Sample records for quantitative trait network

  1. Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

    PubMed

    Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

    2008-04-15

    Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait

  2. Social traits, social networks and evolutionary biology.

    PubMed

    Fisher, D N; McAdam, A G

    2017-12-01

    The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals' network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group-level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic

  3. Mapping quantitative trait loci for traits defined as ratios.

    PubMed

    Yang, Runqing; Li, Jiahan; Xu, Shizhong

    2008-03-01

    Many traits are defined as ratios of two quantitative traits. Methods of QTL mapping for regular quantitative traits are not optimal when applied to ratios due to lack of normality for traits defined as ratios. We develop a new method of QTL mapping for traits defined as ratios. The new method uses a special linear combination of the two component traits, and thus takes advantage of the normal property of the new variable. Simulation study shows that the new method can substantially increase the statistical power of QTL detection relative to the method which treats ratios as regular quantitative traits. The new method also outperforms the method that uses Box-Cox transformed ratio as the phenotype. A real example of QTL mapping for relative growth rate in soybean demonstrates that the new method can detect more QTL than existing methods of QTL mapping for traits defined as ratios.

  4. Quantitative trait loci mapping and gene network analysis implicate protocadherin-15 as a determinant of brain serotonin transporter expression.

    PubMed

    Ye, R; Carneiro, A M D; Han, Q; Airey, D; Sanders-Bush, E; Zhang, B; Lu, L; Williams, R; Blakely, R D

    2014-03-01

    Presynaptic serotonin (5-hydroxytryptamine, 5-HT) transporters (SERT) regulate 5-HT signaling via antidepressant-sensitive clearance of released neurotransmitter. Polymorphisms in the human SERT gene (SLC6A4) have been linked to risk for multiple neuropsychiatric disorders, including depression, obsessive-compulsive disorder and autism. Using BXD recombinant inbred mice, a genetic reference population that can support the discovery of novel determinants of complex traits, merging collective trait assessments with bioinformatics approaches, we examine phenotypic and molecular networks associated with SERT gene and protein expression. Correlational analyses revealed a network of genes that significantly associated with SERT mRNA levels. We quantified SERT protein expression levels and identified region- and gender-specific quantitative trait loci (QTLs), one of which associated with male midbrain SERT protein expression, centered on the protocadherin-15 gene (Pcdh15), overlapped with a QTL for midbrain 5-HT levels. Pcdh15 was also the only QTL-associated gene whose midbrain mRNA expression significantly associated with both SERT protein and 5-HT traits, suggesting an unrecognized role of the cell adhesion protein in the development or function of 5-HT neurons. To test this hypothesis, we assessed SERT protein and 5-HT traits in the Pcdh15 functional null line (Pcdh15(av-) (3J) ), studies that revealed a strong, negative influence of Pcdh15 on these phenotypes. Together, our findings illustrate the power of multidimensional profiling of recombinant inbred lines in the analysis of molecular networks that support synaptic signaling, and that, as in the case of Pcdh15, can reveal novel relationships that may underlie risk for mental illness. © 2014 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

  5. 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.

  6. Quantitative traits and diversification.

    PubMed

    FitzJohn, Richard G

    2010-12-01

    Quantitative traits have long been hypothesized to affect speciation and extinction rates. For example, smaller body size or increased specialization may be associated with increased rates of diversification. Here, I present a phylogenetic likelihood-based method (quantitative state speciation and extinction [QuaSSE]) that can be used to test such hypotheses using extant character distributions. This approach assumes that diversification follows a birth-death process where speciation and extinction rates may vary with one or more traits that evolve under a diffusion model. Speciation and extinction rates may be arbitrary functions of the character state, allowing much flexibility in testing models of trait-dependent diversification. I test the approach using simulated phylogenies and show that a known relationship between speciation and a quantitative character could be recovered in up to 80% of the cases on large trees (500 species). Consistent with other approaches, detecting shifts in diversification due to differences in extinction rates was harder than when due to differences in speciation rates. Finally, I demonstrate the application of QuaSSE to investigate the correlation between body size and diversification in primates, concluding that clade-specific differences in diversification may be more important than size-dependent diversification in shaping the patterns of diversity within this group.

  7. Model-Based Linkage Analysis of a Quantitative Trait.

    PubMed

    Song, Yeunjoo E; Song, Sunah; Schnell, Audrey H

    2017-01-01

    Linkage Analysis is a family-based method of analysis to examine whether any typed genetic markers cosegregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single-marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it also includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single-marker analysis, and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

  8. Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir

    Treesearch

    Nicholas C. Wheeler; Kathleen D. Jermstad; Konstantin V. Krutovsky; Sally N. Aitken; Glenn T. Howe; Jodie Krakowski; David B. Neale

    2005-01-01

    Quantitative trait locus (QTL) analyses are used by geneticists to characterize the genetic architecture of quantitative traits, provide a foundation for marker-aided-selection (MAS), and provide a framework for positional selection of candidate genes. The most useful QTL for breeding applications are those that have been verified in time, space, and/or genetic...

  9. Integrated genomics and molecular breeding approaches for dissecting the complex quantitative traits in crop plants.

    PubMed

    Kujur, Alice; Saxena, Maneesha S; Bajaj, Deepak; Laxmi; Parida, Swarup K

    2013-12-01

    The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of highyielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is essential. Henceforth, understanding the molecular mechanism and dissection of complex quantitative yield and stress tolerance traits is the prime objective in current agricultural biotechnology research. In recent years, tremendous progress has been made in plant genomics and molecular breeding research pertaining to conventional and next-generation whole genome, transcriptome and epigenome sequencing efforts, generation of huge genomic, transcriptomic and epigenomic resources and development of modern genomics-assisted breeding approaches in diverse crop genotypes with contrasting yield and abiotic stress tolerance traits. Unfortunately, the detailed molecular mechanism and gene regulatory networks controlling such complex quantitative traits is not yet well understood in crop plants. Therefore, we propose an integrated strategies involving available enormous and diverse traditional and modern -omics (structural, functional, comparative and epigenomics) approaches/resources and genomics-assisted breeding methods which agricultural biotechnologist can adopt/utilize to dissect and decode the molecular and gene regulatory networks involved in the complex quantitative yield and stress tolerance traits in crop plants. This would provide clues and much needed inputs for rapid selection of novel functionally relevant molecular tags regulating such complex traits to expedite traditional and modern marker-assisted genetic enhancement studies in target crop species for developing high-yielding stress-tolerant varieties.

  10. Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

    PubMed

    Yap, John Stephen; Fan, Jianqing; Wu, Rongling

    2009-12-01

    Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

  11. Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

    PubMed

    Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

    2009-11-01

    Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

  12. Quantitative trait loci and metabolic pathways

    PubMed Central

    McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

    1998-01-01

    The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

  13. Mapping quantitative trait loci for binary trait in the F2:3 design.

    PubMed

    Zhu, Chengsong; Zhang, Yuan-Ming; Guo, Zhigang

    2008-12-01

    In the analysis of inheritance of quantitative traits with low heritability, an F(2:3) design that genotypes plants in F(2) and phenotypes plants in F(2:3) progeny is often used in plant genetics. Although statistical approaches for mapping quantitative trait loci (QTL) in the F(2:3) design have been well developed, those for binary traits of biological interest and economic importance are seldom addressed. In this study, an attempt was made to map binary trait loci (BTL) in the F(2:3) design. The fundamental idea was: the F(2) plants were genotyped, all phenotypic values of each F(2:3) progeny were measured for binary trait, and these binary trait values and the marker genotype informations were used to detect BTL under the penetrance and liability models. The proposed method was verified by a series of Monte-Carlo simulation experiments. These results showed that maximum likelihood approaches under the penetrance and liability models provide accurate estimates for the effects and the locations of BTL with high statistical power, even under of low heritability. Moreover, the penetrance model is as efficient as the liability model, and the F(2:3) design is more efficient than classical F(2) design, even though only a single progeny is collected from each F(2:3) family. With the maximum likelihood approaches under the penetrance and the liability models developed in this study, we can map binary traits as we can do for quantitative trait in the F(2:3) design.

  14. Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

    PubMed

    Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

    2016-04-01

    To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

  15. Personality traits and ego-network dynamics

    PubMed Central

    Centellegher, Simone; López, Eduardo; Saramäki, Jari; Lepri, Bruno

    2017-01-01

    Strong and supportive social relationships are fundamental to our well-being. However, there are costs to their maintenance, resulting in a trade-off between quality and quantity, a typical strategy being to put a lot of effort on a few high-intensity relationships while maintaining larger numbers of less close relationships. It has also been shown that there are persistent individual differences in this pattern; some individuals allocate their efforts more uniformly across their networks, while others strongly focus on their closest relationships. Furthermore, some individuals maintain more stable networks than others. Here, we focus on how personality traits of individuals affect this picture, using mobile phone calls records and survey data from the Mobile Territorial Lab (MTL) study. In particular, we look at the relationship between personality traits and the (i) persistence of social signatures, namely the similarity of the social signature shape of an individual measured in different time intervals; (ii) the turnover in egocentric networks, that is, differences in the set of alters present at two consecutive temporal intervals; and (iii) the rank dynamics defined as the variation of alter rankings in egocentric networks in consecutive intervals. We observe that some traits have effects on the stability of the social signatures as well as network turnover and rank dynamics. As an example, individuals who score highly in the Openness to Experience trait tend to have higher levels of network turnover and larger alter rank variations. On broader terms, our study shows that personality traits clearly affect the ways in which individuals maintain their personal networks. PMID:28253333

  16. Untargeted Metabolic Quantitative Trait Loci Analyses Reveal a Relationship between Primary Metabolism and Potato Tuber Quality1[W][OA

    PubMed Central

    Carreno-Quintero, Natalia; Acharjee, Animesh; Maliepaard, Chris; Bachem, Christian W.B.; Mumm, Roland; Bouwmeester, Harro; Visser, Richard G.F.; Keurentjes, Joost J.B.

    2012-01-01

    Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits. PMID:22223596

  17. Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. III

    Treesearch

    Kathleen D. Jermstad; Daniel L. Bassoni; Keith S. Jech; Gary A. Ritchie; Nicholas C. Wheeler; David B. Neale

    2003-01-01

    Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring...

  18. Quantitative genetic methods depending on the nature of the phenotypic trait.

    PubMed

    de Villemereuil, Pierre

    2018-01-24

    A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. Here, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model and then more recently using generalized linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non-Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modeling (e.g., to study survival in the context of capture-recapture approaches for wild populations); the use of aster models to study a set of traits with conditional relationships (e.g., life-history traits); and, finally, the study of high-dimensional traits, such as gene expression. © 2018 New York Academy of Sciences.

  19. Mapping of epistatic quantitative trait loci in four-way crosses.

    PubMed

    He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

    2011-01-01

    Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

  20. Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

    PubMed

    Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

    2009-11-01

    The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that

  1. Genomic approaches for the elucidation of genes and gene networks underlying cardiovascular traits.

    PubMed

    Adriaens, M E; Bezzina, C R

    2018-06-22

    Genome-wide association studies have shed light on the association between natural genetic variation and cardiovascular traits. However, linking a cardiovascular trait associated locus to a candidate gene or set of candidate genes for prioritization for follow-up mechanistic studies is all but straightforward. Genomic technologies based on next-generation sequencing technology nowadays offer multiple opportunities to dissect gene regulatory networks underlying genetic cardiovascular trait associations, thereby aiding in the identification of candidate genes at unprecedented scale. RNA sequencing in particular becomes a powerful tool when combined with genotyping to identify loci that modulate transcript abundance, known as expression quantitative trait loci (eQTL), or loci modulating transcript splicing known as splicing quantitative trait loci (sQTL). Additionally, the allele-specific resolution of RNA-sequencing technology enables estimation of allelic imbalance, a state where the two alleles of a gene are expressed at a ratio differing from the expected 1:1 ratio. When multiple high-throughput approaches are combined with deep phenotyping in a single study, a comprehensive elucidation of the relationship between genotype and phenotype comes into view, an approach known as systems genetics. In this review, we cover key applications of systems genetics in the broad cardiovascular field.

  2. Evidences of local adaptation in quantitative traits in Prosopis alba (Leguminosae).

    PubMed

    Bessega, C; Pometti, C; Ewens, M; Saidman, B O; Vilardi, J C

    2015-02-01

    Signals of selection on quantitative traits can be detected by the comparison between the genetic differentiation of molecular (neutral) markers and quantitative traits, by multivariate extensions of the same model and by the observation of the additive covariance among relatives. We studied, by three different tests, signals of occurrence of selection in Prosopis alba populations over 15 quantitative traits: three economically important life history traits: height, basal diameter and biomass, 11 leaf morphology traits that may be related with heat-tolerance and physiological responses and spine length that is very important from silvicultural purposes. We analyzed 172 G1-generation trees growing in a common garden belonging to 32 open pollinated families from eight sampling sites in Argentina. The multivariate phenotypes differ significantly among origins, and the highest differentiation corresponded to foliar traits. Molecular genetic markers (SSR) exhibited significant differentiation and allowed us to provide convincing evidence that natural selection is responsible for the patterns of morphological differentiation. The heterogeneous selection over phenotypic traits observed suggested different optima in each population and has important implications for gene resource management. The results suggest that the adaptive significance of traits should be considered together with population provenance in breeding program as a crucial point prior to any selecting program, especially in Prosopis where the first steps are under development.

  3. Effects of normalization on quantitative traits in association test

    PubMed Central

    2009-01-01

    Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

  4. Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

    PubMed Central

    Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

    2015-01-01

    A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

  5. Quantitative genetics of disease traits.

    PubMed

    Wray, N R; Visscher, P M

    2015-04-01

    John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971; 35: 47; Reich, James and Morris Annals of Human Genetics, 1972; 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics. © 2015 Blackwell Verlag GmbH.

  6. Quantitative and Qualitative Differences in Morphological Traits Revealed between Diploid Fragaria Species

    PubMed Central

    SARGENT, DANIEL J.; GEIBEL, M.; HAWKINS, J. A.; WILKINSON, M. J.; BATTEY, N. H.; SIMPSON, D. W.

    2004-01-01

    • Background and Aims The aims of this investigation were to highlight the qualitative and quantitative diversity apparent between nine diploid Fragaria species and produce interspecific populations segregating for a large number of morphological characters suitable for quantitative trait loci analysis. • Methods A qualitative comparison of eight described diploid Fragaria species was performed and measurements were taken of 23 morphological traits from 19 accessions including eight described species and one previously undescribed species. A principal components analysis was performed on 14 mathematically unrelated traits from these accessions, which partitioned the species accessions into distinct morphological groups. Interspecific crosses were performed with accessions of species that displayed significant quantitative divergence and, from these, populations that should segregate for a range of quantitative traits were raised. • Key Results Significant differences between species were observed for all 23 morphological traits quantified and three distinct groups of species accessions were observed after the principal components analysis. Interspecific crosses were performed between these groups, and F2 and backcross populations were raised that should segregate for a range of morphological characters. In addition, the study highlighted a number of distinctive morphological characters in many of the species studied. • Conclusions Diploid Fragaria species are morphologically diverse, yet remain highly interfertile, making the group an ideal model for the study of the genetic basis of phenotypic differences between species through map-based investigation using quantitative trait loci. The segregating interspecific populations raised will be ideal for such investigations and could also provide insights into the nature and extent of genome evolution within this group. PMID:15469944

  7. Genetic interactions contribute less than additive effects to quantitative trait variation in yeast

    PubMed Central

    Bloom, Joshua S.; Kotenko, Iulia; Sadhu, Meru J.; Treusch, Sebastian; Albert, Frank W.; Kruglyak, Leonid

    2015-01-01

    Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL–QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL–QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies. PMID:26537231

  8. Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.

    PubMed

    Ulgen, Ayse; Han, Zhihua; Li, Wentian

    2003-12-31

    We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.

  9. Mapping Quantitative Traits in Unselected Families: Algorithms and Examples

    PubMed Central

    Dupuis, Josée; Shi, Jianxin; Manning, Alisa K.; Benjamin, Emelia J.; Meigs, James B.; Cupples, L. Adrienne; Siegmund, David

    2009-01-01

    Linkage analysis has been widely used to identify from family data genetic variants influencing quantitative traits. Common approaches have both strengths and limitations. Likelihood ratio tests typically computed in variance component analysis can accommodate large families but are highly sensitive to departure from normality assumptions. Regression-based approaches are more robust but their use has primarily been restricted to nuclear families. In this paper, we develop methods for mapping quantitative traits in moderately large pedigrees. Our methods are based on the score statistic which in contrast to the likelihood ratio statistic, can use nonparametric estimators of variability to achieve robustness of the false positive rate against departures from the hypothesized phenotypic model. Because the score statistic is easier to calculate than the likelihood ratio statistic, our basic mapping methods utilize relatively simple computer code that performs statistical analysis on output from any program that computes estimates of identity-by-descent. This simplicity also permits development and evaluation of methods to deal with multivariate and ordinal phenotypes, and with gene-gene and gene-environment interaction. We demonstrate our methods on simulated data and on fasting insulin, a quantitative trait measured in the Framingham Heart Study. PMID:19278016

  10. Quantitative trait nucleotide analysis using Bayesian model selection.

    PubMed

    Blangero, John; Goring, Harald H H; Kent, Jack W; Williams, Jeff T; Peterson, Charles P; Almasy, Laura; Dyer, Thomas D

    2005-10-01

    Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

  11. Genetic Complexity and Quantitative Trait Loci Mapping of Yeast Morphological Traits

    PubMed Central

    Nogami, Satoru; Ohya, Yoshikazu; Yvert, Gaël

    2007-01-01

    Functional genomics relies on two essential parameters: the sensitivity of phenotypic measures and the power to detect genomic perturbations that cause phenotypic variations. In model organisms, two types of perturbations are widely used. Artificial mutations can be introduced in virtually any gene and allow the systematic analysis of gene function via mutants fitness. Alternatively, natural genetic variations can be associated to particular phenotypes via genetic mapping. However, the access to genome manipulation and breeding provided by model organisms is sometimes counterbalanced by phenotyping limitations. Here we investigated the natural genetic diversity of Saccharomyces cerevisiae cellular morphology using a very sensitive high-throughput imaging platform. We quantified 501 morphological parameters in over 50,000 yeast cells from a cross between two wild-type divergent backgrounds. Extensive morphological differences were found between these backgrounds. The genetic architecture of the traits was complex, with evidence of both epistasis and transgressive segregation. We mapped quantitative trait loci (QTL) for 67 traits and discovered 364 correlations between traits segregation and inheritance of gene expression levels. We validated one QTL by the replacement of a single base in the genome. This study illustrates the natural diversity and complexity of cellular traits among natural yeast strains and provides an ideal framework for a genetical genomics dissection of multiple traits. Our results did not overlap with results previously obtained from systematic deletion strains, showing that both approaches are necessary for the functional exploration of genomes. PMID:17319748

  12. Multiple-Line Inference of Selection on Quantitative Traits

    PubMed Central

    Riedel, Nico; Khatri, Bhavin S.; Lässig, Michael; Berg, Johannes

    2015-01-01

    Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population genetics test for selection acting on a quantitative trait that is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inferences. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test can distinguish between different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signature of lineage-specific selection not seen in two-line tests. PMID:26139839

  13. Linkage disequilibrium interval mapping of quantitative trait loci.

    PubMed

    Boitard, Simon; Abdallah, Jihad; de Rochambeau, Hubert; Cierco-Ayrolles, Christine; Mangin, Brigitte

    2006-03-16

    For many years gene mapping studies have been performed through linkage analyses based on pedigree data. Recently, linkage disequilibrium methods based on unrelated individuals have been advocated as powerful tools to refine estimates of gene location. Many strategies have been proposed to deal with simply inherited disease traits. However, locating quantitative trait loci is statistically more challenging and considerable research is needed to provide robust and computationally efficient methods. Under a three-locus Wright-Fisher model, we derived approximate expressions for the expected haplotype frequencies in a population. We considered haplotypes comprising one trait locus and two flanking markers. Using these theoretical expressions, we built a likelihood-maximization method, called HAPim, for estimating the location of a quantitative trait locus. For each postulated position, the method only requires information from the two flanking markers. Over a wide range of simulation scenarios it was found to be more accurate than a two-marker composite likelihood method. It also performed as well as identity by descent methods, whilst being valuable in a wider range of populations. Our method makes efficient use of marker information, and can be valuable for fine mapping purposes. Its performance is increased if multiallelic markers are available. Several improvements can be developed to account for more complex evolution scenarios or provide robust confidence intervals for the location estimates.

  14. Exploiting induced variation to dissect quantitative traits in barley.

    PubMed

    Druka, Arnis; Franckowiak, Jerome; Lundqvist, Udda; Bonar, Nicola; Alexander, Jill; Guzy-Wrobelska, Justyna; Ramsay, Luke; Druka, Ilze; Grant, Iain; Macaulay, Malcolm; Vendramin, Vera; Shahinnia, Fahimeh; Radovic, Slobodanka; Houston, Kelly; Harrap, David; Cardle, Linda; Marshall, David; Morgante, Michele; Stein, Nils; Waugh, Robbie

    2010-04-01

    The identification of genes underlying complex quantitative traits such as grain yield by means of conventional genetic analysis (positional cloning) requires the development of several large mapping populations. However, it is possible that phenotypically related, but more extreme, allelic variants generated by mutational studies could provide a means for more efficient cloning of QTLs (quantitative trait loci). In barley (Hordeum vulgare), with the development of high-throughput genome analysis tools, efficient genome-wide identification of genetic loci harbouring mutant alleles has recently become possible. Genotypic data from NILs (near-isogenic lines) that carry induced or natural variants of genes that control aspects of plant development can be compared with the location of QTLs to potentially identify candidate genes for development--related traits such as grain yield. As yield itself can be divided into a number of allometric component traits such as tillers per plant, kernels per spike and kernel size, mutant alleles that both affect these traits and are located within the confidence intervals for major yield QTLs may represent extreme variants of the underlying genes. In addition, the development of detailed comparative genomic models based on the alignment of a high-density barley gene map with the rice and sorghum physical maps, has enabled an informed prioritization of 'known function' genes as candidates for both QTLs and induced mutant genes.

  15. A test for selection employing quantitative trait locus and mutation accumulation data.

    PubMed

    Rice, Daniel P; Townsend, Jeffrey P

    2012-04-01

    Evolutionary biologists attribute much of the phenotypic diversity observed in nature to the action of natural selection. However, for many phenotypic traits, especially quantitative phenotypic traits, it has been challenging to test for the historical action of selection. An important challenge for biologists studying quantitative traits, therefore, is to distinguish between traits that have evolved under the influence of strong selection and those that have evolved neutrally. Most existing tests for selection employ molecular data, but selection also leaves a mark on the genetic architecture underlying a trait. In particular, the distribution of quantitative trait locus (QTL) effect sizes and the distribution of mutational effects together provide information regarding the history of selection. Despite the increasing availability of QTL and mutation accumulation data, such data have not yet been effectively exploited for this purpose. We present a model of the evolution of QTL and employ it to formulate a test for historical selection. To provide a baseline for neutral evolution of the trait, we estimate the distribution of mutational effects from mutation accumulation experiments. We then apply a maximum-likelihood-based method of inference to estimate the range of selection strengths under which such a distribution of mutations could generate the observed QTL. Our test thus represents the first integration of population genetic theory and QTL data to measure the historical influence of selection.

  16. ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

    PubMed Central

    2010-01-01

    Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and

  17. Dominant Epistasis Between Two Quantitative Trait Loci Governing Sporulation Efficiency in Yeast Saccharomyces cerevisiae

    PubMed Central

    Bergman, Juraj; Mitrikeski, Petar T.

    2015-01-01

    Summary Sporulation efficiency in the yeast Saccharomyces cerevisiae is a well-established model for studying quantitative traits. A variety of genes and nucleotides causing different sporulation efficiencies in laboratory, as well as in wild strains, has already been extensively characterised (mainly by reciprocal hemizygosity analysis and nucleotide exchange methods). We applied a different strategy in order to analyze the variation in sporulation efficiency of laboratory yeast strains. Coupling classical quantitative genetic analysis with simulations of phenotypic distributions (a method we call phenotype modelling) enabled us to obtain a detailed picture of the quantitative trait loci (QTLs) relationships underlying the phenotypic variation of this trait. Using this approach, we were able to uncover a dominant epistatic inheritance of loci governing the phenotype. Moreover, a molecular analysis of known causative quantitative trait genes and nucleotides allowed for the detection of novel alleles, potentially responsible for the observed phenotypic variation. Based on the molecular data, we hypothesise that the observed dominant epistatic relationship could be caused by the interaction of multiple quantitative trait nucleotides distributed across a 60--kb QTL region located on chromosome XIV and the RME1 locus on chromosome VII. Furthermore, we propose a model of molecular pathways which possibly underlie the phenotypic variation of this trait. PMID:27904371

  18. Allelic-based gene-gene interaction associated with quantitative traits.

    PubMed

    Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

    2009-05-01

    Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

  19. Joint analysis of binary and quantitative traits with data sharing and outcome-dependent sampling.

    PubMed

    Zheng, Gang; Wu, Colin O; Kwak, Minjung; Jiang, Wenhua; Joo, Jungnam; Lima, Joao A C

    2012-04-01

    We study the analysis of a joint association between a genetic marker with both binary (case-control) and quantitative (continuous) traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test (or Pearson's test) and F-test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F-test can be applied using the subgroup with the observed quantitative traits. We propose a modified F-test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F-test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F-test and the joint analysis can also be applied to test single trait association (either binary or quantitative trait). Through simulations, we identify the situations under which the proposed tests are more powerful than the existing ones. Application to a real dataset of rheumatoid arthritis is presented. © 2012 Wiley Periodicals, Inc.

  20. Small- and Large-Effect Quantitative Trait Locus Interactions Underlie Variation in Yeast Sporulation Efficiency

    PubMed Central

    Lorenz, Kim; Cohen, Barak A.

    2012-01-01

    Quantitative trait loci (QTL) with small effects on phenotypic variation can be difficult to detect and analyze. Because of this a large fraction of the genetic architecture of many complex traits is not well understood. Here we use sporulation efficiency in Saccharomyces cerevisiae as a model complex trait to identify and study small-effect QTL. In crosses where the large-effect quantitative trait nucleotides (QTN) have been genetically fixed we identify small-effect QTL that explain approximately half of the remaining variation not explained by the major effects. We find that small-effect QTL are often physically linked to large-effect QTL and that there are extensive genetic interactions between small- and large-effect QTL. A more complete understanding of quantitative traits will require a better understanding of the numbers, effect sizes, and genetic interactions of small-effect QTL. PMID:22942125

  1. Identification of quantitative trait loci (QTL) for fruit quality traits and number of weeks of flowering in the cultivated strawberry

    USDA-ARS?s Scientific Manuscript database

    Fruit quality traits and dayneutrality are two major foci of several strawberry breeding programs. The identification of quantitative trait loci (QTL) and molecular markers linked to these traits could improve breeding efficiency. In this work, an F1 population derived from the cross ‘Delmarvel’ × ...

  2. Emerging late adolescent friendship networks and Big Five personality traits: a social network approach.

    PubMed

    Selfhout, Maarten; Burk, William; Branje, Susan; Denissen, Jaap; van Aken, Marcel; Meeus, Wim

    2010-04-01

    The current study focuses on the emergence of friendship networks among just-acquainted individuals, investigating the effects of Big Five personality traits on friendship selection processes. Sociometric nominations and self-ratings on personality traits were gathered from 205 late adolescents (mean age=19 years) at 5 time points during the first year of university. SIENA, a novel multilevel statistical procedure for social network analysis, was used to examine effects of Big Five traits on friendship selection. Results indicated that friendship networks between just-acquainted individuals became increasingly more cohesive within the first 3 months and then stabilized. Whereas individuals high on Extraversion tended to select more friends than those low on this trait, individuals high on Agreeableness tended to be selected more as friends. In addition, individuals tended to select friends with similar levels of Agreeableness, Extraversion, and Openness.

  3. Power Analysis of Artificial Selection Experiments Using Efficient Whole Genome Simulation of Quantitative Traits

    PubMed Central

    Kessner, Darren; Novembre, John

    2015-01-01

    Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50–100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates. PMID:25672748

  4. Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci.

    PubMed

    Burgess-Herbert, Sarah L; Cox, Allison; Tsaih, Shirng-Wern; Paigen, Beverly

    2008-12-01

    Dissecting the genes involved in complex traits can be confounded by multiple factors, including extensive epistatic interactions among genes, the involvement of epigenetic regulators, and the variable expressivity of traits. Although quantitative trait locus (QTL) analysis has been a powerful tool for localizing the chromosomal regions underlying complex traits, systematically identifying the causal genes remains challenging. Here, through its application to plasma levels of high-density lipoprotein cholesterol (HDL) in mice, we demonstrate a strategy for narrowing QTL that utilizes comparative genomics and bioinformatics techniques. We show how QTL detected in multiple crosses are subjected to both combined cross analysis and haplotype block analysis; how QTL from one species are mapped to the concordant regions in another species; and how genomewide scans associating haplotype groups with their phenotypes can be used to prioritize the narrowed regions. Then we illustrate how these individual methods for narrowing QTL can be systematically integrated for mouse chromosomes 12 and 15, resulting in a significantly reduced number of candidate genes, often from hundreds to <10. Finally, we give an example of how additional bioinformatics resources can be combined with experiments to determine the most likely quantitative trait genes.

  5. Quantitative Trait Loci (QTL)-Guided Metabolic Engineering of a Complex Trait.

    PubMed

    Maurer, Matthew J; Sutardja, Lawrence; Pinel, Dominic; Bauer, Stefan; Muehlbauer, Amanda L; Ames, Tyler D; Skerker, Jeffrey M; Arkin, Adam P

    2017-03-17

    Engineering complex phenotypes for industrial and synthetic biology applications is difficult and often confounds rational design. Bioethanol production from lignocellulosic feedstocks is a complex trait that requires multiple host systems to utilize, detoxify, and metabolize a mixture of sugars and inhibitors present in plant hydrolysates. Here, we demonstrate an integrated approach to discovering and optimizing host factors that impact fitness of Saccharomyces cerevisiae during fermentation of a Miscanthus x giganteus plant hydrolysate. We first used high-resolution Quantitative Trait Loci (QTL) mapping and systematic bulk Reciprocal Hemizygosity Analysis (bRHA) to discover 17 loci that differentiate hydrolysate tolerance between an industrially related (JAY291) and a laboratory (S288C) strain. We then used this data to identify a subset of favorable allelic loci that were most amenable for strain engineering. Guided by this "genetic blueprint", and using a dual-guide Cas9-based method to efficiently perform multikilobase locus replacements, we engineered an S288C-derived strain with superior hydrolysate tolerance than JAY291. Our methods should be generalizable to engineering any complex trait in S. cerevisiae, as well as other organisms.

  6. Quantitative trait loci controlling leaf venation in Arabidopsis.

    PubMed

    Rishmawi, Louai; Bühler, Jonas; Jaegle, Benjamin; Hülskamp, Martin; Koornneef, Maarten

    2017-08-01

    Leaf veins provide the mechanical support and are responsible for the transport of nutrients and water to the plant. High vein density is a prerequisite for plants to have C4 photosynthesis. We investigated the genetic variation and genetic architecture of leaf venation traits within the species Arabidopsis thaliana using natural variation. Leaf venation traits, including leaf vein density (LVD) were analysed in 66 worldwide accessions and 399 lines of the multi-parent advanced generation intercross population. It was shown that there is no correlation between LVD and photosynthesis parameters within A. thaliana. Association mapping was performed for LVD and identified 16 and 17 putative quantitative trait loci (QTLs) in the multi-parent advanced generation intercross and worldwide sets, respectively. There was no overlap between the identified QTLs suggesting that many genes can affect the traits. In addition, linkage mapping was performed using two biparental recombinant inbred line populations. Combining linkage and association mapping revealed seven candidate genes. For one of the candidate genes, RCI2c, we demonstrated its function in leaf venation patterning. © 2017 John Wiley & Sons Ltd.

  7. On normality, ethnicity, and missing values in quantitative trait locus mapping

    PubMed Central

    Labbe, Aurélie; Wormald, Hanna

    2005-01-01

    Background This paper deals with the detection of significant linkage for quantitative traits using a variance components approach. Microsatellite markers were obtained for the Genetic Analysis Workshop 14 Collaborative Study on the Genetics of Alcoholism data. Ethnic heterogeneity, highly skewed quantitative measures, and a high rate of missing values are all present in this dataset and well known to impact upon linkage analysis. This makes it a good candidate for investigation. Results As expected, we observed a number of changes in LOD scores, especially for chromosomes 1, 7, and 18, along with the three factors studied. A dramatic example of such changes can be found in chromosome 7. Highly significant linkage to one of the quantitative traits became insignificant when a proper normalizing transformation of the trait was used and when analysis was carried out on an ethnically homogeneous subset of the original pedigrees. Conclusion In agreement with existing literature, transforming a trait to ensure normality using a Box-Cox transformation is highly recommended in order to avoid false-positive linkages. Furthermore, pedigrees should be sorted by ethnic groups and analyses should be carried out separately. Finally, one should be aware that the inclusion of covariates with a high rate of missing values reduces considerably the number of subjects included in the model. In such a case, the loss in power may be large. Imputation methods are then recommended. PMID:16451664

  8. Uncovering the genetic signature of quantitative trait evolution with replicated time series data.

    PubMed

    Franssen, S U; Kofler, R; Schlötterer, C

    2017-01-01

    The genetic architecture of adaptation in natural populations has not yet been resolved: it is not clear to what extent the spread of beneficial mutations (selective sweeps) or the response of many quantitative trait loci drive adaptation to environmental changes. Although much attention has been given to the genomic footprint of selective sweeps, the importance of selection on quantitative traits is still not well studied, as the associated genomic signature is extremely difficult to detect. We propose 'Evolve and Resequence' as a promising tool, to study polygenic adaptation of quantitative traits in evolving populations. Simulating replicated time series data we show that adaptation to a new intermediate trait optimum has three characteristic phases that are reflected on the genomic level: (1) directional frequency changes towards the new trait optimum, (2) plateauing of allele frequencies when the new trait optimum has been reached and (3) subsequent divergence between replicated trajectories ultimately leading to the loss or fixation of alleles while the trait value does not change. We explore these 3 phase characteristics for relevant population genetic parameters to provide expectations for various experimental evolution designs. Remarkably, over a broad range of parameters the trajectories of selected alleles display a pattern across replicates, which differs both from neutrality and directional selection. We conclude that replicated time series data from experimental evolution studies provide a promising framework to study polygenic adaptation from whole-genome population genetics data.

  9. Genomic Rearrangements in Arabidopsis Considered as Quantitative Traits.

    PubMed

    Imprialou, Martha; Kahles, André; Steffen, Joshua G; Osborne, Edward J; Gan, Xiangchao; Lempe, Janne; Bhomra, Amarjit; Belfield, Eric; Visscher, Anne; Greenhalgh, Robert; Harberd, Nicholas P; Goram, Richard; Hein, Jotun; Robert-Seilaniantz, Alexandre; Jones, Jonathan; Stegle, Oliver; Kover, Paula; Tsiantis, Miltos; Nordborg, Magnus; Rätsch, Gunnar; Clark, Richard M; Mott, Richard

    2017-04-01

    To understand the population genetics of structural variants and their effects on phenotypes, we developed an approach to mapping structural variants that segregate in a population sequenced at low coverage. We avoid calling structural variants directly. Instead, the evidence for a potential structural variant at a locus is indicated by variation in the counts of short-reads that map anomalously to that locus. These structural variant traits are treated as quantitative traits and mapped genetically, analogously to a gene expression study. Association between a structural variant trait at one locus, and genotypes at a distant locus indicate the origin and target of a transposition. Using ultra-low-coverage (0.3×) population sequence data from 488 recombinant inbred Arabidopsis thaliana genomes, we identified 6502 segregating structural variants. Remarkably, 25% of these were transpositions. While many structural variants cannot be delineated precisely, we validated 83% of 44 predicted transposition breakpoints by polymerase chain reaction. We show that specific structural variants may be causative for quantitative trait loci for germination and resistance to infection by the fungus Albugo laibachii , isolate Nc14. Further we show that the phenotypic heritability attributable to read-mapping anomalies differs from, and, in the case of time to germination and bolting, exceeds that due to standard genetic variation. Genes within structural variants are also more likely to be silenced or dysregulated. This approach complements the prevalent strategy of structural variant discovery in fewer individuals sequenced at high coverage. It is generally applicable to large populations sequenced at low-coverage, and is particularly suited to mapping transpositions. Copyright © 2017 by the Genetics Society of America.

  10. Quantitative trait locus mapping and analysis of heritable variation in affiliative social behavior and co-occurring traits.

    PubMed

    Knoll, A T; Jiang, K; Levitt, P

    2018-06-01

    Humans exhibit broad heterogeneity in affiliative social behavior. Twin and family studies show that individual differences in core dimensions of social behavior are heritable, yet there are knowledge gaps in understanding the underlying genetic and neurobiological mechanisms. Animal genetic reference panels (GRPs) provide a tractable strategy for examining the behavioral and genetic architecture of complex traits. Here, using males from 50 mouse strains from the BXD GRP, 4 domains of affiliative social behavior-social approach, social recognition, direct social interaction (DSI) (partner sniffing) and vocal communication-were examined in 2 widely used behavioral tasks-the 3-chamber and DSI tasks. There was continuous and broad variation in social and nonsocial traits, with moderate to high heritability of social approach sniff preference (0.31), ultrasonic vocalization (USV) count (0.39), partner sniffing (0.51), locomotor activity (0.54-0.66) and anxiety-like behavior (0.36). Principal component analysis shows that variation in social and nonsocial traits are attributable to 5 independent factors. Genome-wide mapping identified significant quantitative trait loci for USV count on chromosome (Chr) 18 and locomotor activity on Chr X, with suggestive loci and candidate quantitative trait genes identified for all traits with one notable exception-partner sniffing in the DSI task. The results show heritable variation in sociability, which is independent of variation in activity and anxiety-like traits. In addition, a highly heritable and ethological domain of affiliative sociability-partner sniffing-appears highly polygenic. These findings establish a basis for identifying functional natural variants, leading to a new understanding typical and atypical sociability. © 2017 The Authors. Genes, Brain and Behavior published by International Behavioural and Neural Genetics Society and John Wiley & Sons Ltd.

  11. Molecularly tagged genes and quantitative trait loci in cucumber

    USDA-ARS?s Scientific Manuscript database

    Since the release of the cucumber draft genome, significant progress has been made in molecular mapping, tagging or cloning of horticulturally important genes and quantitative trait loci (QTLs) in cucumber, which provides the foundation for practicing marker-assisted selection in cucumber breeding. ...

  12. Educational Software for Mapping Quantitative Trait Loci (QTL)

    ERIC Educational Resources Information Center

    Helms, T. C.; Doetkott, C.

    2007-01-01

    This educational software was developed to aid teachers and students in their understanding of how the process of identifying the most likely quantitative trait loci (QTL) position is determined between two flanking DNA markers. The objective of the software that we developed was to: (1) show how a QTL is mapped to a position on a chromosome using…

  13. The IQ Quantitative Trait Loci Project: A Critique.

    ERIC Educational Resources Information Center

    King, David

    1998-01-01

    Describes the IQ Quantitative Trait Loci (QTL) project, an attempt to identify genes underlying IQ score variations using maps from the Human Genome Project. The essay argues against funding the IQ QTL project because it will end the debates about the genetic basis of intelligence and may lead directly to eugenic programs of genetic testing. (SLD)

  14. Quantitative trait loci associated with anthracnose resistance in sorghum

    USDA-ARS?s Scientific Manuscript database

    With an aim to develop a durable resistance to the fungal disease anthracnose, two unique genetic sources of resistance were selected to create genetic mapping populations to identify regions of the sorghum genome that encode anthracnose resistance. A series of quantitative trait loci were identifi...

  15. Identification of seedling vigor-associated quantitative trait loci in temperate japonica rice

    USDA-ARS?s Scientific Manuscript database

    A quantitative trait loci (QTL) analysis of seedling vigor traits was conducted under dry-seeded conditions using 176 recombinant inbred lines developed from a cross of two California temperate japonica rice varieties M-203 and M-206. Height at early seedling (HES) and late seedling (HLS) stage, gro...

  16. Major Quantitative Trait Loci Affecting Honey Bee Foraging Behavior

    PubMed Central

    Hunt, G. J.; Page-Jr., R. E.; Fondrk, M. K.; Dullum, C. J.

    1995-01-01

    We identified two genomic regions that affect the amount of pollen stored in honey bee colonies and influence whether foragers will collect pollen or nectar. We selected for the amount of pollen stored in combs of honey bee colonies, a colony-level trait, and then used random amplified polymorphic DNA (RAPD) markers and interval mapping procedures with data from backcross colonies to identify two quantitative trait loci (pln1 and pln2, LOD 3.1 and 2.3, respectively). Quantitative trait loci effects were confirmed in a separate cross by demonstrating the cosegregation of marker alleles with the foraging behavior of individual workers. Both pln1 and pln2 had an effect on the amount of pollen carried by foragers returning to the colony, as inferred by the association between linked RAPD marker alleles, D8-.3f and 301-.55, and the individual pollen load weights of returning foragers. The alleles of the two marker loci were nonrandomly distributed with respect to foraging task. The two loci appeared to have different effects on foraging behavior. Individuals with alternative alleles for the marker linked to pln2 (but not pln1) differed with respect to the nectar sugar concentration of their nectar loads. PMID:8601492

  17. Cloning of DOG1, a quantitative trait locus controlling seed dormancy in Arabidopsis.

    PubMed

    Bentsink, Leónie; Jowett, Jemma; Hanhart, Corrie J; Koornneef, Maarten

    2006-11-07

    Genetic variation for seed dormancy in nature is a typical quantitative trait controlled by multiple loci on which environmental factors have a strong effect. Finding the genes underlying dormancy quantitative trait loci is a major scientific challenge, which also has relevance for agriculture and ecology. In this study we describe the identification of the DELAY OF GERMINATION 1 (DOG1) gene previously identified as a quantitative trait locus involved in the control of seed dormancy. This gene was isolated by a combination of positional cloning and mutant analysis and is absolutely required for the induction of seed dormancy. DOG1 is a member of a small gene family of unknown molecular function, with five members in Arabidopsis. The functional natural allelic variation present in Arabidopsis is caused by polymorphisms in the cis-regulatory region of the DOG1 gene and results in considerable expression differences between the DOG1 alleles of the accessions analyzed.

