcinogenesis. We observed firstly molecular karyotypes of 10 matched HCC using Affymetrix single-nucleotide polymorphism (SNP) 6.0 arrays, and found chromosomal fragments with high incidence (more than 70%) of loss of heterozygosity (LOH). Then, we selected 28 microsatellite markers at some gene spanning these chromosomal fragments, and examined the frequency of LOH of 128 matched HCC and 43 matched precancerous lesions-dysplastic nodules (DN) by a PCR-based analysis. Finally, we investigated the expression of proteins encoded by these genes in HCC, DN and the surrounding hepatic tissues. The result of Affymetrix SNP6.0 arrays demonstrated that more than 70% (7/10) cases had chromosomal fragment deletion on 4q13.3-35.1, 8p23.2-21.2, 16q11.2-24.3, and 17p13.3-12. Among 28 microsatellite markers selected, LOH frequencies at D8S262 for DN and HCC were found to be the highest, 51.2% and 72.7%, respectively. Immunohistochemically, the positive rate of its adjacent gene CSMD1 in HCC, DN, and the surrounding hepatic tissues were 27.3% (35/128), 75% (33/44), and 82% (105/128), respectively. LOH at D8S262 may be associated with an early genetic event of hepatocarcinogenesis, and a predictor for the monitor and prevention of HCC. The virtual slides for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1557074981159099 .

Mutations in TULP1, NR2E3, and MFRP genes in Indian families with autosomal recessive retinitis pigmentosa

PubMed Central

Singh, Hardeep; Sahini, Nishika; Jalali, Subhadra; Mohan, Gayathri

2012-01-01

Purpose To identify genes underlying autosomal recessive retinitis pigmentosa (ARRP) by homozygosity mapping. Methods Families with ARRP were recruited after complete ophthalmic evaluation of all members and diagnosis of RP by predefined criteria. Genomic DNA from affected members of 26 families was genotyped on Illumina single nucleotide polymorphism (SNP) 6.0 K arrays with standard procedures. Genotypes were evaluated for homozygous regions that were common and concordant between affected members of each family. The genes mapping to homozygous intervals within these families were screened for pathogenic changes with PCR amplification and sequencing of coding regions. Cosegegration of sequence changes with disease was determined within each pedigree, and each variation was tested for presence in 100 unrelated normal controls. Results A genome-wide scan for homozygosity showed homozygous regions harboring the tubby like protein 1 gene (TULP1; chromosome 6) in one family, the nuclear receptor subfamily 2, group E, member 3 gene (NR2E3; chromosome 15) in three families, and the membrane frizzled-related protein gene (MFRP; chromosome 11) in one family. Screening of the three genes in the respective families revealed homozygous disease-causing mutations in three families. These included a missense mutation in TULP1, a deletion-cum-insertion in NR2E3, and a single base deletion in MFRP. Patients from all three families had a rod-cone type of dystrophy with night blindness initially. The NR2E3 and MFRP genes were associated with fundus features atypical of RP. Conclusions This study shows involvement of the TULP1, NR2E3, and MFRP genes in ARRP in Indian cases. Genome-wide screening with SNP arrays followed by a prioritized candidate gene evaluation is useful in identifying genes in these patients. PMID:22605927

Joint Identification of Genetic Variants for Physical Activity in Korean Population

PubMed Central

Kim, Jayoun; Kim, Jaehee; Min, Haesook; Oh, Sohee; Kim, Yeonjung; Lee, Andy H.; Park, Taesung

2014-01-01

There has been limited research on genome-wide association with physical activity (PA). This study ascertained genetic associations between PA and 344,893 single nucleotide polymorphism (SNP) markers in 8842 Korean samples. PA data were obtained from a validated questionnaire that included information on PA intensity and duration. Metabolic equivalent of tasks were calculated to estimate the total daily PA level for each individual. In addition to single- and multiple-SNP association tests, a pathway enrichment analysis was performed to identify the biological significance of SNP markers. Although no significant SNP was found at genome-wide significance level via single-SNP association tests, 59 genetic variants mapped to 76 genes were identified via a multiple SNP approach using a bootstrap selection stability measure. Pathway analysis for these 59 variants showed that maturity onset diabetes of the young (MODY) was enriched. Joint identification of SNPs could enable the identification of multiple SNPs with good predictive power for PA and a pathway enriched for PA. PMID:25026172

Diagnosis of intrachromosomal amplification of chromosome 21 (iAMP21) by molecular cytogenetics in pediatric acute lymphoblastic leukemia

PubMed Central

Duployez, Nicolas; Boudry-Labis, Elise; Decool, Gauthier; Grzych, Guillaume; Grardel, Nathalie; Abou Chahla, Wadih; Preudhomme, Claude; Roche-Lestienne, Catherine

2015-01-01

Key Clinical Message Intrachromosomal amplification of chromosome 21 (iAMP21) defines a distinct cytogenetic subgroup of B-cell precursor acute lymphoblastic leukemia (BCP-ALL) with poor prognosis that should be investigated in routine practice. Single-nucleotide polymorphism (SNP)-array provides a useful method to detect such cases showing a highly characteristic profile. PMID:26509013

Genome-wide association studies reveal similar genetic architecture with shared and unique QTL for Bacterial Cold Water Disease resistance in two rainbow trout (Oncorhynchus mykiss) breeding populations

USDA-ARS?s Scientific Manuscript database

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57K SNP array and a genome phys...

Improving mapping and SNP-calling performance in multiplexed targeted next-generation sequencing

PubMed Central

2012-01-01

Background Compared to classical genotyping, targeted next-generation sequencing (tNGS) can be custom-designed to interrogate entire genomic regions of interest, in order to detect novel as well as known variants. To bring down the per-sample cost, one approach is to pool barcoded NGS libraries before sample enrichment. Still, we lack a complete understanding of how this multiplexed tNGS approach and the varying performance of the ever-evolving analytical tools can affect the quality of variant discovery. Therefore, we evaluated the impact of different software tools and analytical approaches on the discovery of single nucleotide polymorphisms (SNPs) in multiplexed tNGS data. To generate our own test model, we combined a sequence capture method with NGS in three experimental stages of increasing complexity (E. coli genes, multiplexed E. coli, and multiplexed HapMap BRCA1/2 regions). Results We successfully enriched barcoded NGS libraries instead of genomic DNA, achieving reproducible coverage profiles (Pearson correlation coefficients of up to 0.99) across multiplexed samples, with <10% strand bias. However, the SNP calling quality was substantially affected by the choice of tools and mapping strategy. With the aim of reducing computational requirements, we compared conventional whole-genome mapping and SNP-calling with a new faster approach: target-region mapping with subsequent ‘read-backmapping’ to the whole genome to reduce the false detection rate. Consequently, we developed a combined mapping pipeline, which includes standard tools (BWA, SAMtools, etc.), and tested it on public HiSeq2000 exome data from the 1000 Genomes Project. Our pipeline saved 12 hours of run time per Hiseq2000 exome sample and detected ~5% more SNPs than the conventional whole genome approach. This suggests that more potential novel SNPs may be discovered using both approaches than with just the conventional approach. Conclusions We recommend applying our general ‘two-step’ mapping approach for more efficient SNP discovery in tNGS. Our study has also shown the benefit of computing inter-sample SNP-concordances and inspecting read alignments in order to attain more confident results. PMID:22913592

Natural Allelic Diversity, Genetic Structure and Linkage Disequilibrium Pattern in Wild Chickpea

PubMed Central

Kujur, Alice; Das, Shouvik; Badoni, Saurabh; Kumar, Vinod; Singh, Mohar; Bansal, Kailash C.; Tyagi, Akhilesh K.; Parida, Swarup K.

2014-01-01

Characterization of natural allelic diversity and understanding the genetic structure and linkage disequilibrium (LD) pattern in wild germplasm accessions by large-scale genotyping of informative microsatellite and single nucleotide polymorphism (SNP) markers is requisite to facilitate chickpea genetic improvement. Large-scale validation and high-throughput genotyping of genome-wide physically mapped 478 genic and genomic microsatellite markers and 380 transcription factor gene-derived SNP markers using gel-based assay, fluorescent dye-labelled automated fragment analyser and matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass array have been performed. Outcome revealed their high genotyping success rate (97.5%) and existence of a high level of natural allelic diversity among 94 wild and cultivated Cicer accessions. High intra- and inter-specific polymorphic potential and wider molecular diversity (11–94%) along with a broader genetic base (13–78%) specifically in the functional genic regions of wild accessions was assayed by mapped markers. It suggested their utility in monitoring introgression and transferring target trait-specific genomic (gene) regions from wild to cultivated gene pool for the genetic enhancement. Distinct species/gene pool-wise differentiation, admixed domestication pattern, and differential genome-wide recombination and LD estimates/decay observed in a six structured population of wild and cultivated accessions using mapped markers further signifies their usefulness in chickpea genetics, genomics and breeding. PMID:25222488

Contributions of IKZF1, DDC, CDKN2A, CEBPE, and LMO1 Gene Polymorphisms to Acute Lymphoblastic Leukemia in a Yemeni Population.

PubMed

Al-Absi, Boshra; Razif, Muhammad F M; Noor, Suzita M; Saif-Ali, Riyadh; Aqlan, Mohammed; Salem, Sameer D; Ahmed, Radwan H; Muniandy, Sekaran

2017-10-01

Genome-wide and candidate gene association studies have previously revealed links between a predisposition to acute lymphoblastic leukemia (ALL) and genetic polymorphisms in the following genes: IKZF1 (7p12.2; ID: 10320), DDC (7p12.2; ID: 1644), CDKN2A (9p21.3; ID: 1029), CEBPE (14q11.2; ID: 1053), and LMO1 (11p15; ID: 4004). In this study, we aimed to conduct an investigation into the possible association between polymorphisms in these genes and ALL within a sample of Yemeni children of Arab-Asian descent. Seven single-nucleotide polymorphisms (SNPs) in IKZF1, three SNPs in DDC, two SNPs in CDKN2A, two SNPs in CEBPE, and three SNPs in LMO1 were genotyped in 289 Yemeni children (136 cases and 153 controls), using the nanofluidic Dynamic Array (Fluidigm 192.24 Dynamic Array). Logistic regression analyses were used to estimate ALL risk, and the strength of association was expressed as odds ratios with 95% confidence intervals. We found that the IKZF1 SNP rs10235796 C allele (p = 0.002), the IKZF1 rs6964969 A>G polymorphism (p = 0.048, GG vs. AA), the CDKN2A rs3731246 G>C polymorphism (p = 0.047, GC+CC vs. GG), and the CDKN2A SNP rs3731246 C allele (p = 0.007) were significantly associated with ALL in Yemenis of Arab-Asian descent. In addition, a borderline association was found between IKZF1 rs4132601 T>G variant and ALL risk. No associations were found between the IKZF1 SNPs (rs11978267; rs7789635), DDC SNPs (rs3779084; rs880028; rs7809758), CDKN2A SNP (rs3731217), the CEBPE SNPs (rs2239633; rs12434881) and LMO1 SNPs (rs442264; rs3794012; rs4237770) with ALL in Yemeni children. The IKZF1 SNPs, rs10235796 and rs6964969, and the CDKN2A SNP rs3731246 (previously unreported) could serve as risk markers for ALL susceptibility in Yemeni children.

When Whole-Genome Alignments Just Won't Work: kSNP v2 Software for Alignment-Free SNP Discovery and Phylogenetics of Hundreds of Microbial Genomes

PubMed Central

Gardner, Shea N.; Hall, Barry G.

2013-01-01

Effective use of rapid and inexpensive whole genome sequencing for microbes requires fast, memory efficient bioinformatics tools for sequence comparison. The kSNP v2 software finds single nucleotide polymorphisms (SNPs) in whole genome data. kSNP v2 has numerous improvements over kSNP v1 including SNP gene annotation; better scaling for draft genomes available as assembled contigs or raw, unassembled reads; a tool to identify the optimal value of k; distribution of packages of executables for Linux and Mac OS X for ease of installation and user-friendly use; and a detailed User Guide. SNP discovery is based on k-mer analysis, and requires no multiple sequence alignment or the selection of a single reference genome. Most target sets with hundreds of genomes complete in minutes to hours. SNP phylogenies are built by maximum likelihood, parsimony, and distance, based on all SNPs, only core SNPs, or SNPs present in some intermediate user-specified fraction of targets. The SNP-based trees that result are consistent with known taxonomy. kSNP v2 can handle many gigabases of sequence in a single run, and if one or more annotated genomes are included in the target set, SNPs are annotated with protein coding and other information (UTRs, etc.) from Genbank file(s). We demonstrate application of kSNP v2 on sets of viral and bacterial genomes, and discuss in detail analysis of a set of 68 finished E. coli and Shigella genomes and a set of the same genomes to which have been added 47 assemblies and four “raw read” genomes of H104:H4 strains from the recent European E. coli outbreak that resulted in both bloody diarrhea and hemolytic uremic syndrome (HUS), and caused at least 50 deaths. PMID:24349125

When whole-genome alignments just won't work: kSNP v2 software for alignment-free SNP discovery and phylogenetics of hundreds of microbial genomes.

PubMed

Gardner, Shea N; Hall, Barry G

2013-01-01

Effective use of rapid and inexpensive whole genome sequencing for microbes requires fast, memory efficient bioinformatics tools for sequence comparison. The kSNP v2 software finds single nucleotide polymorphisms (SNPs) in whole genome data. kSNP v2 has numerous improvements over kSNP v1 including SNP gene annotation; better scaling for draft genomes available as assembled contigs or raw, unassembled reads; a tool to identify the optimal value of k; distribution of packages of executables for Linux and Mac OS X for ease of installation and user-friendly use; and a detailed User Guide. SNP discovery is based on k-mer analysis, and requires no multiple sequence alignment or the selection of a single reference genome. Most target sets with hundreds of genomes complete in minutes to hours. SNP phylogenies are built by maximum likelihood, parsimony, and distance, based on all SNPs, only core SNPs, or SNPs present in some intermediate user-specified fraction of targets. The SNP-based trees that result are consistent with known taxonomy. kSNP v2 can handle many gigabases of sequence in a single run, and if one or more annotated genomes are included in the target set, SNPs are annotated with protein coding and other information (UTRs, etc.) from Genbank file(s). We demonstrate application of kSNP v2 on sets of viral and bacterial genomes, and discuss in detail analysis of a set of 68 finished E. coli and Shigella genomes and a set of the same genomes to which have been added 47 assemblies and four "raw read" genomes of H104:H4 strains from the recent European E. coli outbreak that resulted in both bloody diarrhea and hemolytic uremic syndrome (HUS), and caused at least 50 deaths.

Core Genome Multilocus Sequence Typing Scheme for High-Resolution Typing of Enterococcus faecium

PubMed Central

de Been, Mark; Pinholt, Mette; Top, Janetta; Bletz, Stefan; van Schaik, Willem; Brouwer, Ellen; Rogers, Malbert; Kraat, Yvette; Bonten, Marc; Corander, Jukka; Westh, Henrik; Harmsen, Dag

2015-01-01

Enterococcus faecium, a common inhabitant of the human gut, has emerged in the last 2 decades as an important multidrug-resistant nosocomial pathogen. Since the start of the 21st century, multilocus sequence typing (MLST) has been used to study the molecular epidemiology of E. faecium. However, due to the use of a small number of genes, the resolution of MLST is limited. Whole-genome sequencing (WGS) now allows for high-resolution tracing of outbreaks, but current WGS-based approaches lack standardization, rendering them less suitable for interlaboratory prospective surveillance. To overcome this limitation, we developed a core genome MLST (cgMLST) scheme for E. faecium. cgMLST transfers genome-wide single nucleotide polymorphism (SNP) diversity into a standardized and portable allele numbering system that is far less computationally intensive than SNP-based analysis of WGS data. The E. faecium cgMLST scheme was built using 40 genome sequences that represented the diversity of the species. The scheme consists of 1,423 cgMLST target genes. To test the performance of the scheme, we performed WGS analysis of 103 outbreak isolates from five different hospitals in the Netherlands, Denmark, and Germany. The cgMLST scheme performed well in distinguishing between epidemiologically related and unrelated isolates, even between those that had the same sequence type (ST), which denotes the higher discriminatory power of this cgMLST scheme over that of conventional MLST. We also show that in terms of resolution, the performance of the E. faecium cgMLST scheme is equivalent to that of an SNP-based approach. In conclusion, the cgMLST scheme developed in this study facilitates rapid, standardized, and high-resolution tracing of E. faecium outbreaks. PMID:26400782

Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS

PubMed Central

Wang, Yunpeng; Thompson, Wesley K.; Schork, Andrew J.; Holland, Dominic; Chen, Chi-Hua; Bettella, Francesco; Desikan, Rahul S.; Li, Wen; Witoelar, Aree; Zuber, Verena; Devor, Anna; Nöthen, Markus M.; Rietschel, Marcella; Chen, Qiang; Werge, Thomas; Cichon, Sven; Weinberger, Daniel R.; Djurovic, Srdjan; O’Donovan, Michael; Visscher, Peter M.; Andreassen, Ole A.; Dale, Anders M.

2016-01-01

Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3. PMID:26808560

Whole-genome-based Mycobacterium tuberculosis surveillance: a standardized, portable, and expandable approach.

PubMed

Kohl, Thomas A; Diel, Roland; Harmsen, Dag; Rothgänger, Jörg; Walter, Karen Meywald; Merker, Matthias; Weniger, Thomas; Niemann, Stefan

2014-07-01

Whole-genome sequencing (WGS) allows for effective tracing of Mycobacterium tuberculosis complex (MTBC) (tuberculosis pathogens) transmission. However, it is difficult to standardize and, therefore, is not yet employed for interlaboratory prospective surveillance. To allow its widespread application, solutions for data standardization and storage in an easily expandable database are urgently needed. To address this question, we developed a core genome multilocus sequence typing (cgMLST) scheme for clinical MTBC isolates using the Ridom SeqSphere(+) software, which transfers the genome-wide single nucleotide polymorphism (SNP) diversity into an allele numbering system that is standardized, portable, and not computationally intensive. To test its performance, we performed WGS analysis of 26 isolates with identical IS6110 DNA fingerprints and spoligotyping patterns from a longitudinal outbreak in the federal state of Hamburg, Germany (notified between 2001 and 2010). The cgMLST approach (3,041 genes) discriminated the 26 strains with a resolution comparable to that of SNP-based WGS typing (one major cluster of 22 identical or closely related and four outlier isolates with at least 97 distinct SNPs or 63 allelic variants). Resulting tree topologies are highly congruent and grouped the isolates in both cases analogously. Our data show that SNP- and cgMLST-based WGS analyses facilitate high-resolution discrimination of longitudinal MTBC outbreaks. cgMLST allows for a meaningful epidemiological interpretation of the WGS genotyping data. It enables standardized WGS genotyping for epidemiological investigations, e.g., on the regional public health office level, and the creation of web-accessible databases for global TB surveillance with an integrated early warning system. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Core Genome Multilocus Sequence Typing Scheme for High- Resolution Typing of Enterococcus faecium.

PubMed

de Been, Mark; Pinholt, Mette; Top, Janetta; Bletz, Stefan; Mellmann, Alexander; van Schaik, Willem; Brouwer, Ellen; Rogers, Malbert; Kraat, Yvette; Bonten, Marc; Corander, Jukka; Westh, Henrik; Harmsen, Dag; Willems, Rob J L

2015-12-01

Enterococcus faecium, a common inhabitant of the human gut, has emerged in the last 2 decades as an important multidrug-resistant nosocomial pathogen. Since the start of the 21st century, multilocus sequence typing (MLST) has been used to study the molecular epidemiology of E. faecium. However, due to the use of a small number of genes, the resolution of MLST is limited. Whole-genome sequencing (WGS) now allows for high-resolution tracing of outbreaks, but current WGS-based approaches lack standardization, rendering them less suitable for interlaboratory prospective surveillance. To overcome this limitation, we developed a core genome MLST (cgMLST) scheme for E. faecium. cgMLST transfers genome-wide single nucleotide polymorphism(SNP) diversity into a standardized and portable allele numbering system that is far less computationally intensive than SNP-based analysis of WGS data. The E. faecium cgMLST scheme was built using 40 genome sequences that represented the diversity of the species. The scheme consists of 1,423 cgMLST target genes. To test the performance of the scheme, we performed WGS analysis of 103 outbreak isolates from five different hospitals in the Netherlands, Denmark, and Germany. The cgMLST scheme performed well in distinguishing between epidemiologically related and unrelated isolates, even between those that had the same sequence type (ST), which denotes the higher discriminatory power of this cgMLST scheme over that of conventional MLST. We also show that in terms of resolution, the performance of the E. faecium cgMLST scheme is equivalent to that of an SNP-based approach. In conclusion, the cgMLST scheme developed in this study facilitates rapid, standardized, and high-resolution tracing of E. faecium outbreaks.

Targeted and Untargeted Approaches Unravel Novel Candidate Genes and Diagnostic SNPs for Quantitative Resistance of the Potato (Solanum tuberosum L.) to Phytophthora infestans Causing the Late Blight Disease.

PubMed

Mosquera, Teresa; Alvarez, Maria Fernanda; Jiménez-Gómez, José M; Muktar, Meki Shehabu; Paulo, Maria João; Steinemann, Sebastian; Li, Jinquan; Draffehn, Astrid; Hofmann, Andrea; Lübeck, Jens; Strahwald, Josef; Tacke, Eckhard; Hofferbert, Hans-Reinhardt; Walkemeier, Birgit; Gebhardt, Christiane

2016-01-01

The oomycete Phytophthora infestans causes late blight of potato, which can completely destroy the crop. Therefore, for the past 160 years, late blight has been the most important potato disease worldwide. The identification of cultivars with high and durable field resistance to P. infestans is an objective of most potato breeding programs. This type of resistance is polygenic and therefore quantitative. Its evaluation requires multi-year and location trials. Furthermore, quantitative resistance to late blight correlates with late plant maturity, a negative agricultural trait. Knowledge of the molecular genetic basis of quantitative resistance to late blight not compromised by late maturity is very limited. It is however essential for developing diagnostic DNA markers that facilitate the efficient combination of superior resistance alleles in improved cultivars. We used association genetics in a population of 184 tetraploid potato cultivars in order to identify single nucleotide polymorphisms (SNPs) that are associated with maturity corrected resistance (MCR) to late blight. The population was genotyped for almost 9000 SNPs from three different sources. The first source was candidate genes specifically selected for their function in the jasmonate pathway. The second source was novel candidate genes selected based on comparative transcript profiling (RNA-Seq) of groups of genotypes with contrasting levels of quantitative resistance to P. infestans. The third source was the first generation 8.3k SolCAP SNP genotyping array available in potato for genome wide association studies (GWAS). Twenty seven SNPs from all three sources showed robust association with MCR. Some of those were located in genes that are strong candidates for directly controlling quantitative resistance, based on functional annotation. Most important were: a lipoxygenase (jasmonate pathway), a 3-hydroxy-3-methylglutaryl coenzyme A reductase (mevalonate pathway), a P450 protein (terpene biosynthesis), a transcription factor and a homolog of a major gene for resistance to P. infestans from the wild potato species Solanum venturii. The candidate gene approach and GWAS complemented each other as they identified different genes. The results of this study provide new insight in the molecular genetic basis of quantitative resistance in potato and a toolbox of diagnostic SNP markers for breeding applications.

Targeted and Untargeted Approaches Unravel Novel Candidate Genes and Diagnostic SNPs for Quantitative Resistance of the Potato (Solanum tuberosum L.) to Phytophthora infestans Causing the Late Blight Disease

PubMed Central

Jiménez-Gómez, José M.; Muktar, Meki Shehabu; Paulo, Maria João; Steinemann, Sebastian; Li, Jinquan; Draffehn, Astrid; Hofmann, Andrea; Lübeck, Jens; Strahwald, Josef; Tacke, Eckhard; Hofferbert, Hans-Reinhardt; Walkemeier, Birgit; Gebhardt, Christiane

2016-01-01

The oomycete Phytophthora infestans causes late blight of potato, which can completely destroy the crop. Therefore, for the past 160 years, late blight has been the most important potato disease worldwide. The identification of cultivars with high and durable field resistance to P. infestans is an objective of most potato breeding programs. This type of resistance is polygenic and therefore quantitative. Its evaluation requires multi-year and location trials. Furthermore, quantitative resistance to late blight correlates with late plant maturity, a negative agricultural trait. Knowledge of the molecular genetic basis of quantitative resistance to late blight not compromised by late maturity is very limited. It is however essential for developing diagnostic DNA markers that facilitate the efficient combination of superior resistance alleles in improved cultivars. We used association genetics in a population of 184 tetraploid potato cultivars in order to identify single nucleotide polymorphisms (SNPs) that are associated with maturity corrected resistance (MCR) to late blight. The population was genotyped for almost 9000 SNPs from three different sources. The first source was candidate genes specifically selected for their function in the jasmonate pathway. The second source was novel candidate genes selected based on comparative transcript profiling (RNA-Seq) of groups of genotypes with contrasting levels of quantitative resistance to P. infestans. The third source was the first generation 8.3k SolCAP SNP genotyping array available in potato for genome wide association studies (GWAS). Twenty seven SNPs from all three sources showed robust association with MCR. Some of those were located in genes that are strong candidates for directly controlling quantitative resistance, based on functional annotation. Most important were: a lipoxygenase (jasmonate pathway), a 3-hydroxy-3-methylglutaryl coenzyme A reductase (mevalonate pathway), a P450 protein (terpene biosynthesis), a transcription factor and a homolog of a major gene for resistance to P. infestans from the wild potato species Solanum venturii. The candidate gene approach and GWAS complemented each other as they identified different genes. The results of this study provide new insight in the molecular genetic basis of quantitative resistance in potato and a toolbox of diagnostic SNP markers for breeding applications. PMID:27281327

Automated analysis of siRNA screens of cells infected by hepatitis C and dengue viruses based on immunofluorescence microscopy images

NASA Astrophysics Data System (ADS)

Matula, Petr; Kumar, Anil; Wörz, Ilka; Harder, Nathalie; Erfle, Holger; Bartenschlager, Ralf; Eils, Roland; Rohr, Karl

2008-03-01

We present an image analysis approach as part of a high-throughput microscopy siRNA-based screening system using cell arrays for the identification of cellular genes involved in hepatitis C and dengue virus replication. Our approach comprises: cell nucleus segmentation, quantification of virus replication level in the neighborhood of segmented cell nuclei, localization of regions with transfected cells, cell classification by infection status, and quality assessment of an experiment and single images. In particular, we propose a novel approach for the localization of regions of transfected cells within cell array images, which combines model-based circle fitting and grid fitting. By this scheme we integrate information from single cell array images and knowledge from the complete cell arrays. The approach is fully automatic and has been successfully applied to a large number of cell array images from screening experiments. The experimental results show a good agreement with the expected behaviour of positive as well as negative controls and encourage the application to screens from further high-throughput experiments.

Validation of Genotyping-By-Sequencing Analysis in Populations of Tetraploid Alfalfa by 454 Sequencing

PubMed Central

Rocher, Solen; Jean, Martine; Castonguay, Yves; Belzile, François

2015-01-01

Genotyping-by-sequencing (GBS) is a relatively low-cost high throughput genotyping technology based on next generation sequencing and is applicable to orphan species with no reference genome. A combination of genome complexity reduction and multiplexing with DNA barcoding provides a simple and affordable way to resolve allelic variation between plant samples or populations. GBS was performed on ApeKI libraries using DNA from 48 genotypes each of two heterogeneous populations of tetraploid alfalfa (Medicago sativa spp. sativa): the synthetic cultivar Apica (ATF0) and a derived population (ATF5) obtained after five cycles of recurrent selection for superior tolerance to freezing (TF). Nearly 400 million reads were obtained from two lanes of an Illumina HiSeq 2000 sequencer and analyzed with the Universal Network-Enabled Analysis Kit (UNEAK) pipeline designed for species with no reference genome. Following the application of whole dataset-level filters, 11,694 single nucleotide polymorphism (SNP) loci were obtained. About 60% had a significant match on the Medicago truncatula syntenic genome. The accuracy of allelic ratios and genotype calls based on GBS data was directly assessed using 454 sequencing on a subset of SNP loci scored in eight plant samples. Sequencing depth in this study was not sufficient for accurate tetraploid allelic dosage, but reliable genotype calls based on diploid allelic dosage were obtained when using additional quality filtering. Principal Component Analysis of SNP loci in plant samples revealed that a small proportion (<5%) of the genetic variability assessed by GBS is able to differentiate ATF0 and ATF5. Our results confirm that analysis of GBS data using UNEAK is a reliable approach for genome-wide discovery of SNP loci in outcrossed polyploids. PMID:26115486

A Nonsynonymous SNP Catalog of Mycobacterium tuberculosis Virulence Genes and Its Use for Detecting New Potentially Virulent Sublineages.

PubMed

Mikheecheva, Natalya E; Zaychikova, Marina V; Melerzanov, Alexander V; Danilenko, Valery N

2017-04-01

Mycobacterium tuberculosis is divided into several distinct lineages, and various genetic markers such as IS-elements, VNTR, and SNPs are used for lineage identification. We propose an M. tuberculosis classification approach based on functional polymorphisms in virulence genes. An M. tuberculosis virulence genes catalog has been established, including 319 genes from various protein groups, such as proteases, cell wall proteins, fatty acid and lipid metabolism proteins, sigma factors, toxin-antitoxin systems. Another catalog of 1,573 M. tuberculosis isolates of different lineages has been developed. The developed SNP-calling program has identified 3,563 nonsynonymous SNPs. The constructed SNP-based phylogeny reflected the evolutionary relationship between lineages and detected new sublineages. SNP analysis of sublineage F15/LAM4/KZN revealed four lineage-specific mutations in cyp125, mce3B, vapC25, and vapB34. The Ural lineage has been divided into two geographical clusters based on different SNPs in virulence genes. A new sublineage, B0/N-90, was detected inside the Beijing-B0/W-148 by SNPs in irtB, mce3F and vapC46. We have found 27 members of B0/N-90 among the 227 available genomes of the Beijing-B0/W-148 sublineage. Whole-genome sequencing of strain B9741, isolated from an HIV-positive patient, was demonstrated to belong to the new B0/N-90 group. A primer set for PCR detection of B0/N-90 lineage-specific mutations has been developed. The prospective use of mce3 mutant genes as genetically engineered vaccine is discussed. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Single tube genotyping of sickle cell anaemia using PCR-based SNP analysis

PubMed Central

Waterfall, Christy M.; Cobb, Benjamin D.