  18. A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

    PubMed

    Ishikawa, Akira

    2017-11-27

    Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

  19. EM Algorithm for Mapping Quantitative Trait Loci in Multivalent Tetraploids

    USDA-ARS?s Scientific Manuscript database

    Multivalent tetraploids that include many plant species, such as potato, sugarcane and rose, are of paramount importance to agricultural production and biological research. Quantitative trait locus (QTL) mapping in multivalent tetraploids is challenged by their unique cytogenetic properties, such ...

  20. Mapping, fine mapping, and molecular dissection of quantitative trait Loci in domestic animals.

    PubMed

    Georges, Michel

    2007-01-01

    Artificial selection has created myriad breeds of domestic animals, each characterized by unique phenotypes pertaining to behavior, morphology, physiology, and disease. Most domestic animal populations share features with isolated founder populations, making them well suited for positional cloning. Genome sequences are now available for most domestic species, and with them a panoply of tools including high-density single-nucleotide polymorphism panels. As a result, domestic animal populations are becoming invaluable resources for studying the molecular architecture of complex traits and of adaptation. Here we review recent progress and issues in the positional identification of genes underlying complex traits in domestic animals. As many phenotypes studied in animals are quantitative, we focus on mapping, fine mapping, and cloning of quantitative trait loci.

  1. Comprehensive Comparison of Self-Administered Questionnaires for Measuring Quantitative Autistic Traits in Adults

    ERIC Educational Resources Information Center

    Nishiyama, Takeshi; Suzuki, Masako; Adachi, Katsunori; Sumi, Satoshi; Okada, Kensuke; Kishino, Hirohisa; Sakai, Saeko; Kamio, Yoko; Kojima, Masayo; Suzuki, Sadao; Kanne, Stephen M.

    2014-01-01

    We comprehensively compared all available questionnaires for measuring quantitative autistic traits (QATs) in terms of reliability and construct validity in 3,147 non-clinical and 60 clinical subjects with normal intelligence. We examined four full-length forms, the Subthreshold Autism Trait Questionnaire (SATQ), the Broader Autism Phenotype…

  2. Berry and phenology-related traits in grapevine (Vitis vinifera L.): From Quantitative Trait Loci to underlying genes

    PubMed Central

    Costantini, Laura; Battilana, Juri; Lamaj, Flutura; Fanizza, Girolamo; Grando, Maria Stella

    2008-01-01

    Background The timing of grape ripening initiation, length of maturation period, berry size and seed content are target traits in viticulture. The availability of early and late ripening varieties is desirable for staggering harvest along growing season, expanding production towards periods when the fruit gets a higher value in the market and ensuring an optimal plant adaptation to climatic and geographic conditions. Berry size determines grape productivity; seedlessness is especially demanded in the table grape market and is negatively correlated to fruit size. These traits result from complex developmental processes modified by genetic, physiological and environmental factors. In order to elucidate their genetic determinism we carried out a quantitative analysis in a 163 individuals-F1 segregating progeny obtained by crossing two table grape cultivars. Results Molecular linkage maps covering most of the genome (2n = 38 for Vitis vinifera) were generated for each parent. Eighteen pairs of homologous groups were integrated into a consensus map spanning over 1426 cM with 341 markers (mainly microsatellite, AFLP and EST-derived markers) and an average map distance between loci of 4.2 cM. Segregating traits were evaluated in three growing seasons by recording flowering, veraison and ripening dates and by measuring berry size, seed number and weight. QTL (Quantitative Trait Loci) analysis was carried out based on single marker and interval mapping methods. QTLs were identified for all but one of the studied traits, a number of them steadily over more than one year. Clusters of QTLs for different characters were detected, suggesting linkage or pleiotropic effects of loci, as well as regions affecting specific traits. The most interesting QTLs were investigated at the gene level through a bioinformatic analysis of the underlying Pinot noir genomic sequence. Conclusion Our results revealed novel insights into the genetic control of relevant grapevine features. They

  3. Quantile-based permutation thresholds for quantitative trait loci hotspots.

    PubMed

    Neto, Elias Chaibub; Keller, Mark P; Broman, Andrew F; Attie, Alan D; Jansen, Ritsert C; Broman, Karl W; Yandell, Brian S

    2012-08-01

    Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key importance. One approach, randomly allocating observed QTL across the genomic locations separately by trait, implicitly assumes all traits are uncorrelated. Recently, an empirical test for QTL hotspots was proposed on the basis of the number of traits that exceed a predetermined LOD value, such as the standard permutation LOD threshold. The permutation null distribution of the maximum number of traits across all genomic locations preserves the correlation structure among the phenotypes, avoiding the detection of spurious hotspots due to nongenetic correlation induced by uncontrolled environmental factors and unmeasured variables. However, by considering only the number of traits above a threshold, without accounting for the magnitude of the LOD scores, relevant information is lost. In particular, biologically interesting hotspots composed of a moderate to small number of traits with strong LOD scores may be neglected as nonsignificant. In this article we propose a quantile-based permutation approach that simultaneously accounts for the number and the LOD scores of traits within the hotspots. By considering a sliding scale of mapping thresholds, our method can assess the statistical significance of both small and large hotspots. Although the proposed approach can be applied to any type of heritable high-volume "omic" data set, we restrict our attention to expression (e)QTL analysis. We assess and compare the performances of these three methods in simulations and we illustrate how our approach can effectively assess the significance of moderate and small hotspots with strong LOD scores in a yeast expression data set.

  4. Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

    PubMed

    Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

    2016-01-01

    Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability

  5. Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

    PubMed Central

    Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

    2015-01-01

    In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

  6. Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

    PubMed

    Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

    2015-05-01

    In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

  7. Adrenal cortex expression quantitative trait loci in a German Holstein × Charolais cross.

    PubMed

    Brand, Bodo; Scheinhardt, Markus O; Friedrich, Juliane; Zimmer, Daisy; Reinsch, Norbert; Ponsuksili, Siriluck; Schwerin, Manfred; Ziegler, Andreas

    2016-10-06

    The importance of the adrenal gland in regard to lactation and reproduction in cattle has been recognized early. Caused by interest in animal welfare and the impact of stress on economically important traits in farm animals the adrenal gland and its function within the stress response is of increasing interest. However, the molecular mechanisms and pathways involved in stress-related effects on economically important traits in farm animals are not fully understood. Gene expression is an important mechanism underlying complex traits, and genetic variants affecting the transcript abundance are thought to influence the manifestation of an expressed phenotype. We therefore investigated the genetic background of adrenocortical gene expression by applying an adaptive linear rank test to identify genome-wide expression quantitative trait loci (eQTL) for adrenal cortex transcripts in cattle. A total of 10,986 adrenal cortex transcripts and 37,204 single nucleotide polymorphisms (SNPs) were analysed in 145 F2 cows of a Charolais × German Holstein cross. We identified 505 SNPs that were associated with the abundance of 129 transcripts, comprising 482 cis effects and 17 trans effects. These SNPs were located on all chromosomes but X, 16, 24 and 28. Associated genes are mainly involved in molecular and cellular functions comprising free radical scavenging, cellular compromise, cell morphology and lipid metabolism, including genes such as CYP27A1 and LHCGR that have been shown to affect economically important traits in cattle. In this study we showed that adrenocortical eQTL affect the expression of genes known to contribute to the phenotypic manifestation in cattle. Furthermore, some of the identified genes and related molecular pathways were previously shown to contribute to the phenotypic variation of behaviour, temperament and growth at the onset of puberty in the same population investigated here. We conclude that eQTL analysis appears to be a useful approach providing

  8. Quantitative genetic analysis of anxiety trait in bipolar disorder.

    PubMed

    Contreras, J; Hare, E; Chavarría, G; Raventós, H

    2018-01-01

    Bipolar disorder type I (BPI) affects approximately 1% of the world population. Although genetic influences on bipolar disorder are well established, identification of genes that predispose to the illness has been difficult. Most genetic studies are based on categorical diagnosis. One strategy to overcome this obstacle is the use of quantitative endophenotypes, as has been done for other medical disorders. We studied 619 individuals, 568 participants from 61 extended families and 51 unrelated healthy controls. The sample was 55% female and had a mean age of 43.25 (SD 13.90; range 18-78). Heritability and genetic correlation of the trait scale from the Anxiety State and Trait Inventory (STAI) was computed by using the general linear model (SOLAR package software). we observed that anxiety trait meets the following criteria for an endophenotype of bipolar disorder type I (BPI): 1) association with BPI (individuals with BPI showed the highest trait score (F = 15.20 [5,24], p = 0.009), 2) state-independence confirmed after conducting a test-retest in 321 subjects, 3) co-segregation within families 4) heritability of 0.70 (SE: 0.060), p = 2.33 × 10 -14 and 5) genetic correlation with BPI was 0.20, (SE = 0.17, p = 3.12 × 10 -5 ). Confounding factors such as comorbid disorders and pharmacological treatment could affect the clinical relationship between BPI and anxiety trait. Further research is needed to evaluate if anxiety traits are specially related to BPI in comparison with other traits such as anger, attention or response inhibition deficit, pathological impulsivity or low self-directedness. Anxiety trait is a heritable phenotype that follows a normal distribution when measured not only in subjects with BPI but also in unrelated healthy controls. It could be used as an endophenotype in BPI for the identification of genomic regions with susceptibility genes for this disorder. Published by Elsevier B.V.

  9. A strategy to apply quantitative epistasis analysis on developmental traits.

    PubMed

    Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

    2017-05-15

    Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

  10. Neural networks underlying trait aggression depend on MAOA gene alleles.

    PubMed

    Klasen, Martin; Wolf, Dhana; Eisner, Patrick D; Habel, Ute; Repple, Jonathan; Vernaleken, Ingo; Schlüter, Thorben; Eggermann, Thomas; Zerres, Klaus; Zepf, Florian D; Mathiak, Klaus

    2018-03-01

    Low expressing alleles of the MAOA gene (MAOA-L) have been associated with an increased risk for developing an aggressive personality. This suggests an MAOA-L-specific neurobiological vulnerability associated with trait aggression. The neural networks underlying this vulnerability are unknown. The present study investigated genotype-specific associations between resting state brain networks and trait aggression (Buss-Perry Aggression Questionnaire) in 82 healthy Caucasian males. Genotype influences on aggression-related networks were studied for intrinsic and seed-based brain connectivity. Intrinsic connectivity was higher in the ventromedial prefrontal cortex (VMPFC) of MAOA-L compared to high expressing allele (MAOA-H) carriers. Seed-based connectivity analyses revealed genotype differences in the functional involvement of this region. MAOA genotype modulated the relationship between trait aggression and VMPFC connectivity with supramarginal gyrus (SMG) and areas of the default mode network (DMN). Separate analyses for the two groups were performed to better understand how the genotype modulated the relationship between aggression and brain networks. They revealed a positive correlation between VMPFC connectivity and aggression in right angular gyrus (AG) and a negative correlation in right SMG in the MAOA-L group. No such effect emerged in the MAOA-H carriers. The results indicate a particular relevance of VMPFC for aggression in MAOA-L carriers; in specific, a detachment from the DMN along with a strengthened coupling to the AG seems to go along with lower trait aggression. MAOA-L carriers may thus depend on a synchronization of emotion regulation systems (VMPFC) with core areas of empathy (SMG) to prevent aggression.

  11. Selection on domestication traits and quantitative trait loci in crop-wild sunflower hybrids.

    PubMed

    Baack, Eric J; Sapir, Yuval; Chapman, Mark A; Burke, John M; Rieseberg, Loren H

    2008-01-01

    The strength and extent of gene flow from crops into wild populations depends, in part, on the fitness of the crop alleles, as well as that of alleles at linked loci. Interest in crop-wild gene flow has increased with the advent of transgenic plants, but nontransgenic crop-wild hybrids can provide case studies to understand the factors influencing introgression, provided that the genetic architecture and the fitness effects of loci are known. This study used recombinant inbred lines (RILs) generated from a cross between crop and wild sunflowers to assess selection on domestication traits and quantitative trait loci (QTL) in two contrasting environments, in Indiana and Nebraska, USA. Only a small fraction of plants (9%) produced seed in Nebraska, due to adverse weather conditions, while the majority of plants (79%) in Indiana reproduced. Phenotypic selection analysis found that a mixture of crop and wild traits were favoured in Indiana (i.e. had significant selection gradients), including larger leaves, increased floral longevity, larger disk diameter, reduced ray flower size and smaller achene (seed) mass. Selection favouring early flowering was detected in Nebraska. QTLs for fitness were found at the end of linkage groups six (LG6) and nine (LG9) in both field sites, each explaining 11-12% of the total variation. Crop alleles were favoured on LG9, but wild alleles were favoured on LG6. QTLs for numerous domestication traits overlapped with the fitness QTLs, including flowering date, achene mass, head number, and disk diameter. It remains to be seen if these QTL clusters are the product of multiple linked genes, or individual genes with pleiotropic effects. These results indicate that crop trait values and alleles may sometimes be favoured in a noncrop environment and across broad geographical regions.

  12. Variation in heading date conceals quantitative trait loci for other traits of importance in breeding selection of rice

    PubMed Central

    Hori, Kiyosumi; Kataoka, Tomomori; Miura, Kiyoyuki; Yamaguchi, Masayuki; Saka, Norikuni; Nakahara, Takahiro; Sunohara, Yoshihiro; Ebana, Kaworu; Yano, Masahiro

    2012-01-01

    To identify quantitative trait loci (QTLs) associated with the primary target traits for selection in practical rice breeding programs, backcross inbred lines (BILs) derived from crosses between temperate japonica rice cultivars Nipponbare and Koshihikari were evaluated for 50 agronomic traits at six experimental fields located throughout Japan. Thirty-three of the 50 traits were significantly correlated with heading date. Using a linkage map including 647 single-nucleotide polymorphisms (SNPs), a total of 122 QTLs for 38 traits were mapped on all rice chromosomes except chromosomes 5 and 9. Fifty-eight of the 122 QTLs were detected near the heading date QTLs Hd16 and Hd17 and the remaining 64 QTLs were found in other chromosome regions. QTL analysis of 51 BILs having homozygous for the Koshihikari chromosome segments around Hd16 and Hd17 allowed us to detect 40 QTLs associated with 27 traits; 23 of these QTLs had not been detected in the original analysis. Among the 97 QTLs for the 30 traits measured in multiple environments, the genotype-by-environment interaction was significant for 44 QTLs and not significant for 53 QTLs. These results led us to propose a new selection strategy to improve agronomic performance in temperate japonica rice cultivars. PMID:23226082

  13. The effect of induced mutations on quantitative traits in Arabidopsis thaliana: Natural versus artificial conditions.

    PubMed

    Stearns, Frank W; Fenster, Charles B

    2016-12-01

    Mutations are the ultimate source of all genetic variations. New mutations are expected to affect quantitative traits differently depending on the extent to which traits contribute to fitness and the environment in which they are tested. The dogma is that the preponderance of mutations affecting fitness will be skewed toward deleterious while their effects on nonfitness traits will be bidirectionally distributed. There are mixed views on the role of stress in modulating these effects. We quantify mutation effects by inducing mutations in Arabidopsis thaliana (Columbia accession) using the chemical ethylmethane sulfonate. We measured the effects of new mutations relative to a premutation founder for fitness components under both natural (field) and artificial (growth room) conditions. Additionally, we measured three other quantitative traits, not expected to contribute directly to fitness, under artificial conditions. We found that induced mutations were equally as likely to increase as decrease a trait when that trait was not closely related to fitness (traits that were neither survivorship nor reproduction). We also found that new mutations were more likely to decrease fitness or fitness-related traits under more stressful field conditions than under relatively benign artificial conditions. In the benign condition, the effect of new mutations on fitness components was similar to traits not as closely related to fitness. These results highlight the importance of measuring the effects of new mutations on fitness and other traits under a range of conditions.

  14. Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

    PubMed Central

    Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

    2017-01-01

    Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

  15. The Power to Detect Linkage Disequilibrium with Quantitative Traits in Selected Samples

    PubMed Central

    Abecasis, Gonçalo R.; Cookson, William O. C.; Cardon, Lon R.

    2001-01-01

    Results from power studies for linkage detection have led to many ongoing and planned collections of phenotypically extreme nuclear families. Given the great expense of collecting these families and the imminent availability of a dense diallelic marker map, the families are likely to be used in allelic-association as well as linkage studies. However, optimal selection strategies for linkage may not be equally powerful for association. We examine the power to detect linkage disequilibrium for quantitative traits after phenotypic selection. The results encompass six selection strategies that are in widespread use, including single selection (two designs), affected sib pairs, concordant and discordant pairs, and the extreme-concordant and -discordant design. Selection of sibships on the basis of one extreme proband with high or low trait scores provides as much power as discordant sib pairs but requires the screening and phenotyping of substantially fewer initial families from which to select. Analysis of the role of allele frequencies within each selection design indicates that common trait alleles generally offer the most power, but similarities between the marker- and trait-allele frequencies are much more important than the trait-locus frequency alone. Some of the most widespread selection designs, such as single selection, yield power gains only when both the marker and quantitative trait loci (QTL) are relatively rare in the population. In contrast, discordant pairs and the extreme-proband design provide power for the broadest range of QTL–marker-allele frequency differences. Overall, proband selection from either tail provides the best balance of power, robustness, and simplicity of ascertainment for family-based association analysis. PMID:11349228

  16. Current and future developments in patents for quantitative trait loci in dairy cattle.

    PubMed

    Weller, Joel I

    2007-01-01

    Many studies have proposed that rates of genetic gain in dairy cattle can be increased by direct selection on the individual quantitative loci responsible for the genetic variation in these traits, or selection on linked genetic markers. The development of DNA-level genetic markers has made detection of QTL nearly routine in all major livestock species. The studies that attempted to detect genes affecting quantitative traits can be divided into two categories: analysis of candidate genes, and genome scans based on within-family genetic linkage. To date, 12 patent cooperative treaty (PCT) and US patents have been registered for DNA sequences claimed to be associated with effects on economic traits in dairy cattle. All claim effects on milk production, but other traits are also included in some of the claims. Most of the sequences found by the candidate gene approach are of dubious validity, and have been repeated in only very few independent studies. The two missense mutations on chromosomes 6 and 14 affecting milk concentration derived from genome scans are more solidly based, but the claims are also disputed. A few PCT in dairy cattle are commercialized as genetic tests where commercial dairy farmers are the target market.

  17. Synchrony between sensory and cognitive networks is associated with subclinical variation in autistic traits

    PubMed Central

    Young, Jacob S.; Smith, David V.; Coutlee, Christopher G.; Huettel, Scott A.

    2015-01-01

    Individuals with autistic spectrum disorders exhibit distinct personality traits linked to attentional, social, and affective functions, and those traits are expressed with varying levels of severity in the neurotypical and subclinical population. Variation in autistic traits has been linked to reduced functional and structural connectivity (i.e., underconnectivity, or reduced synchrony) with neural networks modulated by attentional, social, and affective functions. Yet, it remains unclear whether reduced synchrony between these neural networks contributes to autistic traits. To investigate this issue, we used functional magnetic resonance imaging to record brain activation while neurotypical participants who varied in their subclinical scores on the Autism-Spectrum Quotient (AQ) viewed alternating blocks of social and nonsocial stimuli (i.e., images of faces and of landscape scenes). We used independent component analysis (ICA) combined with a spatiotemporal regression to quantify synchrony between neural networks. Our results indicated that decreased synchrony between the executive control network (ECN) and a face-scene network (FSN) predicted higher scores on the AQ. This relationship was not explained by individual differences in head motion, preferences for faces, or personality variables related to social cognition. Our findings build on clinical reports by demonstrating that reduced synchrony between distinct neural networks contributes to a range of subclinical autistic traits. PMID:25852527

  18. Quantitative Trait Loci Differentiating the Outbreeding Mimulus Guttatus from the Inbreeding M. Platycalyx

    PubMed Central

    Lin, J. Z.; Ritland, K.

    1997-01-01

    Theoretical predictions about the evolution of selfing depend on the genetic architecture of loci controlling selfing (monogenic vs. polygenic determination, large vs. small effect of alleles, dominance vs. recessiveness), and studies of such architecture are lacking. We inferred the genetic basis of mating system differences between the outbreeding Mimulus guttatus and the inbreeding M. platycalyx by quantitative trait locus (QTL) mapping using random amplified polymorphic DNA and isozyme markers. One to three QTL were detected for each of five mating system characters, and each QTL explained 7.6-28.6% of the phenotypic variance. Taken together, QTL accounted for up to 38% of the variation in mating system characters, and a large proportion of variation was unaccounted for. Inferred QTL often affected more than one trait, contributing to the genetic correlation between those traits. These results are consistent with the hypothesis that quantitative variation in plant mating system characters is primarily controlled by loci with small effect. PMID:9215912

  19. Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast

    PubMed Central

    Jeffares, Daniel C.; Jolly, Clemency; Hoti, Mimoza; Speed, Doug; Shaw, Liam; Rallis, Charalampos; Balloux, Francois; Dessimoz, Christophe; Bähler, Jürg; Sedlazeck, Fritz J.

    2017-01-01

    Large structural variations (SVs) within genomes are more challenging to identify than smaller genetic variants but may substantially contribute to phenotypic diversity and evolution. We analyse the effects of SVs on gene expression, quantitative traits and intrinsic reproductive isolation in the yeast Schizosaccharomyces pombe. We establish a high-quality curated catalogue of SVs in the genomes of a worldwide library of S. pombe strains, including duplications, deletions, inversions and translocations. We show that copy number variants (CNVs) show a variety of genetic signals consistent with rapid turnover. These transient CNVs produce stoichiometric effects on gene expression both within and outside the duplicated regions. CNVs make substantial contributions to quantitative traits, most notably intracellular amino acid concentrations, growth under stress and sugar utilization in winemaking, whereas rearrangements are strongly associated with reproductive isolation. Collectively, these findings have broad implications for evolution and for our understanding of quantitative traits including complex human diseases. PMID:28117401

  20. Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks.

    PubMed

    Milz, Patricia; Pascual-Marqui, Roberto D; Lehmann, Dietrich; Faber, Pascal L

    2016-05-01

    Functional states of the brain are constituted by the temporally attuned activity of spatially distributed neural networks. Such networks can be identified by independent component analysis (ICA) applied to frequency-dependent source-localized EEG data. This methodology allows the identification of networks at high temporal resolution in frequency bands of established location-specific physiological functions. EEG measurements are sensitive to neural activity changes in cortical areas of modality-specific processing. We tested effects of modality-specific processing on functional brain networks. Phasic modality-specific processing was induced via tasks (state effects) and tonic processing was assessed via modality-specific person parameters (trait effects). Modality-specific person parameters and 64-channel EEG were obtained from 70 male, right-handed students. Person parameters were obtained using cognitive style questionnaires, cognitive tests, and thinking modality self-reports. EEG was recorded during four conditions: spatial visualization, object visualization, verbalization, and resting. Twelve cross-frequency networks were extracted from source-localized EEG across six frequency bands using ICA. RMANOVAs, Pearson correlations, and path modelling examined effects of tasks and person parameters on networks. Results identified distinct state- and trait-dependent functional networks. State-dependent networks were characterized by decreased, trait-dependent networks by increased alpha activity in sub-regions of modality-specific pathways. Pathways of competing modalities showed opposing alpha changes. State- and trait-dependent alpha were associated with inhibitory and automated processing, respectively. Antagonistic alpha modulations in areas of competing modalities likely prevent intruding effects of modality-irrelevant processing. Considerable research suggested alpha modulations related to modality-specific states and traits. This study identified the

  1. Quantitative trait loci analysis for net ginning energy requirements in upland cotton (Gossypium hirsutum L.)

    USDA-ARS?s Scientific Manuscript database

    Cotton cultivars with reduced fiber-seed attachment force have the potential to be ginned faster with less energy. The objective of this study was to identify quantitative trait loci (QTL) for net ginning energy (NGE) requirement, and its relationship with other fiber quality traits in upland cotton...

  2. Genetic dissection of fruiting body-related traits using quantitative trait loci mapping in Lentinula edodes.

    PubMed

    Gong, Wen-Bing; Li, Lei; Zhou, Yan; Bian, Yin-Bing; Kwan, Hoi-Shan; Cheung, Man-Kit; Xiao, Yang

    2016-06-01

    To provide a better understanding of the genetic architecture of fruiting body formation of Lentinula edodes, quantitative trait loci (QTLs) mapping was employed to uncover the loci underlying seven fruiting body-related traits (FBRTs). An improved L. edodes genetic linkage map, comprising 572 markers on 12 linkage groups with a total map length of 983.7 cM, was constructed by integrating 82 genomic sequence-based insertion-deletion (InDel) markers into a previously published map. We then detected a total of 62 QTLs for seven target traits across two segregating testcross populations, with individual QTLs contributing 5.5 %-30.2 % of the phenotypic variation. Fifty-three out of the 62 QTLs were clustered in six QTL hotspots, suggesting the existence of main genomic regions regulating the morphological characteristics of fruiting bodies in L. edodes. A stable QTL hotspot on MLG2, containing QTLs for all investigated traits, was identified in both testcross populations. QTLs for related traits were frequently co-located on the linkage groups, demonstrating the genetic basis for phenotypic correlation of traits. Meta-QTL (mQTL) analysis was performed and identified 16 mQTLs with refined positions and narrow confidence intervals (CIs). Nine genes, including those encoding MAP kinase, blue-light photoreceptor, riboflavin-aldehyde-forming enzyme and cyclopropane-fatty-acyl-phospholipid synthase, and cytochrome P450s, were likely to be candidate genes controlling the shape of fruiting bodies. The study has improved our understanding of the genetic architecture of fruiting body formation in L. edodes. To our knowledge, this is the first genome-wide QTL detection of FBRTs in L. edodes. The improved genetic map, InDel markers and QTL hotspot regions revealed here will assist considerably in the conduct of future genetic and breeding studies of L. edodes.

  3. A network of amygdala connections predict individual differences in trait anxiety.

    PubMed

    Greening, Steven G; Mitchell, Derek G V

    2015-12-01

    In this study we demonstrate that the pattern of an amygdala-centric network contributes to individual differences in trait anxiety. Individual differences in trait anxiety were predicted using maximum likelihood estimates of amygdala structural connectivity to multiple brain targets derived from diffusion-tensor imaging (DTI) and probabilistic tractography on 72 participants. The prediction was performed using a stratified sixfold cross validation procedure using a regularized least square regression model. The analysis revealed a reliable network of regions predicting individual differences in trait anxiety. Higher trait anxiety was associated with stronger connections between the amygdala and dorsal anterior cingulate cortex, an area implicated in the generation of emotional reactions, and inferior temporal gyrus and paracentral lobule, areas associated with perceptual and sensory processing. In contrast, higher trait anxiety was associated with weaker connections between amygdala and regions implicated in extinction learning such as medial orbitofrontal cortex, and memory encoding and environmental context recognition, including posterior cingulate cortex and parahippocampal gyrus. Thus, trait anxiety is not only associated with reduced amygdala connectivity with prefrontal areas associated with emotion modulation, but also enhanced connectivity with sensory areas. This work provides novel anatomical insight into potential mechanisms behind information processing biases observed in disorders of emotion. © 2015 Wiley Periodicals, Inc.

  4. Bayesian B-spline mapping for dynamic quantitative traits.

    PubMed

    Xing, Jun; Li, Jiahan; Yang, Runqing; Zhou, Xiaojing; Xu, Shizhong

    2012-04-01

    Owing to their ability and flexibility to describe individual gene expression at different time points, random regression (RR) analyses have become a popular procedure for the genetic analysis of dynamic traits whose phenotypes are collected over time. Specifically, when modelling the dynamic patterns of gene expressions in the RR framework, B-splines have been proved successful as an alternative to orthogonal polynomials. In the so-called Bayesian B-spline quantitative trait locus (QTL) mapping, B-splines are used to characterize the patterns of QTL effects and individual-specific time-dependent environmental errors over time, and the Bayesian shrinkage estimation method is employed to estimate model parameters. Extensive simulations demonstrate that (1) in terms of statistical power, Bayesian B-spline mapping outperforms the interval mapping based on the maximum likelihood; (2) for the simulated dataset with complicated growth curve simulated by B-splines, Legendre polynomial-based Bayesian mapping is not capable of identifying the designed QTLs accurately, even when higher-order Legendre polynomials are considered and (3) for the simulated dataset using Legendre polynomials, the Bayesian B-spline mapping can find the same QTLs as those identified by Legendre polynomial analysis. All simulation results support the necessity and flexibility of B-spline in Bayesian mapping of dynamic traits. The proposed method is also applied to a real dataset, where QTLs controlling the growth trajectory of stem diameters in Populus are located.

  5. Quantitative trait loci associated with the tocochromanol (vitamin E) pathway in barley

    USDA-ARS?s Scientific Manuscript database

    In this study, the Genome-Wide Association Studies approach was used to detect Quantitative Trait Loci associated with tocochromanol concentrations using a panel of 1,466 barley accessions. All major tocochromanol types- alpha-, beta-, delta-, gamma-tocopherol and tocotrienol- were assayed. We found...

  6. Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir.II. Spring and fall cold-hardiness

    Treesearch

    K.D. Jermstad; D.L. Bassoni; N.C. Wheeler; T.S. Anekonda; S.N. Aitken; W.T. Adams; D.B. Neale

    2001-01-01

    Abstract Quantitative trait loci (QTLs) affecting fall and spring cold-hardiness were identified in a three-generation outbred pedigree of coastal Douglas-fir [Pseudotsuga meniziesii (Mirb.) Franco var. menziesii]. Eleven QTLs controlling fall cold-hardiness were detected on four linkage groups, and 15 QTLs controlling spring cold-hardiness were detected on four...

  7. A population genetic interpretation of GWAS findings for human quantitative traits

    PubMed Central

    Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy

    2018-01-01

    Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID

  8. Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. I. Timing of vegetative bud flush.

    Treesearch

    K.D. Jermstad; D.L. Bassoni; K.S. Jech; N.C. Wheeler; D.B. Neale

    2001-01-01

    Abstract Thirty three unique quantitative trait loci (QTLs) affecting the timing of spring bud flush have been identified in an intraspecific mapping population of coastal Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco var. menziesii]. Both terminal and lateral bud flush were measured over a 4-year period on clonal replicates at two test sites, allowing for the...

  9. Quantitative trait loci for energy balance traits in an advanced intercross line derived from mice divergently selected for heat loss

    PubMed Central

    Nielsen, Merlyn K.; Thorn, Stephanie R.; Valdar, William; Pomp, Daniel

    2014-01-01

    Obesity in human populations, currently a serious health concern, is considered to be the consequence of an energy imbalance in which more energy in calories is consumed than is expended. We used interval mapping techniques to investigate the genetic basis of a number of energy balance traits in an F11 advanced intercross population of mice created from an original intercross of lines selected for increased and decreased heat loss. We uncovered a total of 137 quantitative trait loci (QTLs) for these traits at 41 unique sites on 18 of the 20 chromosomes in the mouse genome, with X-linked QTLs being most prevalent. Two QTLs were found for the selection target of heat loss, one on distal chromosome 1 and another on proximal chromosome 2. The number of QTLs affecting the various traits generally was consistent with previous estimates of heritabilities in the same population, with the most found for two bone mineral traits and the least for feed intake and several body composition traits. QTLs were generally additive in their effects, and some, especially those affecting the body weight traits, were sex-specific. Pleiotropy was extensive within trait groups (body weights, adiposity and organ weight traits, bone traits) and especially between body composition traits adjusted and not adjusted for body weight at sacrifice. Nine QTLs were found for one or more of the adiposity traits, five of which appeared to be unique. The confidence intervals among all QTLs averaged 13.3 Mb, much smaller than usually observed in an F2 cross, and in some cases this allowed us to make reasonable inferences about candidate genes underlying these QTLs. This study combined QTL mapping with genetic parameter analysis in a large segregating population, and has advanced our understanding of the genetic architecture of complex traits related to obesity. PMID:24918027

  10. Determination of quantitative trait variants by concordance via application of the a posteriori granddaughter design to the U.S. Holstein population

    USDA-ARS?s Scientific Manuscript database

    Experimental designs that exploit family information can provide substantial predictive power in quantitative trait variant discovery projects. Concordance between quantitative trait locus genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 29 trai...

  11. Trophic level, successional age and trait matching determine specialization of deadwood-based interaction networks of saproxylic beetles

    PubMed Central

    Gossner, Martin M.; Grass, Ingo; Arnstadt, Tobias; Hofrichter, Martin; Floren, Andreas; Linsenmair, Karl Eduard; Weisser, Wolfgang W.; Steffan-Dewenter, Ingolf

    2017-01-01

    The specialization of ecological networks provides important insights into possible consequences of biodiversity loss for ecosystem functioning. However, mostly mutualistic and antagonistic interactions of living organisms have been studied, whereas detritivore networks and their successional changes are largely unexplored. We studied the interactions of saproxylic (deadwood-dependent) beetles with their dead host trees. In a large-scale experiment, 764 logs of 13 tree species were exposed to analyse network structure of three trophic groups of saproxylic beetles over 3 successional years. We found remarkably high specialization of deadwood-feeding xylophages and lower specialization of fungivorous and predatory species. During deadwood succession, community composition, network specialization and network robustness changed differently for the functional groups. To reveal potential drivers of network specialization, we linked species' functional traits to their network roles, and tested for trait matching between plant (i.e. chemical compounds) and beetle (i.e. body size) traits. We found that both plant and animal traits are major drivers of species specialization, and that trait matching can be more important in explaining interactions than neutral processes reflecting species abundance distributions. High network specialization in the early successional stage and decreasing network robustness during succession indicate vulnerability of detritivore networks to reduced tree species diversity and beetle extinctions, with unknown consequences for wood decomposition and nutrient cycling. PMID:28469020

  12. Dissociable relations between amygdala subregional networks and psychopathy trait dimensions in conduct-disordered juvenile offenders.

    PubMed

    Aghajani, Moji; Colins, Olivier F; Klapwijk, Eduard T; Veer, Ilya M; Andershed, Henrik; Popma, Arne; van der Wee, Nic J; Vermeiren, Robert R J M

    2016-11-01

    Psychopathy is a serious psychiatric phenomenon characterized by a pathological constellation of affective (e.g., callous, unemotional), interpersonal (e.g., manipulative, egocentric), and behavioral (e.g., impulsive, irresponsible) personality traits. Though amygdala subregional defects are suggested in psychopathy, the functionality and connectivity of different amygdala subnuclei is typically disregarded in neurocircuit-level analyses of psychopathic personality. Hence, little is known of how amygdala subregional networks may contribute to psychopathy and its underlying trait assemblies in severely antisocial people. We addressed this important issue by uniquely examining the intrinsic functional connectivity of basolateral (BLA) and centromedial (CMA) amygdala networks in relation to affective, interpersonal, and behavioral traits of psychopathy, in conduct-disordered juveniles with a history of serious delinquency (N = 50, mean age = 16.83 ± 1.32). As predicted, amygdalar connectivity profiles exhibited dissociable relations with different traits of psychopathy. Interpersonal psychopathic traits not only related to increased connectivity of BLA and CMA with a corticostriatal network formation accommodating reward processing, but also predicted stronger CMA connectivity with a network of cortical midline structures supporting sociocognitive processes. In contrast, affective psychopathic traits related to diminished CMA connectivity with a frontolimbic network serving salience processing and affective responding. Finally, behavioral psychopathic traits related to heightened BLA connectivity with a frontoparietal cluster implicated in regulatory executive functioning. We suggest that these trait-specific shifts in amygdalar connectivity could be particularly relevant to the psychopathic phenotype, as they may fuel a self-centered, emotionally cold, and behaviorally disinhibited profile. Hum Brain Mapp 37:4017-4033, 2016. © 2016 The Authors Human

  13. Quantitative Trait Loci Controlling Vegetative Growth Rate in the Edible Basidiomycete Pleurotus ostreatus

    PubMed Central

    Larraya, Luis M.; Idareta, Eneko; Arana, Dani; Ritter, Enrique; Pisabarro, Antonio G.; Ramírez, Lucia

    2002-01-01

    Mycelium growth rate is a quantitative characteristic that exhibits continuous variation. This trait has applied interest, as growth rate is correlated with production yield and increased advantage against competitors. In this work, we studied growth rate variation in the edible basidiomycete Pleurotus ostreatus growing as monokaryotic or dikaryotic mycelium on Eger medium or on wheat straw. Our analysis resulted in identification of several genomic regions (quantitative trait loci [QTLs]) involved in the control of growth rate that can be mapped on the genetic linkage map of this fungus. In some cases monokaryotic and dikaryotic QTLs clustered at the same map position, indicating that there are principal genomic areas responsible for growth rate control. The availability of this linkage map of growth rate QTLs can help in the design of rational strain breeding programs based on genomic information. PMID:11872457

  14. Dissociable relations between amygdala subregional networks and psychopathy trait dimensions in conduct‐disordered juvenile offenders

    PubMed Central

    Colins, Olivier F.; Klapwijk, Eduard T.; Veer, Ilya M.; Andershed, Henrik; Popma, Arne; van der Wee, Nic J.; Vermeiren, Robert R.J.M.

    2016-01-01

    Abstract Psychopathy is a serious psychiatric phenomenon characterized by a pathological constellation of affective (e.g., callous, unemotional), interpersonal (e.g., manipulative, egocentric), and behavioral (e.g., impulsive, irresponsible) personality traits. Though amygdala subregional defects are suggested in psychopathy, the functionality and connectivity of different amygdala subnuclei is typically disregarded in neurocircuit‐level analyses of psychopathic personality. Hence, little is known of how amygdala subregional networks may contribute to psychopathy and its underlying trait assemblies in severely antisocial people. We addressed this important issue by uniquely examining the intrinsic functional connectivity of basolateral (BLA) and centromedial (CMA) amygdala networks in relation to affective, interpersonal, and behavioral traits of psychopathy, in conduct‐disordered juveniles with a history of serious delinquency (N = 50, mean age = 16.83 ± 1.32). As predicted, amygdalar connectivity profiles exhibited dissociable relations with different traits of psychopathy. Interpersonal psychopathic traits not only related to increased connectivity of BLA and CMA with a corticostriatal network formation accommodating reward processing, but also predicted stronger CMA connectivity with a network of cortical midline structures supporting sociocognitive processes. In contrast, affective psychopathic traits related to diminished CMA connectivity with a frontolimbic network serving salience processing and affective responding. Finally, behavioral psychopathic traits related to heightened BLA connectivity with a frontoparietal cluster implicated in regulatory executive functioning. We suggest that these trait‐specific shifts in amygdalar connectivity could be particularly relevant to the psychopathic phenotype, as they may fuel a self‐centered, emotionally cold, and behaviorally disinhibited profile. Hum Brain Mapp 37:4017–4033, 2016. © 2016

  15. The quantitative LOD score: test statistic and sample size for exclusion and linkage of quantitative traits in human sibships.

    PubMed

    Page, G P; Amos, C I; Boerwinkle, E

    1998-04-01

    We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

  16. Evaluation of breeding strategies for polledness in dairy cattle using a newly developed simulation framework for quantitative and Mendelian traits.

    PubMed

    Scheper, Carsten; Wensch-Dorendorf, Monika; Yin, Tong; Dressel, Holger; Swalve, Herrmann; König, Sven

    2016-06-29

    Intensified selection of polled individuals has recently gained importance in predominantly horned dairy cattle breeds as an alternative to routine dehorning. The status quo of the current polled breeding pool of genetically-closely related artificial insemination sires with lower breeding values for performance traits raises questions regarding the effects of intensified selection based on this founder pool. We developed a stochastic simulation framework that combines the stochastic simulation software QMSim and a self-designed R program named QUALsim that acts as an external extension. Two traits were simulated in a dairy cattle population for 25 generations: one quantitative (QMSim) and one qualitative trait with Mendelian inheritance (i.e. polledness, QUALsim). The assignment scheme for qualitative trait genotypes initiated realistic initial breeding situations regarding allele frequencies, true breeding values for the quantitative trait and genetic relatedness. Intensified selection for polled cattle was achieved using an approach that weights estimated breeding values in the animal best linear unbiased prediction model for the quantitative trait depending on genotypes or phenotypes for the polled trait with a user-defined weighting factor. Selection response for the polled trait was highest in the selection scheme based on genotypes. Selection based on phenotypes led to significantly lower allele frequencies for polled. The male selection path played a significantly greater role for a fast dissemination of polled alleles compared to female selection strategies. Fixation of the polled allele implies selection based on polled genotypes among males. In comparison to a base breeding scenario that does not take polledness into account, intensive selection for polled substantially reduced genetic gain for this quantitative trait after 25 generations. Reducing selection intensity for polled males while maintaining strong selection intensity among females

  17. Functional linear models for association analysis of quantitative traits.

    PubMed

    Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

    2013-11-01

    Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY

  18. Quantitative trait loci for live animal and carcass composition traits in Jersey and Limousin back-cross cattle finished on pasture or feedlot.

    PubMed

    Morris, C A; Pitchford, W S; Cullen, N G; Esmailizadeh, A K; Hickey, S M; Hyndman, D; Dodds, K G; Afolayan, R A; Crawford, A M; Bottema, C D K

    2009-10-01

    A quantitative trait locus (QTL) study was carried out in two countries, recording live animal and carcass composition traits. Back-cross calves (385 heifers and 398 steers) were generated, with Jersey and Limousin breed backgrounds. The New Zealand cattle were reared on pasture to carcass weights averaging 229 kg, whilst the Australian cattle were reared on grass and finished on grain (for at least 180 days) to carcass weights averaging 335 kg. From 11 live animal traits and 31 carcass composition traits respectively, 5 and 22 QTL were detected in combined-sire analyses, which were significant (P < 0.05) on a genome-wise basis. Fourteen significant traits for carcass composition QTL were on chromosome 2 and these were traits associated with muscling and fatness. This chromosome carried a variant myostatin allele (F94L), segregating from the Limousin ancestry. Despite very different cattle management systems between the two countries, the two populations had a large number of QTL in common. Of the 18 traits which were common to both countries, and which had significant QTL at the genome-wise level, eight were significant in both countries.