2001-01-01

Allele-specific amplification (ASA) is a generally applicable technique for the detection of known single nucleotide polymorphisms (SNPs), deletions, insertions and other sequence variations. Conventionally, two reactions are required to determine the zygosity of DNA in a two-allele system, along with significant upstream optimisation to define the specific test conditions. Here, we combine single tube bi-directional ASA with a ‘matrix-based’ optimisation strategy, speeding up the whole process in a reduced reaction set. We use sickle cell anaemia as our model SNP system, a genetic disease that is currently screened using ASA methods. Discriminatory conditions were rapidly optimised enabling the unambiguous identification of DNA from homozygous sickle cell patients (HbS/S), heterozygous carriers (HbA/S) or normal DNA in a single tube. Simple downstream mathematical analyses based on product yield across the optimisation set allow an insight into the important aspects of priming competition and component interactions in this competitive PCR. This strategy can be applied to any polymorphism, defining specific conditions using a multifactorial approach. The inherent simplicity and low cost of this PCR-based method validates bi-directional ASA as an effective tool in future clinical screening and pharmacogenomic research where more expensive fluorescence-based approaches may not be desirable. PMID:11726702

Efficient computation of significance levels for multiple associations in large studies of correlated data, including genomewide association studies.

PubMed

Dudbridge, Frank; Koeleman, Bobby P C

2004-09-01

Large exploratory studies, including candidate-gene-association testing, genomewide linkage-disequilibrium scans, and array-expression experiments, are becoming increasingly common. A serious problem for such studies is that statistical power is compromised by the need to control the false-positive rate for a large family of tests. Because multiple true associations are anticipated, methods have been proposed that combine evidence from the most significant tests, as a more powerful alternative to individually adjusted tests. The practical application of these methods is currently limited by a reliance on permutation testing to account for the correlated nature of single-nucleotide polymorphism (SNP)-association data. On a genomewide scale, this is both very time-consuming and impractical for repeated explorations with standard marker panels. Here, we alleviate these problems by fitting analytic distributions to the empirical distribution of combined evidence. We fit extreme-value distributions for fixed lengths of combined evidence and a beta distribution for the most significant length. An initial phase of permutation sampling is required to fit these distributions, but it can be completed more quickly than a simple permutation test and need be done only once for each panel of tests, after which the fitted parameters give a reusable calibration of the panel. Our approach is also a more efficient alternative to a standard permutation test. We demonstrate the accuracy of our approach and compare its efficiency with that of permutation tests on genomewide SNP data released by the International HapMap Consortium. The estimation of analytic distributions for combined evidence will allow these powerful methods to be applied more widely in large exploratory studies.

Bovine exome sequence analysis and targeted SNP genotyping of recessive fertility defects BH1, HH2, and HH3 reveal a putative causative mutation in SMC2 for HH3.

PubMed

McClure, Matthew C; Bickhart, Derek; Null, Dan; Vanraden, Paul; Xu, Lingyang; Wiggans, George; Liu, George; Schroeder, Steve; Glasscock, Jarret; Armstrong, Jon; Cole, John B; Van Tassell, Curtis P; Sonstegard, Tad S

2014-01-01

The recent discovery of bovine haplotypes with negative effects on fertility in the Brown Swiss, Holstein, and Jersey breeds has allowed producers to identify carrier animals using commercial single nucleotide polymorphism (SNP) genotyping assays. This study was devised to identify the causative mutations underlying defective bovine embryo development contained within three of these haplotypes (Brown Swiss haplotype 1 and Holstein haplotypes 2 and 3) by combining exome capture with next generation sequencing. Of the 68,476,640 sequence variations (SV) identified, only 1,311 genome-wide SNP were concordant with the haplotype status of 21 sequenced carriers. Validation genotyping of 36 candidate SNP identified only 1 variant that was concordant to Holstein haplotype 3 (HH3), while no variants located within the refined intervals for HH2 or BH1 were concordant. The variant strictly associated with HH3 is a non-synonymous SNP (T/C) within exon 24 of the Structural Maintenance of Chromosomes 2 (SMC2) on Chromosome 8 at position 95,410,507 (UMD3.1). This polymorphism changes amino acid 1135 from phenylalanine to serine and causes a non-neutral, non-tolerated, and evolutionarily unlikely substitution within the NTPase domain of the encoded protein. Because only exome capture sequencing was used, we could not rule out the possibility that the true causative mutation for HH3 might lie in a non-exonic genomic location. Given the essential role of SMC2 in DNA repair, chromosome condensation and segregation during cell division, our findings strongly support the non-synonymous SNP (T/C) in SMC2 as the likely causative mutation. The absence of concordant variations for HH2 or BH1 suggests either the underlying causative mutations lie within a non-exomic region or in exome regions not covered by the capture array.

Bovine Exome Sequence Analysis and Targeted SNP Genotyping of Recessive Fertility Defects BH1, HH2, and HH3 Reveal a Putative Causative Mutation in SMC2 for HH3

PubMed Central

McClure, Matthew C.; Bickhart, Derek; Null, Dan; VanRaden, Paul; Xu, Lingyang; Wiggans, George; Liu, George; Schroeder, Steve; Glasscock, Jarret; Armstrong, Jon; Cole, John B.; Van Tassell, Curtis P.; Sonstegard, Tad S.

2014-01-01

The recent discovery of bovine haplotypes with negative effects on fertility in the Brown Swiss, Holstein, and Jersey breeds has allowed producers to identify carrier animals using commercial single nucleotide polymorphism (SNP) genotyping assays. This study was devised to identify the causative mutations underlying defective bovine embryo development contained within three of these haplotypes (Brown Swiss haplotype 1 and Holstein haplotypes 2 and 3) by combining exome capture with next generation sequencing. Of the 68,476,640 sequence variations (SV) identified, only 1,311 genome-wide SNP were concordant with the haplotype status of 21 sequenced carriers. Validation genotyping of 36 candidate SNP identified only 1 variant that was concordant to Holstein haplotype 3 (HH3), while no variants located within the refined intervals for HH2 or BH1 were concordant. The variant strictly associated with HH3 is a non-synonymous SNP (T/C) within exon 24 of the Structural Maintenance of Chromosomes 2 (SMC2) on Chromosome 8 at position 95,410,507 (UMD3.1). This polymorphism changes amino acid 1135 from phenylalanine to serine and causes a non-neutral, non-tolerated, and evolutionarily unlikely substitution within the NTPase domain of the encoded protein. Because only exome capture sequencing was used, we could not rule out the possibility that the true causative mutation for HH3 might lie in a non-exonic genomic location. Given the essential role of SMC2 in DNA repair, chromosome condensation and segregation during cell division, our findings strongly support the non-synonymous SNP (T/C) in SMC2 as the likely causative mutation. The absence of concordant variations for HH2 or BH1 suggests either the underlying causative mutations lie within a non-exomic region or in exome regions not covered by the capture array. PMID:24667746

The Mobilome; A Major Contributor to Escherichia coli stx2-Positive O26:H11 Strains Intra-Serotype Diversity.

PubMed

Delannoy, Sabine; Mariani-Kurkdjian, Patricia; Webb, Hattie E; Bonacorsi, Stephane; Fach, Patrick

2017-01-01

Shiga toxin-producing Escherichia coli of serotype O26:H11/H- constitute a diverse group of strains and several clones with distinct genetic characteristics have been identified and characterized. Whole genome sequencing was performed using Illumina and PacBio technologies on eight stx2 -positive O26:H11 strains circulating in France. Comparative analyses of the whole genome of the stx2 -positive O26:H11 strains indicate that several clones of EHEC O26:H11 are co-circulating in France. Phylogenetic analysis of the French strains together with stx2 -positive and stx -negative E. coli O26:H11 genomes obtained from Genbank indicates the existence of four clonal complexes (SNP-CCs) separated in two distinct lineages, one of which comprises the "new French clone" (SNP-CC1) that appears genetically closely related to stx -negative attaching and effacing E. coli (AEEC) strains. Interestingly, the whole genome SNP (wgSNP) phylogeny is summarized in the cas gene phylogeny, and a simple qPCR assay targeting the CRISPR array specific to SNP-CC1 (SP_O26-E) can distinguish between the two main lineages. The PacBio sequencing allowed a detailed analysis of the mobile genetic elements (MGEs) of the strains. Numerous MGEs were identified in each strain, including a large number of prophages and up to four large plasmids, representing overall 8.7-19.8% of the total genome size. Analysis of the prophage pool of the strains shows a considerable diversity with a complex history of recombination. Each clonal complex (SNP-CC) is characterized by a unique set of plasmids and phages, including stx -prophages, suggesting evolution through separate acquisition events. Overall, the MGEs appear to play a major role in O26:H11 intra-serotype clonal diversification.

The Mobilome; A Major Contributor to Escherichia coli stx2-Positive O26:H11 Strains Intra-Serotype Diversity

PubMed Central

Delannoy, Sabine; Mariani-Kurkdjian, Patricia; Webb, Hattie E.; Bonacorsi, Stephane; Fach, Patrick

2017-01-01

Shiga toxin-producing Escherichia coli of serotype O26:H11/H- constitute a diverse group of strains and several clones with distinct genetic characteristics have been identified and characterized. Whole genome sequencing was performed using Illumina and PacBio technologies on eight stx2-positive O26:H11 strains circulating in France. Comparative analyses of the whole genome of the stx2-positive O26:H11 strains indicate that several clones of EHEC O26:H11 are co-circulating in France. Phylogenetic analysis of the French strains together with stx2-positive and stx-negative E. coli O26:H11 genomes obtained from Genbank indicates the existence of four clonal complexes (SNP-CCs) separated in two distinct lineages, one of which comprises the “new French clone” (SNP-CC1) that appears genetically closely related to stx-negative attaching and effacing E. coli (AEEC) strains. Interestingly, the whole genome SNP (wgSNP) phylogeny is summarized in the cas gene phylogeny, and a simple qPCR assay targeting the CRISPR array specific to SNP-CC1 (SP_O26-E) can distinguish between the two main lineages. The PacBio sequencing allowed a detailed analysis of the mobile genetic elements (MGEs) of the strains. Numerous MGEs were identified in each strain, including a large number of prophages and up to four large plasmids, representing overall 8.7–19.8% of the total genome size. Analysis of the prophage pool of the strains shows a considerable diversity with a complex history of recombination. Each clonal complex (SNP-CC) is characterized by a unique set of plasmids and phages, including stx-prophages, suggesting evolution through separate acquisition events. Overall, the MGEs appear to play a major role in O26:H11 intra-serotype clonal diversification. PMID:28932209

Identification of the mechanism underlying a human chimera by SNP array analysis.

PubMed

Shin, So Youn; Yoo, Han-Wook; Lee, Beom Hee; Kim, Kun Suk; Seo, Eul-Ju

2012-09-01

Human chimerism resulting from the fusion of two different zygotes is a rare phenomenon. Two mechanisms of chimerism have been hypothesized: dispermic fertilization of an oocyte and its second polar body and dispermic fertilization of two identical gametes from parthenogenetic activation, and these can be identified and discriminated using DNA polymorphism. In the present study we describe a patient with chimerism presenting as a true hermaphrodite and applied single nucleotide polymorphism array analysis to demonstrate dispermic fertilization of two identical gametes from parthenogenetic activation as the underlying mechanism at the whole chromosome level. We suggest that application of genotyping array analysis to the diagnostic process in patients with disorders of sex development will help identify more human chimera patients and increase our understanding of the underlying mechanisms. Copyright © 2012 Wiley Periodicals, Inc.

Computational intelligence in bioinformatics: SNP/haplotype data in genetic association study for common diseases.

PubMed

Kelemen, Arpad; Vasilakos, Athanasios V; Liang, Yulan

2009-09-01

Comprehensive evaluation of common genetic variations through association of single-nucleotide polymorphism (SNP) structure with common complex disease in the genome-wide scale is currently a hot area in human genome research due to the recent development of the Human Genome Project and HapMap Project. Computational science, which includes computational intelligence (CI), has recently become the third method of scientific enquiry besides theory and experimentation. There have been fast growing interests in developing and applying CI in disease mapping using SNP and haplotype data. Some of the recent studies have demonstrated the promise and importance of CI for common complex diseases in genomic association study using SNP/haplotype data, especially for tackling challenges, such as gene-gene and gene-environment interactions, and the notorious "curse of dimensionality" problem. This review provides coverage of recent developments of CI approaches for complex diseases in genetic association study with SNP/haplotype data.

Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers

PubMed Central

2010-01-01

Background At the current price, the use of high-density single nucleotide polymorphisms (SNP) genotyping assays in genomic selection of dairy cattle is limited to applications involving elite sires and dams. The objective of this study was to evaluate the use of low-density assays to predict direct genomic value (DGV) on five milk production traits, an overall conformation trait, a survival index, and two profit index traits (APR, ASI). Methods Dense SNP genotypes were available for 42,576 SNP for 2,114 Holstein bulls and 510 cows. A subset of 1,847 bulls born between 1955 and 2004 was used as a training set to fit models with various sets of pre-selected SNP. A group of 297 bulls born between 2001 and 2004 and all cows born between 1992 and 2004 were used to evaluate the accuracy of DGV prediction. Ridge regression (RR) and partial least squares regression (PLSR) were used to derive prediction equations and to rank SNP based on the absolute value of the regression coefficients. Four alternative strategies were applied to select subset of SNP, namely: subsets of the highest ranked SNP for each individual trait, or a single subset of evenly spaced SNP, where SNP were selected based on their rank for ASI, APR or minor allele frequency within intervals of approximately equal length. Results RR and PLSR performed very similarly to predict DGV, with PLSR performing better for low-density assays and RR for higher-density SNP sets. When using all SNP, DGV predictions for production traits, which have a higher heritability, were more accurate (0.52-0.64) than for survival (0.19-0.20), which has a low heritability. The gain in accuracy using subsets that included the highest ranked SNP for each trait was marginal (5-6%) over a common set of evenly spaced SNP when at least 3,000 SNP were used. Subsets containing 3,000 SNP provided more than 90% of the accuracy that could be achieved with a high-density assay for cows, and 80% of the high-density assay for young bulls. Conclusions Accurate genomic evaluation of the broader bull and cow population can be achieved with a single genotyping assays containing ~ 3,000 to 5,000 evenly spaced SNP. PMID:20950478

A Robust Sound Source Localization Approach for Microphone Array with Model Errors

NASA Astrophysics Data System (ADS)

Xiao, Hua; Shao, Huai-Zong; Peng, Qi-Cong

In this paper, a robust sound source localization approach is proposed. The approach retains good performance even when model errors exist. Compared with previous work in this field, the contributions of this paper are as follows. First, an improved broad-band and near-field array model is proposed. It takes array gain, phase perturbations into account and is based on the actual positions of the elements. It can be used in arbitrary planar geometry arrays. Second, a subspace model errors estimation algorithm and a Weighted 2-Dimension Multiple Signal Classification (W2D-MUSIC) algorithm are proposed. The subspace model errors estimation algorithm estimates unknown parameters of the array model, i. e., gain, phase perturbations, and positions of the elements, with high accuracy. The performance of this algorithm is improved with the increasing of SNR or number of snapshots. The W2D-MUSIC algorithm based on the improved array model is implemented to locate sound sources. These two algorithms compose the robust sound source approach. The more accurate steering vectors can be provided for further processing such as adaptive beamforming algorithm. Numerical examples confirm effectiveness of this proposed approach.

Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes

PubMed Central

Gong, Bin-Sheng; Zhang, Qing-Pu; Zhang, Guang-Mei; Zhang, Shao-Jun; Zhang, Wei; Lv, Hong-Chao; Zhang, Fan; Lv, Sa-Li; Li, Chuan-Xing; Rao, Shao-Qi; Li, Xia

2007-01-01

Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as expression traits. And relationships among the genes, which were co-linked to a common SNP(s), were identified by integrating the two types of information. Further research on the co-expressions among the co-linked genes was carried out after the gene-SNP relationships were established using the Haseman-Elston sib-pair regression. The results showed that the co-expressions among the co-linked genes were significantly higher if the number of connections between the genes and a SNP(s) was more than six. Then, the genes were interconnected via one or more SNP co-linkers to construct a gene-SNP intermixed network. The genes sharing more SNPs tended to have a stronger correlation. Finally, a gene-gene network was constructed with their intensities of relationships (the number of SNP co-linkers shared) as the weights for the edges. PMID:18466544

Quantitative 3-d diagnostic ultrasound imaging using a modified transducer array and an automated image tracking technique.

PubMed

Hossack, John A; Sumanaweera, Thilaka S; Napel, Sandy; Ha, Jun S

2002-08-01

An approach for acquiring dimensionally accurate three-dimensional (3-D) ultrasound data from multiple 2-D image planes is presented. This is based on the use of a modified linear-phased array comprising a central imaging array that acquires multiple, essentially parallel, 2-D slices as the transducer is translated over the tissue of interest. Small, perpendicularly oriented, tracking arrays are integrally mounted on each end of the imaging transducer. As the transducer is translated in an elevational direction with respect to the central imaging array, the images obtained by the tracking arrays remain largely coplanar. The motion between successive tracking images is determined using a minimum sum of absolute difference (MSAD) image matching technique with subpixel matching resolution. An initial phantom scanning-based test of a prototype 8 MHz array indicates that linear dimensional accuracy of 4.6% (2 sigma) is achievable. This result compares favorably with those obtained using an assumed average velocity [31.5% (2 sigma) accuracy] and using an approach based on measuring image-to-image decorrelation [8.4% (2 sigma) accuracy]. The prototype array and imaging system were also tested in a clinical environment, and early results suggest that the approach has the potential to enable a low cost, rapid, screening method for detecting carotid artery stenosis. The average time for performing a screening test for carotid stenosis was reduced from an average of 45 minutes using 2-D duplex Doppler to 12 minutes using the new 3-D scanning approach.

Predictive models for subtypes of autism spectrum disorder based on single-nucleotide polymorphisms and magnetic resonance imaging.

PubMed

Jiao, Y; Chen, R; Ke, X; Cheng, L; Chu, K; Lu, Z; Herskovits, E H

2011-01-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, of which Asperger syndrome and high-functioning autism are subtypes. Our goal is: 1) to determine whether a diagnostic model based on single-nucleotide polymorphisms (SNPs), brain regional thickness measurements, or brain regional volume measurements can distinguish Asperger syndrome from high-functioning autism; and 2) to compare the SNP, thickness, and volume-based diagnostic models. Our study included 18 children with ASD: 13 subjects with high-functioning autism and 5 subjects with Asperger syndrome. For each child, we obtained 25 SNPs for 8 ASD-related genes; we also computed regional cortical thicknesses and volumes for 66 brain structures, based on structural magnetic resonance (MR) examination. To generate diagnostic models, we employed five machine-learning techniques: decision stump, alternating decision trees, multi-class alternating decision trees, logistic model trees, and support vector machines. For SNP-based classification, three decision-tree-based models performed better than the other two machine-learning models. The performance metrics for three decision-tree-based models were similar: decision stump was modestly better than the other two methods, with accuracy = 90%, sensitivity = 0.95 and specificity = 0.75. All thickness and volume-based diagnostic models performed poorly. The SNP-based diagnostic models were superior to those based on thickness and volume. For SNP-based classification, rs878960 in GABRB3 (gamma-aminobutyric acid A receptor, beta 3) was selected by all tree-based models. Our analysis demonstrated that SNP-based classification was more accurate than morphometry-based classification in ASD subtype classification. Also, we found that one SNP--rs878960 in GABRB3--distinguishes Asperger syndrome from high-functioning autism.

Association between ABCG1 polymorphism rs1893590 and high-density lipoprotein (HDL) in an asymptomatic Brazilian population.

PubMed

Zago, V H S; Scherrer, D Z; Parra, E S; Panzoldo, N B; Alexandre, F; Nakandakare, E R; Quintão, E C R; de Faria, E C

2015-03-01

ATP binding cassette transporter G1 (ABCG1) promotes lipidation of nascent high-density lipoprotein (HDL) particles, acting as an intracellular transporter. SNP rs1893590 (c.-204A > C) of ABCG1 gene has been previously studied and reported as functional over plasma HDL-C and lipoprotein lipase activity. This study aimed to investigate the relationships of SNP rs1893590 with plasma lipids and lipoproteins in a large Brazilian population. Were selected 654 asymptomatic and normolipidemic volunteers from both genders. Clinical and anthropometrical data were taken and blood samples were drawn after 12 h fasting. Plasma lipids and lipoproteins, as well as HDL particle size and volume were determined. Genomic DNA was isolated for SNP rs1893590 detection by TaqMan(®) OpenArray(®) Real-Time PCR Plataform (Applied Biosystems). Mann-Whitney U, Chi square and two-way ANOVA were the used statistical tests. No significant differences were found in the comparison analyses between the allele groups for all studied parameters. Conversely, significant interactions were observed between SNP and age over plasma HDL-C, were volunteers under 60 years with AA genotype had increased HDL-C (p = 0.048). Similar results were observed in the group with body mass index (BMI) < 25 kg/m(2), where volunteers with AA genotype had higher HDL-C levels (p = 0.0034), plus an increased HDL particle size (p = 0.01). These findings indicate that SNP rs1893590 of ABCG1 has a significant impact over HDL-C under asymptomatic clinical conditions in an age and BMI dependent way.

An intersection network based on combining SNP co-association and RNA co-expression networks for feed utilization traits in Japanese Black cattle.

PubMed

Okada, D; Endo, S; Matsuda, H; Ogawa, S; Taniguchi, Y; Katsuta, T; Watanabe, T; Iwaisaki, H

2018-05-12

Genome-wide association studies (GWAS) of quantitative traits have detected numerous genetic associations, but they encounter difficulties in pinpointing prominent candidate genes and inferring gene networks. The present study used a systems genetics approach integrating GWAS results with external RNA-expression data to detect candidate gene networks in feed utilization and growth traits of Japanese Black cattle, which are matters of concern. A SNP co-association network was derived from significant correlations between SNPs with effects estimated by GWAS across seven phenotypic traits. The resulting network genes contained significant numbers of annotations related to the traits. Using bovine transcriptome data from a public database, an RNA co-expression network was inferred based on the similarity of expression patterns across different tissues. An intersection network was then generated by superimposing the SNP and RNA networks and extracting shared interactions. This intersection network contained four tissue-specific modules: nervous system, reproductive system, muscular system, and glands. To characterize the structure (topographical properties) of the three networks, their scale-free properties were evaluated, which revealed that the intersection network was the most scale-free. In the sub-network containing the most connected transcription factors (URI1, ROCK2 and ETV6), most genes were widely expressed across tissues, and genes previously shown to be involved in the traits were found. Results indicated that the current approach might be used to construct a gene network that better reflects biological information, providing encouragement for the genetic dissection of economically important quantitative traits.

Multicapillary gel electrophoresis based analysis of genetic variants in the WFS1 gene.

PubMed

Elek, Zsuzsanna; Dénes, Réka; Prokop, Susanne; Somogyi, Anikó; Yowanto, Handy; Luo, Jane; Souquet, Manfred; Guttman, András; Rónai, Zsolt

2016-09-01

The WFS1 gene is one of the thoroughly investigated targets in diabetes research, variants of the gene were suggested to be the genetic components of the common forms (type 1 and type 2) of diabetes. Our project focused on the analysis of polymorphisms (rs4689388, rs148797429, rs4273545) localized in the WFS1 promoter region. Although submarine gel electrophoresis based approaches were also employed in the genetic tests, it was demonstrated that multicapillary electrophoresis offers a state of the art approach for reliable high-throughput SNP and VNTR analysis. Association studies were carried out in a case-control setup. Luciferase reporter assay was employed to test the effect of the investigated loci on the activity of gene expression in vitro. Significant association could be demonstrated between all three polymorphisms and type 2 diabetes in both allele- and genotype-wise settings even using Bonferroni correction. It is notable; however, that the three loci were in strong linkage disequilibrium, thus the observed associations cannot be considered as separate effects. Molecular analyses showed that the rs4273545 GT SNP played a role in the regulation of transcription in vitro. However, this effect took place only in the presence of the region including the rs148797429 site, although this latter locus did not have its own impact on the regulation of gene expression. The paper provides genotyping protocols readily applicable in any multiplex SNP and VNTR analyses, moreover confirms and extends previous results about the role of WFS1 polymorphisms in the genetic risk of diabetes mellitus. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

VCS: Tool for Visualizing Copy Number Variation and Single Nucleotide Polymorphism.

PubMed

Kim, HyoYoung; Sung, Samsun; Cho, Seoae; Kim, Tae-Hun; Seo, Kangseok; Kim, Heebal

2014-12-01

Copy number variation (CNV) or single nucleotide phlyorphism (SNP) is useful genetic resource to aid in understanding complex phenotypes or deseases susceptibility. Although thousands of CNVs and SNPs are currently avaliable in the public databases, they are somewhat difficult to use for analyses without visualization tools. We developed a web-based tool called the VCS (visualization of CNV or SNP) to visualize the CNV or SNP detected. The VCS tool can assist to easily interpret a biological meaning from the numerical value of CNV and SNP. The VCS provides six visualization tools: i) the enrichment of genome contents in CNV; ii) the physical distribution of CNV or SNP on chromosomes; iii) the distribution of log2 ratio of CNVs with criteria of interested; iv) the number of CNV or SNP per binning unit; v) the distribution of homozygosity of SNP genotype; and vi) cytomap of genes within CNV or SNP region.

Contrasting analytical and data-driven frameworks for radiogenomic modeling of normal tissue toxicities in prostate cancer.

PubMed

Coates, James; Jeyaseelan, Asha K; Ybarra, Norma; David, Marc; Faria, Sergio; Souhami, Luis; Cury, Fabio; Duclos, Marie; El Naqa, Issam

2015-04-01

We explore analytical and data-driven approaches to investigate the integration of genetic variations (single nucleotide polymorphisms [SNPs] and copy number variations [CNVs]) with dosimetric and clinical variables in modeling radiation-induced rectal bleeding (RB) and erectile dysfunction (ED) in prostate cancer patients. Sixty-two patients who underwent curative hypofractionated radiotherapy (66 Gy in 22 fractions) between 2002 and 2010 were retrospectively genotyped for CNV and SNP rs5489 in the xrcc1 DNA repair gene. Fifty-four patients had full dosimetric profiles. Two parallel modeling approaches were compared to assess the risk of severe RB (Grade⩾3) and ED (Grade⩾1); Maximum likelihood estimated generalized Lyman-Kutcher-Burman (LKB) and logistic regression. Statistical resampling based on cross-validation was used to evaluate model predictive power and generalizability to unseen data. Integration of biological variables xrcc1 CNV and SNP improved the fit of the RB and ED analytical and data-driven models. Cross-validation of the generalized LKB models yielded increases in classification performance of 27.4% for RB and 14.6% for ED when xrcc1 CNV and SNP were included, respectively. Biological variables added to logistic regression modeling improved classification performance over standard dosimetric models by 33.5% for RB and 21.2% for ED models. As a proof-of-concept, we demonstrated that the combination of genetic and dosimetric variables can provide significant improvement in NTCP prediction using analytical and data-driven approaches. The improvement in prediction performance was more pronounced in the data driven approaches. Moreover, we have shown that CNVs, in addition to SNPs, may be useful structural genetic variants in predicting radiation toxicities. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Combination of RNAseq and SNP nanofluidic array reveals the center of genetic diversity of cacao pathogen Moniliophthora roreri in the upper Magdalena Valley of Colombia and its clonality

USDA-ARS?s Scientific Manuscript database

Moniliophthora roreri is the fungal pathogen that causes frosty pod rot (FPR) disease of Theobroma cacao L., the source of chocolate. FPR occurs in most of the cacao producing countries in the Western Hemisphere, causing yield losses up to 80%. Genetic diversity within the FPR pathogen population ma...

Genotype-Phenotype Analysis, Neuropsychological Assessment, and Growth Hormone Response in a Patient with 18p Deletion Syndrome.

PubMed

Sun, Huihui; Wan, Naijun; Wang, Xinli; Chang, Liang; Cheng, Dazhi

2018-01-01

18p deletion syndrome is a rare chromosomal disease caused by deletion of the short arm of chromosome 18. By using cytogenetic and SNP array analysis, we identified a girl with 18p deletion syndrome exhibiting craniofacial anomalies, intellectual disability, and short stature. G-banding analysis of metaphase cells revealed an abnormal karyotype 46,XX,del(18)(p10). Further, SNP array detected a 15.3-Mb deletion at 18p11.21p11.32 (chr18:12842-15375878) including 61 OMIM genes. Genotype-phenotype correlation analysis showed that clinical manifestations of the patient were correlated with LAMA1, TWSG1, and GNAL deletions. Her neuropsychological assessment test demonstrated delay in most cognitive functions including impaired mathematics, linguistic skills, visual motor perception, respond speed, and executive function. Meanwhile, her integrated visual and auditory continuous performance test (IVA-CPT) indicated a severe comprehensive attention deficit. At age 7 and 1/12 years, her height was 110.8 cm (-2.5 SD height for age). Growth hormone (GH) treatment was initiated. After 27 months treatment, her height was increased to 129.6 cm (-1.0 SD height for age) at 9 and 4/12 years, indicating an effective response to GH treatment. © 2018 S. Karger AG, Basel.

Genetic Identity in Genebanks: Application of the SolCAP 12K SNP Array in Fingerprinting and Diversity Analysis in the Global In Trust Potato Collection.

PubMed

Ellis, David; Chavez, Oswaldo; Coombs, Joseph J; Soto, Julian V; Gomez, Rene; Douches, David S; Panta, Ana; Silvestre, Rocio; Anglin, Noelle Lynette

2018-05-24

Breeders rely on genetic integrity of material from genebanks, however, mislabeling and errors in original data can occur. Paired samples of original material and their in vitro counterparts from 250 diverse potato landrace accessions from the International Potato Center (CIP), were fingerprinted using the Infinium 12K V2 Potato Array to confirm genetic identity and evaluate genetic diversity. Diploid, triploid, and tetraploid accessions were included representing seven cultivated potato taxa (Hawkes, 1990). Fingerprints between mother field plants and in vitro clones, were used to evaluate identity, relatedness, and ancestry. Clones of the same accession grouped together, however eleven (4.4%) accessions were mismatches genetically. SNP genotypes were used to construct a phylogeny to evaluate inter- and intraspecific relationships and population structure. Data suggests that the triploids evaluated are genetically similar. STRUCTURE analysis identified several putative hybrids and suggests six populations with significant gene flow between. This study provides a model for genetic identity of plant genetic resources collections as mistakes in conservation of these collections and in genebanks is a reality and confirmed identity is critical for breeders and other users of these collections, as well as for quality management programs and to provide insights into the diversity of the accessions evaluated.

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.

PubMed

Gebreyesus, Grum; Lund, Mogens S; Buitenhuis, Bart; Bovenhuis, Henk; Poulsen, Nina A; Janss, Luc G

2017-12-05

Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls. Single-nucleotide polymorphisms (SNPs), from 50K SNP arrays, were grouped into non-overlapping genome segments. A segment was defined as one SNP, or a group of 50, 100, or 200 adjacent SNPs, or one chromosome, or the whole genome. Traditional univariate and bivariate genomic best linear unbiased prediction (GBLUP) models were also run for comparison. Reliabilities were calculated through a resampling strategy and using deterministic formula. BayesAS models improved prediction reliability for most of the traits compared to GBLUP models and this gain depended on segment size and genetic architecture of the traits. The gain in prediction reliability was especially marked for the protein composition traits β-CN, κ-CN and β-LG, for which prediction reliabilities were improved by 49 percentage points on average using the MT-BayesAS model with a 100-SNP segment size compared to the bivariate GBLUP. Prediction reliabilities were highest with the BayesAS model that uses a 100-SNP segment size. The bivariate versions of our BayesAS models resulted in extra gains of up to 6% in prediction reliability compared to the univariate versions. Substantial improvement in prediction reliability was possible for most of the traits related to milk protein composition using our novel BayesAS models. Grouping adjacent SNPs into segments provided enhanced information to estimate parameters and allowing the segments to have different (co)variances helped disentangle heterogeneous (co)variances across the genome.

Significant variation between SNP-based HLA imputations in diverse populations: the last mile is the hardest.

PubMed

Pappas, D J; Lizee, A; Paunic, V; Beutner, K R; Motyer, A; Vukcevic, D; Leslie, S; Biesiada, J; Meller, J; Taylor, K D; Zheng, X; Zhao, L P; Gourraud, P-A; Hollenbach, J A; Mack, S J; Maiers, M

2018-05-22

Four single nucleotide polymorphism (SNP)-based human leukocyte antigen (HLA) imputation methods (e-HLA, HIBAG, HLA*IMP:02 and MAGPrediction) were trained using 1000 Genomes SNP and HLA genotypes and assessed for their ability to accurately impute molecular HLA-A, -B, -C and -DRB1 genotypes in the Human Genome Diversity Project cell panel. Imputation concordance was high (>89%) across all methods for both HLA-A and HLA-C, but HLA-B and HLA-DRB1 proved generally difficult to impute. Overall, <27.8% of subjects were correctly imputed for all HLA loci by any method. Concordance across all loci was not enhanced via the application of confidence thresholds; reliance on confidence scores across methods only led to noticeable improvement (+3.2%) for HLA-DRB1. As the HLA complex is highly relevant to the study of human health and disease, a standardized assessment of SNP-based HLA imputation methods is crucial for advancing genomic research. Considerable room remains for the improvement of HLA-B and especially HLA-DRB1 imputation methods, and no imputation method is as accurate as molecular genotyping. The application of large, ancestrally diverse HLA and SNP reference data sets and multiple imputation methods has the potential to make SNP-based HLA imputation methods a tractable option for determining HLA genotypes.

No association between SNP rs498055 on chromosome 10 and late-onset Alzheimer disease in multiple datasets.

PubMed

Liang, Xueying; Schnetz-Boutaud, Nathalie; Bartlett, Jackie; Allen, Melissa J; Gwirtsman, Harry; Schmechel, Don E; Carney, Regina M; Gilbert, John R; Pericak-Vance, Margaret A; Haines, Jonathan L

2008-01-01

SNP rs498055 in the predicted gene LOC439999 on chromosome 10 was recently identified as being strongly associated with late-onset Alzheimer disease (LOAD). This SNP falls within a chromosomal region that has engendered continued interest generated from both preliminary genetic linkage and candidate gene studies. To independently evaluate this interesting candidate SNP we examined four independent datasets, three family-based and one case-control. All the cases were late-onset AD Caucasian patients with minimum age at onset >or= 60 years. None of the three family samples or the combined family-based dataset showed association in either allelic or genotypic family-based association tests at p < 0.05. Both original and OSA two-point LOD scores were calculated. However, there was no evidence indicating linkage no matter what covariates were applied (the highest LOD score was 0.82). The case-control dataset did not demonstrate any association between this SNP and AD (all p-values > 0.52). Our results do not confirm the previous association, but are consistent with a more recent negative association result that used family-based association tests to examine the effect of this SNP in two family datasets. Thus we conclude that rs498055 is not associated with an increased risk of LOAD.

Prediction of Disease Causing Non-Synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP

PubMed Central

Johansen, Morten Bo; Izarzugaza, Jose M. G.; Brunak, Søren; Petersen, Thomas Nordahl; Gupta, Ramneek

2013-01-01

We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features assessing sequence conservation and the predicted surface accessibility to produce a single score which can be used to rank nsSNPs based on their potential to cause disease. NetDiseaseSNP classifies successfully disease-causing and neutral mutations. In addition, we show that NetDiseaseSNP discriminates cancer driver and passenger mutations satisfactorily. Our method outperforms other state-of-the-art methods on several disease/neutral datasets as well as on cancer driver/passenger mutation datasets and can thus be used to pinpoint and prioritize plausible disease candidates among nsSNPs for further investigation. NetDiseaseSNP is publicly available as an online tool as well as a web service: http://www.cbs.dtu.dk/services/NetDiseaseSNP PMID:23935863

A survey about methods dedicated to epistasis detection.

PubMed

Niel, Clément; Sinoquet, Christine; Dina, Christian; Rocheleau, Ghislain

2015-01-01

During the past decade, findings of genome-wide association studies (GWAS) improved our knowledge and understanding of disease genetics. To date, thousands of SNPs have been associated with diseases and other complex traits. Statistical analysis typically looks for association between a phenotype and a SNP taken individually via single-locus tests. However, geneticists admit this is an oversimplified approach to tackle the complexity of underlying biological mechanisms. Interaction between SNPs, namely epistasis, must be considered. Unfortunately, epistasis detection gives rise to analytic challenges since analyzing every SNP combination is at present impractical at a genome-wide scale. In this review, we will present the main strategies recently proposed to detect epistatic interactions, along with their operating principle. Some of these methods are exhaustive, such as multifactor dimensionality reduction, likelihood ratio-based tests or receiver operating characteristic curve analysis; some are non-exhaustive, such as machine learning techniques (random forests, Bayesian networks) or combinatorial optimization approaches (ant colony optimization, computational evolution system).

SNP-RFLPing 2: an updated and integrated PCR-RFLP tool for SNP genotyping.

PubMed

Chang, Hsueh-Wei; Cheng, Yu-Huei; Chuang, Li-Yeh; Yang, Cheng-Hong

2010-04-08

PCR-restriction fragment length polymorphism (RFLP) assay is a cost-effective method for SNP genotyping and mutation detection, but the manual mining for restriction enzyme sites is challenging and cumbersome. Three years after we constructed SNP-RFLPing, a freely accessible database and analysis tool for restriction enzyme mining of SNPs, significant improvements over the 2006 version have been made and incorporated into the latest version, SNP-RFLPing 2. The primary aim of SNP-RFLPing 2 is to provide comprehensive PCR-RFLP information with multiple functionality about SNPs, such as SNP retrieval to multiple species, different polymorphism types (bi-allelic, tri-allelic, tetra-allelic or indels), gene-centric searching, HapMap tagSNPs, gene ontology-based searching, miRNAs, and SNP500Cancer. The RFLP restriction enzymes and the corresponding PCR primers for the natural and mutagenic types of each SNP are simultaneously analyzed. All the RFLP restriction enzyme prices are also provided to aid selection. Furthermore, the previously encountered updating problems for most SNP related databases are resolved by an on-line retrieval system. The user interfaces for functional SNP analyses have been substantially improved and integrated. SNP-RFLPing 2 offers a new and user-friendly interface for RFLP genotyping that can be used in association studies and is freely available at http://bio.kuas.edu.tw/snp-rflping2.

Identification of Promising Mutants Associated with Egg Production Traits Revealed by Genome-Wide Association Study.

PubMed

Yuan, Jingwei; Sun, Congjiao; Dou, Taocun; Yi, Guoqiang; Qu, LuJiang; Qu, Liang; Wang, Kehua; Yang, Ning

2015-01-01

Egg number (EN), egg laying rate (LR) and age at first egg (AFE) are important production traits related to egg production in poultry industry. To better understand the knowledge of genetic architecture of dynamic EN during the whole laying cycle and provide the precise positions of associated variants for EN, LR and AFE, laying records from 21 to 72 weeks of age were collected individually for 1,534 F2 hens produced by reciprocal crosses between White Leghorn and Dongxiang Blue-shelled chicken, and their genotypes were assayed by chicken 600 K Affymetrix high density genotyping arrays. Subsequently, pedigree and SNP-based genetic parameters were estimated and a genome-wide association study (GWAS) was conducted on EN, LR and AFE. The heritability estimates were similar between pedigree and SNP-based estimates varying from 0.17 to 0.36. In the GWA analysis, we identified nine genome-wide significant loci associated with EN of the laying periods from 21 to 26 weeks, 27 to 36 weeks and 37 to 72 weeks. Analysis of GTF2A1 and CLSPN suggested that they influenced the function of ovary and uterus, and may be considered as relevant candidates. The identified SNP rs314448799 for accumulative EN from 21 to 40 weeks on chromosome 5 created phenotypic differences of 6.86 eggs between two homozygous genotypes, which could be potentially applied to the molecular breeding for EN selection. Moreover, our finding showed that LR was a moderate polygenic trait. The suggestive significant region on chromosome 16 for AFE suggested the relationship between sex maturity and immune in the current population. The present study comprehensively evaluates the role of genetic variants in the development of egg laying. The findings will be helpful to investigation of causative genes function and future marker-assisted selection and genomic selection in chickens.

Genetic tests for estimating dairy breed proportion and parentage assignment in East African crossbred cattle.

PubMed

Strucken, Eva M; Al-Mamun, Hawlader A; Esquivelzeta-Rabell, Cecilia; Gondro, Cedric; Mwai, Okeyo A; Gibson, John P

2017-09-12

Smallholder dairy farming in much of the developing world is based on the use of crossbred cows that combine local adaptation traits of indigenous breeds with high milk yield potential of exotic dairy breeds. Pedigree recording is rare in such systems which means that it is impossible to make informed breeding decisions. High-density single nucleotide polymorphism (SNP) assays allow accurate estimation of breed composition and parentage assignment but are too expensive for routine application. Our aim was to determine the level of accuracy achieved with low-density SNP assays. We constructed subsets of 100 to 1500 SNPs from the 735k-SNP Illumina panel by selecting: (a) on high minor allele frequencies (MAF) in a crossbred population; (b) on large differences in allele frequency between ancestral breeds; (c) at random; or (d) with a differential evolution algorithm. These panels were tested on a dataset of 1933 crossbred dairy cattle from Kenya/Uganda and on crossbred populations from Ethiopia (N = 545) and Tanzania (N = 462). Dairy breed proportions were estimated by using the ADMIXTURE program, a regression approach, and SNP-best linear unbiased prediction, and tested against estimates obtained by ADMIXTURE based on the 735k-SNP panel. Performance for parentage assignment was based on opposing homozygotes which were used to calculate the separation value (sv) between true and false assignments. Panels of SNPs based on the largest differences in allele frequency between European dairy breeds and a combined Nelore/N'Dama population gave the best predictions of dairy breed proportion (r 2  = 0.962 to 0.994 for 100 to 1500 SNPs) with an average absolute bias of 0.026. Panels of SNPs based on the highest MAF in the crossbred population (Kenya/Uganda) gave the most accurate parentage assignments (sv = -1 to 15 for 100 to 1500 SNPs). Due to the different required properties of SNPs, panels that did well for breed composition did poorly for parentage assignment and vice versa. A combined panel of 400 SNPs was not able to assign parentages correctly, thus we recommend the use of 200 SNPs either for breed proportion prediction or parentage assignment, independently.

Genome-wide SNP discovery and population structure analysis in pepper (Capsicum annuum) using genotyping by sequencing.

PubMed

Taranto, F; D'Agostino, N; Greco, B; Cardi, T; Tripodi, P

2016-11-21

Knowledge on population structure and genetic diversity in vegetable crops is essential for association mapping studies and genomic selection. Genotyping by sequencing (GBS) represents an innovative method for large scale SNP detection and genotyping of genetic resources. Herein we used the GBS approach for the genome-wide identification of SNPs in a collection of Capsicum spp. accessions and for the assessment of the level of genetic diversity in a subset of 222 cultivated pepper (Capsicum annum) genotypes. GBS analysis generated a total of 7,568,894 master tags, of which 43.4% uniquely aligned to the reference genome CM334. A total of 108,591 SNP markers were identified, of which 105,184 were in C. annuum accessions. In order to explore the genetic diversity of C. annuum and to select a minimal core set representing most of the total genetic variation with minimum redundancy, a subset of 222 C. annuum accessions were analysed using 32,950 high quality SNPs. Based on Bayesian and Hierarchical clustering it was possible to divide the collection into three clusters. Cluster I had the majority of varieties and landraces mainly from Southern and Northern Italy, and from Eastern Europe, whereas clusters II and III comprised accessions of different geographical origins. Considering the genome-wide genetic variation among the accessions included in cluster I, a second round of Bayesian (K = 3) and Hierarchical (K = 2) clustering was performed. These analysis showed that genotypes were grouped not only based on geographical origin, but also on fruit-related features. GBS data has proven useful to assess the genetic diversity in a collection of C. annuum accessions. The high number of SNP markers, uniformly distributed on the 12 chromosomes, allowed the accessions to be distinguished according to geographical origin and fruit-related features. SNP markers and information on population structure developed in this study will undoubtedly support genome-wide association mapping studies and marker-assisted selection programs.

The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines.

PubMed

Chen, Jiafa; Zavala, Cristian; Ortega, Noemi; Petroli, Cesar; Franco, Jorge; Burgueño, Juan; Costich, Denise E; Hearne, Sarah J

2016-01-01

Quality control (QC) of germplasm identity and purity is a critical component of breeding and conservation activities. SNP genotyping technologies and increased availability of markers provide the opportunity to employ genotyping as a low-cost and robust component of this QC. In the public sector available low-cost SNP QC genotyping methods have been developed from a very limited panel of markers of 1,000 to 1,500 markers without broad selection of the most informative SNPs. Selection of optimal SNPs and definition of appropriate germplasm sampling in addition to platform section impact on logistical and resource-use considerations for breeding and conservation applications when mainstreaming QC. In order to address these issues, we evaluated the selection and use of SNPs for QC applications from large DArTSeq data sets generated from CIMMYT maize inbred lines (CMLs). Two QC genotyping strategies were developed, the first is a "rapid QC", employing a small number of SNPs to identify potential mislabeling of seed packages or plots, the second is a "broad QC", employing a larger number of SNP, used to identify each germplasm entry and to measure heterogeneity. The optimal marker selection strategies combined the selection of markers with high minor allele frequency, sampling of clustered SNP in proportion to marker cluster distance and selecting markers that maintain a uniform genomic distribution. The rapid and broad QC SNP panels selected using this approach were further validated using blind test assessments of related re-generation samples. The influence of sampling within each line was evaluated. Sampling 192 individuals would result in close to 100% possibility of detecting a 5% contamination in the entry, and approximately a 98% probability to detect a 2% contamination of the line. These results provide a framework for the establishment of QC genotyping. A comparison of financial and time costs for use of these approaches across different platforms is discussed providing a framework for institutions involved in maize conservation and breeding to assess the resource use effectiveness of QC genotyping. Application of these research findings, in combination with existing QC approaches, will ensure the regeneration, distribution and use in breeding of true to type inbred germplasm. These findings also provide an effective approach to optimize SNP selection for QC genotyping in other species.