  19. Genetic and Quantitative Trait Locus Analysis for Bio-Oil Compounds after Fast Pyrolysis in Maize Cobs.

    PubMed

    Jeffrey, Brandon; Kuzhiyil, Najeeb; de Leon, Natalia; Lübberstedt, Thomas

    2016-01-01

    Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS) in maize cobs. 184 recombinant inbred lines (RILs) of the intermated B73 x Mo17 (IBM) Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL) mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R2 values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.

  20. Organization of brain networks governed by long-range connections index autistic traits in the general population

    PubMed Central

    2013-01-01

    Background The dimensional approach to autism spectrum disorder (ASD) considers ASD as the extreme of a dimension traversing through the entire population. We explored the potential utility of electroencephalography (EEG) functional connectivity as a biomarker. We hypothesized that individual differences in autistic traits of typical subjects would involve a long-range connectivity diminution within the delta band. Methods Resting-state EEG functional connectivity was measured for 74 neurotypical subjects. All participants also provided a questionnaire (Social Responsiveness Scale, SRS) that was completed by an informant who knows the participant in social settings. We conducted multivariate regression between the SRS score and functional connectivity in all EEG frequency bands. We explored modulations of network graph metrics characterizing the optimality of a network using the SRS score. Results Our results show a decay in functional connectivity mainly within the delta and theta bands (the lower part of the EEG spectrum) associated with an increasing number of autistic traits. When inspecting the impact of autistic traits on the global organization of the functional network, we found that the optimal properties of the network are inversely related to the number of autistic traits, suggesting that the autistic dimension, throughout the entire population, modulates the efficiency of functional brain networks. Conclusions EEG functional connectivity at low frequencies and its associated network properties may be associated with some autistic traits in the general population. PMID:23806204

  1. Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean.

    PubMed

    Fang, Chao; Ma, Yanming; Wu, Shiwen; Liu, Zhi; Wang, Zheng; Yang, Rui; Hu, Guanghui; Zhou, Zhengkui; Yu, Hong; Zhang, Min; Pan, Yi; Zhou, Guoan; Ren, Haixiang; Du, Weiguang; Yan, Hongrui; Wang, Yanping; Han, Dezhi; Shen, Yanting; Liu, Shulin; Liu, Tengfei; Zhang, Jixiang; Qin, Hao; Yuan, Jia; Yuan, Xiaohui; Kong, Fanjiang; Liu, Baohui; Li, Jiayang; Zhang, Zhiwu; Wang, Guodong; Zhu, Baoge; Tian, Zhixi

    2017-08-24

    Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

  2. Multienvironment Quantitative Trait Loci Analysis for Photosynthate Acquisition, Accumulation, and Remobilization Traits in Common Bean Under Drought Stress

    PubMed Central

    Asfaw, Asrat; Blair, Matthew W.; Struik, Paul C.

    2012-01-01

    Many of the world’s common bean (Phaseolus vulgaris L.) growing regions are prone to either intermittent or terminal drought stress, making drought the primary cause of yield loss under farmers’ field conditions. Improved photosynthate acquisition, accumulation, and then remobilization have been observed as important mechanisms for adaptation to drought stress. The objective of this study was to tag quantitative trait loci (QTL) for photosynthate acquisition, accumulation, and remobilization to grain by using a recombinant inbred line population developed from the Mesoamerican intragenepool cross of drought-susceptible DOR364 and drought-tolerant BAT477 grown under eight environments differing in drought stress across two continents: Africa and South America. The recombinant inbred line population expressed quantitative variation and transgressive segregation for 11 traits associated with drought tolerance. QTL were detected by both a mixed multienvironment model and by composite interval mapping for each environment using a linkage map constructed with 165 genetic markers that covered 11 linkage groups of the common bean genome. In the multienvironment, mixed model, nine QTL were detected for 10 drought stress tolerance mechanism traits found on six of the 11 linkage groups. Significant QTL × environment interaction was observed for six of the nine QTL. QTL × environment interaction was of the cross-over type for three of the six significant QTL with contrasting effect of the parental alleles across different environments. In the composite interval mapping, we found 69 QTL in total. The majority of these were found for Palmira (47) or Awassa (18), with fewer in Malawi (4). Phenotypic variation explained by QTL in single environments ranged up to 37%, and the most consistent QTL were for Soil Plant Analysis Development (SPAD) leaf chlorophyll reading and pod partitioning traits. QTL alignment between the two detection methods showed that yield QTL on b08 and

  3. Multienvironment quantitative trait Loci analysis for photosynthate acquisition, accumulation, and remobilization traits in common bean under drought stress.

    PubMed

    Asfaw, Asrat; Blair, Matthew W; Struik, Paul C

    2012-05-01

    Many of the world's common bean (Phaseolus vulgaris L.) growing regions are prone to either intermittent or terminal drought stress, making drought the primary cause of yield loss under farmers' field conditions. Improved photosynthate acquisition, accumulation, and then remobilization have been observed as important mechanisms for adaptation to drought stress. The objective of this study was to tag quantitative trait loci (QTL) for photosynthate acquisition, accumulation, and remobilization to grain by using a recombinant inbred line population developed from the Mesoamerican intragenepool cross of drought-susceptible DOR364 and drought-tolerant BAT477 grown under eight environments differing in drought stress across two continents: Africa and South America. The recombinant inbred line population expressed quantitative variation and transgressive segregation for 11 traits associated with drought tolerance. QTL were detected by both a mixed multienvironment model and by composite interval mapping for each environment using a linkage map constructed with 165 genetic markers that covered 11 linkage groups of the common bean genome. In the multienvironment, mixed model, nine QTL were detected for 10 drought stress tolerance mechanism traits found on six of the 11 linkage groups. Significant QTL × environment interaction was observed for six of the nine QTL. QTL × environment interaction was of the cross-over type for three of the six significant QTL with contrasting effect of the parental alleles across different environments. In the composite interval mapping, we found 69 QTL in total. The majority of these were found for Palmira (47) or Awassa (18), with fewer in Malawi (4). Phenotypic variation explained by QTL in single environments ranged up to 37%, and the most consistent QTL were for Soil Plant Analysis Development (SPAD) leaf chlorophyll reading and pod partitioning traits. QTL alignment between the two detection methods showed that yield QTL on b08 and stem

  4. Evaluation and Quantitative trait loci mapping of resistance to powdery mildew in lettuce

    USDA-ARS?s Scientific Manuscript database

    Lettuce (Lactuca sativa L.) is the major leafy vegetable that is susceptible to powdery mildew disease under greenhouse and field conditions. We mapped quantitative trait loci (QTLs) for resistance to powdery mildew under greenhouse conditions in an interspecific population derived from a cross betw...

  5. Quantitative learning strategies based on word networks

    NASA Astrophysics Data System (ADS)

    Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

    2018-02-01

    Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

  6. Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

    PubMed

    Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

    2007-09-01

    Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

  7. Genetic Map Construction and Quantitative Trait Locus (QTL) Detection of Growth-Related Traits in Litopenaeus vannamei for Selective Breeding Applications

    PubMed Central

    Andriantahina, Farafidy; Liu, Xiaolin; Huang, Hao

    2013-01-01

    Growth is a priority trait from the point of view of genetic improvement. Molecular markers linked to quantitative trait loci (QTL) have been regarded as useful for marker-assisted selection (MAS) in complex traits as growth. Using an intermediate F2 cross of slow and fast growth parents, a genetic linkage map of Pacific whiteleg shrimp, Litopenaeusvannamei , based on amplified fragment length polymorphisms (AFLP) and simple sequence repeats (SSR) markers was constructed. Meanwhile, QTL analysis was performed for growth-related traits. The linkage map consisted of 451 marker loci (429 AFLPs and 22 SSRs) which formed 49 linkage groups with an average marker space of 7.6 cM; they spanned a total length of 3627.6 cM, covering 79.50% of estimated genome size. 14 QTLs were identified for growth-related traits, including three QTLs for body weight (BW), total length (TL) and partial carapace length (PCL), two QTLs for body length (BL), one QTL for first abdominal segment depth (FASD), third abdominal segment depth (TASD) and first abdominal segment width (FASW), which explained 2.62 to 61.42% of phenotypic variation. Moreover, comparison of linkage maps between L . vannamei and Penaeus japonicus was applied, providing a new insight into the genetic base of QTL affecting the growth-related traits. The new results will be useful for conducting MAS breeding schemes in L . vannamei . PMID:24086466

  8. Statistical genetics and evolution of quantitative traits

    NASA Astrophysics Data System (ADS)

    Neher, Richard A.; Shraiman, Boris I.

    2011-10-01

    The distribution and heritability of many traits depends on numerous loci in the genome. In general, the astronomical number of possible genotypes makes the system with large numbers of loci difficult to describe. Multilocus evolution, however, greatly simplifies in the limit of weak selection and frequent recombination. In this limit, populations rapidly reach quasilinkage equilibrium (QLE) in which the dynamics of the full genotype distribution, including correlations between alleles at different loci, can be parametrized by the allele frequencies. This review provides a simplified exposition of the concept and mathematics of QLE which is central to the statistical description of genotypes in sexual populations. Key results of quantitative genetics such as the generalized Fisher’s “fundamental theorem,” along with Wright’s adaptive landscape, are shown to emerge within QLE from the dynamics of the genotype distribution. This is followed by a discussion under what circumstances QLE is applicable, and what the breakdown of QLE implies for the population structure and the dynamics of selection. Understanding the fundamental aspects of multilocus evolution obtained through simplified models may be helpful in providing conceptual and computational tools to address the challenges arising in the studies of complex quantitative phenotypes of practical interest.

  9. The network property of the thalamus in the default mode network is correlated with trait mindfulness.

    PubMed

    Wang, X; Xu, M; Song, Y; Li, X; Zhen, Z; Yang, Z; Liu, J

    2014-10-10

    Mindfulness is typically defined as nonjudgmental awareness of experiences in the present moment, which is beneficial for mental and physical well-being. Previous studies have identified multiple regions in the default mode network (DMN) that are involved in mindfulness, but little is known about how these regions work collaboratively as a network. Here, we used resting-state functional magnetic resonance imaging to investigate the role of the DMN in trait mindfulness by correlating spontaneous functional connectivity among DMN nodes with self-reported trait mindfulness in a large population of young human adults. Among all pairs of the DMN nodes, we found that individuals with weaker functional connectivity between the thalamus and posterior cingulate cortex (PCC) were more mindful of the present. Post-hoc analyses of these two nodes further revealed that graph-based nodal properties of the thalamus, not the PCC, were negatively correlated with trait mindfulness, suggesting that a low involvement of the thalamus in the DMN is relevant for high trait mindfulness. Our findings not only suggest the thalamus as a switch between mind-wandering and mindfulness, but also invite future studies on mechanisms of how mindfulness produces beneficial effects by modulating the thalamus. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  10. General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters.

    PubMed

    Hadfield, J D; Nakagawa, S

    2010-03-01

    Although many of the statistical techniques used in comparative biology were originally developed in quantitative genetics, subsequent development of comparative techniques has progressed in relative isolation. Consequently, many of the new and planned developments in comparative analysis already have well-tested solutions in quantitative genetics. In this paper, we take three recent publications that develop phylogenetic meta-analysis, either implicitly or explicitly, and show how they can be considered as quantitative genetic models. We highlight some of the difficulties with the proposed solutions, and demonstrate that standard quantitative genetic theory and software offer solutions. We also show how results from Bayesian quantitative genetics can be used to create efficient Markov chain Monte Carlo algorithms for phylogenetic mixed models, thereby extending their generality to non-Gaussian data. Of particular utility is the development of multinomial models for analysing the evolution of discrete traits, and the development of multi-trait models in which traits can follow different distributions. Meta-analyses often include a nonrandom collection of species for which the full phylogenetic tree has only been partly resolved. Using missing data theory, we show how the presented models can be used to correct for nonrandom sampling and show how taxonomies and phylogenies can be combined to give a flexible framework with which to model dependence.

  11. Comparative mapping reveals quantitative trait loci that affect spawning time in coho salmon (Oncorhynchus kisutch)

    PubMed Central

    Araneda, Cristian; Díaz, Nelson F.; Gomez, Gilda; López, María Eugenia; Iturra, Patricia

    2012-01-01

    Spawning time in salmonids is a sex-limited quantitative trait that can be modified by selection. In rainbow trout (Oncorhynchus mykiss), various quantitative trait loci (QTL) that affect the expression of this trait have been discovered. In this study, we describe four microsatellite loci associated with two possible spawning time QTL regions in coho salmon (Oncorhynchus kisutch). The four loci were identified in females from two populations (early and late spawners) produced by divergent selection from the same base population. Three of the loci (OmyFGT34TUF, One2ASC and One19ASC) that were strongly associated with spawning time in coho salmon (p < 0.0002) were previously associated with QTL for the same trait in rainbow trout; a fourth loci (Oki10) with a suggestive association (p = 0.00035) mapped 10 cM from locus OmyFGT34TUF in rainbow trout. The changes in allelic frequency observed after three generations of selection were greater than expected because of genetic drift. This work shows that comparing information from closely-related species is a valid strategy for identifying QTLs for marker-assisted selection in species whose genomes are poorly characterized or lack a saturated genetic map. PMID:22888302

  12. Influence analysis in quantitative trait loci detection.

    PubMed

    Dou, Xiaoling; Kuriki, Satoshi; Maeno, Akiteru; Takada, Toyoyuki; Shiroishi, Toshihiko

    2014-07-01

    This paper presents systematic methods for the detection of influential individuals that affect the log odds (LOD) score curve. We derive general formulas of influence functions for profile likelihoods and introduce them into two standard quantitative trait locus detection methods-the interval mapping method and single marker analysis. Besides influence analysis on specific LOD scores, we also develop influence analysis methods on the shape of the LOD score curves. A simulation-based method is proposed to assess the significance of the influence of the individuals. These methods are shown useful in the influence analysis of a real dataset of an experimental population from an F2 mouse cross. By receiver operating characteristic analysis, we confirm that the proposed methods show better performance than existing diagnostics. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Congruent climate-related genecological responses from molecular markers and quantitative traits for western white pine (Pinus monticola)

    Treesearch

    Bryce A. Richardson; Gerald E. Rehfeldt; Mee-Sook Kim

    2009-01-01

    Analyses of molecular and quantitative genetic data demonstrate the existence of congruent climate-related patterns in western white pine (Pinus monticola). Two independent studies allowed comparisons of amplified fragment length polymorphism (AFLP) markers with quantitative variation in adaptive traits. Principal component analyses...

  14. Replication of linkage to quantitative trait loci: variation in location and magnitude of the lod score.

    PubMed

    Hsueh, W C; Göring, H H; Blangero, J; Mitchell, B D

    2001-01-01

    Replication of linkage signals from independent samples is considered an important step toward verifying the significance of linkage signals in studies of complex traits. The purpose of this empirical investigation was to examine the variability in the precision of localizing a quantitative trait locus (QTL) by analyzing multiple replicates of a simulated data set with the use of variance components-based methods. Specifically, we evaluated across replicates the variation in both the magnitude and the location of the peak lod scores. We analyzed QTLs whose effects accounted for 10-37% of the phenotypic variance in the quantitative traits. Our analyses revealed that the precision of QTL localization was directly related to the magnitude of the QTL effect. For a QTL with effect accounting for > 20% of total phenotypic variation, > 90% of the linkage peaks fall within 10 cM from the true gene location. We found no evidence that, for a given magnitude of the lod score, the presence of interaction influenced the precision of QTL localization.

  15. CBCL Pediatric Bipolar Disorder Profile and ADHD: Comorbidity and Quantitative Trait Loci Analysis

    ERIC Educational Resources Information Center

    McGough, James J.; Loo, Sandra K.; McCracken, James T.; Dang, Jeffery; Clark, Shaunna; Nelson, Stanley F.; Smalley, Susan L.

    2008-01-01

    The pediatric bipolar disorder profile of the Child Behavior checklist is used to differentiate patterns of comorbidity and to search for quantitative trait loci in multiple affected ADHD sibling pairs. The CBCL-PBD profiling identified 8 percent of individuals with severe psychopathology and increased rates of oppositional defiant, conduct and…

  16. Fruit traits and temporal abundance shape plant-frugivore interaction networks in a seasonal tropical forest.

    PubMed

    Ramos-Robles, Michelle; Dáttilo, Wesley; Díaz-Castelazo, Cecilia; Andresen, Ellen

    2018-04-02

    Interactions between fleshy fruited plants and frugivores are crucial for the structuring and functioning of biotic communities, particularly in tropical forests where both groups are diverse and play different roles in network organization. However, it remains poorly understood how different groups of frugivore species and fruit traits contribute to network structure. We recorded interactions among 28 plant species and three groups of frugivores (birds, bats, and non-flying mammals) in a seasonal forest in Mexico to determine which species contribute more to network structure and evaluate the importance of each species. We also determined whether fruit abundance, water content, morphology traits, and fruiting phenology are related to network parameters: the number of interactions, species contribution to nestedness, and species strength. We found that plants did not depend on a single group of frugivores, but rather on one species of each group: the bird Pitangus sulphuratus, the bat Sturnira parvidens, and the non-flying mammal Procyon lotor. The abundance, size, and water content of the fruits were significantly related to the contribution to nestedness, number of interactions, and species strength index of plant species. Tree species and birds contributed mainly to the nested structure of the network. We show that the structure of plant-frugivore networks in this seasonal forest is non-random and that fruit traits (i.e., abundance, phenology, size, and water content) are important factors shaping plant-frugivore networks. Identification of the key species and their traits that maintain the complex structure of species interactions is therefore fundamental for the integral conservation of tropical forests.

  17. A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

    PubMed

    Anderson, Carl A; McRae, Allan F; Visscher, Peter M

    2006-07-01

    Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

  18. Field-Based High-Throughput Plant Phenotyping Reveals the Temporal Patterns of Quantitative Trait Loci Associated with Stress-Responsive Traits in Cotton

    PubMed Central

    Pauli, Duke; Andrade-Sanchez, Pedro; Carmo-Silva, A. Elizabete; Gazave, Elodie; French, Andrew N.; Heun, John; Hunsaker, Douglas J.; Lipka, Alexander E.; Setter, Tim L.; Strand, Robert J.; Thorp, Kelly R.; Wang, Sam; White, Jeffrey W.; Gore, Michael A.

    2016-01-01

    The application of high-throughput plant phenotyping (HTPP) to continuously study plant populations under relevant growing conditions creates the possibility to more efficiently dissect the genetic basis of dynamic adaptive traits. Toward this end, we employed a field-based HTPP system that deployed sets of sensors to simultaneously measure canopy temperature, reflectance, and height on a cotton (Gossypium hirsutum L.) recombinant inbred line mapping population. The evaluation trials were conducted under well-watered and water-limited conditions in a replicated field experiment at a hot, arid location in central Arizona, with trait measurements taken at different times on multiple days across 2010–2012. Canopy temperature, normalized difference vegetation index (NDVI), height, and leaf area index (LAI) displayed moderate-to-high broad-sense heritabilities, as well as varied interactions among genotypes with water regime and time of day. Distinct temporal patterns of quantitative trait loci (QTL) expression were mostly observed for canopy temperature and NDVI, and varied across plant developmental stages. In addition, the strength of correlation between HTPP canopy traits and agronomic traits, such as lint yield, displayed a time-dependent relationship. We also found that the genomic position of some QTL controlling HTPP canopy traits were shared with those of QTL identified for agronomic and physiological traits. This work demonstrates the novel use of a field-based HTPP system to study the genetic basis of stress-adaptive traits in cotton, and these results have the potential to facilitate the development of stress-resilient cotton cultivars. PMID:26818078

  19. Multivariate machine learning distinguishes cross-network dynamic functional connectivity patterns in state and trait neuropathic pain.

    PubMed

    Cheng, J C; Rogachov, A; Hemington, K S; Kucyi, A; Bosma, R L; Lindquist, M A; Inman, R D; Davis, K D

    2018-04-26

    Communication within the brain is dynamic. Chronic pain can also be dynamic, with varying intensities experienced over time. Little is known of how brain dynamics are disrupted in chronic pain, or relates to patients' pain assessed at various time-scales (e.g., short-term state versus long-term trait). Patients experience pain "traits" indicative of their general condition, but also pain "states" that vary day to day. Here, we used network-based multivariate machine learning to determine how patterns in dynamic and static brain communication are related to different characteristics and timescales of chronic pain. Our models were based on resting state dynamic and static functional connectivity (dFC, sFC) in patients with chronic neuropathic pain (NP) or non-NP. The most prominent networks in the models were the default mode, salience, and executive control networks. We also found that cross-network measures of dFC rather than sFC were better associated with patients' pain, but only in those with NP features. These associations were also more highly and widely associated with measures of trait rather than state pain. Furthermore, greater dynamic connectivity with executive control networks was associated with milder neuropathic pain, but greater dynamic connectivity with limbic networks was associated greater neuropathic pain. Compared with healthy individuals, the dFC features most highly related to trait neuropathic pain were also more abnormal in patients with greater pain. Our findings indicate that dFC reflects patients' overall pain condition (i.e., trait pain), not just their current state, and is impacted by complexities in pain features beyond intensity.

  20. Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

    PubMed Central

    Bürger, R; Gimelfarb, A

    1999-01-01

    Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

  1. Identifying the genes underlying quantitative traits: a rationale for the QTN programme.

    PubMed

    Lee, Young Wha; Gould, Billie A; Stinchcombe, John R

    2014-01-01

    The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the 'QTN programme' and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution.

  2. Identifying the genes underlying quantitative traits: a rationale for the QTN programme

    PubMed Central

    Lee, Young Wha; Gould, Billie A.; Stinchcombe, John R.

    2014-01-01

    The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the ‘QTN programme’ and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution. PMID:24790125

  3. Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

    PubMed Central

    Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

    2017-01-01

    To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696

  4. Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

    PubMed

    Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

    2017-02-01

    To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.

  5. Identification of common coexpression modules based on quantitative network comparison.

    PubMed

    Jo, Yousang; Kim, Sanghyeon; Lee, Doheon

    2018-06-13

    Finding common molecular interactions from different samples is essential work to understanding diseases and other biological processes. Coexpression networks and their modules directly reflect sample-specific interactions among genes. Therefore, identification of common coexpression network or modules may reveal the molecular mechanism of complex disease or the relationship between biological processes. However, there has been no quantitative network comparison method for coexpression networks and we examined previous methods for other networks that cannot be applied to coexpression network. Therefore, we aimed to propose quantitative comparison methods for coexpression networks and to find common biological mechanisms between Huntington's disease and brain aging by the new method. We proposed two similarity measures for quantitative comparison of coexpression networks. Then, we performed experiments using known coexpression networks. We showed the validity of two measures and evaluated threshold values for similar coexpression network pairs from experiments. Using these similarity measures and thresholds, we quantitatively measured the similarity between disease-specific and aging-related coexpression modules and found similar Huntington's disease-aging coexpression module pairs. We identified similar Huntington's disease-aging coexpression module pairs and found that these modules are related to brain development, cell death, and immune response. It suggests that up-regulated cell signalling related cell death and immune/ inflammation response may be the common molecular mechanisms in the pathophysiology of HD and normal brain aging in the frontal cortex.

  6. Heritability and quantitative genetic divergence of serotiny, a fire-persistence plant trait

    PubMed Central

    Hernández-Serrano, Ana; Verdú, Miguel; Santos-del-Blanco, Luís; Climent, José; González-Martínez, Santiago C.; Pausas, Juli G.

    2014-01-01

    Background and Aims Although it is well known that fire acts as a selective pressure shaping plant phenotypes, there are no quantitative estimates of the heritability of any trait related to plant persistence under recurrent fires, such as serotiny. In this study, the heritability of serotiny in Pinus halepensis is calculated, and an evaluation is made as to whether fire has left a selection signature on the level of serotiny among populations by comparing the genetic divergence of serotiny with the expected divergence of neutral molecular markers (QST–FST comparison). Methods A common garden of P. halepensis was used, located in inland Spain and composed of 145 open-pollinated families from 29 provenances covering the entire natural range of P. halepensis in the Iberian Peninsula and Balearic Islands. Narrow-sense heritability (h2) and quantitative genetic differentiation among populations for serotiny (QST) were estimated by means of an ‘animal model’ fitted by Bayesian inference. In order to determine whether genetic differentiation for serotiny is the result of differential natural selection, QST estimates for serotiny were compared with FST estimates obtained from allozyme data. Finally, a test was made of whether levels of serotiny in the different provenances were related to different fire regimes, using summer rainfall as a proxy for fire regime in each provenance. Key Results Serotiny showed a significant narrow-sense heritability (h2) of 0·20 (credible interval 0·09–0·40). Quantitative genetic differentiation among provenances for serotiny (QST = 0·44) was significantly higher than expected under a neutral process (FST = 0·12), suggesting adaptive differentiation. A significant negative relationship was found between the serotiny level of trees in the common garden and summer rainfall of their provenance sites. Conclusions Serotiny is a heritable trait in P. halepensis, and selection acts on it, giving rise to contrasting serotiny levels

  7. Missing heritability in the tails of quantitative traits? A simulation study on the impact of slightly altered true genetic models.

    PubMed

    Pütter, Carolin; Pechlivanis, Sonali; Nöthen, Markus M; Jöckel, Karl-Heinz; Wichmann, Heinz-Erich; Scherag, André

    2011-01-01

    Genome-wide association studies have identified robust associations between single nucleotide polymorphisms and complex traits. As the proportion of phenotypic variance explained is still limited for most of the traits, larger and larger meta-analyses are being conducted to detect additional associations. Here we investigate the impact of the study design and the underlying assumption about the true genetic effect in a bimodal mixture situation on the power to detect associations. We performed simulations of quantitative phenotypes analysed by standard linear regression and dichotomized case-control data sets from the extremes of the quantitative trait analysed by standard logistic regression. Using linear regression, markers with an effect in the extremes of the traits were almost undetectable, whereas analysing extremes by case-control design had superior power even for much smaller sample sizes. Two real data examples are provided to support our theoretical findings and to explore our mixture and parameter assumption. Our findings support the idea to re-analyse the available meta-analysis data sets to detect new loci in the extremes. Moreover, our investigation offers an explanation for discrepant findings when analysing quantitative traits in the general population and in the extremes. Copyright © 2011 S. Karger AG, Basel.

  8. Systems genetics approaches to understand complex traits

    PubMed Central

    Civelek, Mete; Lusis, Aldons J.

    2014-01-01

    Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

  9. Phylogenetic trait-based analyses of ecological networks

    PubMed Central

    Rafferty, Nicole E.; Ives, Anthony R.

    2013-01-01

    Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant–pollinator community to anticipated climate change. The methods allow the statistical assessment of, for example, whether closely related pollinators are more likely to visit plants with similar relative frequencies, and whether closely related pollinators tend to visit closely related plants. The methods can also incorporate trait information, allowing us to identify which plant traits are likely responsible for attracting different pollinators. These questions are important for our study of 14 prairie plants and their 22 insect pollinators. Over the last 70 years, six of the plants have advanced their flowering, while eight have not. When we experimentally forced earlier flowering times, five of the six advanced-flowering species experienced higher pollinator visitation rates, whereas only one of the eight other species had more visits; this network thus appears resilient to climate change, because those species with advanced flowering have ample pollinators earlier in the season. Using the methods developed here, we show that advanced-flowering plants did not have a distinct pollinator community from the other eight species. Furthermore, pollinator phylogeny did not explain pollinator community composition; closely related pollinators were not more likely to visit the same plant species. However, differences among pollinator communities visiting different plants were explained by plant height, floral color, and symmetry. As a result, closely related plants attracted similar numbers of pollinators. By parsing

  10. Phylogenetic trait-based analyses of ecological networks.

    PubMed

    Rafferty, Nicole E; Ives, Anthony R

    2013-10-01

    Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant-pollinator community to anticipated climate change. The methods allow the statistical assessment of, for example, whether closely related pollinators are more likely to visit plants with similar relative frequencies, and whether closely related pollinators tend to visit closely related plants. The methods can also incorporate trait information, allowing us to identify which plant traits are likely responsible for attracting different pollinators. These questions are important for our study of 14 prairie plants and their 22 insect pollinators. Over the last 70 years, six of the plants have advanced their flowering, while eight have not. When we experimentally forced earlier flowering times, five of the six advanced-flowering species experienced higher pollinator visitation rates, whereas only one of the eight other species had more visits; this network thus appears resilient to climate change, because those species with advanced flowering have ample pollinators earlier in the season. Using the methods developed here, we show that advanced-flowering plants did not have a distinct pollinator community from the other eight species. Furthermore, pollinator phylogeny did not explain pollinator community composition; closely related pollinators were not more likely to visit the same plant species. However, differences among pollinator communities visiting different plants were explained by plant height, floral color, and symmetry. As a result, closely related plants attracted similar numbers of pollinators. By parsing out

  11. Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs.

    PubMed

    Cherel, Pierre; Pires, José; Glénisson, Jérôme; Milan, Denis; Iannuccelli, Nathalie; Hérault, Frédéric; Damon, Marie; Le Roy, Pascale

    2011-08-29

    Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected

  12. Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs

    PubMed Central

    2011-01-01

    Background Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Results Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Conclusions Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major

  13. Variation in seed dormancy quantitative trait loci in Arabidopsis thaliana originating from one site.

    PubMed

    Silady, Rebecca A; Effgen, Sigi; Koornneef, Maarten; Reymond, Matthieu

    2011-01-01

    A Quantitative Trait Locus (QTL) analysis was performed using two novel Recombinant Inbred Line (RIL) populations, derived from the progeny between two Arabidopsis thaliana genotypes collected at the same site in Kyoto (Japan) crossed with the reference laboratory strain Landsberg erecta (Ler). We used these two RIL populations to determine the genetic basis of seed dormancy and flowering time, which are assumed to be the main traits controlling life history variation in Arabidopsis. The analysis revealed quantitative variation for seed dormancy that is associated with allelic variation at the seed dormancy QTL DOG1 (for Delay Of Germination 1) in one population and at DOG6 in both. These DOG QTL have been previously identified using mapping populations derived from accessions collected at different sites around the world. Genetic variation within a population may enhance its ability to respond accurately to variation within and between seasons. In contrast, variation for flowering time, which also segregated within each mapping population, is mainly governed by the same QTL.

  14. Comparative mapping of quantitative trait loci sculpting the curd of Brassica oleracea.

    PubMed

    Lan, T H; Paterson, A H

    2000-08-01

    The enlarged inflorescence (curd) of cauliflower and broccoli provide not only a popular vegetable for human consumption, but also a unique opportunity for scientists who seek to understand the genetic basis of plant growth and development. By the comparison of quantitative trait loci (QTL) maps constructed from three different F(2) populations, we identified a total of 86 QTL that control eight curd-related traits in Brassica oleracea. The 86 QTL may reflect allelic variation in as few as 67 different genetic loci and 54 ancestral genes. Although the locations of QTL affecting a trait occasionally corresponded between different populations or between different homeologous Brassica chromosomes, our data supported other molecular and morphological data in suggesting that the Brassica genus is rapidly evolving. Comparative data enabled us to identify a number of candidate genes from Arabidopsis that warrant further investigation to determine if some of them might account for Brassica QTL. The Arabidopsis/Brassica system is an important example of both the challenges and opportunities associated with extrapolation of genomic information from facile models to large-genome taxa including major crops.

  15. A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits

    PubMed Central

    Yang, Runqing; Gao, Huijiang; Wang, Xin; Zhang, Ji; Zeng, Zhao-Bang; Wu, Rongling

    2007-01-01

    Functional mapping has emerged as a powerful tool for mapping quantitative trait loci (QTL) that control developmental patterns of complex dynamic traits. Original functional mapping has been constructed within the context of simple interval mapping, without consideration of separate multiple linked QTL for a dynamic trait. In this article, we present a statistical framework for mapping QTL that affect dynamic traits by capitalizing on the strengths of functional mapping and composite interval mapping. Within this so-called composite functional-mapping framework, functional mapping models the time-dependent genetic effects of a QTL tested within a marker interval using a biologically meaningful parametric function, whereas composite interval mapping models the time-dependent genetic effects of the markers outside the test interval to control the genome background using a flexible nonparametric approach based on Legendre polynomials. Such a semiparametric framework was formulated by a maximum-likelihood model and implemented with the EM algorithm, allowing for the estimation and the test of the mathematical parameters that define the QTL effects and the regression coefficients of the Legendre polynomials that describe the marker effects. Simulation studies were performed to investigate the statistical behavior of composite functional mapping and compare its advantage in separating multiple linked QTL as compared to functional mapping. We used the new mapping approach to analyze a genetic mapping example in rice, leading to the identification of multiple QTL, some of which are linked on the same chromosome, that control the developmental trajectory of leaf age. PMID:17947431

  16. Smoothing of the bivariate LOD score for non-normal quantitative traits.

    PubMed

    Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

    2005-12-30

    Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

  17. DRIFTSEL: an R package for detecting signals of natural selection in quantitative traits.

    PubMed

    Karhunen, M; Merilä, J; Leinonen, T; Cano, J M; Ovaskainen, O

    2013-07-01

    Approaches and tools to differentiate between natural selection and genetic drift as causes of population differentiation are of frequent demand in evolutionary biology. Based on the approach of Ovaskainen et al. (2011), we have developed an R package (DRIFTSEL) that can be used to differentiate between stabilizing selection, diversifying selection and random genetic drift as causes of population differentiation in quantitative traits when neutral marker and quantitative genetic data are available. Apart from illustrating the use of this method and the interpretation of results using simulated data, we apply the package on data from three-spined sticklebacks (Gasterosteus aculeatus) to highlight its virtues. DRIFTSEL can also be used to perform usual quantitative genetic analyses in common-garden study designs. © 2013 John Wiley & Sons Ltd.

  18. The salience network and human personality: Integrity of white matter tracts within anterior and posterior salience network relates to the self-directedness character trait.

    PubMed

    Prillwitz, Conrad; Rüber, Theodor; Reuter, Martin; Montag, Christian; Weber, Bernd; Elger, Christian E; Markett, Sebastian

    2018-04-28

    A prevailing topic in personality neuroscience is the question how personality traits are reflected in the brain. Functional and structural networks have been examined by functional and structural magnetic resonance imaging, however, the structural correlates of functionally defined networks have not been investigated in a personality context. By using the Temperament and Character Inventory (TCI) and Diffusion Tensor Imaging (DTI), the present study assesses in a sample of 116 healthy participants how personality traits proposed in the framework of the biopsychosocial theory on personality relate to white matter pathways delineated by functional network imaging. We show that the character trait self-directedness relates to the overall microstructural integrity of white matter tracts constituting the salience network as indicated by DTI-derived measures. Self-directedness has been proposed as the executive control component of personality and describes the tendency to stay focused on the attainment of long-term goals. The present finding corroborates the view of the salience network as an executive control network that serves maintenance of rules and task-sets to guide ongoing behavior. Copyright © 2018. Published by Elsevier B.V.

  19. Signatures of Evolutionary Adaptation in Quantitative Trait Loci Influencing Trace Element Homeostasis in Liver

    PubMed Central

    Sabidó, Eduard; Bosch, Elena

    2016-01-01

    Essential trace elements possess vital functions at molecular, cellular, and physiological levels in health and disease, and they are tightly regulated in the human body. In order to assess variability and potential adaptive evolution of trace element homeostasis, we quantified 18 trace elements in 150 liver samples, together with the expression levels of 90 genes and abundances of 40 proteins involved in their homeostasis. Additionally, we genotyped 169 single nucleotide polymorphism (SNPs) in the same sample set. We detected significant associations for 8 protein quantitative trait loci (pQTL), 10 expression quantitative trait loci (eQTLs), and 15 micronutrient quantitative trait loci (nutriQTL). Six of these exceeded the false discovery rate cutoff and were related to essential trace elements: 1) one pQTL for GPX2 (rs10133290); 2) two previously described eQTLs for HFE (rs12346) and SELO (rs4838862) expression; and 3) three nutriQTLs: The pathogenic C282Y mutation at HFE affecting iron (rs1800562), and two SNPs within several clustered metallothionein genes determining selenium concentration (rs1811322 and rs904773). Within the complete set of significant QTLs (which involved 30 SNPs and 20 gene regions), we identified 12 SNPs with extreme patterns of population differentiation (FST values in the top 5% percentile in at least one HapMap population pair) and significant evidence for selective sweeps involving QTLs at GPX1, SELENBP1, GPX3, SLC30A9, and SLC39A8. Overall, this detailed study of various molecular phenotypes illustrates the role of regulatory variants in explaining differences in trace element homeostasis among populations and in the human adaptive response to environmental pressures related to micronutrients. PMID:26582562

  20. Novel Autism Subtype-Dependent Genetic Variants Are Revealed by Quantitative Trait and Subphenotype Association Analyses of Published GWAS Data

    PubMed Central

    Hu, Valerie W.; Addington, Anjene; Hyman, Alexander

    2011-01-01

    The heterogeneity of symptoms associated with autism spectrum disorders (ASDs) has presented a significant challenge to genetic analyses. Even when associations with genetic variants have been identified, it has been difficult to associate them with a specific trait or characteristic of autism. Here, we report that quantitative trait analyses of ASD symptoms combined with case-control association analyses using distinct ASD subphenotypes identified on the basis of symptomatic profiles result in the identification of highly significant associations with 18 novel single nucleotide polymorphisms (SNPs). The symptom categories included deficits in language usage, non-verbal communication, social development, and play skills, as well as insistence on sameness or ritualistic behaviors. Ten of the trait-associated SNPs, or quantitative trait loci (QTL), were associated with more than one subtype, providing partial replication of the identified QTL. Notably, none of the novel SNPs is located within an exonic region, suggesting that these hereditary components of ASDs are more likely related to gene regulatory processes (or gene expression) than to structural or functional changes in gene products. Seven of the QTL reside within intergenic chromosomal regions associated with rare copy number variants that have been previously reported in autistic samples. Pathway analyses of the genes associated with the QTL identified in this study implicate neurological functions and disorders associated with autism pathophysiology. This study underscores the advantage of incorporating both quantitative traits as well as subphenotypes into large-scale genome-wide analyses of complex disorders. PMID:21556359

  1. Quantitative Genetic Architecture at Latitudinal Range Boundaries: Reduced Variation but Higher Trait Independence.

    PubMed

    Paccard, Antoine; Van Buskirk, Josh; Willi, Yvonne

    2016-05-01

    Species distribution limits are hypothesized to be caused by small population size and limited genetic variation in ecologically relevant traits, but earlier studies have not evaluated genetic variation in multivariate phenotypes. We asked whether populations at the latitudinal edges of the distribution have altered quantitative genetic architecture of ecologically relevant traits compared with midlatitude populations. We calculated measures of evolutionary potential in nine Arabidopsis lyrata populations spanning the latitudinal range of the species in eastern and midwestern North America. Environments at the latitudinal extremes have reduced water availability, and therefore plants were assessed under wet and dry treatments. We estimated genetic variance-covariance (G-) matrices for 10 traits related to size, development, and water balance. Populations at southern and northern distribution edges had reduced levels of genetic variation across traits, but their G-matrices were more spherical; G-matrix orientation was unrelated to latitude. As a consequence, the predicted short-term response to selection was at least as strong in edge populations as in central populations. These results are consistent with genetic drift eroding variation and reducing the effectiveness of correlational selection at distribution margins. We conclude that genetic variation of isolated traits poorly predicts the capacity to evolve in response to multivariate selection and that the response to selection may frequently be greater than expected at species distribution margins because of genetic drift.

  2. Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

    PubMed

    Han, Lide; Yang, Jian; Zhu, Jun

    2007-06-01

    A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

  3. Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits.

    PubMed

    Yadav, Anupama; Dhole, Kaustubh; Sinha, Himanshu

    2016-12-01

    Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets.