Species trees from consensus single nucleotide polymorphism (SNP) data: Testing phylogenetic approaches with simulated and empirical data.

PubMed

Schmidt-Lebuhn, Alexander N; Aitken, Nicola C; Chuah, Aaron

2017-11-01

Datasets of hundreds or thousands of SNPs (Single Nucleotide Polymorphisms) from multiple individuals per species are increasingly used to study population structure, species delimitation and shallow phylogenetics. The principal software tool to infer species or population trees from SNP data is currently the BEAST template SNAPP which uses a Bayesian coalescent analysis. However, it is computationally extremely demanding and tolerates only small amounts of missing data. We used simulated and empirical SNPs from plants (Australian Craspedia, Asteraceae, and Pelargonium, Geraniaceae) to compare species trees produced (1) by SNAPP, (2) using SVD quartets, and (3) using Bayesian and parsimony analysis with several different approaches to summarising data from multiple samples into one set of traits per species. Our aims were to explore the impact of tree topology and missing data on the results, and to test which data summarising and analyses approaches would best approximate the results obtained from SNAPP for empirical data. SVD quartets retrieved the correct topology from simulated data, as did SNAPP except in the case of a very unbalanced phylogeny. Both methods failed to retrieve the correct topology when large amounts of data were missing. Bayesian analysis of species level summary data scoring the two alleles of each SNP as independent characters and parsimony analysis of data scoring each SNP as one character produced trees with branch length distributions closest to the true trees on which SNPs were simulated. For empirical data, Bayesian inference and Dollo parsimony analysis of data scored allele-wise produced phylogenies most congruent with the results of SNAPP. In the case of study groups divergent enough for missing data to be phylogenetically informative (because of additional mutations preventing amplification of genomic fragments or bioinformatic establishment of homology), scoring of SNP data as a presence/absence matrix irrespective of allele content might be an additional option. As this depends on sampling across species being reasonably even and a random distribution of non-informative instances of missing data, however, further exploration of this approach is needed. Properly chosen data summary approaches to inferring species trees from SNP data may represent a potential alternative to currently available individual-level coalescent analyses especially for quick data exploration and when dealing with computationally demanding or patchy datasets. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

SEURAT: Visual analytics for the integrated analysis of microarray data

PubMed Central

2010-01-01

Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data. PMID:20525257

Single-nucleotide polymorphism genotyping on optical thin-film biosensor chips.

PubMed

Zhong, Xiao-Bo; Reynolds, Robert; Kidd, Judith R; Kidd, Kenneth K; Jenison, Robert; Marlar, Richard A; Ward, David C

2003-09-30

Single-nucleotide polymorphisms (SNPs) constitute the bulk of human genetic variation and provide excellent markers to identify genetic factors contributing to complex disease susceptibility. A rapid, sensitive, and inexpensive assay is important for large-scale SNP scoring. Here we report the development of a multiplex SNP detection system using silicon chips coated to create a thin-film optical biosensor. Allele-discriminating, aldehyde-labeled oligonucleotides are arrayed and covalently attached to a hydrazinederivatized chip surface. Target sequences (e.g., PCR amplicons) then are hybridized in the presence of a mixture of biotinylated detector probes, one for each SNP, and a thermostable DNA ligase. After a stringent wash (0.01 M NaOH), ligation of biotinylated detector probes to perfectly matched capture oligomers is visualized as a color change on the chip surface (gold to blue/purple) after brief incubations with an anti-biotin IgG-horseradish peroxidase conjugate and a precipitable horseradish peroxidase substrate. Testing of PCR fragments is completed in 30-40 min. Up to several hundred SNPs can be assayed on a 36-mm2 chip, and SNP scoring can be done by eye or with a simple digital-camera system. This assay is extremely robust, exhibits high sensitivity and specificity, and is format-flexible and economical. In studies of mutations associated with risk for venous thrombosis and genotyping/haplotyping of African-American samples, we document high-fidelity analysis with 0 misassignments in 500 assays performed in duplicate.

SNP2TFBS - a database of regulatory SNPs affecting predicted transcription factor binding site affinity.

PubMed

Kumar, Sunil; Ambrosini, Giovanna; Bucher, Philipp

2017-01-04

SNP2TFBS is a computational resource intended to support researchers investigating the molecular mechanisms underlying regulatory variation in the human genome. The database essentially consists of a collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. A SNP's effect on TF binding is estimated based on a position weight matrix (PWM) model for the binding specificity of the corresponding factor. These data files are regenerated at regular intervals by an automatic procedure that takes as input a reference genome, a comprehensive SNP catalogue and a collection of PWMs. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs. Homepage: http://ccg.vital-it.ch/snp2tfbs/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genome-wide association mapping reveals a rich genetic architecture of stripe rust resistance loci in emmer wheat (Triticum turgidum ssp. dicoccum).

PubMed

Liu, Weizhen; Maccaferri, Marco; Chen, Xianming; Laghetti, Gaetano; Pignone, Domenico; Pumphrey, Michael; Tuberosa, Roberto

2017-11-01

SNP-based genome scanning in worldwide domesticated emmer germplasm showed high genetic diversity, rapid linkage disequilibrium decay and 51 loci for stripe rust resistance, a large proportion of which were novel. Cultivated emmer wheat (Triticum turgidum ssp. dicoccum), one of the oldest domesticated crops in the world, is a potentially rich reservoir of variation for improvement of resistance/tolerance to biotic and abiotic stresses in wheat. Resistance to stripe rust (Puccinia striiformis f. sp. tritici) in emmer wheat has been under-investigated. Here, we employed genome-wide association (GWAS) mapping with a mixed linear model to dissect effective stripe rust resistance loci in a worldwide collection of 176 cultivated emmer wheat accessions. Adult plants were tested in six environments and seedlings were evaluated with five races from the United States and one from Italy under greenhouse conditions. Five accessions were resistant across all experiments. The panel was genotyped with the wheat 90,000 Illumina iSelect single nucleotide polymorphism (SNP) array and 5106 polymorphic SNP markers with mapped positions were obtained. A high level of genetic diversity and fast linkage disequilibrium decay were observed. In total, we identified 14 loci associated with field resistance in multiple environments. Thirty-seven loci were significantly associated with all-stage (seedling) resistance and six of them were effective against multiple races. Of the 51 total loci, 29 were mapped distantly from previously reported stripe rust resistance genes or quantitative trait loci and represent newly discovered resistance loci. Our results suggest that GWAS is an effective method for characterizing genes in cultivated emmer wheat and confirm that emmer wheat is a rich source of stripe rust resistance loci that can be used for wheat improvement.

High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool.

PubMed

Henriques, Dora; Browne, Keith A; Barnett, Mark W; Parejo, Melanie; Kryger, Per; Freeman, Tom C; Muñoz, Irene; Garnery, Lionel; Highet, Fiona; Jonhston, J Spencer; McCormack, Grace P; Pinto, M Alice

2018-06-04

The natural distribution of the honeybee (Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera, is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A. m. mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation of introgression levels to more effectively monitor and manage A. m. mellifera conservatories.

The genetic architecture of economic and political preferences

PubMed Central

Benjamin, Daniel J.; Cesarini, David; van der Loos, Matthijs J. H. M.; Dawes, Christopher T.; Koellinger, Philipp D.; Magnusson, Patrik K. E.; Chabris, Christopher F.; Conley, Dalton; Laibson, David; Johannesson, Magnus; Visscher, Peter M.

2012-01-01

Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic–based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs. PMID:22566634

Quantitative trait loci underlying resistance to sudden death syndrome (SDS) in MD96-5722 by 'Spencer' recombinant inbred line population of soybean.

PubMed

Anderson, J; Akond, M; Kassem, M A; Meksem, K; Kantartzi, S K

2015-04-01

The best way to protect yield loss of soybean [Glycine max (L.) Merr.] due to sudden death syndrome (SDS), caused by Fusarium virguliforme (Aoki, O'Donnel, Homma & Lattanzi), is the development and use of resistant lines. Mapping quantitative trait loci (QTL) linked to SDS help developing resistant soybean germplasm through molecular marker-assisted selection strategy. QTL for SDS presented herein are from a high-density SNP-based genetic linkage map of MD 96-5722 (a.k.a 'Monocacy') by 'Spencer' recombinant inbred line using SoySNP6K Illumina Infinium BeadChip genotyping array. Ninety-four F 5:7 lines were evaluated for 2 years (2010 and 2011) at two locations (Carbondale and Valmeyer) in southern Illinois, USA to identify QTL controlling SDS resistance using disease index (DX). Composite interval mapping identified 19 SDS controlling QTL which were mapped on 11 separate linkage group (LG) or chromosomes (Chr) out of 20 LG or Chr of soybean genome. Many of these significant QTL identified in one environment/year were confirmed in another year or environment, which suggests a common genetic effects and modes of the pathogen. These new QTL are useful sources for SDS resistance studies in soybean breeding, complementing previously reported loci.

The genetic architecture of economic and political preferences.

PubMed

Benjamin, Daniel J; Cesarini, David; van der Loos, Matthijs J H M; Dawes, Christopher T; Koellinger, Philipp D; Magnusson, Patrik K E; Chabris, Christopher F; Conley, Dalton; Laibson, David; Johannesson, Magnus; Visscher, Peter M

2012-05-22

Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic-based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs.

Identification and genetic mapping for rht-DM, a dominant dwarfing gene in mutant semi-dwarf maize using QTL-seq approach.

PubMed

Chen, Qian; Song, Jun; Du, Wen-Ping; Xu, Li-Yuan; Jiang, Yun; Zhang, Jie; Xiang, Xiao-Li; Yu, Gui-Rong

2018-06-27

Semi-dwarfism is an agronomically important trait in breeding for stable high yields and for resistance to damage by wind and rain (lodging resistance). Many QTLs and genes causing dwarf phenotype have been found in maize. However, because of the yield loss associated with these QTLs and genes, they have been difficult to use in breeding for dwarf stature in maize. Therefore, it is important to find the new dwarfing genes or materials without undesirable characters. The objectives of this study were: (1) to figure out the inheritance of semi-dwarfism in mutants; (2) mapping dwarfing gene or QTL. Maize inbred lines '18599' and 'DM173', which is the dwarf mutant derived from the maize inbred line '173' through 60 Co-γ ray irradiation. F 2 and BC 1 F 1 population were used for genetic analysis. Whole genome resequencing-based technology (QTL-seq) were performed to map dwarfing gene and figured out the SNP markers in predicted region using dwarf bulk and tall bulk from F 2 population. Based on the polymorphic SNP markers from QTL-seq, we were fine-mapping the dwarfing gene using F 2 population. In F 2 population, 398 were dwarf plants and 135 were tall plants. Results of χ 2 tests indicated that the ratio of dwarf plants to tall plants was fitted to 3:1 ratio. Furthermore, the χ 2 tests of BC 1 F 1 population showed that the ratio was fitted to 1:1 ratio. Based on QTL-seq, the dwarfing gene was located at the region from 111.07 to 124.56 Mb of chromosome 9, and we named it rht-DM. Using traditional QTL mapping with SNP markers, the rht-DM was narrowed down to 400 kb region between SNP-21 and SNP-24. The two SNPs were located at 0.43 and 0.11 cM. Segregation analysis of F 2 and BC 1 F 1 indicated that the dwarfing gene was likely a dominant gene. This dwarfing gene was located in the region between 115.02 and 115.42 Mb on chromosome 9.

A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations.

PubMed

Zhang, Han; Wheeler, William; Hyland, Paula L; Yang, Yifan; Shi, Jianxin; Chatterjee, Nilanjan; Yu, Kai

2016-06-01

Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs.

A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations

PubMed Central

Zhang, Han; Wheeler, William; Hyland, Paula L.; Yang, Yifan; Shi, Jianxin; Chatterjee, Nilanjan; Yu, Kai

2016-01-01

Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs. PMID:27362418

Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers

PubMed Central

2011-01-01

Background Most information on genomic variations and their associations with phenotypes are covered exclusively in scientific publications rather than in structured databases. These texts commonly describe variations using natural language; database identifiers are seldom mentioned. This complicates the retrieval of variations, associated articles, as well as information extraction, e. g. the search for biological implications. To overcome these challenges, procedures to map textual mentions of variations to database identifiers need to be developed. Results This article describes a workflow for normalization of variation mentions, i.e. the association of them to unique database identifiers. Common pitfalls in the interpretation of single nucleotide polymorphism (SNP) mentions are highlighted and discussed. The developed normalization procedure achieves a precision of 98.1 % and a recall of 67.5% for unambiguous association of variation mentions with dbSNP identifiers on a text corpus based on 296 MEDLINE abstracts containing 527 mentions of SNPs. The annotated corpus is freely available at http://www.scai.fraunhofer.de/snp-normalization-corpus.html. Conclusions Comparable approaches usually focus on variations mentioned on the protein sequence and neglect problems for other SNP mentions. The results presented here indicate that normalizing SNPs described on DNA level is more difficult than the normalization of SNPs described on protein level. The challenges associated with normalization are exemplified with ambiguities and errors, which occur in this corpus. PMID:21992066

Unravelling the Genetic Diversity among Cassava Bemisia tabaci Whiteflies Using NextRAD Sequencing.

PubMed

Wosula, Everlyne N; Chen, Wenbo; Fei, Zhangjun; Legg, James P

2017-11-01

Bemisia tabaci threatens production of cassava in Africa through vectoring viruses that cause cassava mosaic disease (CMD) and cassava brown streak disease (CBSD). B. tabaci sampled from cassava in eight countries in Africa were genotyped using NextRAD sequencing, and their phylogeny and population genetics were investigated using the resultant single nucleotide polymorphism (SNP) markers. SNP marker data and short sequences of mitochondrial DNA cytochrome oxidase I (mtCOI) obtained from the same insect were compared. Eight genetically distinct groups were identified based on mtCOI, whereas phylogenetic analysis using SNPs identified six major groups, which were further confirmed by PCA and multidimensional analyses. STRUCTURE analysis identified four ancestral B. tabaci populations that have contributed alleles to the six SNP-based groups. Significant gene flows were detected between several of the six SNP-based groups. Evidence of gene flow was strongest for SNP-based groups occurring in central Africa. Comparison of the mtCOI and SNP identities of sampled insects provided a strong indication that hybrid populations are emerging in parts of Africa recently affected by the severe CMD pandemic. This study reveals that mtCOI is not an effective marker at distinguishing cassava-colonizing B. tabaci haplogroups, and that more robust SNP-based multilocus markers should be developed. Significant gene flows between populations could lead to the emergence of haplogroups that might alter the dynamics of cassava virus spread and disease severity in Africa. Continuous monitoring of genetic compositions of whitefly populations should be an essential component in efforts to combat cassava viruses in Africa. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Association Genetics of Coastal Douglas Fir (Pseudotsuga menziesii var. menziesii, Pinaceae). I. Cold-Hardiness Related Traits

Treesearch

Andrew J. Eckert; Andrew D. Bower; Jill L. Wegrzyn; Barnaly Pande; Kathleen D. Jermstad; Konstantin V. Krutovsky; J. Bradley St. Clair; David B. Neale

2009-01-01

Adaptation to cold is one of the greatest challenges to forest trees. This process is highly synchronized with environmental cues relating to photoperiod and temperature. Here, we use a candidate gene-based approach to search for genetic associations between 384 single-nucleotide polymorphism (SNP) markers from 117 candidate genes and 21 cold-hardiness related traits....

SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification

PubMed Central

McClure, Matthew C.; McCarthy, John; Flynn, Paul; McClure, Jennifer C.; Dair, Emma; O'Connell, D. K.; Kearney, John F.

2018-01-01

A major use of genetic data is parentage verification and identification as inaccurate pedigrees negatively affect genetic gain. Since 2012 the international standard for single nucleotide polymorphism (SNP) verification in Bos taurus cattle has been the ISAG SNP panels. While these ISAG panels provide an increased level of parentage accuracy over microsatellite markers (MS), they can validate the wrong parent at ≤1% misconcordance rate levels, indicating that more SNP are needed if a more accurate pedigree is required. With rapidly increasing numbers of cattle being genotyped in Ireland that represent 61 B. taurus breeds from a wide range of farm types: beef/dairy, AI/pedigree/commercial, purebred/crossbred, and large to small herd size the Irish Cattle Breeding Federation (ICBF) analyzed different SNP densities to determine that at a minimum ≥500 SNP are needed to consistently predict only one set of parents at a ≤1% misconcordance rate. For parentage validation and prediction ICBF uses 800 SNP (ICBF800) selected based on SNP clustering quality, ISAG200 inclusion, call rate (CR), and minor allele frequency (MAF) in the Irish cattle population. Large datasets require sample and SNP quality control (QC). Most publications only deal with SNP QC via CR, MAF, parent-progeny conflicts, and Hardy-Weinberg deviation, but not sample QC. We report here parentage, SNP QC, and a genomic sample QC pipelines to deal with the unique challenges of >1 million genotypes from a national herd such as SNP genotype errors from mis-tagging of animals, lab errors, farm errors, and multiple other issues that can arise. We divide the pipeline into two parts: a Genotype QC and an Animal QC pipeline. The Genotype QC identifies samples with low call rate, missing or mixed genotype classes (no BB genotype or ABTG alleles present), and low genotype frequencies. The Animal QC handles situations where the genotype might not belong to the listed individual by identifying: >1 non-matching genotypes per animal, SNP duplicates, sex and breed prediction mismatches, parentage and progeny validation results, and other situations. The Animal QC pipeline make use of ICBF800 SNP set where appropriate to identify errors in a computationally efficient yet still highly accurate method. PMID:29599798

Recommendations for Accurate Resolution of Gene and Isoform Allele-Specific Expression in RNA-Seq Data

PubMed Central

Wood, David L. A.; Nones, Katia; Steptoe, Anita; Christ, Angelika; Harliwong, Ivon; Newell, Felicity; Bruxner, Timothy J. C.; Miller, David; Cloonan, Nicole; Grimmond, Sean M.

2015-01-01

Genetic variation modulates gene expression transcriptionally or post-transcriptionally, and can profoundly alter an individual’s phenotype. Measuring allelic differential expression at heterozygous loci within an individual, a phenomenon called allele-specific expression (ASE), can assist in identifying such factors. Massively parallel DNA and RNA sequencing and advances in bioinformatic methodologies provide an outstanding opportunity to measure ASE genome-wide. In this study, matched DNA and RNA sequencing, genotyping arrays and computationally phased haplotypes were integrated to comprehensively and conservatively quantify ASE in a single human brain and liver tissue sample. We describe a methodological evaluation and assessment of common bioinformatic steps for ASE quantification, and recommend a robust approach to accurately measure SNP, gene and isoform ASE through the use of personalized haplotype genome alignment, strict alignment quality control and intragenic SNP aggregation. Our results indicate that accurate ASE quantification requires careful bioinformatic analyses and is adversely affected by sample specific alignment confounders and random sampling even at moderate sequence depths. We identified multiple known and several novel ASE genes in liver, including WDR72, DSP and UBD, as well as genes that contained ASE SNPs with imbalance direction discordant with haplotype phase, explainable by annotated transcript structure, suggesting isoform derived ASE. The methods evaluated in this study will be of use to researchers performing highly conservative quantification of ASE, and the genes and isoforms identified as ASE of interest to researchers studying those loci. PMID:25965996

Exome Array Analysis of Nuclear Lens Opacity.

PubMed

Loomis, Stephanie J; Klein, Alison P; Lee, Kristine E; Chen, Fei; Bomotti, Samantha; Truitt, Barbara; Iyengar, Sudha K; Klein, Ronald; Klein, Barbara E K; Duggal, Priya

2018-06-01

Nuclear cataract is the most common subtype of age-related cataract, the leading cause of blindness worldwide. It results from advanced nuclear sclerosis, or opacity in the center of the optic lens, and is affected by both genetic and environmental risk factors, including smoking. We sought to understand the genetic factors associated with nuclear sclerosis through interrogation of rare and low frequency coding variants using exome array data. We analyzed Illumina Human Exome Array data for 1,488 participants of European ancestry in the Beaver Dam Eye Study who were without cataract surgery for association with nuclear sclerosis grade, controlling for age and sex. We performed single-variant regression analysis for 32,138 variants with minor allele frequency (MAF) ≥0.003. In addition, gene-based analysis of 11,844 genes containing at least two variants with MAF < 0.05 was performed using a gene-based unified burden and non-burden sequence kernel association test (SKAT-O). Additionally, both single-variant and gene-based analyses were analyzed stratified by smoking status. No single-variant test was statistically significant after Bonferroni correction (p < 1.6 × 10 -6 ; top single nucleotide polymorphism (SNP): rs144458991, p = 2.83 × 10 -5 ). Gene-based tests were suggestively associated with the gene RNF149 overall (p = 8.29 × 10 -6 ) and among never smokers (N = 790, p = 2.67 × 10 -6 ). This study did not find a significant genetic association with nuclear sclerosis, the possible association with the RNF149 gene highlights a potential candidate gene for future studies that aim to understand the genetic architecture of nuclear sclerosis.

Analysis of high-order SNP barcodes in mitochondrial D-loop for chronic dialysis susceptibility.

PubMed

Yang, Cheng-Hong; Lin, Yu-Da; Chuang, Li-Yeh; Chang, Hsueh-Wei

2016-10-01

Positively identifying disease-associated single nucleotide polymorphism (SNP) markers in genome-wide studies entails the complex association analysis of a huge number of SNPs. Such large numbers of SNP barcode (SNP/genotype combinations) continue to pose serious computational challenges, especially for high-dimensional data. We propose a novel exploiting SNP barcode method based on differential evolution, termed IDE (improved differential evolution). IDE uses a "top combination strategy" to improve the ability of differential evolution to explore high-order SNP barcodes in high-dimensional data. We simulate disease data and use real chronic dialysis data to test four global optimization algorithms. In 48 simulated disease models, we show that IDE outperforms existing global optimization algorithms in terms of exploring ability and power to detect the specific SNP/genotype combinations with a maximum difference between cases and controls. In real data, we show that IDE can be used to evaluate the relative effects of each individual SNP on disease susceptibility. IDE generated significant SNP barcode with less computational complexity than the other algorithms, making IDE ideally suited for analysis of high-order SNP barcodes. Copyright © 2016 Elsevier Inc. All rights reserved.

Green way genesis of silver nanoparticles using multiple fruit peels waste and its antimicrobial, anti-oxidant and anti-tumor cell line studies

NASA Astrophysics Data System (ADS)

Naganathan, Kiruthika; Thirunavukkarasu, Somanathan

2017-04-01

Green synthesis of silver nanoparticles (SNP) opens a new path to kill and prevent various infectious diseases and also tumor. In this study, we have synthesized silver nanoparticles using multiple fruit peel waste (pomegranate, orange, banana and apple (POBA)). The primarily nanoparticles formation has been confirmed by the color change. The synthesized SNP were analyzed by various physicochemical techniques such as UV- Visible spectroscopy, x-ray diffraction (XRD), fourier transform infra red (FT-IR) spectroscopy and transmission electron microscope (TEM). The formation of SNP was confirmed by its absorbance peak observed at 430 nm in UV-Visible spectrum. Further, the obtained SNP were identified by XRD and TEM, respectively to know the crystalline nature and size and shape of the particles. The activities of SNP were checked with human pathogens (Salmonella, E.coli and Pseudomonas), plant pathogen (Fusarium) and marine pathogen (Aeromonas hydrophila) and also studied the scavenging effect and anticancer properties against MCF-7 cell lines. This studies proves that the SNP prepared from fruit waste peel extract approach appears extremely fast, cost efficient, eco-friendly and alternative for conventional methods of SNP synthesis to promote the usage of these nanoparticles in medicinal application.

Genomic regions underlying susceptibility to bovine tuberculosis in Holstein-Friesian cattle.

PubMed

Raphaka, Kethusegile; Matika, Oswald; Sánchez-Molano, Enrique; Mrode, Raphael; Coffey, Mike Peter; Riggio, Valentina; Glass, Elizabeth Janet; Woolliams, John Arthur; Bishop, Stephen Christopher; Banos, Georgios

2017-03-23

The significant social and economic loss as a result of bovine tuberculosis (bTB) presents a continuous challenge to cattle industries in the UK and worldwide. However, host genetic variation in cattle susceptibility to bTB provides an opportunity to select for resistant animals and further understand the genetic mechanisms underlying disease dynamics. The present study identified genomic regions associated with susceptibility to bTB using genome-wide association (GWA), regional heritability mapping (RHM) and chromosome association approaches. Phenotypes comprised de-regressed estimated breeding values of 804 Holstein-Friesian sires and pertained to three bTB indicator traits: i) positive reactors to the skin test with positive post-mortem examination results (phenotype 1); ii) positive reactors to the skin test regardless of post-mortem examination results (phenotype 2) and iii) as in (ii) plus non-reactors and inconclusive reactors to the skin tests with positive post-mortem examination results (phenotype 3). Genotypes based on the 50 K SNP DNA array were available and a total of 34,874 SNPs remained per animal after quality control. The estimated polygenic heritability for susceptibility to bTB was 0.26, 0.37 and 0.34 for phenotypes 1, 2 and 3, respectively. GWA analysis identified a putative SNP on Bos taurus autosomes (BTA) 2 associated with phenotype 1, and another on BTA 23 associated with phenotype 2. Genomic regions encompassing these SNPs were found to harbour potentially relevant annotated genes. RHM confirmed the effect of these genomic regions and identified new regions on BTA 18 for phenotype 1 and BTA 3 for phenotypes 2 and 3. Heritabilities of the genomic regions ranged between 0.05 and 0.08 across the three phenotypes. Chromosome association analysis indicated a major role of BTA 23 on susceptibility to bTB. Genomic regions and candidate genes identified in the present study provide an opportunity to further understand pathways critical to cattle susceptibility to bTB and enhance genetic improvement programmes aiming at controlling and eradicating the disease.

A genome-wide association search for type 2 diabetes genes in African Americans.