  4. Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

    PubMed Central

    Yadav, Anupama; Dhole, Kaustubh

    2016-01-01

    Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets. PMID:28172852

  5. Behavior characteristics of the attention network of military personnel with high and low trait anxiety

    PubMed Central

    Pan, Yu; Cai, Wenpeng; Dong, Wei; Xiao, Jie; Yan, Jin; Cheng, Qi

    2017-01-01

    Abstract Converging evidence reveals significant increase in both state anxiety and trait anxiety during the past 2 decades among military servicemen and servicewomen in China. In the present study, we employed the Chinese version of the State-trait Anxiety Inventory (STAI) to examine trait and state anxiety in Chinese military servicemen and servicewomen. We further evaluated orienting, alerting and execution inhibition using the attention network test. Healthy military servicemen and servicewomen were recruited for the present study. The STAI was used to measure both state and trait anxiety and the attention network test was done to determine reaction time and accuracy rate. Fifty-seven subjects were eligible for the study. Their mean STAI score was 3.2 ± 2.8 (range, 1–17) and 29 (50.9%) subjects were categorized into the high trait anxiety group and 28 (49.1%) subjects into the low trait anxiety group. The reaction time of the high trait anxiety group to incongruent, congruent, and neutral target was significantly longer than that of the low trait anxiety group (P < .05). Moreover, the accurate rate of the high trait anxiety group for incongruent, congruent, and neutral target was significantly higher than that of the low trait anxiety group (P < .05). Repeated analysis of variance showed marked effect of trait anxiety, cue types, and target types on reaction time. There was significant interaction among trait anxiety, target types, and cue types. Trait anxiety and target types also had marked effect on the accurate rate. Multivariate analysis showed no marked effect of trait anxiety on the alerting, orienting, and execution inhibition subnetwork. The present study has demonstrated that military service personnel with high trait anxiety requires more time for cognitive processing of external information but exhibits enhanced reaction accuracy rate compared to those with low trait anxiety. Our findings indicate that interventional strategies to

  6. Behavior characteristics of the attention network of military personnel with high and low trait anxiety.

    PubMed

    Pan, Yu; Cai, Wenpeng; Dong, Wei; Xiao, Jie; Yan, Jin; Cheng, Qi

    2017-04-01

    Converging evidence reveals significant increase in both state anxiety and trait anxiety during the past 2 decades among military servicemen and servicewomen in China. In the present study, we employed the Chinese version of the State-trait Anxiety Inventory (STAI) to examine trait and state anxiety in Chinese military servicemen and servicewomen. We further evaluated orienting, alerting and execution inhibition using the attention network test.Healthy military servicemen and servicewomen were recruited for the present study. The STAI was used to measure both state and trait anxiety and the attention network test was done to determine reaction time and accuracy rate.Fifty-seven subjects were eligible for the study. Their mean STAI score was 3.2 ± 2.8 (range, 1-17) and 29 (50.9%) subjects were categorized into the high trait anxiety group and 28 (49.1%) subjects into the low trait anxiety group. The reaction time of the high trait anxiety group to incongruent, congruent, and neutral target was significantly longer than that of the low trait anxiety group (P < .05). Moreover, the accurate rate of the high trait anxiety group for incongruent, congruent, and neutral target was significantly higher than that of the low trait anxiety group (P < .05). Repeated analysis of variance showed marked effect of trait anxiety, cue types, and target types on reaction time. There was significant interaction among trait anxiety, target types, and cue types. Trait anxiety and target types also had marked effect on the accurate rate. Multivariate analysis showed no marked effect of trait anxiety on the alerting, orienting, and execution inhibition subnetwork.The present study has demonstrated that military service personnel with high trait anxiety requires more time for cognitive processing of external information but exhibits enhanced reaction accuracy rate compared to those with low trait anxiety. Our findings indicate that interventional strategies to improve the

  7. Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

    PubMed

    Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

    2015-08-01

    Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

  8. Network Approach to Autistic Traits: Group and Subgroup Analyses of ADOS Item Scores

    ERIC Educational Resources Information Center

    Anderson, George M.; Montazeri, Farhad; de Bildt, Annelies

    2015-01-01

    A network conceptualization might contribute to understanding the occurrence and interacting nature of behavioral traits in the autism realm. Networks were constructed based on correlations of item scores of the Autism Diagnostic Observation Schedule for Modules 1, 2 and 3 obtained for a group of 477 Dutch individuals with developmental disorders.…

  9. Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data.

    PubMed

    Li, Zitong; Sillanpää, Mikko J

    2015-12-01

    Advanced platforms have recently become available for automatic and systematic quantification of plant growth and development. These new techniques can efficiently produce multiple measurements of phenotypes over time, and introduce time as an extra dimension to quantitative trait locus (QTL) studies. Functional mapping utilizes a class of statistical models for identifying QTLs associated with the growth characteristics of interest. A major benefit of functional mapping is that it integrates information over multiple timepoints, and therefore could increase the statistical power for QTL detection. We review the current development of computationally efficient functional mapping methods which provide invaluable tools for analyzing large-scale timecourse data that are readily available in our post-genome era. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. The influence of genetic drift and selection on quantitative traits in a plant pathogenic fungus.

    PubMed

    Stefansson, Tryggvi S; McDonald, Bruce A; Willi, Yvonne

    2014-01-01

    Genetic drift and selection are ubiquitous evolutionary forces acting to shape genetic variation in populations. While their relative importance has been well studied in plants and animals, less is known about their relative importance in fungal pathogens. Because agro-ecosystems are more homogeneous environments than natural ecosystems, stabilizing selection may play a stronger role than genetic drift or diversifying selection in shaping genetic variation among populations of fungal pathogens in agro-ecosystems. We tested this hypothesis by conducting a QST/FST analysis using agricultural populations of the barley pathogen Rhynchosporium commune. Population divergence for eight quantitative traits (QST) was compared with divergence at eight neutral microsatellite loci (FST) for 126 pathogen strains originating from nine globally distributed field populations to infer the effects of genetic drift and types of selection acting on each trait. Our analyses indicated that five of the eight traits had QST values significantly lower than FST, consistent with stabilizing selection, whereas one trait, growth under heat stress (22°C), showed evidence of diversifying selection and local adaptation (QST>FST). Estimates of heritability were high for all traits (means ranging between 0.55-0.84), and average heritability across traits was negatively correlated with microsatellite gene diversity. Some trait pairs were genetically correlated and there was significant evidence for a trade-off between spore size and spore number, and between melanization and growth under benign temperature. Our findings indicate that many ecologically and agriculturally important traits are under stabilizing selection in R. commune and that high within-population genetic variation is maintained for these traits.

  11. Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

    PubMed

    Baker, Robert L; Leong, Wen Fung; Brock, Marcus T; Markelz, R J Cody; Covington, Michael F; Devisetty, Upendra K; Edwards, Christine E; Maloof, Julin; Welch, Stephen; Weinig, Cynthia

    2015-10-01

    Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

  12. Genome-scan analysis for quantitative trait loci in an F2 tilapia hybrid.

    PubMed

    Cnaani, A; Zilberman, N; Tinman, S; Hulata, G; Ron, M

    2004-09-01

    We searched for genetic linkage between DNA markers and quantitative trait loci (QTLs) for innate immunity, response to stress, biochemical parameters of blood, and fish size in an F2 population derived from an interspecific tilapia hybrid (Oreochromis mossambicusx O. aureus). A family of 114 fish was scanned for 40 polymorphic microsatellite DNA markers and two polymorphic genes, covering approximately 80% of the tilapia genome. These fish had previously been phenotyped for seven immune-response traits and six blood parameters. Critical values for significance were P <0.05 with the false discovery rate (FDR) controlled at 40%. The genome-scan analysis resulted in 35 significant marker-trait associations, involving 26 markers in 16 linkage groups. In a second experiment, nine markers were re-sampled in a second family of 79 fish of the same species hybrid. Seven markers (GM180, GM553, MHC-I, UNH848, UNH868, UNH898 and UNH925) in five linkage groups (LG 1, 3, 4, 22 and 23) were associated with stress response traits. An additional six markers (GM47, GM552, UNH208, UNH881, UNH952, UNH998) in five linkage groups (LG 4, 16, 19, 20 and 23) were verified for their associations with immune response traits, by linkage to several different traits. The portion of variance explained by each QTL was 11% on average, with a maximum of 29%. The average additive effect of QTLs was 0.2 standard deviation units of stress response traits and fish size, with a maximum of 0.33. In three linkage groups (LG 1, 3 and 23) markers were associated with stress response, body weight and sex determination, confirming the location of QTLs reported by several other studies.

  13. Exercise and diet affect quantitative trait loci for body weight and composition traits in an advanced intercross population of mice

    PubMed Central

    Kelly, Scott A.; Hua, Kunjie; Pomp, Daniel

    2012-01-01

    Driven by the recent obesity epidemic, interest in understanding the complex genetic and environmental basis of body weight and composition is great. We investigated this by searching for quantitative trait loci (QTLs) affecting a number of weight and adiposity traits in a G10 advanced intercross population produced from crosses of mice in inbred strain C57BL/6J with those in a strain selected for high voluntary wheel running. The mice in this population were fed either a high-fat or a control diet throughout the study and also measured for four exercise traits prior to death, allowing us to test for pre- and postexercise QTLs as well as QTL-by-diet and QTL-by-exercise interactions. Our genome scan uncovered a number of QTLs, of which 40% replicated QTLs previously found for similar traits in an earlier (G4) generation. For those replicated QTLs, the confidence intervals were reduced from an average of 19 Mb in the G4 to 8 Mb in the G10. Four QTLs on chromosomes 3, 8, 13, and 18 were especially prominent in affecting the percentage of fat in the mice. About of all QTLs showed interactions with diet, exercise, or both, their genotypic effects on the traits showing a variety of patterns depending on the diet or level of exercise. It was concluded that the indirect effects of these QTLs provide an underlying genetic basis for the considerable variability in weight or fat loss typically found among individuals on the same diet and/or exercise regimen. PMID:23048196

  14. Comparative quantitative trait locus mapping of maize flowering-related traits in an F2:3 and recombinant inbred line population.

    PubMed

    Liu, Y H; Yi, Q; Hou, X B; Zhang, X G; Zhang, J J; Liu, H M; Hu, Y F; Huang, Y B

    2016-06-30

    Flowering-related traits in maize are affected by complex factors and are important for the improvement of cropping systems in the maize zone. Quantitative trait loci (QTLs) detected using different materials and methods usually vary. In the present study, 266 maize (Zea mays) F2:3 families and 301 recombinant inbred lines (RIL) derived from a cross between 08-641 (founding parent from southeast China) and Ye478 (founding parent from China) were evaluated for four flowering-related traits, including days to tasseling (DTT), days to pollen shedding (DPS), days to silking (DTS), and anthesis-silking interval. Sixty-six QTLs controlling the target traits were detected in the F2:3 and RIL populations via single environment analysis and joint analysis across all environments (JAAE). The QTLs explained 0.8-13.47% of the phenotypic variation, with 12 QTLs explaining more than 10%. The results of meta-QTL (MQTL) analysis indicated that 41 QTLs could be integrated into 14 MQTLs. One MQTL included 2.9 QTLs, ranging from two to ten QTLs for one to three traits. QTLs, including MQTL1-1 and MQTL9-1, were detected across the F2:3 and RIL populations via SAE and JAAE. Among the MQTLs, nine QTLs were integrated into MQTL9-1 and affected DTT, DPS, and DTS, with the favored allele being derived from 08-641. MQTL3-2 showed high phenotypic variation and was suitable for fine mapping to determine the genetic mechanisms of flowering. MQTL3-2 could be applied to improve inbred lines using marker-assisted selection.

  15. Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

    PubMed

    Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

    2016-10-01

    Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

  16. A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

    PubMed

    Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

    2011-09-01

    Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

  17. Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium.

    PubMed

    Palmer, Nicholette D; Goodarzi, Mark O; Langefeld, Carl D; Wang, Nan; Guo, Xiuqing; Taylor, Kent D; Fingerlin, Tasha E; Norris, Jill M; Buchanan, Thomas A; Xiang, Anny H; Haritunians, Talin; Ziegler, Julie T; Williams, Adrienne H; Stefanovski, Darko; Cui, Jinrui; Mackay, Adrienne W; Henkin, Leora F; Bergman, Richard N; Gao, Xiaoyi; Gauderman, James; Varma, Rohit; Hanis, Craig L; Cox, Nancy J; Highland, Heather M; Below, Jennifer E; Williams, Amy L; Burtt, Noel P; Aguilar-Salinas, Carlos A; Huerta-Chagoya, Alicia; Gonzalez-Villalpando, Clicerio; Orozco, Lorena; Haiman, Christopher A; Tsai, Michael Y; Johnson, W Craig; Yao, Jie; Rasmussen-Torvik, Laura; Pankow, James; Snively, Beverly; Jackson, Rebecca D; Liu, Simin; Nadler, Jerry L; Kandeel, Fouad; Chen, Yii-Der I; Bowden, Donald W; Rich, Stephen S; Raffel, Leslie J; Rotter, Jerome I; Watanabe, Richard M; Wagenknecht, Lynne E

    2015-05-01

    Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

  18. Role Of Social Networks In Resilience Of Naval Recruits: A Quantitative Analysis

    DTIC Science & Technology

    2016-06-01

    comprises 1,297 total surveys from a total of eight divisions of recruits at two different time periods. Quantitative analyses using surveys and network... surveys from a total of eight divisions of recruits at two different time periods. Quantitative analyses using surveys and network data examine the effects...NETWORKS IN RESILIENCE OF NAVAL RECRUITS: A QUANTITATIVE ANALYSIS by Andrea M. Watling June 2016 Thesis Advisor: Edward H. Powley Co

  19. Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

    PubMed Central

    Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang

    2008-01-01

    Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146

  20. Comprehensive comparison of self-administered questionnaires for measuring quantitative autistic traits in adults.

    PubMed

    Nishiyama, Takeshi; Suzuki, Masako; Adachi, Katsunori; Sumi, Satoshi; Okada, Kensuke; Kishino, Hirohisa; Sakai, Saeko; Kamio, Yoko; Kojima, Masayo; Suzuki, Sadao; Kanne, Stephen M

    2014-05-01

    We comprehensively compared all available questionnaires for measuring quantitative autistic traits (QATs) in terms of reliability and construct validity in 3,147 non-clinical and 60 clinical subjects with normal intelligence. We examined four full-length forms, the Subthreshold Autism Trait Questionnaire (SATQ), the Broader Autism Phenotype Questionnaire, the Social Responsiveness Scale2-Adult Self report (SRS2-AS), and the Autism-Spectrum Quotient (AQ). The SRS2-AS and the AQ each had several short forms that we also examined, bringing the total to 11 forms. Though all QAT questionnaires showed acceptable levels of test-retest reliability, the AQ and SRS2-AS, including their short forms, exhibited poor internal consistency and discriminant validity, respectively. The SATQ excelled in terms of classical test theory and due to its short length.

  1. Use of single nucleotide polymorphisms (SNP) to fine-map quantitative trait loci (QTL) in swine

    USDA-ARS?s Scientific Manuscript database

    Mapping quantitative trait loci (QTL) in swine at the US Meat Animal Research Center has relied heavily on linkage mapping in either F2 or Backcross families. QTL identified in the initial scans typically have very broad confidence intervals and further refinement of the QTL’s position is needed bef...

  2. Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait.

    PubMed

    Knight, Jo; North, Bernard V; Sham, Pak C; Curtis, David

    2003-12-31

    This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits.

  3. Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait

    PubMed Central

    Knight, Jo; North, Bernard V; Sham, Pak C; Curtis, David

    2003-01-01

    This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits. PMID:14975142

  4. Depressive Symptoms and Their Interactions With Emotions and Personality Traits Over Time: Interaction Networks in a Psychiatric Clinic.

    PubMed

    Semino, Laura N; Marksteiner, Josef; Brauchle, Gernot; Danay, Erik

    2017-04-13

    Associations between depression, personality traits, and emotions are complex and reciprocal. The aim of this study is to explore these interactions in dynamical networks and in a linear way over time depending on the severity of depression. Participants included 110 patients with depressive symptoms (DSM-5 criteria) who were recruited between October 2015 and February 2016 during their inpatient stay in a general psychiatric hospital in Hall in Tyrol, Austria. The patients filled out the Beck Depression Inventory-II, a German emotional competence questionnaire (Emotionale Kompetenz Fragebogen), Positive and Negative Affect Schedule, and the German versions of the Big Five Inventory-short form and State-Trait-Anxiety-Depression Inventory regarding symptoms, emotions, and personality during their inpatient stay and at a 3-month follow-up by mail. Network and regression analyses were performed to explore interactions both in a linear and a dynamical way at baseline and 3 months later. Regression analyses showed that emotions and personality traits gain importance for the prediction of depressive symptoms with decreasing symptomatology at follow-up (personality: baseline, adjusted R2 = 0.24, P < .001; follow-up, adjusted R2 = 0.65, P < .001). Network analyses additionally showed that the interaction network of depression, emotions, and personality traits is significantly denser and more interconnected (network comparison test: P = .03) at follow-up than at baseline, meaning that with decreased symptoms interconnections get stronger. During depression, personality traits and emotions are walled off and not strongly interconnected with depressive symptoms in networks. With decreasing depressive symptomatology, interfusing of these areas begins and interconnections become stronger. This finding has practical implications for interventions in an acute depressive state and with decreased symptoms. The network approach offers a new perspective on interactions and is a way

  5. Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

    PubMed Central

    Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter

    2016-01-01

    Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308

  6. Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

    PubMed

    Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

    2007-01-01

    Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

  7. A common brain network among state, trait, and pathological anxiety from whole-brain functional connectivity.

    PubMed

    Takagi, Yu; Sakai, Yuki; Abe, Yoshinari; Nishida, Seiji; Harrison, Ben J; Martínez-Zalacaín, Ignacio; Soriano-Mas, Carles; Narumoto, Jin; Tanaka, Saori C

    2018-05-15

    Anxiety is one of the most common mental states of humans. Although it drives us to avoid frightening situations and to achieve our goals, it may also impose significant suffering and burden if it becomes extreme. Because we experience anxiety in a variety of forms, previous studies investigated neural substrates of anxiety in a variety of ways. These studies revealed that individuals with high state, trait, or pathological anxiety showed altered neural substrates. However, no studies have directly investigated whether the different dimensions of anxiety share a common neural substrate, despite its theoretical and practical importance. Here, we investigated a brain network of anxiety shared by different dimensions of anxiety in a unified analytical framework using functional magnetic resonance imaging (fMRI). We analyzed different datasets in a single scale, which was defined by an anxiety-related brain network derived from whole brain. We first conducted the anxiety provocation task with healthy participants who tended to feel anxiety related to obsessive-compulsive disorder (OCD) in their daily life. We found a common state anxiety brain network across participants (1585 trials obtained from 10 participants). Then, using the resting-state fMRI in combination with the participants' behavioral trait anxiety scale scores (879 participants from the Human Connectome Project), we demonstrated that trait anxiety shared the same brain network as state anxiety. Furthermore, the brain network between common to state and trait anxiety could detect patients with OCD, which is characterized by pathological anxiety-driven behaviors (174 participants from multi-site datasets). Our findings provide direct evidence that different dimensions of anxiety have a substantial biological inter-relationship. Our results also provide a biologically defined dimension of anxiety, which may promote further investigation of various human characteristics, including psychiatric disorders, from

  8. Anatomy of the dorsal default-mode network in conduct disorder: Association with callous-unemotional traits.

    PubMed

    Sethi, Arjun; Sarkar, Sagari; Dell'Acqua, Flavio; Viding, Essi; Catani, Marco; Murphy, Declan G M; Craig, Michael C

    2018-04-01

    We recently reported that emotional detachment in adult psychopathy was associated with structural abnormalities in the dorsal 'default-mode' network (DMN). However, it is unclear whether these differences are present in young people at risk of psychopathy. The most widely recognised group at risk for psychopathy are children/adolescents with conduct disorder (CD) and callous-unemotional (CU) traits. We therefore examined the microstructure of the dorsal DMN in 27 CD youths (14-with/13-without CU traits) compared to 16 typically developing controls using DTI tractography. Both CD groups had significantly (p < 0.025) reduced dorsal DMN radial diffusivity compared to controls. In those with diagnostically significant CU traits, exploratory analyses (uncorrected for multiple comparisons) suggested that radial diffusivity was negatively correlated with CU severity (Left: rho = -0.68, p = 0.015). These results suggest that CD youths have microstructural abnormalities in the same network as adults with psychopathy. Further, the association with childhood/adolescent measures of emotional detachment (CU traits) resembles the relationship between emotional detachment and network microstructure in adult psychopaths. However, these changes appear to occur in opposite directions - with increased myelination in adolescent CD but reduced integrity in adult psychopathy. Collectively, these findings suggest that developmental abnormalities in dorsal DMN may play a role in the emergence of psychopathy. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. A powerful approach reveals numerous expression quantitative trait haplotypes in multiple tissues.

    PubMed

    Ying, Dingge; Li, Mulin Jun; Sham, Pak Chung; Li, Miaoxin

    2018-04-26

    Recently many studies showed single nucleotide polymorphisms (SNPs) affect gene expression and contribute to development of complex traits/diseases in a tissue context-dependent manner. However, little is known about haplotype's influence on gene expression and complex traits, which reflects the interaction effect between SNPs. In the present study, we firstly proposed a regulatory region guided eQTL haplotype association analysis approach, and then systematically investigate the expression quantitative trait loci (eQTL) haplotypes in 20 different tissues by the approach. The approach has a powerful design of reducing computational burden by the utilization of regulatory predictions for candidate SNP selection and multiple testing corrections on non-independent haplotypes. The application results in multiple tissues showed that haplotype-based eQTLs not only increased the number of eQTL genes in a tissue specific manner, but were also enriched in loci that associated with complex traits in a tissue-matched manner. In addition, we found that tag SNPs of eQTL haplotypes from whole blood were selectively enriched in certain combination of regulatory elements (e.g. promoters and enhancers) according to predicted chromatin states. In summary, this eQTL haplotype detection approach, together with the application results, shed insights into synergistic effect of sequence variants on gene expression and their susceptibility to complex diseases. The executable application "eHaplo" is implemented in Java and is publicly available at http://grass.cgs.hku.hk/limx/ehaplo/. jonsonfox@gmail.com, limiaoxin@mail.sysu.edu.cn. Supplementary data are available at Bioinformatics online.

  10. Little effect of HSP90 inhibition on the quantitative wing traits variation in Drosophila melanogaster.

    PubMed

    Takahashi, Kazuo H

    2017-02-01

    Drosophila wings have been a model system to study the effect of HSP90 on quantitative trait variation. The effect of HSP90 inhibition on environmental buffering of wing morphology varies among studies while the genetic buffering effect of it was examined in only one study and was not detected. Variable results so far might show that the genetic background influences the environmental and genetic buffering effect of HSP90. In the previous studies, the number of the genetic backgrounds used is limited. To examine the effect of HSP90 inhibition with a larger number of genetic backgrounds than the previous studies, 20 wild-type strains of Drosophila melanogaster were used in this study. Here I investigated the effect of HSP90 inhibition on the environmental buffering of wing shape and size by assessing within-individual and among-individual variations, and as a result, I found little or very weak effects on environmental and genetic buffering. The current results suggest that the role of HSP90 as a global regulator of environmental and genetic buffering is limited at least in quantitative traits.

  11. Potential of promotion of alleles by genome editing to improve quantitative traits in livestock breeding programs.

    PubMed

    Jenko, Janez; Gorjanc, Gregor; Cleveland, Matthew A; Varshney, Rajeev K; Whitelaw, C Bruce A; Woolliams, John A; Hickey, John M

    2015-07-02

    Genome editing (GE) is a method that enables specific nucleotides in the genome of an individual to be changed. To date, use of GE in livestock has focussed on simple traits that are controlled by a few quantitative trait nucleotides (QTN) with large effects. The aim of this study was to evaluate the potential of GE to improve quantitative traits that are controlled by many QTN, referred to here as promotion of alleles by genome editing (PAGE). Multiple scenarios were simulated to test alternative PAGE strategies for a quantitative trait. They differed in (i) the number of edits per sire (0 to 100), (ii) the number of edits per generation (0 to 500), and (iii) the extent of use of PAGE (i.e. editing all sires or only a proportion of them). The base line scenario involved selecting individuals on true breeding values (i.e., genomic selection only (GS only)-genomic selection with perfect accuracy) for several generations. Alternative scenarios complemented this base line scenario with PAGE (GS + PAGE). The effect of different PAGE strategies was quantified by comparing response to selection, changes in allele frequencies, the number of distinct QTN edited, the sum of absolute effects of the edited QTN per generation, and inbreeding. Response to selection after 20 generations was between 1.08 and 4.12 times higher with GS + PAGE than with GS only. Increases in response to selection were larger with more edits per sire and more sires edited. When the total resources for PAGE were limited, editing a few sires for many QTN resulted in greater response to selection and inbreeding compared to editing many sires for a few QTN. Between the scenarios GS only and GS + PAGE, there was little difference in the average change in QTN allele frequencies, but there was a major difference for the QTN with the largest effects. The sum of the effects of the edited QTN decreased across generations. This study showed that PAGE has great potential for application in livestock

  12. Comparative mapping of quantitative trait loci for tassel-related traits of maize in F2:3 and RIL populations.

    PubMed

    Yi, Qiang; Liu, Yinghong; Zhang, Xiangge; Hou, Xianbin; Zhang, Junjie; Liu, Hanmei; Hu, Yufeng; Yu, Guowu; Huang, Yubi

    2018-03-01

    Tassel architecture is an important trait in maize breeding and hybrid seed production. In this study, we investigated total tassel length (TTL) and tassel branch number (TBN) in 266 F 2:3 families across six environments and in 301 recombinant inbred lines (RILs) across three environments, where all the plants were derived from a cross between 08-641 and Ye478. We compared the genetic architecture of the two traits across two generations through combined analysis. In total, 27 quantitative trait loci (QTLs) (15 in F 2:3 ; 16 in RIL), two QTL × environment interactions (both in F 2:3 ), 11 pairs of epistatic interactions (seven in F 2:3 ; four in RIL) and four stable QTLs in both the F 2:3 and RILs were detected. The RIL population had higher detection power than the F 2:3 population. Nevertheless, QTL × environment interactions and epistatic interactions could be more easily detected in the F 2:3 population than in the RILs. Overall, the QTL mapping results in the F 2:3 and RILs were greatly influenced by genetic generations and environments. Finally, fine mapping for a novel and major QTL, qTTL-2-3 (bin 2.07), which accounted for over 8.49% of the phenotypic variation across different environments and generations, could be useful in marker-assisted breeding.

  13. Investigation of the Genetic Diversity and Quantitative Trait Loci Accounting for Important Agronomic and Seed Quality Traits in Brassica carinata

    PubMed Central

    Zhang, Wenshan; Hu, Dandan; Raman, Rosy; Guo, Shaomin; Wei, Zili; Shen, Xueqi; Meng, Jinling; Raman, Harsh; Zou, Jun

    2017-01-01

    Brassica carinata (BBCC) is an allotetraploid in Brassicas with unique alleles for agronomic traits and has huge potential as source for biodiesel production. To investigate the genome-wide molecular diversity, population structure and linkage disequilibrium (LD) pattern in this species, we genotyped a panel of 81 accessions of B. carinata with genotyping by sequencing approach DArTseq, generating a total of 54,510 polymorphic markers. Two subpopulations were exhibited in the B. carinata accessions. The average distance of LD decay (r2 = 0.1) in B subgenome (0.25 Mb) was shorter than that of C subgenome (0.40 Mb). Genome-wide association analysis (GWAS) identified a total of seven markers significantly associated with five seed quality traits in two experiments. To further identify the quantitative trait loci (QTL) for important agronomic and seed quality traits, we phenotyped a doubled haploid (DH) mapping population derived from the “YW” cross between two parents (Y-BcDH64 and W-BcDH76) representing from the two subpopulations. The YW DH population and its parents were grown in three contrasting environments; spring (Hezheng and Xining, China), semi-winter (Wuhan, China), and spring (Wagga Wagga, Australia) across 5 years for QTL mapping. Genetic bases of phenotypic variation in seed yield and its seven related traits, and six seed quality traits were determined. A total of 282 consensus QTL accounting for these traits were identified including nine major QTL for flowering time, oleic acid, linolenic acid, pod number of main inflorescence, and seed weight. Of these, 109 and 134 QTL were specific to spring and semi-winter environment, respectively, while 39 consensus QTL were identified in both contrasting environments. Two QTL identified for linolenic acid (B3) and erucic acid (C7) were validated in the diverse lines used for GWAS. A total of 25 QTL accounting for flowering time, erucic acid, and oleic acid were aligned to the homologous QTL or candidate gene

  14. Mapping quantitative trait loci affecting Arabidopsis thaliana seed morphology features extracted computationally from images.

    PubMed

    Moore, Candace R; Gronwall, David S; Miller, Nathan D; Spalding, Edgar P

    2013-01-01

    Seeds are studied to understand dispersal and establishment of the next generation, as units of agricultural yield, and for other important reasons. Thus, elucidating the genetic architecture of seed size and shape traits will benefit basic and applied plant biology research. This study sought quantitative trait loci (QTL) controlling the size and shape of Arabidopsis thaliana seeds by computational analysis of seed phenotypes in recombinant inbred lines derived from the small-seeded Landsberg erecta × large-seeded Cape Verde Islands accessions. On the order of 10(3) seeds from each recombinant inbred line were automatically measured with flatbed photo scanners and custom image analysis software. The eight significant QTL affecting seed area explained 63% of the variation, and overlapped with five of the six major-axis (length) QTL and three of the five minor-axis (width) QTL, which accounted for 57% and 38% of the variation in those traits, respectively. Because the Arabidopsis seed is exalbuminous, lacking an endosperm at maturity, the results are relatable to embryo length and width. The Cvi allele generally had a positive effect of 2.6-4.0%. Analysis of variance showed heritability of the three traits ranged between 60% and 73%. Repeating the experiment with 2.2 million seeds from a separate harvest of the RIL population and approximately 0.5 million seeds from 92 near-isogenic lines confirmed the aforementioned results. Structured for download are files containing phenotype measurements, all sets of seed images, and the seed trait measuring tool.

  15. Genome-wide Association Study to Identify Quantitative Trait Loci for Meat and Carcass Quality Traits in Berkshire

    PubMed Central

    Iqbal, Asif; Kim, You-Sam; Kang, Jun-Mo; Lee, Yun-Mi; Rai, Rajani; Jung, Jong-Hyun; Oh, Dong-Yup; Nam, Ki-Chang; Lee, Hak-Kyo; Kim, Jong-Joo

    2015-01-01

    Meat and carcass quality attributes are of crucial importance influencing consumer preference and profitability in the pork industry. A set of 400 Berkshire pigs were collected from Dasan breeding farm, Namwon, Chonbuk province, Korea that were born between 2012 and 2013. To perform genome wide association studies (GWAS), eleven meat and carcass quality traits were considered, including carcass weight, backfat thickness, pH value after 24 hours (pH24), Commission Internationale de l’Eclairage lightness in meat color (CIE L), redness in meat color (CIE a), yellowness in meat color (CIE b), filtering, drip loss, heat loss, shear force and marbling score. All of the 400 animals were genotyped with the Porcine 62K SNP BeadChips (Illumina Inc., USA). A SAS general linear model procedure (SAS version 9.2) was used to pre-adjust the animal phenotypes before GWAS with sire and sex effects as fixed effects and slaughter age as a covariate. After fitting the fixed and covariate factors in the model, the residuals of the phenotype regressed on additive effects of each single nucleotide polymorphism (SNP) under a linear regression model (PLINK version 1.07). The significant SNPs after permutation testing at a chromosome-wise level were subjected to stepwise regression analysis to determine the best set of SNP markers. A total of 55 significant (p<0.05) SNPs or quantitative trait loci (QTL) were detected on various chromosomes. The QTLs explained from 5.06% to 8.28% of the total phenotypic variation of the traits. Some QTLs with pleiotropic effect were also identified. A pair of significant QTL for pH24 was also found to affect both CIE L and drip loss percentage. The significant QTL after characterization of the functional candidate genes on the QTL or around the QTL region may be effectively and efficiently used in marker assisted selection to achieve enhanced genetic improvement of the trait considered. PMID:26580276

  16. Slow erosion of a quantitative apple resistance to Venturia inaequalis based on an isolate-specific Quantitative Trait Locus.

    PubMed

    Caffier, Valérie; Le Cam, Bruno; Al Rifaï, Mehdi; Bellanger, Marie-Noëlle; Comby, Morgane; Denancé, Caroline; Didelot, Frédérique; Expert, Pascale; Kerdraon, Tifenn; Lemarquand, Arnaud; Ravon, Elisa; Durel, Charles-Eric

    2016-10-01

    Quantitative plant resistance affects the aggressiveness of pathogens and is usually considered more durable than qualitative resistance. However, the efficiency of a quantitative resistance based on an isolate-specific Quantitative Trait Locus (QTL) is expected to decrease over time due to the selection of isolates with a high level of aggressiveness on resistant plants. To test this hypothesis, we surveyed scab incidence over an eight-year period in an orchard planted with susceptible and quantitatively resistant apple genotypes. We sampled 79 Venturia inaequalis isolates from this orchard at three dates and we tested their level of aggressiveness under controlled conditions. Isolates sampled on resistant genotypes triggered higher lesion density and exhibited a higher sporulation rate on apple carrying the resistance allele of the QTL T1 compared to isolates sampled on susceptible genotypes. Due to this ability to select aggressive isolates, we expected the QTL T1 to be non-durable. However, our results showed that the quantitative resistance based on the QTL T1 remained efficient in orchard over an eight-year period, with only a slow decrease in efficiency and no detectable increase of the aggressiveness of fungal isolates over time. We conclude that knowledge on the specificity of a QTL is not sufficient to evaluate its durability. Deciphering molecular mechanisms associated with resistance QTLs, genetic determinants of aggressiveness and putative trade-offs within pathogen populations is needed to help in understanding the erosion processes. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice.

    PubMed

    van Nas, Atila; Ingram-Drake, Leslie; Sinsheimer, Janet S; Wang, Susanna S; Schadt, Eric E; Drake, Thomas; Lusis, Aldons J

    2010-07-01

    By treating the transcript abundance as a quantitative trait, gene expression can be mapped to local or distant genomic regions relative to the gene encoding the transcript. Local expression quantitative trait loci (eQTL) generally act in cis (that is, control the expression of only the contiguous structural gene), whereas distal eQTL act in trans. Distal eQTL are more difficult to identify with certainty due to the fact that significant thresholds are very high since all regions of the genome must be tested, and confounding factors such as batch effects can produce false positives. Here, we compare findings from two large genetic crosses between mouse strains C3H/HeJ and C57BL/6J to evaluate the reliability of distal eQTL detection, including "hotspots" influencing the expression of multiple genes in trans. We found that >63% of local eQTL and >18% of distal eQTL were replicable at a threshold of LOD > 4.3 between crosses and 76% of local and >24% of distal eQTL at a threshold of LOD > 6. Additionally, at LOD > 4.3 four tissues studied (adipose, brain, liver, and muscle) exhibited >50% preservation of local eQTL and >17% preservation of distal eQTL. We observed replicated distal eQTL hotspots between the crosses on chromosomes 9 and 17. Finally, >69% of local eQTL and >10% of distal eQTL were preserved in most tissues between sexes. We conclude that most local eQTL are highly replicable between mouse crosses, tissues, and sex as compared to distal eQTL, which exhibited modest replicability.

  18. QEEG and LORETA in Teenagers With Conduct Disorder and Psychopathic Traits.

    PubMed

    Calzada-Reyes, Ana; Alvarez-Amador, Alfredo; Galán-García, Lídice; Valdés-Sosa, Mitchell

    2017-05-01

    Few studies have investigated the impact of the psychopathic traits on the EEG of teenagers with conduct disorder (CD). To date, there is no other research studying low-resolution brain electromagnetic tomography (LORETA) technique using quantitative EEG (QEEG) analysis in adolescents with CD and psychopathic traits. To find electrophysiological differences specifically related to the psychopathic traits. The current investigation compares the QEEG and the current source density measures between adolescents with CD and psychopathic traits and adolescents with CD without psychopathic traits. The resting EEG activity and LORETA for the EEG fast spectral bands were evaluated in 42 teenagers with CD, 25 with and 17 without psychopathic traits according to the Antisocial Process Screening Device. All adolescents were assessed using the DSM-IV-TR criteria. The EEG visual inspection characteristics and the use of frequency domain quantitative analysis techniques (narrow band spectral parameters) are described. QEEG analysis showed a pattern of beta activity excess on the bilateral frontal-temporal regions and decreases of alpha band power on the left central-temporal and right frontal-central-temporal regions in the psychopathic traits group. Current source density calculated at 17.18 Hz showed an increase within fronto-temporo-striatal regions in the psychopathic relative to the nonpsychopathic traits group. These findings indicate that QEEG analysis and techniques of source localization may reveal differences in brain electrical activity among teenagers with CD and psychopathic traits, which was not obvious to visual inspection. Taken together, these results suggest that abnormalities in a fronto-temporo-striatal network play a relevant role in the neurobiological basis of psychopathic behavior.

  19. Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

    PubMed Central

    Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

    2007-01-01

    Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

  20. Functional connectivity within and between intrinsic brain networks correlates with trait mind wandering.

    PubMed

    Godwin, Christine A; Hunter, Michael A; Bezdek, Matthew A; Lieberman, Gregory; Elkin-Frankston, Seth; Romero, Victoria L; Witkiewitz, Katie; Clark, Vincent P; Schumacher, Eric H

    2017-08-01

    Individual differences across a variety of cognitive processes are functionally associated with individual differences in intrinsic networks such as the default mode network (DMN). The extent to which these networks correlate or anticorrelate has been associated with performance in a variety of circumstances. Despite the established role of the DMN in mind wandering processes, little research has investigated how large-scale brain networks at rest relate to mind wandering tendencies outside the laboratory. Here we examine the extent to which the DMN, along with the dorsal attention network (DAN) and frontoparietal control network (FPCN) correlate with the tendency to mind wander in daily life. Participants completed the Mind Wandering Questionnaire and a 5-min resting state fMRI scan. In addition, participants completed measures of executive function, fluid intelligence, and creativity. We observed significant positive correlations between trait mind wandering and 1) increased DMN connectivity at rest and 2) increased connectivity between the DMN and FPCN at rest. Lastly, we found significant positive correlations between trait mind wandering and fluid intelligence (Ravens) and creativity (Remote Associates Task). We interpret these findings within the context of current theories of mind wandering and executive function and discuss the possibility that certain instances of mind wandering may not be inherently harmful. Due to the controversial nature of global signal regression (GSReg) in functional connectivity analyses, we performed our analyses with and without GSReg and contrast the results from each set of analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. E-Index for Differentiating Complex Dynamic Traits

    PubMed Central

    Qi, Jiandong; Sun, Jianfeng; Wang, Jianxin

    2016-01-01

    While it is a daunting challenge in current biology to understand how the underlying network of genes regulates complex dynamic traits, functional mapping, a tool for mapping quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs), has been applied in a variety of cases to tackle this challenge. Though useful and powerful, functional mapping performs well only when one or more model parameters are clearly responsible for the developmental trajectory, typically being a logistic curve. Moreover, it does not work when the curves are more complex than that, especially when they are not monotonic. To overcome this inadaptability, we therefore propose a mathematical-biological concept and measurement, E-index (earliness-index), which cumulatively measures the earliness degree to which a variable (or a dynamic trait) increases or decreases its value. Theoretical proofs and simulation studies show that E-index is more general than functional mapping and can be applied to any complex dynamic traits, including those with logistic curves and those with nonmonotonic curves. Meanwhile, E-index vector is proposed as well to capture more subtle differences of developmental patterns. PMID:27064292

  2. Validation and Estimation of Additive Genetic Variation Associated with DNA Tests for Quantitative Beef Cattle Traits

    USDA-ARS?s Scientific Manuscript database

    The U.S. National Beef Cattle Evaluation Consortium (NBCEC) has been involved in the validation of commercial DNA tests for quantitative beef quality traits since their first appearance on the U.S. market in the early 2000s. The NBCEC Advisory Council initially requested that the NBCEC set up a syst...

  3. Identification of quantitative trait loci associated with boiled seed hardness in soybean

    PubMed Central

    Hirata, Kaori; Masuda, Ryoichi; Tsubokura, Yasutaka; Yasui, Takeshi; Yamada, Tetsuya; Takahashi, Koji; Nagaya, Taiko; Sayama, Takashi; Ishimoto, Masao; Hajika, Makita

    2014-01-01

    Boiled seed hardness is an important factor in the processing of soybean food products such as nimame and natto. Little information is available on the genetic basis for boiled seed hardness, despite the wide variation in this trait. DNA markers linked to the gene controlling this trait should be useful in soybean breeding programs because of the difficulty of its evaluation. In this report, quantitative trait locus (QTL) analysis was performed to reveal the genetic factors associated with boiled seed hardness using a recombinant inbred line population developed from a cross between two Japanese cultivars, ‘Natto-shoryu’ and ‘Hyoukei-kuro 3’, which differ largely in boiled seed hardness, which in ‘Natto-shoryu’ is about twice that of ‘Hyoukei-kuro 3’. Two significantly stable QTLs, qHbs3-1 and qHbs6-1, were identified on chromosomes 3 and 6, for which the ‘Hyoukei-kuro 3’ alleles contribute to decrease boiled seed hardness for both QTLs. qHbs3-1 also showed significant effects in progeny of a residual heterozygous line and in a different segregating population. Given its substantial effect on boiled seed hardness, SSR markers closely linked to qHbs3-1, such as BARCSOYSSR_03_0165 and BARCSOYSSR_03_0185, could be useful for marker-assisted selection in soybean breeding. PMID:25914591

  4. Quantitative trait loci for magnitude of the plasma cortisol response to confinement in rainbow trout.

    PubMed

    Quillet, E; Krieg, F; Dechamp, N; Hervet, C; Bérard, A; Le Roy, P; Guyomard, R; Prunet, P; Pottinger, T G

    2014-04-01

    Better understanding of the mechanisms underlying interindividual variation in stress responses and their links with production traits is a key issue for sustainable animal breeding. In this study, we searched for quantitative trait loci (QTL) controlling the magnitude of the plasma cortisol stress response and compared them to body size traits in five F2 full-sib families issued from two rainbow trout lines divergently selected for high or low post-confinement plasma cortisol level. Approximately 1000 F2 individuals were individually tagged and exposed to two successive acute confinement challenges (1 month interval). Post-stress plasma cortisol concentrations were determined for each fish. A medium density genome scan was carried out (268 markers, overall marker spacing less than 10 cM). QTL detection was performed using qtlmap software, based on an interval mapping method (http://www.inra.fr/qtlmap). Overall, QTL of medium individual effects on cortisol responsiveness (<10% of phenotypic variance) were detected on 18 chromosomes, strongly supporting the hypothesis that control of the trait is polygenic. Although a core array of QTL controlled cortisol concentrations at both challenges, several QTL seemed challenge specific, suggesting that responses to the first and to a subsequent exposure to the confinement stressor are distinct traits sharing only part of their genetic control. Chromosomal location of the steroidogenic acute regulatory protein (STAR) makes it a good potential candidate gene for one of the QTL. Finally, comparison of body size traits QTL (weight, length and body conformation) with cortisol-associated QTL did not support evidence for negative genetic relationships between the two types of traits. © 2014 Stichting International Foundation for Animal Genetics.

  5. Mapping of quantitative trait loci associated with partial resistance to phytophthora sojae and flooding tolerance in soybean

    USDA-ARS?s Scientific Manuscript database

    Phytophthora root rot (PRR) caused by Phytophthora sojae Kaufm. & Gerd. and flooding can limit growth and productivity, of soybean [Glycine max (L.) Merr.], especially on poorly drained soils. The primary objective of this research project was to map quantitative trait loci (QTL) associated with f...

  6. Deficiency mapping of quantitative trait loci affecting longevity in Drosophila melanogaster.

    PubMed Central

    Pasyukova, E G; Vieira, C; Mackay, T F

    2000-01-01

    In a previous study, sex-specific quantitative trait loci (QTL) affecting adult longevity were mapped by linkage to polymorphic roo transposable element markers, in a population of recombinant inbred lines derived from the Oregon and 2b strains of Drosophila melanogaster. Two life span QTL were each located on chromosomes 2 and 3, within sections 33E-46C and 65D-85F on the cytological map, respectively. We used quantitative deficiency complementation mapping to further resolve the locations of life span QTL within these regions. The Oregon and 2b strains were each crossed to 47 deficiencies spanning cytological regions 32F-44E and 64C-76B, and quantitative failure of the QTL alleles to complement the deficiencies was assessed. We initially detected a minimum of five and four QTL in the chromosome 2 and 3 regions, respectively, illustrating that multiple linked factors contribute to each QTL detected by recombination mapping. The QTL locations inferred from deficiency mapping did not generally correspond to those of candidate genes affecting oxidative and thermal stress or glucose metabolism. The chromosome 2 QTL in the 35B-E region was further resolved to a minimum of three tightly linked QTL, containing six genetically defined loci, 24 genes, and predicted genes that are positional candidates corresponding to life span QTL. This region was also associated with quantitative variation in life span in a sample of 10 genotypes collected from nature. Quantitative deficiency complementation is an efficient method for fine-scale QTL mapping in Drosophila and can be further improved by controlling the background genotype of the strains to be tested. PMID:11063689

  7. Gene regulatory networks reused to build novel traits: co-option of an eye-related gene regulatory network in eye-like organs and red wing patches on insect wings is suggested by optix expression.

    PubMed

    Monteiro, Antónia

    2012-03-01

    Co-option of the eye developmental gene regulatory network may have led to the appearance of novel functional traits on the wings of flies and butterflies. The first trait is a recently described wing organ in a species of extinct midge resembling the outer layers of the midge's own compound eye. The second trait is red pigment patches on Heliconius butterfly wings connected to the expression of an eye selector gene, optix. These examples, as well as others, are discussed regarding the type of empirical evidence and burden of proof that have been used to infer gene network co-option underlying the origin of novel traits. A conceptual framework describing increasing confidence in inference of network co-option is proposed. Novel research directions to facilitate inference of network co-option are also highlighted, especially in cases where the pre-existent and novel traits do not resemble each other. Copyright © 2012 WILEY Periodicals, Inc.

  8. Identification of Quantitative Trait Loci Controlling Gene Expression during the Innate Immunity Response of Soybean1[W][OA

    PubMed Central

    Valdés-López, Oswaldo; Thibivilliers, Sandra; Qiu, Jing; Xu, Wayne Wenzhong; Nguyen, Tran H.N.; Libault, Marc; Le, Brandon H.; Goldberg, Robert B.; Hill, Curtis B.; Hartman, Glen L.; Diers, Brian; Stacey, Gary

    2011-01-01

    Microbe-associated molecular pattern-triggered immunity (MTI) is an important component of the plant innate immunity response to invading pathogens. However, most of our knowledge of MTI comes from studies of model systems with relatively little work done with crop plants. In this work, we report on variation in both the microbe-associated molecular pattern-triggered oxidative burst and gene expression across four soybean (Glycine max) genotypes. Variation in MTI correlated with the level of pathogen resistance for each genotype. A quantitative trait locus analysis on these traits identified four loci that appeared to regulate gene expression during MTI in soybean. Likewise, we observed that both MTI variation and pathogen resistance were quantitatively inherited. The approach utilized in this study may have utility for identifying key resistance loci useful for developing improved soybean cultivars. PMID:21963820

  9. Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine

    Treesearch

    A. Groover; M. Devey; T. Fiddler; J. Lee; R. Megraw; T. Mitchel-Olds; B. Sherman; S. Vujcic; C. Williams; D. Neale

    1994-01-01

    We report the identification of quantitative trait loci (QTL) influencing wood specific gravity (WSG) in an outbred pedigree of loblolly pine (Pinus taeda L.) . QTL mapping in an outcrossing species is complicated by the presence of multiple alleles (>2) at QTL and marker loci. Multiple alleles at QTL allow the examination of interaction among...

  10. A Semiquantitative Framework for Gene Regulatory Networks: Increasing the Time and Quantitative Resolution of Boolean Networks

    PubMed Central

    Kerkhofs, Johan; Geris, Liesbet

    2015-01-01

    Boolean models have been instrumental in predicting general features of gene networks and more recently also as explorative tools in specific biological applications. In this study we introduce a basic quantitative and a limited time resolution to a discrete (Boolean) framework. Quantitative resolution is improved through the employ of normalized variables in unison with an additive approach. Increased time resolution stems from the introduction of two distinct priority classes. Through the implementation of a previously published chondrocyte network and T helper cell network, we show that this addition of quantitative and time resolution broadens the scope of biological behaviour that can be captured by the models. Specifically, the quantitative resolution readily allows models to discern qualitative differences in dosage response to growth factors. The limited time resolution, in turn, can influence the reachability of attractors, delineating the likely long term system behaviour. Importantly, the information required for implementation of these features, such as the nature of an interaction, is typically obtainable from the literature. Nonetheless, a trade-off is always present between additional computational cost of this approach and the likelihood of extending the model’s scope. Indeed, in some cases the inclusion of these features does not yield additional insight. This framework, incorporating increased and readily available time and semi-quantitative resolution, can help in substantiating the litmus test of dynamics for gene networks, firstly by excluding unlikely dynamics and secondly by refining falsifiable predictions on qualitative behaviour. PMID:26067297

  11. Construction of a genetic linkage map and analysis of quantitative trait loci associated with the agronomically important traits of Pleurotus eryngii.

    PubMed

    Im, Chak Han; Park, Young-Hoon; Hammel, Kenneth E; Park, Bokyung; Kwon, Soon Wook; Ryu, Hojin; Ryu, Jae-San

    2016-07-01

    Breeding new strains with improved traits is a long-standing goal of mushroom breeders that can be expedited by marker-assisted selection (MAS). We constructed a genetic linkage map of Pleurotus eryngii based on segregation analysis of markers in postmeiotic monokaryons from KNR2312. In total, 256 loci comprising 226 simple sequence-repeat (SSR) markers, 2 mating-type factors, and 28 insertion/deletion (InDel) markers were mapped. The map consisted of 12 linkage groups (LGs) spanning 1047.8cM, with an average interval length of 4.09cM. Four independent populations (Pd3, Pd8, Pd14, and Pd15) derived from crossing between four monokaryons from KNR2532 as a tester strain and 98 monokaryons from KNR2312 were used to characterize quantitative trait loci (QTL) for nine traits such as yield, quality, cap color, and earliness. Using composite interval mapping (CIM), 71 QTLs explaining between 5.82% and 33.17% of the phenotypic variations were identified. Clusters of more than five QTLs for various traits were identified in three genomic regions, on LGs 1, 7 and 9. Regardless of the population, 6 of the 9 traits studied and 18 of the 71 QTLs found in this study were identified in the largest cluster, LG1, in the range from 65.4 to 110.4cM. The candidate genes for yield encoding transcription factor, signal transduction, mycelial growth and hydrolase are suggested by using manual and computational analysis of genome sequence corresponding to QTL region with the highest likelihood odds (LOD) for yield. The genetic map and the QTLs established in this study will help breeders and geneticists to develop selection markers for agronomically important characteristics of mushrooms and to identify the corresponding genes. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Quantitative trait locus gene mapping: a new method for locating alcohol response genes.

    PubMed

    Crabbe, J C

    1996-01-01

    Alcoholism is a multigenic trait with important non-genetic determinants. Studies with genetic animal models of susceptibility to several of alcohol's effects suggest that several genes contributing modest effects on susceptibility (Quantitative Trait Loci, or QTLs) are important. A new technique of QTL gene mapping has allowed the identification of the location in mouse genome of several such QTLs. The method is described, and the locations of QTLs affecting the acute alcohol withdrawal reaction are described as an example of the method. Verification of these QTLs in ancillary studies is described and the strengths, limitations, and future directions to be pursued are discussed. QTL mapping is a promising method for identifying genes in rodents with the hope of directly extrapolating the results to the human genome. This review is based on a paper presented at the First International Congress of the Latin American Society for Biomedical Research on Alcoholism, Santiago, Chile, November 1994.

  13. Mapping and validation of quantitative trait loci associated with concentrations of 16 elements in unmilled rice grain

    USDA-ARS?s Scientific Manuscript database

    In this study, quantitative trait loci (QTLs) affecting the concentrations of 16 elements in whole, unmilled rice (Oryza sativa L.) grain were identified. Two rice mapping populations, the ‘Lemont’ x ‘TeQing’ recombinant inbred lines (LT-RILs), and the TeQing-into-Lemont backcross introgression lin...

  14. Identification of quantitative trait loci (QTL) controlling protein, oil, and five major fatty acids’ contents in soybean

    USDA-ARS?s Scientific Manuscript database

    Improved seed composition in soybean (Glycine max L. Merr.) for protein and oil quality is one of the major goals of soybean breeders. A group of genes that act as quantitative traits with their effects can alter protein, oil, palmitic, stearic, oleic, linoleic, and linolenic acids percentage in soy...

  15. The influence of floral traits on specialization and modularity of plant–pollinator networks in a biodiversity hotspot in the Peruvian Andes

    PubMed Central

    Watts, Stella; Dormann, Carsten F.; Martín González, Ana M.; Ollerton, Jeff

    2016-01-01

    Background and Aims Modularity is a ubiquitous and important structural property of ecological networks which describes the relative strengths of sets of interacting species and gives insights into the dynamics of ecological communities. However, this has rarely been studied in species-rich, tropical plant–pollinator networks. Working in a biodiversity hotspot in the Peruvian Andes we assessed the structure of quantitative plant–pollinator networks in nine valleys, quantifying modularity among networks, defining the topological roles of species and the influence of floral traits on specialization. Methods A total of 90 transects were surveyed for plants and pollinators at different altitudes and across different life zones. Quantitative modularity (QuanBiMo) was used to detect modularity and six indices were used to quantify specialization. Key Results All networks were highly structured, moderately specialized and significantly modular regardless of size. The strongest hubs were Baccharis plants, Apis mellifera, Bombus funebris and Diptera spp., which were the most ubiquitous and abundant species with the longest phenologies. Species strength showed a strong association with the modular structure of plant–pollinator networks. Hubs and connectors were the most centralized participants in the networks and were ranked highest (high generalization) when quantifying specialization with most indices. However, complementary specialization d' quantified hubs and connectors as moderately specialized. Specialization and topological roles of species were remarkably constant across some sites, but highly variable in others. Networks were dominated by ecologically and functionally generalist plant species with open access flowers which are closely related taxonomically with similar morphology and rewards. Plants associated with hummingbirds had the highest level of complementary specialization and exclusivity in modules (functional specialists) and the longest corollas

  16. The influence of floral traits on specialization and modularity of plant-pollinator networks in a biodiversity hotspot in the Peruvian Andes.

    PubMed

    Watts, Stella; Dormann, Carsten F; Martín González, Ana M; Ollerton, Jeff

    2016-09-01

    Modularity is a ubiquitous and important structural property of ecological networks which describes the relative strengths of sets of interacting species and gives insights into the dynamics of ecological communities. However, this has rarely been studied in species-rich, tropical plant-pollinator networks. Working in a biodiversity hotspot in the Peruvian Andes we assessed the structure of quantitative plant-pollinator networks in nine valleys, quantifying modularity among networks, defining the topological roles of species and the influence of floral traits on specialization. A total of 90 transects were surveyed for plants and pollinators at different altitudes and across different life zones. Quantitative modularity (QuanBiMo) was used to detect modularity and six indices were used to quantify specialization. All networks were highly structured, moderately specialized and significantly modular regardless of size. The strongest hubs were Baccharis plants, Apis mellifera, Bombus funebris and Diptera spp., which were the most ubiquitous and abundant species with the longest phenologies. Species strength showed a strong association with the modular structure of plant-pollinator networks. Hubs and connectors were the most centralized participants in the networks and were ranked highest (high generalization) when quantifying specialization with most indices. However, complementary specialization d' quantified hubs and connectors as moderately specialized. Specialization and topological roles of species were remarkably constant across some sites, but highly variable in others. Networks were dominated by ecologically and functionally generalist plant species with open access flowers which are closely related taxonomically with similar morphology and rewards. Plants associated with hummingbirds had the highest level of complementary specialization and exclusivity in modules (functional specialists) and the longest corollas. We have demonstrated that the topology of

  17. Adaptive Differentiation of Quantitative Traits in the Globally Distributed Weed, Wild Radish (Raphanus raphanistrum)

    PubMed Central

    Sahli, Heather F.; Conner, Jeffrey K.; Shaw, Frank H.; Howe, Stephen; Lale, Allison

    2008-01-01

    Weedy species with wide geographical distributions may face strong selection to adapt to new environments, which can lead to adaptive genetic differentiation among populations. However, genetic drift, particularly due to founder effects, will also commonly result in differentiation in colonizing species. To test whether selection has contributed to trait divergence, we compared differentiation at eight microsatellite loci (measured as FST) to differentiation of quantitative floral and phenological traits (measured as QST) of wild radish (Raphanus raphanistrum) across populations from three continents. We sampled eight populations: seven naturalized populations and one from its native range. By comparing estimates of QST and FST, we found that petal size was the only floral trait that may have diverged more than expected due to drift alone, but inflorescence height, flowering time, and rosette formation have greatly diverged between the native and nonnative populations. Our results suggest the loss of a rosette and the evolution of early flowering time may have been the key adaptations enabling wild radish to become a major agricultural weed. Floral adaptation to different pollinators does not seem to have been as necessary for the success of wild radish in new environments. PMID:18854585

  18. Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

    PubMed

    Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

    2015-04-01

    Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

  19. Genetic Mapping of Quantitative Trait Loci Controlling Growth and Wood Quality Traits in Eucalyptus Grandis Using a Maternal Half-Sib Family and Rapd Markers

    PubMed Central

    Grattapaglia, D.; Bertolucci, FLG.; Penchel, R.; Sederoff, R. R.

    1996-01-01

    Quantitative trait loci (QTL) mapping of forest productivity traits was performed using an open pollinated half-sib family of Eucalyptus grandis. For volume growth, a sequential QTL mapping approach was applied using bulk segregant analysis (BSA), selective genotyping (SG) and cosegregation analysis (CSA). Despite the low heritability of this trait and the heterogeneous genetic background employed for mapping. BSA detected one putative QTL and SG two out of the three later found by CSA. The three putative QTL for volume growth were found to control 13.7% of the phenotypic variation, corresponding to an estimated 43.7% of the genetic variation. For wood specific gravity five QTL were identified controlling 24.7% of the phenotypic variation corresponding to 49% of the genetic variation. Overlapping QTL for CBH, WSG and percentage dry weight of bark were observed. A significant case of digenic epistasis was found, involving unlinked QTL for volume. Our results demonstrate the applicability of the within half-sib design for QTL mapping in forest trees and indicate the existence of major genes involved in the expression of economically important traits related to forest productivity in Eucalyptus grandis. These findings have important implications for marker-assisted tree breeding. PMID:8913761

  20. MicroRNA-guided prioritization of genome-wide association signals reveals the importance of microRNA-target gene networks for complex traits in cattle.

    PubMed

    Fang, Lingzhao; Sørensen, Peter; Sahana, Goutam; Panitz, Frank; Su, Guosheng; Zhang, Shengli; Yu, Ying; Li, Bingjie; Ma, Li; Liu, George; Lund, Mogens Sandø; Thomsen, Bo

    2018-06-19

    MicroRNAs (miRNA) are key modulators of gene expression and so act as putative fine-tuners of complex phenotypes. Here, we hypothesized that causal variants of complex traits are enriched in miRNAs and miRNA-target networks. First, we conducted a genome-wide association study (GWAS) for seven functional and milk production traits using imputed sequence variants (13~15 million) and >10,000 animals from three dairy cattle breeds, i.e., Holstein (HOL), Nordic red cattle (RDC) and Jersey (JER). Second, we analyzed for enrichments of association signals in miRNAs and their miRNA-target networks. Our results demonstrated that genomic regions harboring miRNA genes were significantly (P < 0.05) enriched with GWAS signals for milk production traits and mastitis, and that enrichments within miRNA-target gene networks were significantly higher than in random gene-sets for the majority of traits. Furthermore, most between-trait and across-breed correlations of enrichments with miRNA-target networks were significantly greater than with random gene-sets, suggesting pleiotropic effects of miRNAs. Intriguingly, genes that were differentially expressed in response to mammary gland infections were significantly enriched in the miRNA-target networks associated with mastitis. All these findings were consistent across three breeds. Collectively, our observations demonstrate the importance of miRNAs and their targets for the expression of complex traits.

  1. Quantitative trait locus for reading disability on chromosome 6

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

    Cardon, L.R.; Smith, S.D.; Kimberling, W.J.

    1994-10-14

    Interval mapping of data from two independent samples of sib pairs, at least one member of whom was reading disabled, revealed evidence for a quantitative trait locus (QTL) on chromosome 6. Results obtained from analyses of reading performance from 114 sib pairs genotyped for DNA markers localized the QTL to 6p21.3. Analyses of corresponding data from an independent sample of 50 dizygotic twin pairs provided evidence for linkage to the same region. In combination, the replicate samples yielded a x{sup 2} value of 16.73 (P = 0.0002). Examination of twin and kindred siblings with more extreme deficits in reading performancemore » yielded even stronger evidence for a QTL (x{sup 2} = 27.35, P < 0.00001). The position of the QTL was narrowly defined with a 100:1 confidence interval to a 2-centimorgan region within the human leukocyte antigen complex. 23 refs., 4 figs.« less

  2. Molecular Dissection of a Major Gene Effect on a Quantitative Trait: The Level of Alcohol Dehydrogenase Expression in Drosophila Melanogaster

    PubMed Central

    Stam, L. F.; Laurie, C. C.

    1996-01-01

    A molecular mapping experiment shows that a major gene effect on a quantitative trait, the level of alcohol dehydrogenase expression in Drosophila melanogaster, is due to multiple polymorphisms within the Adh gene. These polymorphisms are located in an intron, the coding sequence, and the 3' untranslated region. Because of nonrandom associations among polymorphisms at different sites, the individual effects combine (in some cases epistatically) to produce ``superalleles'' with large effect. These results have implications for the interpretation of major gene effects detected by quantitative trait locus mapping methods. They show that large effects due to a single locus may be due to multiple associated polymorphisms (or sequential fixations in isolated populations) rather than individual mutations of large effect. PMID:8978044

  3. Disorganized Amygdala Networks in Conduct-Disordered Juvenile Offenders With Callous-Unemotional Traits.

    PubMed

    Aghajani, Moji; Klapwijk, Eduard T; van der Wee, Nic J; Veer, Ilya M; Rombouts, Serge A R B; Boon, Albert E; van Beelen, Peter; Popma, Arne; Vermeiren, Robert R J M; Colins, Olivier F

    2017-08-15

    The developmental trajectory of psychopathy seemingly begins early in life and includes the presence of callous-unemotional (CU) traits (e.g., deficient emotional reactivity, callousness) in conduct-disordered (CD) youth. Though subregion-specific anomalies in amygdala function have been suggested in CU pathophysiology among antisocial populations, system-level studies of CU traits have typically examined the amygdala as a unitary structure. Hence, nothing is yet known of how amygdala subregional network function may contribute to callous-unemotionality in severely antisocial people. We addressed this important issue by uniquely examining the intrinsic functional connectivity of basolateral amygdala (BLA) and centromedial amygdala (CMA) networks across three matched groups of juveniles: CD offenders with CU traits (CD/CU+; n = 25), CD offenders without CU traits (CD/CU-; n = 25), and healthy control subjects (n = 24). We additionally examined whether perturbed amygdala subregional connectivity coincides with altered volume and shape of the amygdaloid complex. Relative to CD/CU- and healthy control youths, CD/CU+ youths showed abnormally increased BLA connectivity with a cluster that included both dorsal and ventral portions of the anterior cingulate and medial prefrontal cortices, along with posterior cingulate, sensory associative, and striatal regions. In contrast, compared with CD/CU- and healthy control youths, CD/CU+ youths showed diminished CMA connectivity with ventromedial/orbitofrontal regions. Critically, these connectivity changes coincided with local hypotrophy of BLA and CMA subregions (without being statistically correlated) and were associated to more severe CU symptoms. These findings provide unique insights into a putative mechanism for perturbed attention-emotion interactions, which could bias salience processing and associative learning in youth with CD/CU+. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights

  4. Confirmatory Factor Analytic Structure and Measurement Invariance of Quantitative Autistic Traits Measured by the Social Responsiveness Scale-2

    ERIC Educational Resources Information Center

    Frazier, Thomas W.; Ratliff, Kristin R.; Gruber, Chris; Zhang, Yi; Law, Paul A.; Constantino, John N.

    2014-01-01

    Understanding the factor structure of autistic symptomatology is critical to the discovery and interpretation of causal mechanisms in autism spectrum disorder. We applied confirmatory factor analysis and assessment of measurement invariance to a large ("N" = 9635) accumulated collection of reports on quantitative autistic traits using…

  5. Interspecies synteny mapping identifies a quantitative trait locus for bone mineral density on human chromosome Xp22.

    PubMed

    Parsons, Claire A; Mroczkowski, H Joel; McGuigan, Fiona E A; Albagha, Omar M E; Manolagas, Stavros; Reid, David M; Ralston, Stuart H; Shmookler Reis, Robert J

    2005-11-01

    Bone mineral density (BMD) is a complex trait with a strong genetic component and an important predictor of osteoporotic fracture risk. Here we report the use of a cross-species strategy to identify genes that regulate BMD, proceeding from quantitative trait mapping in mice to association mapping of the syntenic region in the human genome. We identified a quantitative trait locus (QTL) on the mouse X-chromosome for post-maturity change in spine BMD in a cross of SAMP6 and AKR/J mice and conducted association mapping of the syntenic region on human chromosome Xp22. We studied 76 single nucleotide polymorphisms (SNP) from the human region in two sets of DNA pools prepared from individuals with lumbar spine-BMD (LS-BMD) values falling into the top and bottom 13th percentiles of a population-based study of 3100 post-menopausal women. This procedure identified a region of significant association for two adjacent SNP (rs234494 and rs234495) within the Xp22 locus (P<0.001). Individual genotyping for rs234494 in the BMD pools confirmed the presence of an association for alleles (P=0.018) and genotypes (P=0.008). Analysis of rs234494 and rs234495 in 1053 women derived from the same population who were not selected for BMD values showed an association with LS-BMD for rs234495 (P=0.01) and for haplotypes defined by both SNP (P=0.002). Our study illustrates that interspecies synteny can be used to identify and refine QTL for complex traits and represents the first example where a human QTL for BMD regulation has been mapped using this approach.

  6. CSGRqtl: A Comparative Quantitative Trait Locus Database for Saccharinae Grasses.

    PubMed

    Zhang, Dong; Paterson, Andrew H

    2017-01-01

    Conventional biparental quantitative trait locus (QTL) mapping has led to some successes in the identification of causal genes in many organisms. QTL likelihood intervals not only provide "prior information" for finer-resolution approaches such as GWAS but also provide better statistical power than GWAS to detect variants with low/rare frequency in a natural population. Here, we describe a new element of an ongoing effort to provide online resources to facilitate study and improvement of the important Saccharinae clade. The primary goal of this new resource is the anchoring of published QTLs for this clade to the Sorghum genome. Genetic map alignments translate a wealth of genomic information from sorghum to Saccharum spp., Miscanthus spp., and other taxa. In addition, genome alignments facilitate comparison of the Saccharinae QTL sets to those of other taxa that enjoy comparable resources, exemplified herein by rice.

  7. Speed breeding for multiple quantitative traits in durum wheat.

    PubMed

    Alahmad, Samir; Dinglasan, Eric; Leung, Kung Ming; Riaz, Adnan; Derbal, Nora; Voss-Fels, Kai P; Able, Jason A; Bassi, Filippo M; Christopher, Jack; Hickey, Lee T

    2018-01-01

    Plant breeding requires numerous generations to be cycled and evaluated before an improved cultivar is released. This lengthy process is required to introduce and test multiple traits of interest. However, a technology for rapid generation advance named 'speed breeding' was successfully deployed in bread wheat ( Triticum aestivum L.) to achieve six generations per year while imposing phenotypic selection for foliar disease resistance and grain dormancy. Here, for the first time the deployment of this methodology is presented in durum wheat ( Triticum durum Desf.) by integrating selection for key traits, including above and below ground traits on the same set of plants. This involved phenotyping for seminal root angle (RA), seminal root number (RN), tolerance to crown rot (CR), resistance to leaf rust (LR) and plant height (PH). In durum wheat, these traits are desirable in environments where yield is limited by in-season rainfall with the occurrence of CR and epidemics of LR. To evaluate this multi-trait screening approach, we applied selection to a large segregating F 2 population (n = 1000) derived from a bi-parental cross (Outrob4/Caparoi). A weighted selection index (SI) was developed and applied. The gain for each trait was determined by evaluating F 3 progeny derived from 100 'selected' and 100 'unselected' F 2 individuals. Transgressive segregation was observed for all assayed traits in the Outrob4/Caparoi F 2 population. Application of the SI successfully shifted the population mean for four traits, as determined by a significant mean difference between 'selected' and 'unselected' F 3 families for CR tolerance, LR resistance, RA and RN. No significant shift for PH was observed. The novel multi-trait phenotyping method presents a useful tool for rapid selection of early filial generations or for the characterization of fixed lines out-of-season. Further, it offers efficient use of resources by assaying multiple traits on the same set of plants. Results

  8. Quantitative trait locus mapping and functional genomics of an organophosphate resistance trait in the western corn rootworm, Diabrotica virgifera virgifera.

    PubMed

    Coates, B S; Alves, A P; Wang, H; Zhou, X; Nowatzki, T; Chen, H; Rangasamy, M; Robertson, H M; Whitfield, C W; Walden, K K; Kachman, S D; French, B W; Meinke, L J; Hawthorne, D; Abel, C A; Sappington, T W; Siegfried, B D; Miller, N J

    2016-02-01

    The western corn rootworm, Diabrotica virgifera virgifera, is an insect pest of corn and population suppression with chemical insecticides is an important management tool. Traits conferring organophosphate insecticide resistance have increased in frequency amongst D. v. virgifera populations, resulting in the reduced efficacy in many corn-growing regions of the USA. We used comparative functional genomic and quantitative trait locus (QTL) mapping approaches to investigate the genetic basis of D. v. virgifera resistance to the organophosphate methyl-parathion. RNA from adult methyl-parathion resistant and susceptible adults was hybridized to 8331 microarray probes. The results predicted that 11 transcripts were significantly up-regulated in resistant phenotypes, with the most significant (fold increases ≥ 2.43) being an α-esterase-like transcript. Differential expression was validated only for the α-esterase (ST020027A20C03), with 11- to 13-fold greater expression in methyl-parathion resistant adults (P < 0.05). Progeny with a segregating methyl-parathion resistance trait were obtained from a reciprocal backcross design. QTL analyses of high-throughput single nucleotide polymorphism genotype data predicted involvement of a single genome interval. These data suggest that a specific carboyxesterase may function in field-evolved corn rootworm resistance to organophosphates, even though direct linkage between the QTL and this locus could not be established. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  9. Topological Phenotypes Constitute a New Dimension in the Phenotypic Space of Leaf Venation Networks

    PubMed Central

    Ronellenfitsch, Henrik; Lasser, Jana; Daly, Douglas C.; Katifori, Eleni

    2015-01-01

    The leaves of angiosperms contain highly complex venation networks consisting of recursively nested, hierarchically organized loops. We describe a new phenotypic trait of reticulate vascular networks based on the topology of the nested loops. This phenotypic trait encodes information orthogonal to widely used geometric phenotypic traits, and thus constitutes a new dimension in the leaf venation phenotypic space. We apply our metric to a database of 186 leaves and leaflets representing 137 species, predominantly from the Burseraceae family, revealing diverse topological network traits even within this single family. We show that topological information significantly improves identification of leaves from fragments by calculating a “leaf venation fingerprint” from topology and geometry. Further, we present a phenomenological model suggesting that the topological traits can be explained by noise effects unique to specimen during development of each leaf which leave their imprint on the final network. This work opens the path to new quantitative identification techniques for leaves which go beyond simple geometric traits such as vein density and is directly applicable to other planar or sub-planar networks such as blood vessels in the brain. PMID:26700471

  10. Quantitative Trait Loci Mapping in Brassica rapa Revealed the Structural and Functional Conservation of Genetic Loci Governing Morphological and Yield Component Traits in the A, B, and C Subgenomes of Brassica Species

    PubMed Central

    Li, Xiaonan; Ramchiary, Nirala; Dhandapani, Vignesh; Choi, Su Ryun; Hur, Yoonkang; Nou, Ill-Sup; Yoon, Moo Kyoung; Lim, Yong Pyo

    2013-01-01

    Brassica rapa is an important crop species that produces vegetables, oilseed, and fodder. Although many studies reported quantitative trait loci (QTL) mapping, the genes governing most of its economically important traits are still unknown. In this study, we report QTL mapping for morphological and yield component traits in B. rapa and comparative map alignment between B. rapa, B. napus, B. juncea, and Arabidopsis thaliana to identify candidate genes and conserved QTL blocks between them. A total of 95 QTL were identified in different crucifer blocks of the B. rapa genome. Through synteny analysis with A. thaliana, B. rapa candidate genes and intronic and exonic single nucleotide polymorphisms in the parental lines were detected from whole genome resequenced data, a few of which were validated by mapping them to the QTL regions. Semi-quantitative reverse transcriptase PCR analysis showed differences in the expression levels of a few genes in parental lines. Comparative mapping identified five key major evolutionarily conserved crucifer blocks (R, J, F, E, and W) harbouring QTL for morphological and yield components traits between the A, B, and C subgenomes of B. rapa, B. juncea, and B. napus. The information of the identified candidate genes could be used for breeding B. rapa and other related Brassica species. PMID:23223793

  11. In silico mapping of quantitative trait loci in maize.

    PubMed

    Parisseaux, B; Bernardo, R

    2004-08-01

    Quantitative trait loci (QTL) are most often detected through designed mapping experiments. An alternative approach is in silico mapping, whereby genes are detected using existing phenotypic and genomic databases. We explored the usefulness of in silico mapping via a mixed-model approach in maize (Zea mays L.). Specifically, our objective was to determine if the procedure gave results that were repeatable across populations. Multilocation data were obtained from the 1995-2002 hybrid testing program of Limagrain Genetics in Europe. Nine heterotic patterns comprised 22,774 single crosses. These single crosses were made from 1,266 inbreds that had data for 96 simple sequence repeat (SSR) markers. By a mixed-model approach, we estimated the general combining ability effects associated with marker alleles in each heterotic pattern. The numbers of marker loci with significant effects--37 for plant height, 24 for smut [Ustilago maydis (DC.) Cda.] resistance, and 44 for grain moisture--were consistent with previous results from designed mapping experiments. Each trait had many loci with small effects and few loci with large effects. For smut resistance, a marker in bin 8.05 on chromosome 8 had a significant effect in seven (out of a maximum of 18) instances. For this major QTL, the maximum effect of an allele substitution ranged from 5.4% to 41.9%, with an average of 22.0%. We conclude that in silico mapping via a mixed-model approach can detect associations that are repeatable across different populations. We speculate that in silico mapping will be more useful for gene discovery than for selection in plant breeding programs. Copyright 2004 Springer-Verlag

  12. Quantitative trait loci for seed isoflavones contents in 'MD96-5722' by 'Spencer' recombinant inbred lines of soybean

    USDA-ARS?s Scientific Manuscript database

    Isoflavones from soybeans (Glycine max L. Merr.) have significant impact on human health in reducing the risk of several major diseases. Breeding soybean for high isoflavones content in the seed is possible through marker assisted selection (MAS), which can be based on quantitative trait loci (QTL)....

  13. Identification of Quantitative Trait Loci for Resistance to RSIVD in Red Sea Bream (Pagrus major).

    PubMed

    Sawayama, Eitaro; Tanizawa, Shiho; Kitamura, Shin-Ichi; Nakayama, Kei; Ohta, Kohei; Ozaki, Akiyuki; Takagi, Motohiro

    2017-12-01

    Red sea bream iridoviral disease (RSIVD) is a major viral disease in red sea bream farming in Japan. Previously, we identified one candidate male individual of red sea bream that was significantly associated with convalescent individuals after RSIVD. The purpose of this study is to identify the quantitative trait loci (QTL) linked to the RSIVD-resistant trait for future marker-assisted selection (MAS). Two test families were developed using the candidate male in 2014 (Fam-2014) and 2015 (Fam-2015). These test families were challenged with RSIV, and phenotypes were evaluated. Then, de novo genome sequences of red sea bream were obtained through next-generation sequencing, and microsatellite markers were searched and selected for linkage map construction. One immune-related gene, MHC class IIβ, was also used for linkage map construction. Of the microsatellite markers searched, 148 and 197 were mapped on 23 and 27 linkage groups in the female and male linkage maps, respectively, covering approximately 65% of genomes in both sexes. One QTL linked to an RSIVD-resistant trait was found in linkage group 2 of the candidate male in Fam-2014, and the phenotypic variance of the QTL was 31.1%. The QTL was closely linked to MHC class IIβ. Moreover, the QTL observed in Fam-2014 was also significantly linked to an RSIVD-resistant trait in the candidate male of Fam-2015. Our results suggest that the RSIVD-resistant trait in the candidate male was controlled by one major QTL closely linked to the MHC class IIβ gene and could be useful for MAS of red sea bream.

  14. Comparative mapping of quantitative trait loci associated with waterlogging tolerance in barley (Hordeum vulgare L.).

    PubMed

    Li, Haobing; Vaillancourt, René; Mendham, Neville; Zhou, Meixue

    2008-08-27

    Resistance to soil waterlogging stress is an important plant breeding objective in high rainfall or poorly drained areas across many countries in the world. The present study was conducted to identify quantitative trait loci (QTLs) associated with waterlogging tolerance (e.g. leaf chlorosis, plant survival and biomass reduction) in barley and compare the QTLs identified across two seasons and in two different populations using a composite map constructed with SSRs, RFLP and Diversity Array Technology (DArT) markers. Twenty QTLs for waterlogging tolerance related traits were found in the two barley double haploid (DH) populations. Several of these QTLs were validated through replication of experiments across seasons or by co-location across populations. Some of these QTLs affected multiple waterlogging tolerance related traits, for example, QTL Qwt4-1 contributed not only to reducing barley leaf chlorosis, but also increasing plant biomass under waterlogging stress, whereas other QTLs controlled both leaf chlorosis and plant survival. Improving waterlogging tolerance in barley is still at an early stage compared with other traits. QTLs identified in this study have made it possible to use marker assisted selection (MAS) in combination with traditional field selection to significantly enhance barley breeding for waterlogging tolerance. There may be some degree of homoeologous relationship between QTLs controlling barley waterlogging tolerance and that in other crops as discussed in this study.

  15. Integrative genetic analysis of transcription modules: towards filling the gap between genetic lociand inherited traits

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

    Li, Hongqiang; Chen, Hao; Bao, Lei

    2005-01-01

    Genetic loci that regulate inherited traits are routinely identified using quantitative trait locus (QTL) mapping methods. However, the genotype-phenotype associations do not provide information on the gene expression program through which the genetic loci regulate the traits. Transcription modules are 'selfconsistent regulatory units' and are closely related to the modular components of gene regulatory network [Ihmels, J., Friedlander, G., Bergmann, S., Sarig, O., Ziv, Y. and Barkai, N. (2002) Revealing modular organization in the yeast transcriptional network. Nat. Genet., 31, 370-377; Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D. and Friedman, N. (2003) Module networks: identifyingmore » regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet., 34, 166-176]. We used genome-wide genotype and gene expression data of a genetic reference population that consists of mice of 32 recombinant inbred strains to identify the transcription modules and the genetic loci regulating them. Twenty-nine transcription modules defined by genetic variations were identified. Statistically significant associations between the transcription modules and 18 classical physiological and behavioral traits were found. Genome-wide interval mapping showed that major QTLs regulating the transcription modules are often co-localized with the QTLs regulating the associated classical traits. The association and the possible co-regulation of the classical trait and transcription module indicate that the transcription module may be involved in the gene pathways connecting the QTL and the classical trait. Our results show that a transcription module may associate with multiple seemingly unrelated classical traits and a classical trait may associate with different modules. Literature mining results provided strong independent evidences for the relations among genes of the transcription modules, genes in the regions of the QTLs

  16. Comparison of Maximum Likelihood Estimation Approach and Regression Approach in Detecting Quantitative Trait Lco Using RAPD Markers

    Treesearch

    Changren Weng; Thomas L. Kubisiak; C. Dana Nelson; James P. Geaghan; Michael Stine

    1999-01-01

    Single marker regression and single marker maximum likelihood estimation were tied to detect quantitative trait loci (QTLs) controlling the early height growth of longleaf pine and slash pine using a ((longleaf pine x slash pine) x slash pine) BC, population consisting of 83 progeny. Maximum likelihood estimation was found to be more power than regression and could...

  17. The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

    PubMed

    Goudet, Jérôme; Büchi, Lucie

    2006-02-01

    To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

  18. Multi-ethnic meta-analysis identifies RAI1 as a possible obstructive sleep apnea related quantitative trait locus in men

    USDA-ARS?s Scientific Manuscript database

    Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single et...

  19. Mapping of quantitative trait loci for resistance to fall armyworm and southwestern corn borer leaf-feeding damage in maize.

    USDA-ARS?s Scientific Manuscript database

    Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), and southwestern corn borer (SWCB), Diatraea grandiosella Dyar are damaging insect pests of maize resulting in significant yield and economic losses. A previous study identified quantitative trait loci (QTL) that contribute to reduced leaf-fe...

  20. SplicePlot: a utility for visualizing splicing quantitative trait loci.

    PubMed

    Wu, Eric; Nance, Tracy; Montgomery, Stephen B

    2014-04-01

    RNA sequencing has provided unprecedented resolution of alternative splicing and splicing quantitative trait loci (sQTL). However, there are few tools available for visualizing the genotype-dependent effects of splicing at a population level. SplicePlot is a simple command line utility that produces intuitive visualization of sQTLs and their effects. SplicePlot takes mapped RNA sequencing reads in BAM format and genotype data in VCF format as input and outputs publication-quality Sashimi plots, hive plots and structure plots, enabling better investigation and understanding of the role of genetics on alternative splicing and transcript structure. Source code and detailed documentation are available at http://montgomerylab.stanford.edu/spliceplot/index.html under Resources and at Github. SplicePlot is implemented in Python and is supported on Linux and Mac OS. A VirtualBox virtual machine running Ubuntu with SplicePlot already installed is also available.

  1. Allelic variations and differential expressions detected at quantitative trait loci for salt stress tolerance in wheat.

    PubMed

    Oyiga, Benedict C; Sharma, Ram C; Baum, Michael; Ogbonnaya, Francis C; Léon, Jens; Ballvora, Agim

    2018-05-01

    The increasing salinization of agricultural lands is a threat to global wheat production. Understanding of the mechanistic basis of salt tolerance (ST) is essential for developing breeding and selection strategies that would allow for increased wheat production under saline conditions to meet the increasing global demand. We used a set that consists of 150 internationally derived winter and facultative wheat cultivars genotyped with a 90K SNP chip and phenotyped for ST across three growth stages and for ionic (leaf K + and Na +  contents) traits to dissect the genetic architecture regulating ST in wheat. Genome-wide association mapping revealed 187 Single Nucleotide Polymorphism (SNPs) (R 2  = 3.00-30.67%), representing 37 quantitative trait loci (QTL), significantly associated with the ST traits. Of these, four QTL on 1BS, 2AL, 2BS and 3AL were associated with ST across the three growth stages and with the ionic traits. Novel QTL were also detected on 1BS and 1DL. Candidate genes linked to these polymorphisms were uncovered, and expression analyses were performed and validated on them under saline and non-saline conditions using transcriptomics and qRT-PCR data. Expressed sequence comparisons in contrasting ST wheat genotypes identified several non-synonymous/missense mutation sites that are contributory to the ST trait variations, indicating the biological relevance of these polymorphisms that can be exploited in breeding for ST in wheat. © 2017 The Authors. Plant, Cell & Environment published by JohnWiley & Sons Ltd.

  2. Global genetic architecture of an erythroid quantitative trait locus, HMIP-2.

    PubMed

    Menzel, Stephan; Rooks, Helen; Zelenika, Diana; Mtatiro, Siana N; Gnanakulasekaran, Akshala; Drasar, Emma; Cox, Sharon; Liu, Li; Masood, Mariam; Silver, Nicholas; Garner, Chad; Vasavda, Nisha; Howard, Jo; Makani, Julie; Adekile, Adekunle; Pace, Betty; Spector, Tim; Farrall, Martin; Lathrop, Mark; Thein, Swee Lay

    2014-11-01

    HMIP-2 is a human quantitative trait locus affecting peripheral numbers, size and hemoglobin composition of red blood cells, with a marked effect on the persistence of the fetal form of hemoglobin, HbF, in adults. The locus consists of multiple common variants in an enhancer region for MYB (chr 6q23.3), which encodes the hematopoietic transcription factor cMYB. Studying a European population cohort and four African-descended groups of patients with sickle cell anemia, we found that all share a set of two spatially separate HbF-promoting alleles at HMIP-2, termed "A" and "B." These typically occurred together ("A-B") on European chromosomes, but existed on separate homologous chromosomes in Africans. Using haplotype signatures for "A" and "B," we interrogated public population datasets. Haplotypes carrying only "A" or "B" were typical for populations in Sub-Saharan Africa. The "A-B" combination was frequent in European, Asian, and Amerindian populations. Both alleles were infrequent in tropical regions, possibly undergoing negative selection by geographical factors, as has been reported for malaria with other hematological traits. We propose that the ascertainment of worldwide distribution patterns for common, HbF-promoting alleles can aid their further genetic characterization, including the investigation of gene-environment interaction during human migration and adaptation. © 2014 The Authors. Annals of Human Genetics published by University College London (UCL) and John Wiley & Sons Ltd.