PubMed

Palmer, Nicholette D; McDonough, Caitrin W; Hicks, Pamela J; Roh, Bong H; Wing, Maria R; An, S Sandy; Hester, Jessica M; Cooke, Jessica N; Bostrom, Meredith A; Rudock, Megan E; Talbert, Matthew E; Lewis, Joshua P; Ferrara, Assiamira; Lu, Lingyi; Ziegler, Julie T; Sale, Michele M; Divers, Jasmin; Shriner, Daniel; Adeyemo, Adebowale; Rotimi, Charles N; Ng, Maggie C Y; Langefeld, Carl D; Freedman, Barry I; Bowden, Donald W; Voight, Benjamin F; Scott, Laura J; Steinthorsdottir, Valgerdur; Morris, Andrew P; Dina, Christian; Welch, Ryan P; Zeggini, Eleftheria; Huth, Cornelia; Aulchenko, Yurii S; Thorleifsson, Gudmar; McCulloch, Laura J; Ferreira, Teresa; Grallert, Harald; Amin, Najaf; Wu, Guanming; Willer, Cristen J; Raychaudhuri, Soumya; McCarroll, Steve A; Langenberg, Claudia; Hofmann, Oliver M; Dupuis, Josée; Qi, Lu; Segrè, Ayellet V; van Hoek, Mandy; Navarro, Pau; Ardlie, Kristin; Balkau, Beverley; Benediktsson, Rafn; Bennett, Amanda J; Blagieva, Roza; Boerwinkle, Eric; Bonnycastle, Lori L; Boström, Kristina Bengtsson; Bravenboer, Bert; Bumpstead, Suzannah; Burtt, Noël P; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn; Couper, David J; Crawford, Gabe; Doney, Alex S F; Elliott, Katherine S; Elliott, Amanda L; Erdos, Michael R; Fox, Caroline S; Franklin, Christopher S; Ganser, Martha; Gieger, Christian; Grarup, Niels; Green, Todd; Griffin, Simon; Groves, Christopher J; Guiducci, Candace; Hadjadj, Samy; Hassanali, Neelam; Herder, Christian; Isomaa, Bo; Jackson, Anne U; Johnson, Paul R V; Jørgensen, Torben; Kao, Wen H L; Klopp, Norman; Kong, Augustine; Kraft, Peter; Kuusisto, Johanna; Lauritzen, Torsten; Li, Man; Lieverse, Aloysius; Lindgren, Cecilia M; Lyssenko, Valeriya; Marre, Michel; Meitinger, Thomas; Midthjell, Kristian; Morken, Mario A; Narisu, Narisu; Nilsson, Peter; Owen, Katharine R; Payne, Felicity; Perry, John R B; Petersen, Ann-Kristin; Platou, Carl; Proença, Christine; Prokopenko, Inga; Rathmann, Wolfgang; Rayner, N William; Robertson, Neil R; Rocheleau, Ghislain; Roden, Michael; Sampson, Michael J; Saxena, Richa; Shields, Beverley M; Shrader, Peter; Sigurdsson, Gunnar; Sparsø, Thomas; Strassburger, Klaus; Stringham, Heather M; Sun, Qi; Swift, Amy J; Thorand, Barbara; Tichet, Jean; Tuomi, Tiinamaija; van Dam, Rob M; van Haeften, Timon W; van Herpt, Thijs; van Vliet-Ostaptchouk, Jana V; Walters, G Bragi; Weedon, Michael N; Wijmenga, Cisca; Witteman, Jacqueline; Bergman, Richard N; Cauchi, Stephane; Collins, Francis S; Gloyn, Anna L; Gyllensten, Ulf; Hansen, Torben; Hide, Winston A; Hitman, Graham A; Hofman, Albert; Hunter, David J; Hveem, Kristian; Laakso, Markku; Mohlke, Karen L; Morris, Andrew D; Palmer, Colin N A; Pramstaller, Peter P; Rudan, Igor; Sijbrands, Eric; Stein, Lincoln D; Tuomilehto, Jaakko; Uitterlinden, Andre; Walker, Mark; Wareham, Nicholas J; Watanabe, Richard M; Abecasis, Goncalo R; Boehm, Bernhard O; Campbell, Harry; Daly, Mark J; Hattersley, Andrew T; Hu, Frank B; Meigs, James B; Pankow, James S; Pedersen, Oluf; Wichmann, H-Erich; Barroso, Inês; Florez, Jose C; Frayling, Timothy M; Groop, Leif; Sladek, Rob; Thorsteinsdottir, Unnur; Wilson, James F; Illig, Thomas; Froguel, Philippe; van Duijn, Cornelia M; Stefansson, Kari; Altshuler, David; Boehnke, Michael; McCarthy, Mark I; Soranzo, Nicole; Wheeler, Eleanor; Glazer, Nicole L; Bouatia-Naji, Nabila; Mägi, Reedik; Randall, Joshua; Johnson, Toby; Elliott, Paul; Rybin, Denis; Henneman, Peter; Dehghan, Abbas; Hottenga, Jouke Jan; Song, Kijoung; Goel, Anuj; Egan, Josephine M; Lajunen, Taina; Doney, Alex; Kanoni, Stavroula; Cavalcanti-Proença, Christine; Kumari, Meena; Timpson, Nicholas J; Zabena, Carina; Ingelsson, Erik; An, Ping; O'Connell, Jeffrey; Luan, Jian'an; Elliott, Amanda; McCarroll, Steven A; Roccasecca, Rosa Maria; Pattou, François; Sethupathy, Praveen; Ariyurek, Yavuz; Barter, Philip; Beilby, John P; Ben-Shlomo, Yoav; Bergmann, Sven; Bochud, Murielle; Bonnefond, Amélie; Borch-Johnsen, Knut; Böttcher, Yvonne; Brunner, Eric; Bumpstead, Suzannah J; Chen, Yii-Der Ida; Chines, Peter; Clarke, Robert; Coin, Lachlan J M; Cooper, Matthew N; Crisponi, Laura; Day, Ian N M; de Geus, Eco J C; Delplanque, Jerome; Fedson, Annette C; Fischer-Rosinsky, Antje; Forouhi, Nita G; Frants, Rune; Franzosi, Maria Grazia; Galan, Pilar; Goodarzi, Mark O; Graessler, Jürgen; Grundy, Scott; Gwilliam, Rhian; Hallmans, Göran; Hammond, Naomi; Han, Xijing; Hartikainen, Anna-Liisa; Hayward, Caroline; Heath, Simon C; Hercberg, Serge; Hicks, Andrew A; Hillman, David R; Hingorani, Aroon D; Hui, Jennie; Hung, Joe; Jula, Antti; Kaakinen, Marika; Kaprio, Jaakko; Kesaniemi, Y Antero; Kivimaki, Mika; Knight, Beatrice; Koskinen, Seppo; Kovacs, Peter; Kyvik, Kirsten Ohm; Lathrop, G Mark; Lawlor, Debbie A; Le Bacquer, Olivier; Lecoeur, Cécile; Li, Yun; Mahley, Robert; Mangino, Massimo; Manning, Alisa K; Martínez-Larrad, María Teresa; McAteer, Jarred B; McPherson, Ruth; Meisinger, Christa; Melzer, David; Meyre, David; Mitchell, Braxton D; Mukherjee, Sutapa; Naitza, Silvia; Neville, Matthew J; Oostra, Ben A; Orrù, Marco; Pakyz, Ruth; Paolisso, Giuseppe; Pattaro, Cristian; Pearson, Daniel; Peden, John F; Pedersen, Nancy L; Perola, Markus; Pfeiffer, Andreas F H; Pichler, Irene; Polasek, Ozren; Posthuma, Danielle; Potter, Simon C; Pouta, Anneli; Province, Michael A; Psaty, Bruce M; Rayner, Nigel W; Rice, Kenneth; Ripatti, Samuli; Rivadeneira, Fernando; Rolandsson, Olov; Sandbaek, Annelli; Sandhu, Manjinder; Sanna, Serena; Sayer, Avan Aihie; Scheet, Paul; Seedorf, Udo; Sharp, Stephen J; Shields, Beverley; Sijbrands, Eric J G; Silveira, Angela; Simpson, Laila; Singleton, Andrew; Smith, Nicholas L; Sovio, Ulla; Swift, Amy; Syddall, Holly; Syvänen, Ann-Christine; Tanaka, Toshiko; Tönjes, Anke; Uitterlinden, André G; van Dijk, Ko Willems; Varma, Dhiraj; Visvikis-Siest, Sophie; Vitart, Veronique; Vogelzangs, Nicole; Waeber, Gérard; Wagner, Peter J; Walley, Andrew; Ward, Kim L; Watkins, Hugh; Wild, Sarah H; Willemsen, Gonneke; Witteman, Jaqueline C M; Yarnell, John W G; Zelenika, Diana; Zethelius, Björn; Zhai, Guangju; Zhao, Jing Hua; Zillikens, M Carola; Borecki, Ingrid B; Loos, Ruth J F; Meneton, Pierre; Magnusson, Patrik K E; Nathan, David M; Williams, Gordon H; Silander, Kaisa; Salomaa, Veikko; Smith, George Davey; Bornstein, Stefan R; Schwarz, Peter; Spranger, Joachim; Karpe, Fredrik; Shuldiner, Alan R; Cooper, Cyrus; Dedoussis, George V; Serrano-Ríos, Manuel; Lind, Lars; Palmer, Lyle J; Franks, Paul W; Ebrahim, Shah; Marmot, Michael; Kao, W H Linda; Pramstaller, Peter Paul; Wright, Alan F; Stumvoll, Michael; Hamsten, Anders; Buchanan, Thomas A; Valle, Timo T; Rotter, Jerome I; Siscovick, David S; Penninx, Brenda W J H; Boomsma, Dorret I; Deloukas, Panos; Spector, Timothy D; Ferrucci, Luigi; Cao, Antonio; Scuteri, Angelo; Schlessinger, David; Uda, Manuela; Ruokonen, Aimo; Jarvelin, Marjo-Riitta; Waterworth, Dawn M; Vollenweider, Peter; Peltonen, Leena; Mooser, Vincent; Sladek, Robert

2012-01-01

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.

An Undergraduate Course and Laboratory in Digital Signal Processing with Field Programmable Gate Arrays

ERIC Educational Resources Information Center

Meyer-Base, U.; Vera, A.; Meyer-Base, A.; Pattichis, M. S.; Perry, R. J.

2010-01-01

In this paper, an innovative educational approach to introducing undergraduates to both digital signal processing (DSP) and field programmable gate array (FPGA)-based design in a one-semester course and laboratory is described. While both DSP and FPGA-based courses are currently present in different curricula, this integrated approach reduces the…

Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight.

PubMed

Al-Mamun, Hawlader A; Kwan, Paul; Clark, Samuel A; Ferdosi, Mohammad H; Tellam, Ross; Gondro, Cedric

2015-08-14

Body weight (BW) is an important trait for meat production in sheep. Although over the past few years, numerous quantitative trait loci (QTL) have been detected for production traits in cattle, few QTL studies have been reported for sheep, with even fewer on meat production traits. Our objective was to perform a genome-wide association study (GWAS) with the medium-density Illumina Ovine SNP50 BeadChip to identify genomic regions and corresponding haplotypes associated with BW in Australian Merino sheep. A total of 1781 Australian Merino sheep were genotyped using the medium-density Illumina Ovine SNP50 BeadChip. Among the 53 862 single nucleotide polymorphisms (SNPs) on this array, 48 640 were used to perform a GWAS using a linear mixed model approach. Genotypes were phased with hsphase; to estimate SNP haplotype effects, linkage disequilibrium blocks were identified in the detected QTL region. Thirty-nine SNPs were associated with BW at a Bonferroni-corrected genome-wide significance threshold of 1 %. One region on sheep (Ovis aries) chromosome 6 (OAR6) between 36.15 and 38.56 Mb, included 13 significant SNPs that were associated with BW; the most significant SNP was OAR6_41936490.1 (P = 2.37 × 10(-16)) at 37.69 Mb with an allele substitution effect of 2.12 kg, which corresponds to 0.248 phenotypic standard deviations for BW. The region that surrounds this association signal on OAR6 contains three genes: leucine aminopeptidase 3 (LAP3), which is involved in the processing of the oxytocin precursor; NCAPG non-SMC condensin I complex, subunit G (NCAPG), which is associated with foetal growth and carcass size in cattle; and ligand dependent nuclear receptor corepressor-like (LCORL), which is associated with height in humans and cattle. The GWAS analysis detected 39 SNPs associated with BW in sheep and a major QTL region was identified on OAR6. In several other mammalian species, regions that are syntenic with this region have been found to be associated with body size traits, which may reflect that the underlying biological mechanisms share a common ancestry. These findings should facilitate the discovery of causative variants for BW and contribute to marker-assisted selection.

Genome-wide DArT and SNP scan for QTL associated with resistance to stripe rust (Puccinia striiformis f. sp. tritici) in elite ICARDA wheat (Triticum aestivum L.) germplasm.

PubMed

Jighly, Abdulqader; Oyiga, Benedict C; Makdis, Farid; Nazari, Kumarse; Youssef, Omran; Tadesse, Wuletaw; Abdalla, Osman; Ogbonnaya, Francis C

2015-07-01

Identified DArT and SNP markers including a first reported QTL on 3AS, validated large effect APR on 3BS. The different genes can be used to incorporate stripe resistance in cultivated varieties. Stripe rust [yellow rust, caused by Puccinia striiformis f. sp. tritici (Pst)] is a serious disease in wheat (Triticum aestivum). This study employed genome-wide association mapping (GWAM) to identify markers linked to stripe rust resistance genes using Diversity Arrays Technology (DArT(®)) and single-nucleotide polymorphism (SNP) Infinium 9K assays in 200 ICARDA wheat genotypes, phenotyped for seedling and adult plant resistance in two sites over two growing seasons in Syria. Only 25.8 % of the genotypes showed resistance at seedling stage while about 33 and 44 % showed moderate resistance and resistance response, respectively. Mixed-linear model adjusted for false discovery rate at p < 0.05 identified 12 DArT and 29 SNP markers on chromosome arms 3AS, 3AL, 1AL, 2AL, 2BS, 2BL, 3BS, 3BL, 5BL, 6AL, and 7DS significantly linked to Pst resistance genes. Of these, the locus on 3AS has not been previously reported to confer resistance to stripe rust in wheat. The QTL on 3AS, 3AL, 1AL, 2AL, and 2BS were effective at seedling and adult plant growth stages while those on 3BS, 3BL, 5BL, 6AL and 7DS were effective at adult plant stage. The 3BS QTL was validated in Cham-6 × Cham-8 recombinant inbred line population; composite interval analysis identified a stripe resistance QTL flanked by the DArT marker, wPt-798970, contributed by Cham-6 parent which accounted for 31.2 % of the phenotypic variation. The DArT marker "wPt-798970" lies 1.6 cM away from the 3BS QTL detected within GWAM. Epistatic interactions were also investigated; only the QTL on 1AL, 3AS and 6AL exhibited interactions with other loci. These results suggest that GWAM can be an effective approach for identifying and improving resistance to stripe rust in wheat.

The easy road to genome-wide medium density SNP screening in a non-model species: development and application of a 10 K SNP-chip for the house sparrow (Passer domesticus).

PubMed

Hagen, Ingerid J; Billing, Anna M; Rønning, Bernt; Pedersen, Sindre A; Pärn, Henrik; Slate, Jon; Jensen, Henrik

2013-05-01

With the advent of next generation sequencing, new avenues have opened to study genomics in wild populations of non-model species. Here, we describe a successful approach to a genome-wide medium density Single Nucleotide Polymorphism (SNP) panel in a non-model species, the house sparrow (Passer domesticus), through the development of a 10 K Illumina iSelect HD BeadChip. Genomic DNA and cDNA derived from six individuals were sequenced on a 454 GS FLX system and generated a total of 1.2 million sequences, in which SNPs were detected. As no reference genome exists for the house sparrow, we used the zebra finch (Taeniopygia guttata) reference genome to determine the most likely position of each SNP. The 10 000 SNPs on the SNP-chip were selected to be distributed evenly across 31 chromosomes, giving on average one SNP per 100 000 bp. The SNP-chip was screened across 1968 individual house sparrows from four island populations. Of the original 10 000 SNPs, 7413 were found to be variable, and 99% of these SNPs were successfully called in at least 93% of all individuals. We used the SNP-chip to demonstrate the ability of such genome-wide marker data to detect population sub-division, and compared these results to similar analyses using microsatellites. The SNP-chip will be used to map Quantitative Trait Loci (QTL) for fitness-related phenotypic traits in natural populations. © 2013 Blackwell Publishing Ltd.

The pitfalls of platform comparison: DNA copy number array technologies assessed

PubMed Central

2009-01-01

Background The accurate and high resolution mapping of DNA copy number aberrations has become an important tool by which to gain insight into the mechanisms of tumourigenesis. There are various commercially available platforms for such studies, but there remains no general consensus as to the optimal platform. There have been several previous platform comparison studies, but they have either described older technologies, used less-complex samples, or have not addressed the issue of the inherent biases in such comparisons. Here we describe a systematic comparison of data from four leading microarray technologies (the Affymetrix Genome-wide SNP 5.0 array, Agilent High-Density CGH Human 244A array, Illumina HumanCNV370-Duo DNA Analysis BeadChip, and the Nimblegen 385 K oligonucleotide array). We compare samples derived from primary breast tumours and their corresponding matched normals, well-established cancer cell lines, and HapMap individuals. By careful consideration and avoidance of potential sources of bias, we aim to provide a fair assessment of platform performance. Results By performing a theoretical assessment of the reproducibility, noise, and sensitivity of each platform, notable differences were revealed. Nimblegen exhibited between-replicate array variances an order of magnitude greater than the other three platforms, with Agilent slightly outperforming the others, and a comparison of self-self hybridizations revealed similar patterns. An assessment of the single probe power revealed that Agilent exhibits the highest sensitivity. Additionally, we performed an in-depth visual assessment of the ability of each platform to detect aberrations of varying sizes. As expected, all platforms were able to identify large aberrations in a robust manner. However, some focal amplifications and deletions were only detected in a subset of the platforms. Conclusion Although there are substantial differences in the design, density, and number of replicate probes, the comparison indicates a generally high level of concordance between platforms, despite differences in the reproducibility, noise, and sensitivity. In general, Agilent tended to be the best aCGH platform and Affymetrix, the superior SNP-CGH platform, but for specific decisions the results described herein provide a guide for platform selection and study design, and the dataset a resource for more tailored comparisons. PMID:19995423

Exome sequencing and SNP analysis detect novel compound heterozygosity in fatty acid hydroxylase-associated neurodegeneration

PubMed Central

Pierson, Tyler Mark; Simeonov, Dimitre R; Sincan, Murat; Adams, David A; Markello, Thomas; Golas, Gretchen; Fuentes-Fajardo, Karin; Hansen, Nancy F; Cherukuri, Praveen F; Cruz, Pedro; Blackstone, Craig; Tifft, Cynthia; Boerkoel, Cornelius F; Gahl, William A

2012-01-01

Fatty acid hydroxylase-associated neurodegeneration due to fatty acid 2-hydroxylase deficiency presents with a wide range of phenotypes including spastic paraplegia, leukodystrophy, and/or brain iron deposition. All previously described families with this disorder were consanguineous, with homozygous mutations in the probands. We describe a 10-year-old male, from a non-consanguineous family, with progressive spastic paraplegia, dystonia, ataxia, and cognitive decline associated with a sural axonal neuropathy. The use of high-throughput sequencing techniques combined with SNP array analyses revealed a novel paternally derived missense mutation and an overlapping novel maternally derived ∼28-kb genomic deletion in FA2H. This patient provides further insight into the consistent features of this disorder and expands our understanding of its phenotypic presentation. The presence of a sural nerve axonal neuropathy had not been previously associated with this disorder and so may extend the phenotype. PMID:22146942