  3. Detection of linkage between a quantitative trait and a marker locus by the lod score method: sample size and sampling considerations.

    PubMed

    Demenais, F; Lathrop, G M; Lalouel, J M

    1988-07-01

    A simulation study is here conducted to measure the power of the lod score method to detect linkage between a quantitative trait and a marker locus in various situations. The number of families necessary to detect such linkage with 80% power is assessed for different sets of parameters at the trait locus and different values of the recombination fraction. The effects of varying the mode of sampling families and the sibship size are also evaluated.

  4. Identification of Candidate Genes Underlying an Iron Efficiency Quantitative Trait Locus in Soybean1

    PubMed Central

    Peiffer, Gregory A.; King, Keith E.; Severin, Andrew J.; May, Gregory D.; Cianzio, Silvia R.; Lin, Shun Fu; Lauter, Nicholas C.; Shoemaker, Randy C.

    2012-01-01

    Prevalent on calcareous soils in the United States and abroad, iron deficiency is among the most common and severe nutritional stresses in plants. In soybean (Glycine max) commercial plantings, the identification and use of iron-efficient genotypes has proven to be the best form of managing this soil-related plant stress. Previous studies conducted in soybean identified a significant iron efficiency quantitative trait locus (QTL) explaining more than 70% of the phenotypic variation for the trait. In this research, we identified candidate genes underlying this QTL through molecular breeding, mapping, and transcriptome sequencing. Introgression mapping was performed using two related near-isogenic lines in which a region located on soybean chromosome 3 required for iron efficiency was identified. The region corresponds to the previously reported iron efficiency QTL. The location was further confirmed through QTL mapping conducted in this study. Transcriptome sequencing and quantitative real-time-polymerase chain reaction identified two genes encoding transcription factors within the region that were significantly induced in soybean roots under iron stress. The two induced transcription factors were identified as homologs of the subgroup lb basic helix-loop-helix (bHLH) genes that are known to regulate the strategy I response in Arabidopsis (Arabidopsis thaliana). Resequencing of these differentially expressed genes unveiled a significant deletion within a predicted dimerization domain. We hypothesize that this deletion disrupts the Fe-DEFICIENCY-INDUCED TRANSCRIPTION FACTOR (FIT)/bHLH heterodimer that has been shown to induce known iron acquisition genes. PMID:22319075

  5. Universality and predictability in molecular quantitative genetics.

    PubMed

    Nourmohammad, Armita; Held, Torsten; Lässig, Michael

    2013-12-01

    Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology. Copyright © 2013. Published by Elsevier Ltd.

  6. Functional traits determine formation of mutualism and predation interactions in seed-rodent dispersal system of a subtropical forest

    NASA Astrophysics Data System (ADS)

    Chang, Gang; Zhang, Zhibin

    2014-02-01

    Network structure in plant-animal systems has been widely investigated but the roles of functional traits of plants and animals in formation of mutualism and predation interactions and community structure are still not fully understood. In this study, we quantitatively assessed interaction strength of mutualism and predation between 5 tree species and 7 rodent species by using semi-natural enclosures in a subtropical forest in southwest China. Seeds with high handling-time and nutrition traits (for both rat and mouse species) or high tannin trait (for mouse species) show high mutualism but low predation with rodents; while seeds with low handling-time and low nutrition traits show high predation but low mutualism with rodents. Large-sized rat species are more linked to seeds with high handling-time and high nutrition traits, while small-sized mouse species are more connected with seeds with low handling-time, low nutrition value and high tannin traits. Anti-predation seed traits tend to increase chance of mutualism instead of reducing predation by rodents, suggesting formation of mutualism may be connected with that of predation. Our study demonstrates that seed and animal traits play significant roles in the formation of mutualism and predation and network structure of the seed-rodent dispersal system.

  7. Quantitative genetics

    USDA-ARS?s Scientific Manuscript database

    The majority of economically important traits targeted for cotton improvement are quantitatively inherited. In this chapter, the current state of cotton quantitative genetics is described and separated into four components. These components include: 1) traditional quantitative inheritance analysis, ...

  8. Functional mapping of quantitative trait loci associated with rice tillering.

    PubMed

    Liu, G F; Li, M; Wen, J; Du, Y; Zhang, Y-M

    2010-10-01

    Several biologically significant parameters that are related to rice tillering are closely associated with rice grain yield. Although identification of the genes that control rice tillering and therefore influence crop yield would be valuable for rice production management and genetic improvement, these genes remain largely unidentified. In this study, we carried out functional mapping of quantitative trait loci (QTLs) for rice tillering in 129 doubled haploid lines, which were derived from a cross between IR64 and Azucena. We measured the average number of tillers in each plot at seven developmental stages and fit the growth trajectory of rice tillering with the Wang-Lan-Ding mathematical model. Four biologically meaningful parameters in this model--the potential maximum for tiller number (K), the optimum tiller time (t(0)), and the increased rate (r), or the reduced rate (c) at the time of deviation from t(0)--were our defined variables for multi-marker joint analysis under the framework of penalized maximum likelihood, as well as composite interval mapping. We detected a total of 27 QTLs that accounted for 2.49-8.54% of the total phenotypic variance. Nine common QTLs across multi-marker joint analysis and composite interval mapping showed high stability, while one QTL was environment-specific and three were epistatic. We also identified several genomic segments that are associated with multiple traits. Our results describe the genetic basis of rice tiller development, enable further marker-assisted selection in rice cultivar development, and provide useful information for rice production management.

  9. Inconsistencies in spontaneous and intentional trait inferences.

    PubMed

    Ma, Ning; Vandekerckhove, Marie; Baetens, Kris; Van Overwalle, Frank; Seurinck, Ruth; Fias, Wim

    2012-11-01

    This study explores the fMRI correlates of observers making trait inferences about other people under conflicting social cues. Participants were presented with several behavioral descriptions involving an agent that implied a particular trait. The last behavior was either consistent or inconsistent with the previously implied trait. This was done under instructions that elicited either spontaneous trait inferences ('read carefully') or intentional trait inferences ('infer a trait'). The results revealed that when the behavioral descriptions violated earlier trait implications, regardless of instruction, the medial prefrontal cortex (mPFC) was more strongly recruited as well as the domain-general conflict network including the posterior medial frontal cortex (pmFC) and the right prefrontal cortex (rPFC). These latter two areas were more strongly activated under intentional than spontaneous instructions. These findings suggest that when trait-relevant behavioral information is inconsistent, not only is activity increased in the mentalizing network responsible for trait processing, but control is also passed to a higher level conflict monitoring network in order to detect and resolve the contradiction.

  10. Quantitative Trait Loci for Yield and Yield-Related Traits in Spring Barley Populations Derived from Crosses between European and Syrian Cultivars

    PubMed Central

    Krystkowiak, Karolina; Sawikowska, Aneta; Frohmberg, Wojciech; Górny, Andrzej; Kędziora, Andrzej; Jankowiak, Janusz; Józefczyk, Damian; Karg, Grzegorz; Andrusiak, Joanna; Krajewski, Paweł; Szarejko, Iwona; Surma, Maria; Adamski, Tadeusz; Guzy-Wróbelska, Justyna; Kuczyńska, Anetta

    2016-01-01

    In response to climatic changes, breeding programmes should be aimed at creating new cultivars with improved resistance to water scarcity. The objective of this study was to examine the yield potential of barley recombinant inbred lines (RILs) derived from three cross-combinations of European and Syrian spring cultivars, and to identify quantitative trait loci (QTLs) for yield-related traits in these populations. RILs were evaluated in field experiments over a period of three years (2011 to 2013) and genotyped with simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers; a genetic map for each population was constructed and then one consensus map was developed. Biological interpretation of identified QTLs was achieved by reference to Ensembl Plants barley gene space. Twelve regions in the genomes of studied RILs were distinguished after QTL analysis. Most of the QTLs were identified on the 2H chromosome, which was the hotspot region in all three populations. Syrian parental cultivars contributed alleles decreasing traits' values at majority of QTLs for grain weight, grain number, spike length and time to heading, and numerous alleles increasing stem length. The phenomic and molecular approaches distinguished the lines with an acceptable grain yield potential combining desirable features or alleles from their parents, that is, early heading from the Syrian breeding line (Cam/B1/CI08887//CI05761) and short plant stature from the European semidwarf cultivar (Maresi). PMID:27227880

  11. Quantitative 3D investigation of Neuronal network in mouse spinal cord model

    NASA Astrophysics Data System (ADS)

    Bukreeva, I.; Campi, G.; Fratini, M.; Spanò, R.; Bucci, D.; Battaglia, G.; Giove, F.; Bravin, A.; Uccelli, A.; Venturi, C.; Mastrogiacomo, M.; Cedola, A.

    2017-01-01

    The investigation of the neuronal network in mouse spinal cord models represents the basis for the research on neurodegenerative diseases. In this framework, the quantitative analysis of the single elements in different districts is a crucial task. However, conventional 3D imaging techniques do not have enough spatial resolution and contrast to allow for a quantitative investigation of the neuronal network. Exploiting the high coherence and the high flux of synchrotron sources, X-ray Phase-Contrast multiscale-Tomography allows for the 3D investigation of the neuronal microanatomy without any aggressive sample preparation or sectioning. We investigated healthy-mouse neuronal architecture by imaging the 3D distribution of the neuronal-network with a spatial resolution of 640 nm. The high quality of the obtained images enables a quantitative study of the neuronal structure on a subject-by-subject basis. We developed and applied a spatial statistical analysis on the motor neurons to obtain quantitative information on their 3D arrangement in the healthy-mice spinal cord. Then, we compared the obtained results with a mouse model of multiple sclerosis. Our approach paves the way to the creation of a “database” for the characterization of the neuronal network main features for a comparative investigation of neurodegenerative diseases and therapies.

  12. Phylogenetic comparative methods on phylogenetic networks with reticulations.

    PubMed

    Bastide, Paul; Solís-Lemus, Claudia; Kriebel, Ricardo; Sparks, K William; Ané, Cécile

    2018-04-25

    The goal of Phylogenetic Comparative Methods (PCMs) is to study the distribution of quantitative traits among related species. The observed traits are often seen as the result of a Brownian Motion (BM) along the branches of a phylogenetic tree. Reticulation events such as hybridization, gene flow or horizontal gene transfer, can substantially affect a species' traits, but are not modeled by a tree. Phylogenetic networks have been designed to represent reticulate evolution. As they become available for downstream analyses, new models of trait evolution are needed, applicable to networks. One natural extension of the BM is to use a weighted average model for the trait of a hybrid, at a reticulation point. We develop here an efficient recursive algorithm to compute the phylogenetic variance matrix of a trait on a network, in only one preorder traversal of the network. We then extend the standard PCM tools to this new framework, including phylogenetic regression with covariates (or phylogenetic ANOVA), ancestral trait reconstruction, and Pagel's λ test of phylogenetic signal. The trait of a hybrid is sometimes outside of the range of its two parents, for instance because of hybrid vigor or hybrid depression. These two phenomena are rather commonly observed in present-day hybrids. Transgressive evolution can be modeled as a shift in the trait value following a reticulation point. We develop a general framework to handle such shifts, and take advantage of the phylogenetic regression view of the problem to design statistical tests for ancestral transgressive evolution in the evolutionary history of a group of species. We study the power of these tests in several scenarios, and show that recent events have indeed the strongest impact on the trait distribution of present-day taxa. We apply those methods to a dataset of Xiphophorus fishes, to confirm and complete previous analysis in this group. All the methods developed here are available in the Julia package PhyloNetworks.

  13. Exploring the interaction among EPHX1, GSTP1, SERPINE2, and TGFB1 contributing to the quantitative traits of chronic obstructive pulmonary disease in Chinese Han population.

    PubMed

    An, Li; Lin, Yingxiang; Yang, Ting; Hua, Lin

    2016-05-18

    Currently, the majority of genetic association studies on chronic obstructive pulmonary disease (COPD) risk focused on identifying the individual effects of single nucleotide polymorphisms (SNPs) as well as their interaction effects on the disease. However, conventional genetic studies often use binary disease status as the primary phenotype, but for COPD, many quantitative traits have the potential correlation with the disease status and closely reflect pathological changes. Here, we genotyped 44 SNPs from four genes (EPHX1, GSTP1, SERPINE2, and TGFB1) in 310 patients and 203 controls which belonged to the Chinese Han population to test the two-way and three-way genetic interactions with COPD-related quantitative traits using recently developed generalized multifactor dimensionality reduction (GMDR) and quantitative multifactor dimensionality reduction (QMDR) algorithms. Based on the 310 patients and the whole samples of 513 subjects, the best gene-gene interactions models were detected for four lung-function-related quantitative traits. For the forced expiratory volume in 1 s (FEV1), the best interaction was seen from EPHX1, SERPINE2, and GSTP1. For FEV1%pre, the forced vital capacity (FVC), and FEV1/FVC, the best interactions were seen from SERPINE2 and TGFB1. The results of this study provide further evidence for the genotype combinations at risk of developing COPD in Chinese Han population and improve the understanding on the genetic etiology of COPD and COPD-related quantitative traits.

  14. Origin of Peer Influence in Social Networks

    NASA Astrophysics Data System (ADS)

    Pinheiro, Flávio L.; Santos, Marta D.; Santos, Francisco C.; Pacheco, Jorge M.

    2014-03-01

    Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends' friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.

  15. Cloning of quantitative trait genes from rice reveals conservation and divergence of photoperiod flowering pathways in Arabidopsis and rice

    PubMed Central

    Matsubara, Kazuki; Hori, Kiyosumi; Ogiso-Tanaka, Eri; Yano, Masahiro

    2014-01-01

    Flowering time in rice (Oryza sativa L.) is determined primarily by daylength (photoperiod), and natural variation in flowering time is due to quantitative trait loci involved in photoperiodic flowering. To date, genetic analysis of natural variants in rice flowering time has resulted in the positional cloning of at least 12 quantitative trait genes (QTGs), including our recently cloned QTGs, Hd17, and Hd16. The QTGs have been assigned to specific photoperiodic flowering pathways. Among them, 9 have homologs in the Arabidopsis genome, whereas it was evident that there are differences in the pathways between rice and Arabidopsis, such that the rice Ghd7–Ehd1–Hd3a/RFT1 pathway modulated by Hd16 is not present in Arabidopsis. In this review, we describe QTGs underlying natural variation in rice flowering time. Additionally, we discuss the implications of the variation in adaptive divergence and its importance in rice breeding. PMID:24860584

  16. Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson.

    PubMed

    Thomson, M J; Tai, T H; McClung, A M; Lai, X-H; Hinga, M E; Lobos, K B; Xu, Y; Martinez, C P; McCouch, S R

    2003-08-01

    An advanced backcross population between an accession of Oryza rufipogon (IRGC 105491) and the U.S. cultivar Jefferson (Oryza sativa ssp. japonica) was developed to identify quantitative trait loci (QTLs) for yield, yield components and morphological traits. The genetic linkage map generated for this population consisted of 153 SSR and RFLP markers with an average interval size of 10.3 cM. Thirteen traits were examined, nine of which were measured in multiple environments. Seventy-six QTLs above an experiment-wise significance threshold of P<0.01 (corresponding to an interval mapping LOD>3.6 or a composite interval mapping LOD>3.9) were identified. For the traits measured in multiple environments, 47% of the QTLs were detected in at least two environments. The O. rufipogon allele was favorable for 53% of the yield and yield component QTLs, including loci for yield, grains per panicle, panicle length, and grain weight. Morphological traits related to the domestication process and/or weedy characteristics, including plant height, shattering, tiller type and awns, were found clustered on chromosomes 1 and 4. Comparisons to previous studies involving wild x cultivated crosses revealed O. rufipogon alleles with stable effects in multiple genetic backgrounds and environments, several of which have not been detected in studies between Oryza sativa cultivars, indicating potentially novel alleles from O. rufipogon. Some O. rufipogon-derived QTLs, however, were in similar regions as previously reported QTLs from Oryza sativa cultivars, providing evidence for conservation of these QTLs across the Oryza genus. In addition, several QTLs for grain weight, plant height, and flowering time were localized to putative homeologous regions in maize where QTLs for these traits have been previously reported, supporting the hypothesis of functional conservation of QTLs across the grasses.

  17. Psychopathic traits associated with abnormal hemodynamic activity in salience and default mode networks during auditory oddball task.

    PubMed

    Anderson, Nathaniel E; Maurer, J Michael; Steele, Vaughn R; Kiehl, Kent A

    2018-06-01

    Psychopathy is a personality disorder accompanied by abnormalities in emotional processing and attention. Recent theoretical applications of network-based models of cognition have been used to explain the diverse range of abnormalities apparent in psychopathy. Still, the physiological basis for these abnormalities is not well understood. A significant body of work has examined psychopathy-related abnormalities in simple attention-based tasks, but these studies have largely been performed using electrocortical measures, such as event-related potentials (ERPs), and they often have been carried out among individuals with low levels of psychopathic traits. In this study, we examined neural activity during an auditory oddball task using functional magnetic resonance imaging (fMRI) during a simple auditory target detection (oddball) task among 168 incarcerated adult males, with psychopathic traits assessed via the Hare Psychopathy Checklist-Revised (PCL-R). Event-related contrasts demonstrated that the largest psychopathy-related effects were apparent between the frequent standard stimulus condition and a task-off, implicit baseline. Negative correlations with interpersonal-affective dimensions (Factor 1) of the PCL-R were apparent in regions comprising default mode and salience networks. These findings support models of psychopathy describing impaired integration across functional networks. They additionally corroborate reports which have implicated failures of efficient transition between default mode and task-positive networks. Finally, they demonstrate a neurophysiological basis for abnormal mobilization of attention and reduced engagement with stimuli that have little motivational significance among those with high psychopathic traits.

  18. Selective DNA Pooling for Determination of Linkage between a Molecular Marker and a Quantitative Trait Locus

    PubMed Central

    Darvasi, A.; Soller, M.

    1994-01-01

    Selective genotyping is a method to reduce costs in marker-quantitative trait locus (QTL) linkage determination by genotyping only those individuals with extreme, and hence most informative, quantitative trait values. The DNA pooling strategy (termed: ``selective DNA pooling'') takes this one step further by pooling DNA from the selected individuals at each of the two phenotypic extremes, and basing the test for linkage on marker allele frequencies as estimated from the pooled samples only. This can reduce genotyping costs of marker-QTL linkage determination by up to two orders of magnitude. Theoretical analysis of selective DNA pooling shows that for experiments involving backcross, F(2) and half-sib designs, the power of selective DNA pooling for detecting genes with large effect, can be the same as that obtained by individual selective genotyping. Power for detecting genes with small effect, however, was found to decrease strongly with increase in the technical error of estimating allele frequencies in the pooled samples. The effect of technical error, however, can be markedly reduced by replication of technical procedures. It is also shown that a proportion selected of 0.1 at each tail will be appropriate for a wide range of experimental conditions. PMID:7896115

  19. Quantitative trait loci mapping of heat tolerance in broccoli (Brassica oleracea var. italica) using genotyping-by-sequencing.

    PubMed

    Branham, Sandra E; Stansell, Zachary J; Couillard, David M; Farnham, Mark W

    2017-03-01

    Five quantitative trait loci and one epistatic interaction were associated with heat tolerance in a doubled haploid population of broccoli evaluated in three summer field trials. Predicted rising global temperatures due to climate change have generated a demand for crops that are resistant to yield and quality losses from heat stress. Broccoli (Brassica oleracea var. italica) is a cool weather crop with high temperatures during production decreasing both head quality and yield. Breeding for heat tolerance in broccoli has potential to both expand viable production areas and extend the growing season but breeding efficiency is constrained by limited genetic information. A doubled haploid (DH) broccoli population segregating for heat tolerance was evaluated for head quality in three summer fields in Charleston, SC, USA. Multiple quantitative trait loci (QTL) mapping of 1,423 single nucleotide polymorphisms developed through genotyping-by-sequencing identified five QTL and one positive epistatic interaction that explained 62.1% of variation in heat tolerance. The QTL identified here can be used to develop markers for marker-assisted selection and to increase our understanding of the molecular mechanisms underlying plant response to heat stress.

  20. Quantitative trait loci controlling cyanogenic glucoside and dry matter content in cassava (Manihot esculenta Crantz) roots.

    PubMed

    Balyejusa Kizito, Elizabeth; Rönnberg-Wästljung, Ann-Christin; Egwang, Thomas; Gullberg, Urban; Fregene, Martin; Westerbergh, Anna

    2007-09-01

    Cassava (Manihot esculenta Crantz) is a starchy root crop grown in the tropics mainly by small-scale farmers even though agro-industrial processing is rapidly increasing. For this processing market improved varieties with high dry matter root content (DMC) is required. Potentially toxic cyanogenic glucosides are synthesized in the leaves and translocated to the roots. Selection for varieties with low cyanogenic glucoside potential (CNP) and high DMC is among the principal objectives in cassava breeding programs. However, these traits are highly influenced by the environmental conditions and the genetic control of these traits is not well understood. An S(1) population derived from a cross between two bred cassava varieties (MCOL 1684 and Rayong 1) that differ in CNP and DMC was used to study the heritability and genetic basis of these traits. A broad-sense heritability of 0.43 and 0.42 was found for CNP and DMC, respectively. The moderate heritabilities for DMC and CNP indicate that the phenotypic variation of these traits is explained by a genetic component. We found two quantitative trait loci (QTL) on two different linkage groups controlling CNP and six QTL on four different linkage groups controlling DMC. One QTL for CNP and one QTL for DMC mapped near each other, suggesting pleiotrophy and/or linkage of QTL. The two QTL for CNP showed additive effects while the six QTL for DMC showed additive effect, dominance or overdominance. This study is a first step towards developing molecular marker tools for efficient breeding of CNP and DMC in cassava.

  1. Detection of quantitative trait loci in Bos indicus and Bos taurus cattle using genome-wide association studies

    PubMed Central

    2013-01-01

    Background The apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between Bos indicus and Bos taurus because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a Bos taurus or Bos indicus ancestor. Methods Phenotype data on one or more traits and SNP genotype data for 10 181 cattle from Bos taurus, Bos indicus and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. indicus or B. taurus on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin. Results Fitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies. Conclusions The results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. indicus and B. taurus cattle. Thus, the QTL that segregate in

  2. Quantitative trait locus linkage analysis in a large Amish pedigree identifies novel candidate loci for erythrocyte traits

    PubMed Central

    Hinckley, Jesse D; Abbott, Diana; Burns, Trudy L; Heiman, Meadow; Shapiro, Amy D; Wang, Kai; Di Paola, Jorge

    2013-01-01

    We characterized a large Amish pedigree and, in 384 pedigree members, analyzed the genetic variance components with covariate screen as well as genome-wide quantitative trait locus (QTL) linkage analysis of red blood cell count (RBC), hemoglobin (HB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), platelet count (PLT), and white blood cell count (WBC) using SOLAR. Age and gender were found to be significant covariates in many CBC traits. We obtained significant heritability estimates for RBC, MCV, MCH, MCHC, RDW, PLT, and WBC. We report four candidate loci with Logarithm of the odds (LOD) scores above 2.0: 6q25 (MCH), 9q33 (WBC), 10p12 (RDW), and 20q13 (MCV). We also report eleven candidate loci with LOD scores between 1.5 and <2.0. Bivariate linkage analysis of MCV and MCH on chromosome 20 resulted in a higher maximum LOD score of 3.14. Linkage signals on chromosomes 4q28, 6p22, 6q25, and 20q13 are concomitant with previously reported QTL. All other linkage signals reported herein represent novel evidence of candidate QTL. Interestingly rs1800562, the most common causal variant of hereditary hemochromatosis in HFE (6p22) was associated with MCH and MCHC in this family. Linkage studies like the one presented here will allow investigators to focus the search for rare variants amidst the noise encountered in the large amounts of data generated by whole-genome sequencing. PMID:24058921

  3. Network morphospace

    PubMed Central

    Avena-Koenigsberger, Andrea; Goñi, Joaquín; Solé, Ricard; Sporns, Olaf

    2015-01-01

    The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of networked systems share a set of common architectural features. This raises important questions about their origin, for example whether such network attributes reflect common design principles or constraints imposed by selectional forces that have shaped the evolution of network topology. Is it possible to place the many patterns and forms of complex networks into a common space that reveals their relations, and what are the main rules and driving forces that determine which positions in such a space are occupied by systems that have actually evolved? We suggest that these questions can be addressed by combining concepts from two currently relatively unconnected fields. One is theoretical morphology, which has conceptualized the relations between morphological traits defined by mathematical models of biological form. The second is network science, which provides numerous quantitative tools to measure and classify different patterns of local and global network architecture across disparate types of systems. Here, we explore a new theoretical concept that lies at the intersection between both fields, the ‘network morphospace’. Defined by axes that represent specific network traits, each point within such a space represents a location occupied by networks that share a set of common ‘morphological’ characteristics related to aspects of their connectivity. Mapping a network morphospace reveals the extent to which the space is filled by existing networks, thus allowing a distinction between actual and impossible designs and highlighting the generative potential of rules and constraints that pervade the evolution of complex systems. PMID:25540237

  4. Prioritizing quantitative trait loci for root system architecture in tetraploid wheat

    PubMed Central

    Maccaferri, Marco; El-Feki, Walid; Nazemi, Ghasemali; Salvi, Silvio; Canè, Maria Angela; Colalongo, Maria Chiara; Stefanelli, Sandra; Tuberosa, Roberto

    2016-01-01

    Optimization of root system architecture (RSA) traits is an important objective for modern wheat breeding. Linkage and association mapping for RSA in two recombinant inbred line populations and one association mapping panel of 183 elite durum wheat (Triticum turgidum L. var. durum Desf.) accessions evaluated as seedlings grown on filter paper/polycarbonate screening plates revealed 20 clusters of quantitative trait loci (QTLs) for root length and number, as well as 30 QTLs for root growth angle (RGA). Divergent RGA phenotypes observed by seminal root screening were validated by root phenotyping of field-grown adult plants. QTLs were mapped on a high-density tetraploid consensus map based on transcript-associated Illumina 90K single nucleotide polymorphisms (SNPs) developed for bread and durum wheat, thus allowing for an accurate cross-referencing of RSA QTLs between durum and bread wheat. Among the main QTL clusters for root length and number highlighted in this study, 15 overlapped with QTLs for multiple RSA traits reported in bread wheat, while out of 30 QTLs for RGA, only six showed co-location with previously reported QTLs in wheat. Based on their relative additive effects/significance, allelic distribution in the association mapping panel, and co-location with QTLs for grain weight and grain yield, the RSA QTLs have been prioritized in terms of breeding value. Three major QTL clusters for root length and number (RSA_QTL_cluster_5#, RSA_QTL_cluster_6#, and RSA_QTL_cluster_12#) and nine RGA QTL clusters (QRGA.ubo-2A.1, QRGA.ubo-2A.3, QRGA.ubo-2B.2/2B.3, QRGA.ubo-4B.4, QRGA.ubo-6A.1, QRGA.ubo-6A.2, QRGA.ubo-7A.1, QRGA.ubo-7A.2, and QRGA.ubo-7B) appear particularly valuable for further characterization towards a possible implementation of breeding applications in marker-assisted selection and/or cloning of the causal genes underlying the QTLs. PMID:26880749

  5. Prioritizing quantitative trait loci for root system architecture in tetraploid wheat.

    PubMed

    Maccaferri, Marco; El-Feki, Walid; Nazemi, Ghasemali; Salvi, Silvio; Canè, Maria Angela; Colalongo, Maria Chiara; Stefanelli, Sandra; Tuberosa, Roberto

    2016-02-01

    Optimization of root system architecture (RSA) traits is an important objective for modern wheat breeding. Linkage and association mapping for RSA in two recombinant inbred line populations and one association mapping panel of 183 elite durum wheat (Triticum turgidum L. var. durum Desf.) accessions evaluated as seedlings grown on filter paper/polycarbonate screening plates revealed 20 clusters of quantitative trait loci (QTLs) for root length and number, as well as 30 QTLs for root growth angle (RGA). Divergent RGA phenotypes observed by seminal root screening were validated by root phenotyping of field-grown adult plants. QTLs were mapped on a high-density tetraploid consensus map based on transcript-associated Illumina 90K single nucleotide polymorphisms (SNPs) developed for bread and durum wheat, thus allowing for an accurate cross-referencing of RSA QTLs between durum and bread wheat. Among the main QTL clusters for root length and number highlighted in this study, 15 overlapped with QTLs for multiple RSA traits reported in bread wheat, while out of 30 QTLs for RGA, only six showed co-location with previously reported QTLs in wheat. Based on their relative additive effects/significance, allelic distribution in the association mapping panel, and co-location with QTLs for grain weight and grain yield, the RSA QTLs have been prioritized in terms of breeding value. Three major QTL clusters for root length and number (RSA_QTL_cluster_5#, RSA_QTL_cluster_6#, and RSA_QTL_cluster_12#) and nine RGA QTL clusters (QRGA.ubo-2A.1, QRGA.ubo-2A.3, QRGA.ubo-2B.2/2B.3, QRGA.ubo-4B.4, QRGA.ubo-6A.1, QRGA.ubo-6A.2, QRGA.ubo-7A.1, QRGA.ubo-7A.2, and QRGA.ubo-7B) appear particularly valuable for further characterization towards a possible implementation of breeding applications in marker-assisted selection and/or cloning of the causal genes underlying the QTLs. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  6. Preliminary evidence for associations between molecular markers and quantitative traits in a set of bread wheat (Triticum aestivum L.) cultivars and breeding lines.

    PubMed

    Abdollahi Mandoulakani, Babak; Nasri, Shilan; Dashchi, Sahar; Arzhang, Sorour; Bernousi, Iraj; Abbasi Holasou, Hossein

    The identification of polymorphic markers associated with various quantitative traits allows us to test their performance for the exploitation of the extensive quantitative variation maintained in gene banks. In the current study, a set of 97 wheat germplasm accessions including 48 cultivars and 49 breeding lines were evaluated for 18 agronomic traits. The accessions were also genotyped with 23 ISSR, nine IRAP and 20 REMAP markers, generating a total of 658 clear and scorable bands, 86% of which were polymorphic. Both neighbor-joining dendrogram and Bayesian analysis of clustering of individuals revealed that the accessions could be divided into four genetically distinct groups, indicating the presence of a population structure in current wheat germplasm. Associations between molecular markers and 18 agronomic traits were analyzed using the mixed linear model (MLM) approach. A total of 94 loci were found to be significantly associated with agronomic traits (P≤0.01). The highest number of bands significantly associated with the 18 traits varied from 11 for number of spikelets spike -1 (NSS) to two for grain yield in row (GRY). Loci ISSR16-9 and REMAP13-10 were associated with three different traits. The results of the current study provide useful information about the performance of retrotransposon-based and ISSR molecular markers that could be helpful in selecting potentially elite gene bank samples for wheat-breeding programs. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

  7. Quantitative Trait Loci for Cold Tolerance of Rice Recombinant Inbred Lines in Low Temperature Environments

    PubMed Central

    Jiang, Wenzhu; Jin, Yong-Mei; Lee, Joohyun; Lee, Kang-Ie; Piao, Rihua; Han, Longzhi; Shin, Jin-Chul; Jin, Rong-De; Cao, Tiehua; Pan, Hong-Yu; Du, Xinglin; Koh, Hee-Jong

    2011-01-01

    Low temperature is one of the major environmental stresses in rice cultivation in high-altitude and high-latitude regions. In this study, we cultivated a set of recombinant inbred lines (RIL) derived from Dasanbyeo (indica) / TR22183 (japonica) crosses in Yanji (high-latitude area), Kunming (high-altitude area), Chuncheon (cold water irrigation) and Suwon (normal) to evaluate the main effects of quantitative trait loci (QTL) and epistatic QTL (E-QTL) with regard to their interactions with environments for coldrelated traits. Six QTLs for spikelet fertility (SF) were identified in three cold treatment locations. Among them, four QTLs on chromosomes 2, 7, 8, and 10 were validated by several near isogenic lines (NILs) under cold treatment in Chuncheon. A total of 57 QTLs and 76 E-QTLs for nine cold-related traits were identified as distributing on all 12 chromosomes; among them, 19 QTLs and E-QTLs showed significant interactions of QTLs and environments (QEIs). The total phenotypic variation explained by each trait ranged from 13.2 to 29.1% in QTLs, 10.6 to 29.0% in EQTLs, 2.2 to 8.8% in QEIs and 1.0% to 7.7% in E-QTL × environment interactions (E-QEIs). These results demonstrate that epistatic effects and QEIs are important properties of QTL parameters for cold tolerance at the reproductive stage. In order to develop cold tolerant varieties adaptable to wide-ranges of cold stress, a strategy facilitating marker-assisted selection (MAS) is being adopted to accumulate QTLs identified from different environments. PMID:22080374

  8. Genetic Mapping of Quantitative Trait Loci for Grain Yield under Drought in Rice under Controlled Greenhouse Conditions

    NASA Astrophysics Data System (ADS)

    Solis, Julio; Gutierrez, Andres; Mangu, Venkata; Sanchez, Eduardo; Bedre, Renesh; Linscombe, Steve; Baisakh, Niranjan

    2017-12-01

    Drought stress is a constant threat to rice production worldwide. Most Mmodern rice cultivars are sensitive to drought, and the effect is severe at the reproductive stage. Conventional breeding for drought resistant (DR) rice varieties is slow and limited due to the quantitative nature of the DR traits. Identification of genes (QTLs)/markers associated with DR traits is a prerequisite for marker-assisted breeding. Grain yield is the most important trait and to this end drought yield QTLs have been identified under field conditions. The present study reports identification of drought yield QTLs under controlled conditions without confounding effects of other factors prevalent under natural conditions. A linkage map covering 1,781.5 cM with an average resolution of 9.76 cM was constructed using an F2 population from a cross between two Japonica cultivars, Cocodrie (drought sensitive) and Vandana (drought tolerant) with 213 markers distributed over 12 rice chromosomes. A subset of 59 markers (22 genic SSRs and 37 SNPs) derived from the transcriptome of the parents were also placed in the map. Single marker analysis using 187 F2:3 progeny identified 6 markers distributed on chromosomes 1, 5, and 8 to be associated with grain yield under drought (GYD). Composite interval mapping identified six genomic regions/quantitative trait loci (QTL) on chromosome 1, 5, 8, and 9 to be associated with GYD. QTLs located on chromosome 1 (qGYD1.2, qGYD1.3), chromosome 5 (qGYD5.1) and chromosome 8 (qGYD8.1) were contributed by Vandana alleles, whereas the QTLs, qGYD1.1 and qQYD9.1 were contributed by Cocodrie alelles. The additive positive phenotypic variance explained by the QTLs ranged from 30.0% to 34.0%. Candidate genes annotation within QTLs suggested the role of transcription factors and genes involved in osmotic potential regulation through catalytic/metabolic pathways in drought resistance tolerance mechanism contributing to yield.

  9. Genome-Wide Search for Quantitative Trait Loci Controlling Important Plant and Flower Traits in Petunia Using an Interspecific Recombinant Inbred Population of Petunia axillaris and Petunia exserta.

    PubMed

    Cao, Zhe; Guo, Yufang; Yang, Qian; He, Yanhong; Fetouh, Mohammed; Warner, Ryan M; Deng, Zhanao

    2018-05-15

    A major bottleneck in plant breeding has been the much limited genetic base and much reduced genetic diversity in domesticated, cultivated germplasm. Identification and utilization of favorable gene loci or alleles from wild or progenitor species can serve as an effective approach to increasing genetic diversity and breaking this bottleneck in plant breeding. This study was conducted to identify quantitative trait loci (QTL) in wild or progenitor petunia species that can be used to improve important horticultural traits in garden petunia. An F 7 recombinant inbred population derived between Petunia axillaris and P. exserta was phenotyped for plant height, plant spread, plant size, flower counts, flower diameter, flower length, and days to anthesis, in Florida in two consecutive years. Transgressive segregation was observed for all seven traits in both years. The broad-sense heritability estimates for the traits ranged from 0.20 (days to anthesis) to 0.62 (flower length). A genome-wide genetic linkage map consisting 368 single nucleotide polymorphism bins and extending over 277 cM was searched to identify QTL for these traits. Nineteen QTL were identified and localized to five linkage groups. Eleven of the loci were identified consistently in both years; several loci explained up to 34.0% and 24.1% of the phenotypic variance for flower length and flower diameter, respectively. Multiple loci controlling different traits are co-localized in four intervals in four linkage groups. These intervals contain desirable alleles that can be introgressed into commercial petunia germplasm to expand the genetic base and improve plant performance and flower characteristics in petunia. Copyright © 2018, G3: Genes, Genomes, Genetics.

  10. Genes and quantitative trait loci (QTL) controlling trace element concentrations in perennial grasses grown on phytotoxic soil contaminated with heavy metals

    USDA-ARS?s Scientific Manuscript database

    Perennial grasses cover diverse soils throughout the world, including sites contaminated with heavy metals, producing forages that must be safe for livestock and wildlife. Chromosome regions known as quantitative trait loci (QTLs) controlling forage mineral concentrations were mapped in a populatio...

  11. Mapping Quantitative Trait Loci in Crosses between Outbred Lines Using Least Squares

    PubMed Central

    Haley, C. S.; Knott, S. A.; Elsen, J. M.

    1994-01-01

    The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F(1) (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects and effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at

  12. Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping

    PubMed Central

    2012-01-01

    Background Proanthocyanidins (PAs), or condensed tannins, are flavonoid polymers, widespread throughout the plant kingdom, which provide protection against herbivores while conferring organoleptic and nutritive values to plant-derived foods, such as wine. However, the genetic basis of qualitative and quantitative PA composition variation is still poorly understood. To elucidate the genetic architecture of the complex grape PA composition, we first carried out quantitative trait locus (QTL) analysis on a 191-individual pseudo-F1 progeny. Three categories of PA variables were assessed: total content, percentages of constitutive subunits and composite ratio variables. For nine functional candidate genes, among which eight co-located with QTLs, we performed association analyses using a diversity panel of 141 grapevine cultivars in order to identify causal SNPs. Results Multiple QTL analysis revealed a total of 103 and 43 QTLs, respectively for seed and skin PA variables. Loci were mainly of additive effect while some loci were primarily of dominant effect. Results also showed a large involvement of pairwise epistatic interactions in shaping PA composition. QTLs for PA variables in skin and seeds differed in number, position, involvement of epistatic interaction and allelic effect, thus revealing different genetic determinisms for grape PA composition in seeds and skin. Association results were consistent with QTL analyses in most cases: four out of nine tested candidate genes (VvLAR1, VvMYBPA2, VvCHI1, VvMYBPA1) showed at least one significant association with PA variables, especially VvLAR1 revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel. Conclusions This study presents the first QTL analysis on grape berry PA composition with a comparison between skin and seeds, together with an association study. Our results suggest a complex genetic control for PA traits and different

  13. Psychopathic traits moderate peer influence on adolescent delinquency.

    PubMed

    Kerr, Margaret; Van Zalk, Maarten; Stattin, Håkan

    2012-08-01

    Peer influence on adolescent delinquency is well established, but little is known about moderators of peer influence. In this study, we examined adolescents' (targets) and their peers' psychopathic personality traits as moderators of peer influence on delinquency in peer networks. We used three separate dimensions of the psychopathic personality: grandiose-manipulative traits, callous-unemotional traits, and impulsive-irresponsible traits. We used a peer network approach with five waves of longitudinal data from 847 adolescents in one community. Peer nominations were not limited to the school context, thus allowing us to capture all potentially important peers. In addition, peers reported on their own delinquency, thus allowing us to avoid problems of false consensus or projection that arise when individuals report on their peers' delinquency. We used simulation investigation for empirical network analyses (SIENA), which is the only program currently available that can be used to study peer influence effects in peer networks of multiple relationships while controlling for selection effects. Targets' and peers' callous-unemotional and grandiose-manipulative traits uniquely moderated peer influence on delinquency. Relative to those with low levels, targets who were high on these traits were less influenced by peers' delinquency, and peers who were high on these traits were more influential on targets' delinquency. Selection effects were found for impulsive-irresponsible traits, but these traits did not moderate peer influence on delinquency. As the first study to look at moderating effects of psychopathic traits on peer influence, this study advances knowledge about peer influence on delinquency and about psychopathic traits in adolescents. In addition, the study contributes to the literature by looking at unique effects of the three dimensions of psychopathy and taking a peer network approach, in which network effects, self-selection, and other selection effects are

  14. Construction of a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq) and its application to Quantitative Trait Loci (QTL) analysis for boll weight in upland cotton (Gossypium hirsutum.).

    PubMed

    Zhang, Zhen; Shang, Haihong; Shi, Yuzhen; Huang, Long; Li, Junwen; Ge, Qun; Gong, Juwu; Liu, Aiying; Chen, Tingting; Wang, Dan; Wang, Yanling; Palanga, Koffi Kibalou; Muhammad, Jamshed; Li, Weijie; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Song, Weiwu; Cai, Juan; Li, Pengtao; Rashid, Harun or; Gong, Wankui; Yuan, Youlu

    2016-04-11

    Upland Cotton (Gossypium hirsutum) is one of the most important worldwide crops it provides natural high-quality fiber for the industrial production and everyday use. Next-generation sequencing is a powerful method to identify single nucleotide polymorphism markers on a large scale for the construction of a high-density genetic map for quantitative trait loci mapping. In this research, a recombinant inbred lines population developed from two upland cotton cultivars 0-153 and sGK9708 was used to construct a high-density genetic map through the specific locus amplified fragment sequencing method. The high-density genetic map harbored 5521 single nucleotide polymorphism markers which covered a total distance of 3259.37 cM with an average marker interval of 0.78 cM without gaps larger than 10 cM. In total 18 quantitative trait loci of boll weight were identified as stable quantitative trait loci and were detected in at least three out of 11 environments and explained 4.15-16.70 % of the observed phenotypic variation. In total, 344 candidate genes were identified within the confidence intervals of these stable quantitative trait loci based on the cotton genome sequence. These genes were categorized based on their function through gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and eukaryotic orthologous groups analysis. This research reported the first high-density genetic map for Upland Cotton (Gossypium hirsutum) with a recombinant inbred line population using single nucleotide polymorphism markers developed by specific locus amplified fragment sequencing. We also identified quantitative trait loci of boll weight across 11 environments and identified candidate genes within the quantitative trait loci confidence intervals. The results of this research would provide useful information for the next-step work including fine mapping, gene functional analysis, pyramiding breeding of functional genes as well as marker-assisted selection.

  15. Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk.

    PubMed

    Buitenhuis, A J; Sundekilde, U K; Poulsen, N A; Bertram, H C; Larsen, L B; Sørensen, P

    2013-05-01

    Small components and metabolites in milk are significant for the utilization of milk, not only in dairy food production but also as disease predictors in dairy cattle. This study focused on estimation of genetic parameters and detection of quantitative trait loci for metabolites in bovine milk. For this purpose, milk samples were collected in mid lactation from 371 Danish Holstein cows in first to third parity. A total of 31 metabolites were detected and identified in bovine milk by using (1)H nuclear magnetic resonance (NMR) spectroscopy. Cows were genotyped using a bovine high-density single nucleotide polymorphism (SNP) chip. Based on the SNP data, a genomic relationship matrix was calculated and used as a random factor in a model together with 2 fixed factors (herd and lactation stage) to estimate the heritability and breeding value for individual metabolites in the milk. Heritability was in the range of 0 for lactic acid to >0.8 for orotic acid and β-hydroxybutyrate. A single SNP association analysis revealed 7 genome-wide significant quantitative trait loci [malonate: Bos taurus autosome (BTA)2 and BTA7; galactose-1-phosphate: BTA2; cis-aconitate: BTA11; urea: BTA12; carnitine: BTA25; and glycerophosphocholine: BTA25]. These results demonstrate that selection for metabolites in bovine milk may be possible. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  16. Population size is weakly related to quantitative genetic variation and trait differentiation in a stream fish.

    PubMed

    Wood, Jacquelyn L A; Tezel, Defne; Joyal, Destin; Fraser, Dylan J

    2015-09-01

    How population size influences quantitative genetic variation and differentiation among natural, fragmented populations remains unresolved. Small, isolated populations might occupy poor quality habitats and lose genetic variation more rapidly due to genetic drift than large populations. Genetic drift might furthermore overcome selection as population size decreases. Collectively, this might result in directional changes in additive genetic variation (VA ) and trait differentiation (QST ) from small to large population size. Alternatively, small populations might exhibit larger variation in VA and QST if habitat fragmentation increases variability in habitat types. We explored these alternatives by investigating VA and QST using nine fragmented populations of brook trout varying 50-fold in census size N (179-8416) and 10-fold in effective number of breeders, Nb (18-135). Across 15 traits, no evidence was found for consistent differences in VA and QST with population size and almost no evidence for increased variability of VA or QST estimates at small population size. This suggests that (i) small populations of some species may retain adaptive potential according to commonly adopted quantitative genetic measures and (ii) populations of varying sizes experience a variety of environmental conditions in nature, however extremely large studies are likely required before any firm conclusions can be made. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

  17. Quantitative variation in water-use efficiency across water regimes and its relationship with circadian, vegetative, reproductive, and leaf gas-exchange traits.

    PubMed

    Edwards, Christine E; Ewers, Brent E; McClung, C Robertson; Lou, Ping; Weinig, Cynthia

    2012-05-01

    Drought limits light harvesting, resulting in lower plant growth and reproduction. One trait important for plant drought response is water-use efficiency (WUE). We investigated (1) how the joint genetic architecture of WUE, reproductive characters, and vegetative traits changed across drought and well-watered conditions, (2) whether traits with distinct developmental bases (e.g. leaf gas exchange versus reproduction) differed in the environmental sensitivity of their genetic architecture, and (3) whether quantitative variation in circadian period was related to drought response in Brassica rapa. Overall, WUE increased in drought, primarily because stomatal conductance, and thus water loss, declined more than carbon fixation. Genotypes with the highest WUE in drought expressed the lowest WUE in well-watered conditions, and had the largest vegetative and floral organs in both treatments. Thus, large changes in WUE enabled some genotypes to approach vegetative and reproductive trait optima across environments. The genetic architecture differed for gas-exchange and vegetative traits across drought and well-watered conditions, but not for floral traits. Correlations between circadian and leaf gas-exchange traits were significant but did not vary across treatments, indicating that circadian period affects physiological function regardless of water availability. These results suggest that WUE is important for drought tolerance in Brassica rapa and that artificial selection for increased WUE in drought will not result in maladaptive expression of other traits that are correlated with WUE.

  18. A quantitative trait locus mixture model that avoids spurious LOD score peaks.

    PubMed

    Feenstra, Bjarke; Skovgaard, Ib M

    2004-06-01

    In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented.

  19. Statistical correction of the Winner’s Curse explains replication variability in quantitative trait genome-wide association studies

    PubMed Central

    Pe’er, Itsik

    2017-01-01

    Genome-wide association studies (GWAS) have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10−14), even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner’s Curse (p < 10−16). We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94). In contrast, ancestry differences between replication and discovery (13 studies, 385 loci) cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium. PMID:28715421

  20. Species traits and network structure predict the success and impacts of pollinator invasions.

    PubMed

    Valdovinos, Fernanda S; Berlow, Eric L; Moisset de Espanés, Pablo; Ramos-Jiliberto, Rodrigo; Vázquez, Diego P; Martinez, Neo D

    2018-05-31

    Species invasions constitute a major and poorly understood threat to plant-pollinator systems. General theory predicting which factors drive species invasion success and subsequent effects on native ecosystems is particularly lacking. We address this problem using a consumer-resource model of adaptive behavior and population dynamics to evaluate the invasion success of alien pollinators into plant-pollinator networks and their impact on native species. We introduce pollinator species with different foraging traits into network models with different levels of species richness, connectance, and nestedness. Among 31 factors tested, including network and alien properties, we find that aliens with high foraging efficiency are the most successful invaders. Networks exhibiting high alien-native diet overlap, fraction of alien-visited plant species, most-generalist plant connectivity, and number of specialist pollinator species are the most impacted by invaders. Our results mimic several disparate observations conducted in the field and potentially elucidate the mechanisms responsible for their variability.

  1. A genome scan for selection signatures comparing farmed Atlantic salmon with two wild populations: Testing colocalization among outlier markers, candidate genes, and quantitative trait loci for production traits.

    PubMed

    Liu, Lei; Ang, Keng Pee; Elliott, J A K; Kent, Matthew Peter; Lien, Sigbjørn; MacDonald, Danielle; Boulding, Elizabeth Grace

    2017-03-01

    Comparative genome scans can be used to identify chromosome regions, but not traits, that are putatively under selection. Identification of targeted traits may be more likely in recently domesticated populations under strong artificial selection for increased production. We used a North American Atlantic salmon 6K SNP dataset to locate genome regions of an aquaculture strain (Saint John River) that were highly diverged from that of its putative wild founder population (Tobique River). First, admixed individuals with partial European ancestry were detected using STRUCTURE and removed from the dataset. Outlier loci were then identified as those showing extreme differentiation between the aquaculture population and the founder population. All Arlequin methods identified an overlapping subset of 17 outlier loci, three of which were also identified by BayeScan. Many outlier loci were near candidate genes and some were near published quantitative trait loci (QTLs) for growth, appetite, maturity, or disease resistance. Parallel comparisons using a wild, nonfounder population (Stewiacke River) yielded only one overlapping outlier locus as well as a known maturity QTL. We conclude that genome scans comparing a recently domesticated strain with its wild founder population can facilitate identification of candidate genes for traits known to have been under strong artificial selection.

  2. Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

    PubMed Central

    Zeng, Yuxiang; Ji, Zhijuan; Wen, Zhihua; Liang, Yan; Yang, Changdeng

    2016-01-01

    Grain length is an important quantitative trait in rice (Oryza sativa L.) that influences both grain yield and exterior quality. Although many quantitative trait loci (QTLs) for grain length have been identified, it is still unclear how different alleles from different QTLs regulate grain length coordinately. To explore the mechanisms of QTL combination in the determination of grain length, five mapping populations, including two F2 populations, an F3 population, an F7 recombinant inbred line (RIL) population, and an F8 RIL population, were developed from the cross between the U.S. tropical japonica variety ‘Lemont’ and the Chinese indica variety ‘Yangdao 4’ and grown under different environmental conditions. Four QTLs (qGL-3-1, qGL-3-2, qGL-4, and qGL-7) for grain length were detected using both composite interval mapping and multiple interval mapping methods in the mapping populations. In each locus, there was an allele from one parent that increased grain length and another allele from another parent that decreased it. The eight alleles in the four QTLs were analyzed to determine whether these alleles act additively across loci, and lead to a linear relationship between the predicted breeding value of QTLs and phenotype. Linear regression analysis suggested that the combination of eight alleles determined grain length. Plants carrying more grain length-increasing alleles had longer grain length than those carrying more grain length-decreasing alleles. This trend was consistent in all five mapping populations and demonstrated the regulation of grain length by the four QTLs. Thus, these QTLs are ideal resources for modifying grain length in rice. PMID:26942914

  3. Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.).

    PubMed

    Jiang, Congcong; Shi, Jiaqin; Li, Ruiyuan; Long, Yan; Wang, Hao; Li, Dianrong; Zhao, Jianyi; Meng, Jinling

    2014-04-01

    This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations. Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F2 population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.

  4. An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus)

    PubMed Central

    2014-01-01

    Background Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Results Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. Conclusions The integrated map described herein enhances the utility of genomic tools over

  5. A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

    PubMed Central

    Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan; Van Gilst, Wiek H.; Asselbergs, Folkert W.; Gilbert-Diamond, Diane

    2013-01-01

    We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. PMID:23805232

  6. Quantitative trait loci × environment interactions for plant morphology vary over ontogeny in Brassica rapa.

    PubMed

    Dechaine, Jennifer M; Brock, Marcus T; Iniguez-Luy, Federico L; Weinig, Cynthia

    2014-01-01

    Growth in plants occurs via the addition of repeating modules, suggesting that the genetic architecture of similar subunits may vary between earlier- and later-developing modules. These complex environment × ontogeny interactions are not well elucidated, as studies examining quantitative trait loci (QTLs) expression over ontogeny have not included multiple environments. Here, we characterized the genetic architecture of vegetative traits and onset of reproduction over ontogeny in recombinant inbred lines of Brassica rapa in the field and glasshouse. The magnitude of genetic variation in plasticity of seedling internodes was greater than in those produced later in ontogeny. We correspondingly detected that QTLs for seedling internode length were environment-specific, whereas later in ontogeny the majority of QTLs affected internode lengths in all treatments. The relationship between internode traits and onset of reproduction varied with environment and ontogenetic stage. This relationship was observed only in the glasshouse environment and was largely attributable to one environment-specific QTL. Our results provide the first evidence of a QTL × environment × ontogeny interaction, and provide QTL resolution for differences between early- and later-stage plasticity for stem elongation. These results also suggest potential constraints on morphological evolution in early vs later modules as a result of associations with reproductive timing. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  7. Mapping quantitative trait loci for fear-like behaviors in mice.

    PubMed

    Gershenfeld, H K; Paul, S M

    1997-11-15

    Two mouse models developed for screening anxiolytic drugs were selected for genetic analysis, namely "wall-seeking" tendency in an open field ("thigmotaxis") and the light-to-dark transition (LD) paradigm, a conflict test. These tests measure differences in naturalistic tendencies of mice to explore a novel environment and to avoid a bright light or the center of an open field. In an F2 intercross of two strains of mice (A/J and C57BL/6J) that differ markedly in these behaviors, we estimated a broad sense heritability ranging from 0.3 to 0.59. With this intercross (n = 518), we have mapped several quantitative trait loci (QTL) for these behaviors by performing a genome-wide search. A significant QTL on chromosome 10 (near D10Mit237; LOD of 9.3) that affects LD behavior was identified, and suggestive QTL (LOD > 2.8) were mapped to chromosomes 6, 15, 19, and X. For center time behaviors, QTL were identified on chromosome 1 (LOD of 7.7 and 4.0 for the initial 5-min epoch and the first trial average of the next two 5-min epochs, respectively), and suggestive QTL (LOD > 2.8) were mapped to chromosomes 6 and 14. These QTL individually explain from 2.3 to 8.4% of the phenotypic variance. Collectively, the multiple independent QTL explain from 3.5 to 26.5% of the F2 population's phenotypic variance, depending on the trait. The complexity and heterogeneity of the genetic factors underlying these fear-like behaviors are illustrated by the lack of shared QTL between paradigms and by mapping different QTL for repeated trials of behavior. The identification of QTL affecting individual differences in fear-like behavior may lead to the identification of new gene products and pathways that modulate behavior, providing targets for rational drug design.

  8. Genome-wide Linkage Analysis for Identifying Quantitative Trait Loci Involved in the Regulation of Lipoprotein a (Lpa) Levels

    PubMed Central

    López, Sonia; Buil, Alfonso; Ordoñez, Jordi; Souto, Juan Carlos; Almasy, Laura; Lathrop, Mark; Blangero, John; Blanco-Vaca, Francisco; Fontcuberta, Jordi; Soria, José Manuel

    2009-01-01

    Lipoprotein Lp(a) levels are highly heritable and are associated with cardiovascular risk. We performed a genome-wide linkage analysis to delineate the genomic regions that influence the concentration of Lp(a) in families from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) Project. Lp(a) levels were measured in 387 individuals belonging to 21 extended Spanish families. A total of 485 DNA microsatellite markers were genotyped to provide a 7.1 cM genetic map. A variance component linkage method was used to evaluate linkage and to detect quantitative trait loci (QTLs). The main QTL that showed strong evidence of linkage with Lp(a) levels was located at the structural gene for apo(a) on Chromosome 6 (LOD score=13.8). Interestingly, another QTL influencing Lp(a) concentration was located on Chromosome 2 with a LOD score of 2.01. This region contains several candidate genes. One of them is the tissue factor pathway inhibitor (TFPI), which has antithrombotic action and also has the ability to bind lipoproteins. However, quantitative trait association analyses performed with 12 SNPs in TFPI gene revealed no association with Lp(a) levels. Our study confirms previous results on the genetic basis of Lp(a) levels. In addition, we report a new QTL on Chromosome 2 involved in the quantitative variation of Lp(a). These data should serve as the basis for further detection of candidate genes and to elucidate the relationship between the concentration of Lp(a) and cardiovascular risk. PMID:18560444

  9. Identification of quantitative trait loci and candidate genes for cadmium tolerance in Populus

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

    Induri, Brahma R; Ellis, Danielle R; Slavov, Goncho T.

    2012-01-01

    Understanding genetic variation for the response of Populus to heavy metals like cadmium (Cd) is an important step in elucidating the underlying mechanisms of tolerance. In this study, a pseudo-backcross pedigree of Populus trichocarpa Torr. & Gray and Populus deltoides Bart. was characterized for growth and performance traits after Cd exposure. A total of 16 quantitative trait loci (QTL) at logarithm of odds (LOD) ratio 2.5 were detected for total dry weight, its components and root volume. Major QTL for Cd responses were mapped to two different linkage groups and the relative allelic effects were in opposing directions on themore » two chromosomes, suggesting differential mechanisms at these two loci. The phenotypic variance explained by Cd QTL ranged from 5.9 to 11.6% and averaged 8.2% across all QTL. A whole-genome microarray study led to the identification of nine Cd-responsive genes from these QTL. Promising candidates for Cd tolerance include an NHL repeat membrane-spanning protein, a metal transporter and a putative transcription factor. Additional candidates in the QTL intervals include a putative homolog of a glutamate cysteine ligase, and a glutathione-S-transferase. Functional characterization of these candidate genes should enhance our understanding of Cd metabolism and transport and phytoremediation capabilities of Populus.« less

  10. Autism traits in the RASopathies.

    PubMed

    Adviento, Brigid; Corbin, Iris L; Widjaja, Felicia; Desachy, Guillaume; Enrique, Nicole; Rosser, Tena; Risi, Susan; Marco, Elysa J; Hendren, Robert L; Bearden, Carrie E; Rauen, Katherine A; Weiss, Lauren A

    2014-01-01

    Mutations in Ras/mitogen-activated protein kinase (Ras/MAPK) pathway genes lead to a class of disorders known as RASopathies, including neurofibromatosis type 1 (NF1), Noonan syndrome (NS), Costello syndrome (CS), and cardio-facio-cutaneous syndrome (CFC). Previous work has suggested potential genetic and phenotypic overlap between dysregulation of Ras/MAPK signalling and autism spectrum disorders (ASD). Although the literature offers conflicting evidence for association of NF1 and autism, there has been no systematic evaluation of autism traits in the RASopathies as a class to support a role for germline Ras/MAPK activation in ASDs. We examined the association of autism traits with NF1, NS, CS and CFC, comparing affected probands with unaffected sibling controls and subjects with idiopathic ASDs using the qualitative Social Communication Questionnaire (SCQ) and the quantitative Social Responsiveness Scale (SRS). Each of the four major RASopathies showed evidence for increased qualitative and quantitative autism traits compared with sibling controls. Further, each RASopathy exhibited a distinct distribution of quantitative social impairment. Levels of social responsiveness show some evidence of correlation between sibling pairs, and autism-like impairment showed a male bias similar to idiopathic ASDs. Higher prevalence and severity of autism traits in RASopathies compared to unaffected siblings suggests that dysregulation of Ras/MAPK signalling during development may be implicated in ASD risk. Evidence for sex bias and potential sibling correlation suggests that autism traits in the RASopathies share characteristics with autism traits in the general population and clinical ASD population and can shed light on idiopathic ASDs.

  11. Quantitative trait loci and candidate genes associated with starch pasting viscosity characteristics in cassava (Manihot esculenta Crantz).

    PubMed

    Thanyasiriwat, T; Sraphet, S; Whankaew, S; Boonseng, O; Bao, J; Lightfoot, D A; Tangphatsornruang, S; Triwitayakorn, K

    2014-01-01

    Starch pasting viscosity is an important quality trait in cassava (Manihot esculenta Crantz) cultivars. The aim here was to identify loci and candidate genes associated with the starch pasting viscosity. Quantitative trait loci (QTL) mapping for seven pasting viscosity parameters was carried out using 100 lines of an F1 mapping population from a cross between two cassava cultivars Huay Bong 60 and Hanatee. Starch samples were obtained from roots of cassava grown in 2008 and 2009 at Rayong, and in 2009 at Lop Buri province, Thailand. The traits showed continuous distribution among the F1 progeny with transgressive variation. Fifteen QTL were identified from mean trait data, with Logarithm of Odds (LOD) values from 2.77-13.01 and phenotype variations explained (PVE) from10.0-48.4%. In addition, 48 QTL were identified in separate environments. The LOD values ranged from 2.55-8.68 and explained 6.6-43.7% of phenotype variation. The loci were located on 19 linkage groups. The most important QTL for pasting temperature (PT) (qPT.1LG1) from mean trait values showed largest effect with highest LOD value (13.01) and PVE (48.4%). The QTL co-localised with PT and pasting time (PTi) loci that were identified in separate environments. Candidate genes were identified within the QTL peak regions. However, the major genes of interest, encoding the family of glycosyl or glucosyl transferases and hydrolases, were located at the periphery of QTL peaks. The loci identified could be effectively applied in breeding programmes to improve cassava starch quality. Alleles of candidate genes should be further studied in order to better understand their effects on starch quality traits. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

  12. Comparative analysis of quantitative efficiency evaluation methods for transportation networks.

    PubMed

    He, Yuxin; Qin, Jin; Hong, Jian

    2017-01-01

    An effective evaluation of transportation network efficiency could offer guidance for the optimal control of urban traffic. Based on the introduction and related mathematical analysis of three quantitative evaluation methods for transportation network efficiency, this paper compares the information measured by them, including network structure, traffic demand, travel choice behavior and other factors which affect network efficiency. Accordingly, the applicability of various evaluation methods is discussed. Through analyzing different transportation network examples it is obtained that Q-H method could reflect the influence of network structure, traffic demand and user route choice behavior on transportation network efficiency well. In addition, the transportation network efficiency measured by this method and Braess's Paradox can be explained with each other, which indicates a better evaluation of the real operation condition of transportation network. Through the analysis of the network efficiency calculated by Q-H method, it can also be drawn that a specific appropriate demand is existed to a given transportation network. Meanwhile, under the fixed demand, both the critical network structure that guarantees the stability and the basic operation of the network and a specific network structure contributing to the largest value of the transportation network efficiency can be identified.

  13. Validation of a major quantitative trait locus associated with host response to experimental infection with Porcine Reproductive and Respiratory Syndrome virus

    USDA-ARS?s Scientific Manuscript database

    Infectious diseases are costly to the swine industry and porcine reproductive and respiratory syndrome virus (PRRSV) is the most devastating. In earlier work, a quantitative trait locus associated with resistance/susceptibility to PRRSV was identified on Sus scrofa chromosome 4 (SSC4) using ~560 exp...

  14. A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.)

    PubMed Central

    2011-01-01

    Background A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS). Results Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in

  15. A consensus linkage map for molecular markers and quantitative trait loci associated with economically important traits in melon (Cucumis melo L.).

    PubMed

    Diaz, Aurora; Fergany, Mohamed; Formisano, Gelsomina; Ziarsolo, Peio; Blanca, José; Fei, Zhanjun; Staub, Jack E; Zalapa, Juan E; Cuevas, Hugo E; Dace, Gayle; Oliver, Marc; Boissot, Nathalie; Dogimont, Catherine; Pitrat, Michel; Hofstede, René; van Koert, Paul; Harel-Beja, Rotem; Tzuri, Galil; Portnoy, Vitaly; Cohen, Shahar; Schaffer, Arthur; Katzir, Nurit; Xu, Yong; Zhang, Haiying; Fukino, Nobuko; Matsumoto, Satoru; Garcia-Mas, Jordi; Monforte, Antonio J

    2011-07-28

    A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS). Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in a broad array of

  16. Linkage Analysis of a Model Quantitative Trait in Humans: Finger Ridge Count Shows Significant Multivariate Linkage to 5q14.1

    PubMed Central

    Medland, Sarah E; Loesch, Danuta Z; Mdzewski, Bogdan; Zhu, Gu; Montgomery, Grant W; Martin, Nicholas G

    2007-01-01

    The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers. PMID:17907812

  17. Influences of sampling effort on detected patterns and structuring processes of a Neotropical plant-hummingbird network.

    PubMed

    Vizentin-Bugoni, Jeferson; Maruyama, Pietro K; Debastiani, Vanderlei J; Duarte, L da S; Dalsgaard, Bo; Sazima, Marlies

    2016-01-01

    Virtually all empirical ecological interaction networks to some extent suffer from undersampling. However, how limitations imposed by sampling incompleteness affect our understanding of ecological networks is still poorly explored, which may hinder further advances in the field. Here, we use a plant-hummingbird network with unprecedented sampling effort (2716 h of focal observations) from the Atlantic Rainforest in Brazil, to investigate how sampling effort affects the description of network structure (i.e. widely used network metrics) and the relative importance of distinct processes (i.e. species abundances vs. traits) in determining the frequency of pairwise interactions. By dividing the network into time slices representing a gradient of sampling effort, we show that quantitative metrics, such as interaction evenness, specialization (H2 '), weighted nestedness (wNODF) and modularity (Q; QuanBiMo algorithm) were less biased by sampling incompleteness than binary metrics. Furthermore, the significance of some network metrics changed along the sampling effort gradient. Nevertheless, the higher importance of traits in structuring the network was apparent even with small sampling effort. Our results (i) warn against using very poorly sampled networks as this may bias our understanding of networks, both their patterns and structuring processes, (ii) encourage the use of quantitative metrics little influenced by sampling when performing spatio-temporal comparisons and (iii) indicate that in networks strongly constrained by species traits, such as plant-hummingbird networks, even small sampling is sufficient to detect their relative importance for the frequencies of interactions. Finally, we argue that similar effects of sampling are expected for other highly specialized subnetworks. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

  18. Quantitative trait locus mapping of deep rooting by linkage and association analysis in rice

    PubMed Central

    Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Wei, Haibin; Feng, Fangjun; Wang, Pei; Xia, Hui; Li, Tiemei; Luo, Lijun

    2015-01-01

    Deep rooting is a very important trait for plants’ drought avoidance, and it is usually represented by the ratio of deep rooting (RDR). Three sets of rice populations were used to determine the genetic base for RDR. A linkage mapping population with 180 recombinant inbred lines and an association mapping population containing 237 rice varieties were used to identify genes linked to RDR. Six quantitative trait loci (QTLs) of RDR were identified as being located on chromosomes 1, 2, 4, 7, and 10. Using 1 019 883 single-nucleotide polymorphisms (SNPs), a genome-wide association study of the RDR was performed. Forty-eight significant SNPs of the RDR were identified and formed a clear peak on the short arm of chromosome 1 in a Manhattan plot. Compared with the shallow-rooting group and the whole collection, the deep-rooting group had selective sweep regions on chromosomes 1 and 2, especially in the major QTL region on chromosome 2. Seven of the nine candidate SNPs identified by association mapping were verified in two RDR extreme groups. The findings from this study will be beneficial to rice drought-resistance research and breeding. PMID:26022253

  19. Mapping quantitative trait loci controlling early growth in a (longleaf pine × slash pine) × slash pine BC1 family

    Treesearch

    C. Weng; Thomas L. Kubisiak; C. Dana Nelson; M. Stine

    2002-01-01

    Random amplified polymorphic DNA (RAPD) markers were employed to map the genome and quantitative trait loci controlling the early growth of a pine hybrid F1 tree (Pinus palustris Mill. × P. elliottii Engl.) and a recurrent slash pine tree (P. ellottii Engl.) in a (longleaf pine × slash pine...

  20. A quantitative trait locus mixture model that avoids spurious LOD score peaks.

    PubMed Central

    Feenstra, Bjarke; Skovgaard, Ib M

    2004-01-01

    In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented. PMID:15238544

  1. Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics

    PubMed Central

    Bennett, Eric J.; Rush, John; Gygi, Steven P.; Harper, J. Wade

    2010-01-01

    Dynamic reorganization of signaling systems frequently accompany pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex Absolute Quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules while only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. PMID:21145461

  2. Multiple Quantitative Trait Loci Influence the Shape of a Male-Specific Genital Structure in Drosophila melanogaster

    PubMed Central

    McNeil, Casey L.; Bain, Clint L.; Macdonald, Stuart J.

    2011-01-01

    The observation that male genitalia diverge more rapidly than other morphological traits during evolution is taxonomically widespread and likely due to some form of sexual selection. One way to elucidate the evolutionary forces acting on these traits is to detail the genetic architecture of variation both within and between species, a program of research that is considerably more tractable in a model system. Drosophila melanogaster and its sibling species, D. simulans, D. mauritiana, and D. sechellia, are morphologically distinguishable only by the shape of the posterior lobe, a male-specific elaboration of the genital arch. We extend earlier studies identifying quantitative trait loci (QTL) responsible for lobe divergence across species and report the first genetic dissection of lobe shape variation within a species. Using an advanced intercross mapping design, we identify three autosomal QTL contributing to the difference in lobe shape between a pair of D. melanogaster inbred lines. The QTL each contribute 4.6–10.7% to shape variation, and two show a significant epistatic interaction. Interestingly, these intraspecific QTL map to the same locations as interspecific lobe QTL, implying some shared genetic control of the trait within and between species. As a first step toward a mechanistic understanding of natural lobe shape variation, we find an association between our QTL data and a set of genes that show sex-biased expression in the developing genital imaginal disc (the precursor of the adult genitalia). These genes are good candidates to harbor naturally segregating polymorphisms contributing to posterior lobe shape. PMID:22384345

  3. Quantitative Trait Loci for Light Sensitivity, Body Weight, Body Size, and Morphological Eye Parameters in the Bumblebee, Bombus terrestris.

    PubMed

    Maebe, Kevin; Meeus, Ivan; De Riek, Jan; Smagghe, Guy

    2015-01-01

    Bumblebees such as Bombus terrestris are essential pollinators in natural and managed ecosystems. In addition, this species is intensively used in agriculture for its pollination services, for instance in tomato and pepper greenhouses. Here we performed a quantitative trait loci (QTL) analysis on B. terrestris using 136 microsatellite DNA markers to identify genes linked with 20 traits including light sensitivity, body size and mass, and eye and hind leg measures. By composite interval mapping (IM), we found 83 and 34 suggestive QTLs for 19 of the 20 traits at the linkage group wide significance levels of p = 0.05 and 0.01, respectively. Furthermore, we also found five significant QTLs at the genome wide significant level of p = 0.05. Individual QTLs accounted for 7.5-53.3% of the phenotypic variation. For 15 traits, at least one QTL was confirmed with multiple QTL model mapping. Multivariate principal components analysis confirmed 11 univariate suggestive QTLs but revealed three suggestive QTLs not identified by the individual traits. We also identified several candidate genes linked with light sensitivity, in particular the Phosrestin-1-like gene is a primary candidate for its phototransduction function. In conclusion, we believe that the suggestive and significant QTLs, and markers identified here, can be of use in marker-assisted breeding to improve selection towards light sensitive bumblebees, and thus also the pollination service of bumblebees.

  4. [The study of tomato fruit weight quantitative trait locus and its application in genetics teaching].

    PubMed

    Wang, Hai-yan

    2015-08-01

    The classical research cases, which have greatly promoted the development of genetics in history, can be combined with the content of courses in genetics teaching to train students' ability of scientific thinking and genetic analysis. The localization and clone of gene controlling tomato fruit weight is a pioneer work in quantitative trait locus (QTL) studies and represents a complete process of QTL research in plants. Application of this integrated case in genetics teaching, which showed a wonderful process of scientific discovery and the fascination of genetic research, has inspired students' interest in genetics and achieved a good teaching effect.

  5. Quantitative trait loci (QTLs) for water use and crop production traits co-locate with major QTL for tolerance to water deficit in a fine-mapping population of pearl millet (Pennisetum glaucum L. R.Br.).

    PubMed

    Tharanya, Murugesan; Kholova, Jana; Sivasakthi, Kaliamoorthy; Seghal, Deepmala; Hash, Charles Tom; Raj, Basker; Srivastava, Rakesh Kumar; Baddam, Rekha; Thirunalasundari, Thiyagarajan; Yadav, Rattan; Vadez, Vincent

    2018-04-21

    Four genetic regions associated with water use traits, measured at different levels of plant organization, and with agronomic traits were identified within a previously reported region for terminal water deficit adaptation on linkage group 2. Close linkages between these traits showed the value of phenotyping both for agronomic and secondary traits to better understand plant productive processes. Water saving traits are critical for water stress adaptation of pearl millet, whereas maximizing water use is key to the absence of stress. This research aimed at demonstrating the close relationship between traits measured at different levels of plant organization, some putatively involved in water stress adaptation, and those responsible for agronomic performance. A fine-mapping population of pearl millet, segregating for a previously identified quantitative trait locus (QTL) for adaptation to terminal drought stress on LG02, was phenotyped for traits at different levels of plant organization in different experimental environments (pot culture, high-throughput phenotyping platform, lysimeters, and field). The linkages among traits across the experimental systems were analysed using principal component analysis and QTL co-localization approach. Four regions within the LG02-QTL were found and revealed substantial co-mapping of water use and agronomic traits. These regions, identified across experimental systems, provided genetic evidence of the tight linkages between traits phenotyped at a lower level of plant organization and agronomic traits assessed in the field, therefore deepening our understanding of complex traits and then benefiting both geneticists and breeders. In short: (1) under no/mild stress conditions, increasing biomass and tiller production increased water use and eventually yield; (2) under severe stress conditions, water savings at vegetative stage, from lower plant vigour and fewer tillers in that population, led to more water available during grain

  6. A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa).

    PubMed

    Liu, Shiwei; Liu, Yihui; Zhao, Jiawei; Cai, Shitao; Qian, Hongmei; Zuo, Kaijing; Zhao, Lingxia; Zhang, Lida

    2017-04-01

    Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  7. Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits*

    PubMed Central

    Sharma, Amitabh; Gulbahce, Natali; Pevzner, Samuel J.; Menche, Jörg; Ladenvall, Claes; Folkersen, Lasse; Eriksson, Per; Orho-Melander, Marju; Barabási, Albert-László

    2013-01-01

    Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits. We apply a prediction pipeline incorporating interactome, co-expression, and comorbidity data to Global Lipids Genetics Consortium (GLGC) GWAS for four traits of interest, identifying phenotypically coherent modules. These modules provide insights regarding gene involvement in complex phenotypes with multiple susceptibility alleles and low effect sizes. To experimentally test our predictions, we selected four candidate genes and genotyped representative SNPs in the Malmö Diet and Cancer Cardiovascular Cohort. We found significant associations with LDL-C and total-cholesterol levels for a synonymous SNP (rs234706) in the cystathionine beta-synthase (CBS) gene (p = 1 × 10−5 and adjusted-p = 0.013, respectively). Further, liver samples taken from 206 patients revealed that patients with the minor allele of rs234706 had significant dysregulation of CBS (p = 0.04). Despite the known biological role of CBS in lipid metabolism, SNPs within the locus have not yet been identified in GWAS of lipoprotein traits. Thus, the GWAS-based Comorbidity Module (GCM) approach identifies candidate genes missed by GWAS studies, serving as a broadly applicable tool for the investigation of other complex disease phenotypes. PMID:23882023

  8. Quantitative trait loci from the host genetic background modulate the durability of a resistance gene: a rational basis for sustainable resistance breeding in plants.

    PubMed

    Quenouille, J; Paulhiac, E; Moury, B; Palloix, A

    2014-06-01

    The combination of major resistance genes with quantitative resistance factors is hypothesized as a promising breeding strategy to preserve the durability of resistant cultivar, as recently observed in different pathosystems. Using the pepper (Capsicum annuum)/Potato virus Y (PVY, genus Potyvirus) pathosystem, we aimed at identifying plant genetic factors directly affecting the frequency of virus adaptation to the major resistance gene pvr2(3) and at comparing them with genetic factors affecting quantitative resistance. The resistance breakdown frequency was a highly heritable trait (h(2)=0.87). Four loci including additive quantitative trait loci (QTLs) and epistatic interactions explained together 70% of the variance of pvr2(3) breakdown frequency. Three of the four QTLs controlling pvr2(3) breakdown frequency were also involved in quantitative resistance, strongly suggesting that QTLs controlling quantitative resistance have a pleiotropic effect on the durability of the major resistance gene. With the first mapping of QTLs directly affecting resistance durability, this study provides a rationale for sustainable resistance breeding. Surprisingly, a genetic trade-off was observed between the durability of PVY resistance controlled by pvr2(3) and the spectrum of the resistance against different potyviruses. This trade-off seemed to have been resolved by the combination of minor-effect durability QTLs under long-term farmer selection.

  9. Comparative analysis of quantitative efficiency evaluation methods for transportation networks

    PubMed Central

    He, Yuxin; Hong, Jian

    2017-01-01

    An effective evaluation of transportation network efficiency could offer guidance for the optimal control of urban traffic. Based on the introduction and related mathematical analysis of three quantitative evaluation methods for transportation network efficiency, this paper compares the information measured by them, including network structure, traffic demand, travel choice behavior and other factors which affect network efficiency. Accordingly, the applicability of various evaluation methods is discussed. Through analyzing different transportation network examples it is obtained that Q-H method could reflect the influence of network structure, traffic demand and user route choice behavior on transportation network efficiency well. In addition, the transportation network efficiency measured by this method and Braess’s Paradox can be explained with each other, which indicates a better evaluation of the real operation condition of transportation network. Through the analysis of the network efficiency calculated by Q-H method, it can also be drawn that a specific appropriate demand is existed to a given transportation network. Meanwhile, under the fixed demand, both the critical network structure that guarantees the stability and the basic operation of the network and a specific network structure contributing to the largest value of the transportation network efficiency can be identified. PMID:28399165

  10. Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors.

    PubMed

    Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

    2007-01-01

    We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.

  11. Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the α subunit of protein kinase CK2

    PubMed Central

    Takahashi, Yuji; Shomura, Ayahiko; Sasaki, Takuji; Yano, Masahiro

    2001-01-01

    Hd6 is a quantitative trait locus involved in rice photoperiod sensitivity. It was detected in backcross progeny derived from a cross between the japonica variety Nipponbare and the indica variety Kasalath. To isolate a gene at Hd6, we used a large segregating population for the high-resolution and fine-scale mapping of Hd6 and constructed genomic clone contigs around the Hd6 region. Linkage analysis with P1-derived artificial chromosome clone-derived DNA markers delimited Hd6 to a 26.4-kb genomic region. We identified a gene encoding the α subunit of protein kinase CK2 (CK2α) in this region. The Nipponbare allele of CK2α contains a premature stop codon, and the resulting truncated product is undoubtedly nonfunctional. Genetic complementation analysis revealed that the Kasalath allele of CK2α increases days-to-heading. Map-based cloning with advanced backcross progeny enabled us to identify a gene underlying a quantitative trait locus even though it exhibited a relatively small effect on the phenotype. PMID:11416158

  12. Quantitative Autism Traits in First Degree Relatives: Evidence for the Broader Autism Phenotype in Fathers, but Not in Mothers and Siblings

    ERIC Educational Resources Information Center

    De la Marche, Wouter; Noens, Ilse; Luts, Jan; Scholte, Evert; Van Huffel, Sabine; Steyaert, Jean

    2012-01-01

    Autism spectrum disorder (ASD) symptoms are present in unaffected relatives and individuals from the general population. Results are inconclusive, however, on whether unaffected relatives have higher levels of quantitative autism traits (QAT) or not. This might be due to differences in research populations, because behavioral data and molecular…

  13. Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

    NASA Astrophysics Data System (ADS)

    Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

    2017-03-01

    Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

  14. Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.

    PubMed

    Covarrubias-Pazaran, Giovanny

    2016-01-01

    Most traits of agronomic importance are quantitative in nature, and genetic markers have been used for decades to dissect such traits. Recently, genomic selection has earned attention as next generation sequencing technologies became feasible for major and minor crops. Mixed models have become a key tool for fitting genomic selection models, but most current genomic selection software can only include a single variance component other than the error, making hybrid prediction using additive, dominance and epistatic effects unfeasible for species displaying heterotic effects. Moreover, Likelihood-based software for fitting mixed models with multiple random effects that allows the user to specify the variance-covariance structure of random effects has not been fully exploited. A new open-source R package called sommer is presented to facilitate the use of mixed models for genomic selection and hybrid prediction purposes using more than one variance component and allowing specification of covariance structures. The use of sommer for genomic prediction is demonstrated through several examples using maize and wheat genotypic and phenotypic data. At its core, the program contains three algorithms for estimating variance components: Average information (AI), Expectation-Maximization (EM) and Efficient Mixed Model Association (EMMA). Kernels for calculating the additive, dominance and epistatic relationship matrices are included, along with other useful functions for genomic analysis. Results from sommer were comparable to other software, but the analysis was faster than Bayesian counterparts in the magnitude of hours to days. In addition, ability to deal with missing data, combined with greater flexibility and speed than other REML-based software was achieved by putting together some of the most efficient algorithms to fit models in a gentle environment such as R.

  15. Bone Mineral Density Variation in Men is influenced by Sex-Specific and Non Sex-Specific Quantitative Trait Loci

    PubMed Central

    Peacock, Munro; Koller, Daniel L.; Lai, Dongbing; Hui, Siu; Foroud, Tatiana; Econs, Michael J.

    2009-01-01

    Introduction A major predictor of age-related osteoporotic fracture is peak areal bone mineral density (aBMD) which is a highly heritable trait. However, few linkage and association studies have been performed in men to identify the genes contributing to normal variation in aBMD. The aim of this study was to perform a genome wide scan in healthy men to identify quantitative trait loci (QTL) that were significantly linked to aBMD and to test whether any of these might be sex-specific. Methods aBMD at the spine and hip were measured in 515 pairs of brothers, aged 18-61 (405 white pairs, 110 black pairs). Linkage analysis in the brother sample was compared with results in a previously published sample of 774 sister pairs to identify sex-specific quantitative trait loci (QTL). Results A genome wide scan identified significant QTL (LOD>3.6) for aBMD on chromosomes 4q21 (hip), 7q34 (spine), 14q32 (hip), 19p13 (hip), 21q21 (hip), and 22q13 (hip). Analysis suggested that the QTL on chromosome 7q34, 14q32, and 21q21 were male-specific whereas the others were not sex-specific. Conclusions This study demonstrates that six QTL were significantly linked with aBMD in men. One was linked to spine and five were linked to hip. When compared to published data in women from the same geographical region, the QTL on chromosomes 7, 14 and 21 were male-specific. The occurrence of sex-specific genes in humans for aBMD has important implications for the pathogenesis and treatment of osteoporosis. PMID:19427925

  16. Oxidative stress survival in a clinical Saccharomyces cerevisiae isolate is influenced by a major quantitative trait nucleotide.

    PubMed

    Diezmann, Stephanie; Dietrich, Fred S

    2011-07-01

    One of the major challenges in characterizing eukaryotic genetic diversity is the mapping of phenotypes that are the cumulative effect of multiple alleles. We have investigated tolerance of oxidative stress in the yeast Saccharomyces cerevisiae, a trait showing phenotypic variation in the population. Initial crosses identified that this is a quantitative trait. Microorganisms experience oxidative stress in many environments, including during infection of higher eukaryotes. Natural variation in oxidative stress tolerance is an important aspect of response to oxidative stress exerted by the human immune system and an important trait in microbial pathogens. A clinical isolate of the usually benign yeast S. cerevisiae was found to survive oxidative stress significantly better than the laboratory strain. We investigated the genetic basis of increased peroxide survival by crossing those strains, phenotyping 1500 segregants, and genotyping of high-survival segregants by hybridization of bulk and single segregant DNA to microarrays. This effort has led to the identification of an allele of the transcription factor Rds2 as contributing to stress response. Rds2 has not previously been associated with the survival of oxidative stress. The identification of its role in the oxidative stress response here is an example of a specific trait that appears to be beneficial to Saccharomyces cerevisiae when growing as a pathogen. Understanding the role of this fungal-specific transcription factor in pathogenicity will be important in deciphering how fungi infect and colonize the human host and could eventually lead to a novel drug target.

  17. Quantitative Trait Locus Analysis for Deep-Sowing Germination Ability in the Maize IBM Syn10 DH Population

    PubMed Central

    Liu, Hongjun; Zhang, Lin; Wang, Jiechen; Li, Changsheng; Zeng, Xing; Xie, Shupeng; Zhang, Yongzhong; Liu, Sisi; Hu, Songlin; Wang, Jianhua; Lee, Michael; Lübberstedt, Thomas; Zhao, Guangwu

    2017-01-01

    Deep-sowing is an effective measure to ensure seeds absorbing water from deep soil layer and emerging normally in arid and semiarid regions. However, existing varieties demonstrate poor germination ability in deep soil layer and some key quantitative trait loci (QTL) or genes related to deep-sowing germination ability remain to be identified and analyzed. In this study, a high-resolution genetic map based on 280 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population which comprised 6618 bin markers was used for the QTL analysis of deep-sowing germination related traits. The results showed significant differences in germination related traits under deep-sowing condition (12.5 cm) and standard-germination condition (2 cm) between two parental lines. In total, 8, 11, 13, 15, and 18 QTL for germination rate, seedling length, mesocotyl length, plumule length, and coleoptile length were detected for the two sowing conditions, respectively. These QTL explained 2.51–7.8% of the phenotypic variance with LOD scores ranging from 2.52 to 7.13. Additionally, 32 overlapping QTL formed 11 QTL clusters on all chromosomes except for chromosome 8, indicating the minor effect genes have a pleiotropic role in regulating various traits. Furthermore, we identified six candidate genes related to deep-sowing germination ability, which were co-located in the cluster regions. The results provide a basis for molecular marker assisted breeding and functional study in deep-sowing germination ability of maize. PMID:28588594

  18. Quantitative Trait Locus Analysis for Deep-Sowing Germination Ability in the Maize IBM Syn10 DH Population.

    PubMed

    Liu, Hongjun; Zhang, Lin; Wang, Jiechen; Li, Changsheng; Zeng, Xing; Xie, Shupeng; Zhang, Yongzhong; Liu, Sisi; Hu, Songlin; Wang, Jianhua; Lee, Michael; Lübberstedt, Thomas; Zhao, Guangwu

    2017-01-01

    Deep-sowing is an effective measure to ensure seeds absorbing water from deep soil layer and emerging normally in arid and semiarid regions. However, existing varieties demonstrate poor germination ability in deep soil layer and some key quantitative trait loci (QTL) or genes related to deep-sowing germination ability remain to be identified and analyzed. In this study, a high-resolution genetic map based on 280 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population which comprised 6618 bin markers was used for the QTL analysis of deep-sowing germination related traits. The results showed significant differences in germination related traits under deep-sowing condition (12.5 cm) and standard-germination condition (2 cm) between two parental lines. In total, 8, 11, 13, 15, and 18 QTL for germination rate, seedling length, mesocotyl length, plumule length, and coleoptile length were detected for the two sowing conditions, respectively. These QTL explained 2.51-7.8% of the phenotypic variance with LOD scores ranging from 2.52 to 7.13. Additionally, 32 overlapping QTL formed 11 QTL clusters on all chromosomes except for chromosome 8, indicating the minor effect genes have a pleiotropic role in regulating various traits. Furthermore, we identified six candidate genes related to deep-sowing germination ability, which were co-located in the cluster regions. The results provide a basis for molecular marker assisted breeding and functional study in deep-sowing germination ability of maize.

  19. Identification of Quantitative Trait Loci Controlling Root and Shoot Traits Associated with Drought Tolerance in a Lentil (Lens culinaris Medik.) Recombinant Inbred Line Population

    PubMed Central

    Idrissi, Omar; Udupa, Sripada M.; De Keyser, Ellen; McGee, Rebecca J.; Coyne, Clarice J.; Saha, Gopesh C.; Muehlbauer, Fred J.; Van Damme, Patrick; De Riek, Jan

    2016-01-01

    Drought is one of the major abiotic stresses limiting lentil productivity in rainfed production systems. Specific rooting patterns can be associated with drought avoidance mechanisms that can be used in lentil breeding programs. In all, 252 co-dominant and dominant markers were used for Quantitative Trait Loci (QTL) analysis on 132 lentil recombinant inbred lines based on greenhouse experiments for root and shoot traits during two seasons under progressive drought-stressed conditions. Eighteen QTLs controlling a total of 14 root and shoot traits were identified. A QTL-hotspot genomic region related to a number of root and shoot characteristics associated with drought tolerance such as dry root biomass, root surface area, lateral root number, dry shoot biomass and shoot length was identified. Interestingly, a QTL (QRSratioIX-2.30) related to root-shoot ratio, an important trait for drought avoidance, explaining the highest phenotypic variance of 27.6 and 28.9% for the two consecutive seasons, respectively, was detected. This QTL was closed to the co-dominant SNP marker TP6337 and also flanked by the two SNP TP518 and TP1280. An important QTL (QLRNIII-98.64) related to lateral root number was found close to TP3371 and flanked by TP5093 and TP6072 SNP markers. Also, a QTL (QSRLIV-61.63) associated with specific root length was identified close to TP1873 and flanked by F7XEM6b SRAP marker and TP1035 SNP marker. These two QTLs were detected in both seasons. Our results could be used for marker-assisted selection in lentil breeding programs targeting root and shoot characteristics conferring drought avoidance as an efficient alternative to slow and labor-intensive conventional breeding methods. PMID:27602034

  20. Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii

    DOE PAGES

    Milano, Elizabeth R.; Payne, Courtney E.; Wolfrum, Edward J.; ...

    2018-02-03

    Biofuels derived from lignocellulosic plant material are an important component of current renewable energy strategies. Improvement efforts in biofuel feedstock crops have been primarily focused on increasing biomass yield with less consideration for tissue quality or composition. Four primary components found in the plant cell wall contribute to the overall quality of plant tissue and conversion characteristics, cellulose and hemicellulose polysaccharides are the primary targets for fuel conversion, while lignin and ash provide structure and defense. We explore the genetic architecture of tissue characteristics using a quantitative trait loci (QTL) mapping approach in Panicum hallii, a model lignocellulosic grass system.more » Diversity in the mapping population was generated by crossing xeric and mesic varietals, comparative to northern upland and southern lowland ecotypes in switchgrass. We use near-infrared spectroscopy with a primary analytical method to create a P. hallii specific calibration model to quickly quantify cell wall components. Ash, lignin, glucan, and xylan comprise 68% of total dry biomass in P. hallii: comparable to other feedstocks. We identified 14 QTL and one epistatic interaction across these four cell wall traits and found almost half of the QTL to localize to a single linkage group. Panicum hallii serves as the genomic model for its close relative and emerging biofuel crop, switchgrass (P. virgatum). We used high throughput phenotyping to map genomic regions that impact natural variation in leaf tissue composition. Understanding the genetic architecture of tissue traits in a tractable model grass system will lead to a better understanding of cell wall structure as well as provide genomic resources for bioenergy crop breeding programs.« less

  1. Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii

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

    Milano, Elizabeth R.; Payne, Courtney E.; Wolfrum, Edward J.

    Biofuels derived from lignocellulosic plant material are an important component of current renewable energy strategies. Improvement efforts in biofuel feedstock crops have been primarily focused on increasing biomass yield with less consideration for tissue quality or composition. Four primary components found in the plant cell wall contribute to the overall quality of plant tissue and conversion characteristics, cellulose and hemicellulose polysaccharides are the primary targets for fuel conversion, while lignin and ash provide structure and defense. We explore the genetic architecture of tissue characteristics using a quantitative trait loci (QTL) mapping approach in Panicum hallii, a model lignocellulosic grass system.more » Diversity in the mapping population was generated by crossing xeric and mesic varietals, comparative to northern upland and southern lowland ecotypes in switchgrass. We use near-infrared spectroscopy with a primary analytical method to create a P. hallii specific calibration model to quickly quantify cell wall components. Ash, lignin, glucan, and xylan comprise 68% of total dry biomass in P. hallii: comparable to other feedstocks. We identified 14 QTL and one epistatic interaction across these four cell wall traits and found almost half of the QTL to localize to a single linkage group. Panicum hallii serves as the genomic model for its close relative and emerging biofuel crop, switchgrass (P. virgatum). We used high throughput phenotyping to map genomic regions that impact natural variation in leaf tissue composition. Understanding the genetic architecture of tissue traits in a tractable model grass system will lead to a better understanding of cell wall structure as well as provide genomic resources for bioenergy crop breeding programs.« less

  2. Testing natural selection vs. genetic drift in phenotypic evolution using quantitative trait locus data.

    PubMed Central

    Orr, H A

    1998-01-01

    Evolutionary biologists have long sought a way to determine whether a phenotypic difference between two taxa was caused by natural selection or random genetic drift. Here I argue that data from quantitative trait locus (QTL) analyses can be used to test the null hypothesis of neutral phenotypic evolution. I propose a sign test that compares the observed number of plus and minus alleles in the "high line" with that expected under neutrality, conditioning on the known phenotypic difference between the taxa. Rejection of the null hypothesis implies a role for directional natural selection. This test is applicable to any character in any organism in which QTL analysis can be performed. PMID:9691061

  3. Quantitative traits for the tail suspension test: automation, optimization, and BXD RI mapping.

    PubMed

    Lad, Heena V; Liu, Lin; Payá-Cano, José L; Fernandes, Cathy; Schalkwyk, Leonard C

    2007-07-01

    Immobility in the tail suspension test (TST) is considered a model of despair in a stressful situation, and acute treatment with antidepressants reduces immobility. Inbred strains of mouse exhibit widely differing baseline levels of immobility in the TST and several quantitative trait loci (QTLs) have been nominated. The labor of manual scoring and various scoring criteria make obtaining robust data and comparisons across different laboratories problematic. Several studies have validated strain gauge and video analysis methods by comparison with manual scoring. We set out to find objective criteria for automated scoring parameters that maximize the biological information obtained, using a video tracking system on tapes of tail suspension tests of 24 lines of the BXD recombinant inbred panel and the progenitor strains C57BL/6J and DBA/2J. The maximum genetic effect size is captured using the highest time resolution and a low mobility threshold. Dissecting the trait further by comparing genetic association of multiple measures reveals good evidence for loci involved in immobility on chromosomes 4 and 15. These are best seen when using a high threshold for immobility, despite the overall better heritability at the lower threshold. A second trial of the test has greater duration of immobility and a completely different genetic profile. Frequency of mobility is also an independent phenotype, with a distal chromosome 1 locus.

  4. Comparative quantitative trait loci for silique length and seed weight in Brassica napus.

    PubMed

    Fu, Ying; Wei, Dayong; Dong, Hongli; He, Yajun; Cui, Yixin; Mei, Jiaqin; Wan, Huafang; Li, Jiana; Snowdon, Rod; Friedt, Wolfgang; Li, Xiaorong; Qian, Wei

    2015-09-23

    Silique length (SL) and seed weight (SW) are important yield-associated traits in rapeseed (Brassica napus). Although many quantitative trait loci (QTL) for SL and SW have been identified in B. napus, comparative analysis for those QTL is seldom performed. In the present study, 20 and 21 QTL for SL and SW were identified in doubled haploid (DH) and DH-derived reconstructed F2 populations in rapeseed, explaining 55.1-74.3% and 24.4-62.9% of the phenotypic variation across three years, respectively. Of which, 17 QTL with partially or completely overlapped confidence interval on chromosome A09, were homologous with two overlapped QTL on chromosome C08 by aligning QTL confidence intervals with the reference genomes of Brassica crops. By high density selective genotyping of DH lines with extreme phenotypes, using a Brassica single-nucleotide polymorphism (SNP) array, the QTL on chromosome A09 was narrowed, and aligned into 1.14-Mb region from 30.84 to 31.98 Mb on chromosome R09 of B. rapa and 1.05-Mb region from 27.21 to 28.26 Mb on chromosome A09 of B. napus. The alignment of QTL with Brassica reference genomes revealed homologous QTL on A09 and C08 for SL. The narrowed QTL region provides clues for gene cloning and breeding cultivars by marker-assisted selection.

  5. Quantitative Assessment of Transportation Network Vulnerability with Dynamic Traffic Simulation Methods

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

    Shekar, Venkateswaran; Fiondella, Lance; Chatterjee, Samrat

    Transportation networks are critical to the social and economic function of nations. Given the continuing increase in the populations of cities throughout the world, the criticality of transportation infrastructure is expected to increase. Thus, it is ever more important to mitigate congestion as well as to assess the impact disruptions would have on individuals who depend on transportation for their work and livelihood. Moreover, several government organizations are responsible for ensuring transportation networks are available despite the constant threat of natural disasters and terrorist activities. Most of the previous transportation network vulnerability research has been performed in the context ofmore » static traffic models, many of which are formulated as traditional optimization problems. However, transportation networks are dynamic because their usage varies over time. Thus, more appropriate methods to characterize the vulnerability of transportation networks should consider their dynamic properties. This paper presents a quantitative approach to assess the vulnerability of a transportation network to disruptions with methods from traffic simulation. Our approach can prioritize the critical links over time and is generalizable to the case where both link and node disruptions are of concern. We illustrate the approach through a series of examples. Our results demonstrate that the approach provides quantitative insight into the time varying criticality of links. Such an approach could be used as the objective function of less traditional optimization methods that use simulation and other techniques to evaluate the relative utility of a particular network defense to reduce vulnerability and increase resilience.« less

  6. Genetic dissection of milk yield traits and mastitis resistance quantitative trait loci on chromosome 20 in dairy cattle.

    PubMed

    Kadri, Naveen K; Guldbrandtsen, Bernt; Lund, Mogens S; Sahana, Goutam

    2015-12-01

    Intense selection to increase milk yield has had negative consequences for mastitis incidence in dairy cattle. Due to low heritability of mastitis resistance and an unfavorable genetic correlation with milk yield, a reduction in mastitis through traditional breeding has been difficult to achieve. Here, we examined quantitative trait loci (QTL) that segregate for clinical mastitis and milk yield on Bos taurus autosome 20 (BTA20) to determine whether both traits are affected by a single polymorphism (pleiotropy) or by multiple closely linked polymorphisms. In the latter but not the former situation, undesirable genetic correlation could potentially be broken by selecting animals that have favorable variants for both traits. First, we performed a within-breed association study using a haplotype-based method in Danish Holstein cattle (HOL). Next, we analyzed Nordic Red dairy cattle (RDC) and Danish Jersey cattle (JER) with the goal of determining whether these QTL identified in Holsteins were segregating across breeds. Genotypes for 12,566 animals (5,966 HOL, 5,458 RDC, and 1,142 JER) were determined by using the Illumina Bovine SNP50 BeadChip (50K; Illumina, San Diego, CA), which identifies 1,568 single nucleotide polymorphisms on BTA20. Data were combined, phased, and clustered into haplotype states, followed by within- and across-breed haplotype-based association analyses using a linear mixed model. Association signals for both clinical mastitis and milk yield peaked in the 26- to 40-Mb region on BTA20 in HOL. Single-variant association analyses were carried out in the QTL region using whole sequence level variants imputed from references of 2,036 HD genotypes (BovineHD BeadChip; Illumina) and 242 whole-genome sequences. The milk QTL were also segregating in RDC and JER on the BTA20-targeted region; however, an indication of differences in the causal factor(s) was observed across breeds. A previously reported F279Y mutation (rs385640152) within the growth hormone

  7. Dynamics of cullin-RING ubiquitin ligase network revealed by systematic quantitative proteomics.

    PubMed

    Bennett, Eric J; Rush, John; Gygi, Steven P; Harper, J Wade

    2010-12-10

    Dynamic reorganization of signaling systems frequently accompanies pathway perturbations, yet quantitative studies of network remodeling by pathway stimuli are lacking. Here, we report the development of a quantitative proteomics platform centered on multiplex absolute quantification (AQUA) technology to elucidate the architecture of the cullin-RING ubiquitin ligase (CRL) network and to evaluate current models of dynamic CRL remodeling. Current models suggest that CRL complexes are controlled by cycles of CRL deneddylation and CAND1 binding. Contrary to expectations, acute CRL inhibition with MLN4924, an inhibitor of the NEDD8-activating enzyme, does not result in a global reorganization of the CRL network. Examination of CRL complex stoichiometry reveals that, independent of cullin neddylation, a large fraction of cullins are assembled with adaptor modules, whereas only a small fraction are associated with CAND1. These studies suggest an alternative model of CRL dynamicity where the abundance of adaptor modules, rather than cycles of neddylation and CAND1 binding, drives CRL network organization. Copyright © 2010 Elsevier Inc. All rights reserved.

  8. Quantitative genetic analysis of agronomic and morphological traits in sorghum, Sorghum bicolor

    PubMed Central

    Mohammed, Riyazaddin; Are, Ashok K.; Bhavanasi, Ramaiah; Munghate, Rajendra S.; Kavi Kishor, Polavarapu B.; Sharma, Hari C.

    2015-01-01

    The productivity in sorghum is low, owing to various biotic and abiotic constraints. Combining insect resistance with desirable agronomic and morphological traits is important to increase sorghum productivity. Therefore, it is important to understand the variability for various agronomic traits, their heritabilities and nature of gene action to develop appropriate strategies for crop improvement. Therefore, a full diallel set of 10 parents and their 90 crosses including reciprocals were evaluated in replicated trials during the 2013–14 rainy and postrainy seasons. The crosses between the parents with early- and late-flowering flowered early, indicating dominance of earliness for anthesis in the test material used. Association between the shoot fly resistance, morphological, and agronomic traits suggested complex interactions between shoot fly resistance and morphological traits. Significance of the mean sum of squares for GCA (general combining ability) and SCA (specific combining ability) of all the studied traits suggested the importance of both additive and non-additive components in inheritance of these traits. The GCA/SCA, and the predictability ratios indicated predominance of additive gene effects for majority of the traits studied. High broad-sense and narrow-sense heritability estimates were observed for most of the morphological and agronomic traits. The significance of reciprocal combining ability effects for days to 50% flowering, plant height and 100 seed weight, suggested maternal effects for inheritance of these traits. Plant height and grain yield across seasons, days to 50% flowering, inflorescence exsertion, and panicle shape in the postrainy season showed greater specific combining ability variance, indicating the predominance of non-additive type of gene action/epistatic interactions in controlling the expression of these traits. Additive gene action in the rainy season, and dominance in the postrainy season for days to 50% flowering and plant

  9. Quantitative trait locus mapping of deep rooting by linkage and association analysis in rice.

    PubMed

    Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Wei, Haibin; Feng, Fangjun; Wang, Pei; Xia, Hui; Li, Tiemei; Luo, Lijun

    2015-08-01

    Deep rooting is a very important trait for plants' drought avoidance, and it is usually represented by the ratio of deep rooting (RDR). Three sets of rice populations were used to determine the genetic base for RDR. A linkage mapping population with 180 recombinant inbred lines and an association mapping population containing 237 rice varieties were used to identify genes linked to RDR. Six quantitative trait loci (QTLs) of RDR were identified as being located on chromosomes 1, 2, 4, 7, and 10. Using 1 019 883 single-nucleotide polymorphisms (SNPs), a genome-wide association study of the RDR was performed. Forty-eight significant SNPs of the RDR were identified and formed a clear peak on the short arm of chromosome 1 in a Manhattan plot. Compared with the shallow-rooting group and the whole collection, the deep-rooting group had selective sweep regions on chromosomes 1 and 2, especially in the major QTL region on chromosome 2. Seven of the nine candidate SNPs identified by association mapping were verified in two RDR extreme groups. The findings from this study will be beneficial to rice drought-resistance research and breeding. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  10. 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

  11. Mapping Quantitative Trait Loci (QTL) in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL.

    PubMed

    Cavanagh, Colin R; Jonas, Elisabeth; Hobbs, Matthew; Thomson, Peter C; Tammen, Imke; Raadsma, Herman W

    2010-09-16

    An (Awassi × Merino) × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL) for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1) and 3.5 (cohort 2) years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3), 15 significant (LOD ≥ 2), and 11 suggestive QTL (1.7 ≤ LOD < 2) were detected on eleven chromosomes. Regression analysis confirmed 28 of these QTL and an additional 17 suggestive (P < 0.1) and two significant (P < 0.05) QTL were identified using this method. QTL with pleiotropic effects for two or more tissues were identified on chromosomes 1, 6, 10, 14, 16 and 23. No tissue-specific QTL were identified.A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.

  12. A genome-wide linkage scan for quantitative trait loci underlying obesity related phenotypes in 434 Caucasian families.

    PubMed

    Zhao, Lan-Juan; Xiao, Peng; Liu, Yong-Jun; Xiong, Dong-Hai; Shen, Hui; Recker, Robert R; Deng, Hong-Wen

    2007-03-01

    To identify quantitative trait loci (QTLs) that contribute to obesity, we performed a large-scale whole genome linkage scan (WGS) involving 4,102 individuals from 434 Caucasian families. The most pronounced linkage evidence was found at the genomic region 20p11-12 for fat mass (LOD = 3.31) and percentage fat mass (PFM) (LOD = 2.92). We also identified several regions showing suggestive linkage signals (threshold LOD = 1.9) for obesity phenotypes, including 5q35, 8q13, 10p12, and 17q11.

  13. Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

    PubMed Central

    Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

    2007-01-01

    We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus. PMID:18466597

  14. Identification of quantitative trait loci affecting resistance to gastro-intestinal parasites in a double backcross population of Red Maasai and Dorper sheep

    USDA-ARS?s Scientific Manuscript database

    A genome-wide scan for quantitative trait loci (QTL) affecting gastrointestinal (GI) nematode resistance was completed using a double backcross sheep population derived from Red Maasai and Dorper ewes bred to F1 rams. These breeds were chosen, because Red Maasai sheep are known to be more tolerant ...

  15. Whole Genome Re-Sequencing Identifies a Quantitative Trait Locus Repressing Carbon Reserve Accumulation during Optimal Growth in Chlamydomonas reinhardtii

    PubMed Central

    Goold, Hugh Douglas; Nguyen, Hoa Mai; Kong, Fantao; Beyly-Adriano, Audrey; Légeret, Bertrand; Billon, Emmanuelle; Cuiné, Stéphan; Beisson, Fred; Peltier, Gilles; Li-Beisson, Yonghua

    2016-01-01

    Microalgae have emerged as a promising source for biofuel production. Massive oil and starch accumulation in microalgae is possible, but occurs mostly when biomass growth is impaired. The molecular networks underlying the negative correlation between growth and reserve formation are not known. Thus isolation of strains capable of accumulating carbon reserves during optimal growth would be highly desirable. To this end, we screened an insertional mutant library of Chlamydomonas reinhardtii for alterations in oil content. A mutant accumulating five times more oil and twice more starch than wild-type during optimal growth was isolated and named constitutive oil accumulator 1 (coa1). Growth in photobioreactors under highly controlled conditions revealed that the increase in oil and starch content in coa1 was dependent on light intensity. Genetic analysis and DNA hybridization pointed to a single insertional event responsible for the phenotype. Whole genome re-sequencing identified in coa1 a >200 kb deletion on chromosome 14 containing 41 genes. This study demonstrates that, 1), the generation of algal strains accumulating higher reserve amount without compromising biomass accumulation is feasible; 2), light is an important parameter in phenotypic analysis; and 3), a chromosomal region (Quantitative Trait Locus) acts as suppressor of carbon reserve accumulation during optimal growth. PMID:27141848

  16. Mapping complex traits as a dynamic system

    PubMed Central

    Sun, Lidan; Wu, Rongling

    2017-01-01

    Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476

  17. Are quantitative trait-dependent sampling designs cost-effective for analysis of rare and common variants?

    PubMed

    Yilmaz, Yildiz E; Bull, Shelley B

    2011-11-29

    Use of trait-dependent sampling designs in whole-genome association studies of sequence data can reduce total sequencing costs with modest losses of statistical efficiency. In a quantitative trait (QT) analysis of data from the Genetic Analysis Workshop 17 mini-exome for unrelated individuals in the Asian subpopulation, we investigate alternative designs that sequence only 50% of the entire cohort. In addition to a simple random sampling design, we consider extreme-phenotype designs that are of increasing interest in genetic association analysis of QTs, especially in studies concerned with the detection of rare genetic variants. We also evaluate a novel sampling design in which all individuals have a nonzero probability of being selected into the sample but in which individuals with extreme phenotypes have a proportionately larger probability. We take differential sampling of individuals with informative trait values into account by inverse probability weighting using standard survey methods which thus generalizes to the source population. In replicate 1 data, we applied the designs in association analysis of Q1 with both rare and common variants in the FLT1 gene, based on knowledge of the generating model. Using all 200 replicate data sets, we similarly analyzed Q1 and Q4 (which is known to be free of association with FLT1) to evaluate relative efficiency, type I error, and power. Simulation study results suggest that the QT-dependent selection designs generally yield greater than 50% relative efficiency compared to using the entire cohort, implying cost-effectiveness of 50% sample selection and worthwhile reduction of sequencing costs.

  18. Quantitative Trait Loci Associated with the Tocochromanol (Vitamin E) Pathway in Barley.

    PubMed

    Graebner, Ryan C; Wise, Mitchell; Cuesta-Marcos, Alfonso; Geniza, Matthew; Blake, Tom; Blake, Victoria C; Butler, Joshua; Chao, Shiaomen; Hole, David J; Horsley, Rich; Jaiswal, Pankaj; Obert, Don; Smith, Kevin P; Ullrich, Steven; Hayes, Patrick M

    2015-01-01

    The Genome-Wide Association Studies approach was used to detect Quantitative Trait Loci associated with tocochromanol concentrations using a panel of 1,466 barley accessions. All major tocochromanol types- α-, β-, δ-, γ-tocopherol and tocotrienol- were assayed. We found 13 single nucleotide polymorphisms associated with the concentration of one or more of these tocochromanol forms in barley, seven of which were within 2 cM of sequences homologous to cloned genes associated with tocochromanol production in barley and/or other plants. These associations confirmed a prior report based on bi-parental QTL mapping. This knowledge will aid future efforts to better understand the role of tocochromanols in barley, with specific reference to abiotic stress resistance. It will also be useful in developing barley varieties with higher tocochromanol concentrations, although at current recommended daily consumption amounts, barley would not be an effective sole source of vitamin E. However, it could be an important contributor in the context of whole grains in a balanced diet.

  19. Early experiences in establishing a regional quantitative imaging network for PET/CT clinical trials.

    PubMed

    Doot, Robert K; Thompson, Tove; Greer, Benjamin E; Allberg, Keith C; Linden, Hannah M; Mankoff, David A; Kinahan, Paul E

    2012-11-01

    The Seattle Cancer Care Alliance (SCCA) is a Pacific Northwest regional network that enables patients from community cancer centers to participate in multicenter oncology clinical trials where patients can receive some trial-related procedures at their local center. Results of positron emission tomography (PET) scans performed at community cancer centers are not currently used in SCCA Network trials since clinical trials customarily accept results from only trial-accredited PET imaging centers located at academic and large hospitals. Oncologists would prefer the option of using standard clinical PET scans from Network sites in multicenter clinical trials to increase accrual of patients for whom additional travel requirements for imaging are a barrier to recruitment. In an effort to increase accrual of rural and other underserved populations to Network trials, researchers and clinicians at the University of Washington, SCCA and its Network are assessing the feasibility of using PET scans from all Network sites in their oncology clinical trials. A feasibility study is required because the reproducibility of multicenter PET measurements ranges from approximately 3% to 40% at national academic centers. Early experiences from both national and local PET phantom imaging trials are discussed, and next steps are proposed for including patient PET scans from the emerging regional quantitative imaging network in clinical trials. There are feasible methods to determine and characterize PET quantitation errors and improve data quality by either prospective scanner calibration or retrospective post hoc corrections. These methods should be developed and implemented in multicenter clinical trials employing quantitative PET imaging of patients. Copyright © 2012 Elsevier Inc. All rights reserved.

  20. Genetic variation affecting host-parasite interactions: major-effect quantitative trait loci affect the transmission of sigma virus in Drosophila melanogaster.

    PubMed

    Bangham, Jenny; Knott, Sara A; Kim, Kang-Wook; Young, Robert S; Jiggins, Francis M

    2008-09-01

    In natural populations, genetic variation affects resistance to disease. Whether that genetic variation comprises lots of small-effect polymorphisms or a small number of large-effect polymorphisms has implications for adaptation, selection and how genetic variation is maintained in populations. Furthermore, how much genetic variation there is, and the genes that underlie this variation, affects models of co-evolution between parasites and their hosts. We are studying the genetic variation that affects the resistance of Drosophila melanogaster to its natural pathogen--the vertically transmitted sigma virus. We have carried out three separate quantitative trait locus mapping analyses to map gene variants on the second chromosome that cause variation in the rate at which males transmit the infection to their offspring. All three crosses identified a locus in a similar chromosomal location that causes a large drop in the rate at which the virus is transmitted. We also found evidence for an additional smaller-effect quantitative trait locus elsewhere on the chromosome. Our data, together with previous experiments on the sigma virus and parasitoid wasps, indicate that the resistance of D. melanogaster to co-evolved pathogens is controlled by a limited number of major-effect polymorphisms.

  1. Restriction fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the mosquito Aedes aegypti

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

    Severson, D.W.; Thathy, V.; Mori, A.

    Susceptibility of the mosquito Aedes aegypti to the malarial parasite Plasmodium gallinaceum was investigated as a quantitative trait using restriction fragment length polymorphisms (RFLP). Two F{sub 2} populations of mosquitoes were independently prepared from pairwise matings between a highly susceptible and a refractory strain of A. aegypti. RFLP were tested for association with oocyst development on the mosquito midgut. Two putative quantitative trait loci (QTL) were identified that significantly affect susceptibility. One QTL, pgs [2,LF98], is located on chromosome 2 and accounted for 65 and 49% of the observed phenotypic variance in the two populations, respectively. A second QTL, pgs[3,MalI],more » is located on chromosome 3 and accounted for 14 and 10% of the observed phenotypic variance in the two populations, respectively. Both QTL exhibit a partial dominance effect on susceptibility, wherein the dominance effect is derived from the refractory parent. No indication of epistasis between these QTL was detected. Evidence suggests that either a tightly linked cluster of independent genes or a single locus affecting susceptibility to various mosquito-borne parasites and pathogens has evolved near the LF98 locus; in addition to P. gallinaceum susceptibility, this general genome region has previously been implicated in susceptibility to the filaria nematode Brugia malayi and the yellow fever virus. 35 refs., 2 figs., 3 tabs.« less

  2. Quantitative trait loci for response to ethanol in an intercontinental set of recombinant inbred lines of Drosophila melanogaster.

    PubMed

    Defays, Raquel; Bertoli, Carlos Ignacio

    2012-12-01

    Alcohol, a drug widely abused, impacts the central nervous system functioning of diverse organisms. The behavioral responses to acute alcohol exposure are remarkably similar among humans and fruit flies. In its natural environment, rich in fermentation products, the fruit fly Drosophila melanogaster encounters relatively high levels of ethanol. The effects of ethanol and its metabolites on Drosophila have been studied for decades, as a model for adaptive evolution. Although extensive work has been done for elucidating patterns of genetic variation, substantially less is known about the genomic regions or genes that underlie the genetic variation of this important trait. To identify regions containing genes involved in the responses to ethanol, we used a mapping population of recombinant inbred (RIL) lines to map quantitative trait loci (QTL) that affect variation in resistance and recovery from ethanol sedation in adults and ethanol resistance in larvae. We mapped fourteen QTL affecting the response to ethanol on the three chromosomes. Seven of the QTL influence the resistance to ethanol in adults, two QTL are related to ethanol-coma recovery in adults and five affect the survival to ethanol in larvae. Most of the QTL were trait specific, suggesting that overlapping but generally unique genetic architectures underlie each trait. Each QTL explained up to 16.8% of the genetic variance among lines. Potential candidate loci contained within our QTL regions were identified and analyzed. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. Microarray-assisted fine-mapping of quantitative trait loci for cold tolerance in rice.

    PubMed

    Liu, Fengxia; Xu, Wenying; Song, Qian; Tan, Lubin; Liu, Jiayong; Zhu, Zuofeng; Fu, Yongcai; Su, Zhen; Sun, Chuanqing

    2013-05-01

    Many important agronomic traits, including cold stress resistance, are complex and controlled by quantitative trait loci (QTLs). Isolation of these QTLs will greatly benefit the agricultural industry but it is a challenging task. This study explored an integrated strategy by combining microarray with QTL-mapping in order to identify cold-tolerant QTLs from a cold-tolerant variety IL112 at early-seedling stage. All the early seedlings of IL112 survived normally for 9 d at 4-5°C, while Guichao2 (GC2), an indica cultivar, died after 4 d under the same conditions. Using the F2:3 population derived from the progeny of GC2 and IL112, we identified seven QTLs for cold tolerance. Furthermore, we performed Affymetrix rice whole-genome array hybridization and obtained the expression profiles of IL112 and GC2 under both low-temperature and normal conditions. Four genes were selected as cold QTL-related candidates, based on microarray data mining and QTL-mapping. One candidate gene, LOC_Os07g22494, was shown to be highly associated with cold tolerance in a number of rice varieties and in the F2:3 population, and its overexpression transgenic rice plants displayed strong tolerance to low temperature at early-seedling stage. The results indicated that overexpression of this gene (LOC_Os07g22494) could increase cold tolerance in rice seedlings. Therefore, this study provides a promising strategy for identifying candidate genes in defined QTL regions.

  4. Nonparametric evaluation of quantitative traits in population-based association studies when the genetic model is unknown.

    PubMed

    Konietschke, Frank; Libiger, Ondrej; Hothorn, Ludwig A

    2012-01-01

    Statistical association between a single nucleotide polymorphism (SNP) genotype and a quantitative trait in genome-wide association studies is usually assessed using a linear regression model, or, in the case of non-normally distributed trait values, using the Kruskal-Wallis test. While linear regression models assume an additive mode of inheritance via equi-distant genotype scores, Kruskal-Wallis test merely tests global differences in trait values associated with the three genotype groups. Both approaches thus exhibit suboptimal power when the underlying inheritance mode is dominant or recessive. Furthermore, these tests do not perform well in the common situations when only a few trait values are available in a rare genotype category (disbalance), or when the values associated with the three genotype categories exhibit unequal variance (variance heterogeneity). We propose a maximum test based on Marcus-type multiple contrast test for relative effect sizes. This test allows model-specific testing of either dominant, additive or recessive mode of inheritance, and it is robust against variance heterogeneity. We show how to obtain mode-specific simultaneous confidence intervals for the relative effect sizes to aid in interpreting the biological relevance of the results. Further, we discuss the use of a related all-pairwise comparisons contrast test with range preserving confidence intervals as an alternative to Kruskal-Wallis heterogeneity test. We applied the proposed maximum test to the Bogalusa Heart Study dataset, and gained a remarkable increase in the power to detect association, particularly for rare genotypes. Our simulation study also demonstrated that the proposed non-parametric tests control family-wise error rate in the presence of non-normality and variance heterogeneity contrary to the standard parametric approaches. We provide a publicly available R library nparcomp that can be used to estimate simultaneous confidence intervals or compatible

  5. Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

    PubMed

    Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

    2018-06-01

    Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

  6. Fabp7 Maps to a Quantitative Trait Locus for a Schizophrenia Endophenotype

    PubMed Central

    Watanabe, Akiko; Toyota, Tomoko; Owada, Yuji; Hayashi, Takeshi; Iwayama, Yoshimi; Matsumata, Miho; Ishitsuka, Yuichi; Nakaya, Akihiro; Maekawa, Motoko; Ohnishi, Tetsuo; Arai, Ryoichi; Sakurai, Katsuyasu; Yamada, Kazuo; Kondo, Hisatake; Hashimoto, Kenji; Osumi, Noriko; Yoshikawa, Takeo

    2007-01-01

    Deficits in prepulse inhibition (PPI) are a biological marker for schizophrenia. To unravel the mechanisms that control PPI, we performed quantitative trait loci (QTL) analysis on 1,010 F2 mice derived by crossing C57BL/6 (B6) animals that show high PPI with C3H/He (C3) animals that show low PPI. We detected six major loci for PPI, six for the acoustic startle response, and four for latency to response peak, some of which were sex-dependent. A promising candidate on the Chromosome 10-QTL was Fabp7 (fatty acid binding protein 7, brain), a gene with functional links to the N-methyl-D-aspartic acid (NMDA) receptor and expression in astrocytes. Fabp7-deficient mice showed decreased PPI and a shortened startle response latency, typical of the QTL's proposed effects. A quantitative complementation test supported Fabp7 as a potential PPI-QTL gene, particularly in male mice. Disruption of Fabp7 attenuated neurogenesis in vivo. Human FABP7 showed altered expression in schizophrenic brains and genetic association with schizophrenia, which were both evident in males when samples were divided by sex. These results suggest that FABP7 plays a novel and crucial role, linking the NMDA, neurodevelopmental, and glial theories of schizophrenia pathology and the PPI endophenotype, with larger or overt effects in males. We also discuss the results from the perspective of fetal programming. PMID:18001149

  7. Mapping of quantitative trait loci using the skew-normal distribution.

    PubMed

    Fernandes, Elisabete; Pacheco, António; Penha-Gonçalves, Carlos

    2007-11-01

    In standard interval mapping (IM) of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. When this assumption of normality is violated, the most commonly adopted strategy is to use the previous model after data transformation. However, an appropriate transformation may not exist or may be difficult to find. Also this approach can raise interpretation issues. An interesting alternative is to consider a skew-normal mixture model in standard IM, and the resulting method is here denoted as skew-normal IM. This flexible model that includes the usual symmetric normal distribution as a special case is important, allowing continuous variation from normality to non-normality. In this paper we briefly introduce the main peculiarities of the skew-normal distribution. The maximum likelihood estimates of parameters of the skew-normal distribution are obtained by the expectation-maximization (EM) algorithm. The proposed model is illustrated with real data from an intercross experiment that shows a significant departure from the normality assumption. The performance of the skew-normal IM is assessed via stochastic simulation. The results indicate that the skew-normal IM has higher power for QTL detection and better precision of QTL location as compared to standard IM and nonparametric IM.

  8. Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype

    PubMed Central

    Kappen, Claudia

    2016-01-01

    The process of patterning along the anterior-posterior axis in vertebrates is highly conserved. The function of Hox genes in the axis patterning process is particularly well documented for bone development in the vertebral column and the limbs. We here show that Hoxb6, in skeletal elements at the cervico-thoracic junction, controls multiple independent aspects of skeletal pattern, implicating discrete developmental pathways as substrates for this transcription factor. In addition, we demonstrate that Hoxb6 function is subject to modulation by genetic factors. These results establish Hox-controlled skeletal pattern as a quantitative trait modulated by gene-gene interactions, and provide evidence that distinct modifiers influence the function of conserved developmental genes in fundamental patterning processes. PMID:26800342

  9. The meaning of functional trait composition of food webs for ecosystem functioning.

    PubMed

    Gravel, Dominique; Albouy, Camille; Thuiller, Wilfried

    2016-05-19

    There is a growing interest in using trait-based approaches to characterize the functional structure of animal communities. Quantitative methods have been derived mostly for plant ecology, but it is now common to characterize the functional composition of various systems such as soils, coral reefs, pelagic food webs or terrestrial vertebrate communities. With the ever-increasing availability of distribution and trait data, a quantitative method to represent the different roles of animals in a community promise to find generalities that will facilitate cross-system comparisons. There is, however, currently no theory relating the functional composition of food webs to their dynamics and properties. The intuitive interpretation that more functional diversity leads to higher resource exploitation and better ecosystem functioning was brought from plant ecology and does not apply readily to food webs. Here we appraise whether there are interpretable metrics to describe the functional composition of food webs that could foster a better understanding of their structure and functioning. We first distinguish the various roles that traits have on food web topology, resource extraction (bottom-up effects), trophic regulation (top-down effects), and the ability to keep energy and materials within the community. We then discuss positive effects of functional trait diversity on food webs, such as niche construction and bottom-up effects. We follow with a discussion on the negative effects of functional diversity, such as enhanced competition (both exploitation and apparent) and top-down control. Our review reveals that most of our current understanding of the impact of functional trait diversity on food web properties and functioning comes from an over-simplistic representation of network structure with well-defined levels. We, therefore, conclude with propositions for new research avenues for both theoreticians and empiricists. © 2016 The Author(s).

  10. The meaning of functional trait composition of food webs for ecosystem functioning

    PubMed Central

    Albouy, Camille

    2016-01-01

    There is a growing interest in using trait-based approaches to characterize the functional structure of animal communities. Quantitative methods have been derived mostly for plant ecology, but it is now common to characterize the functional composition of various systems such as soils, coral reefs, pelagic food webs or terrestrial vertebrate communities. With the ever-increasing availability of distribution and trait data, a quantitative method to represent the different roles of animals in a community promise to find generalities that will facilitate cross-system comparisons. There is, however, currently no theory relating the functional composition of food webs to their dynamics and properties. The intuitive interpretation that more functional diversity leads to higher resource exploitation and better ecosystem functioning was brought from plant ecology and does not apply readily to food webs. Here we appraise whether there are interpretable metrics to describe the functional composition of food webs that could foster a better understanding of their structure and functioning. We first distinguish the various roles that traits have on food web topology, resource extraction (bottom-up effects), trophic regulation (top-down effects), and the ability to keep energy and materials within the community. We then discuss positive effects of functional trait diversity on food webs, such as niche construction and bottom-up effects. We follow with a discussion on the negative effects of functional diversity, such as enhanced competition (both exploitation and apparent) and top-down control. Our review reveals that most of our current understanding of the impact of functional trait diversity on food web properties and functioning comes from an over-simplistic representation of network structure with well-defined levels. We, therefore, conclude with propositions for new research avenues for both theoreticians and empiricists. PMID:27114571

  11. Classification of cassava genotypes based on qualitative and quantitative data.

    PubMed

    Oliveira, E J; Oliveira Filho, O S; Santos, V S

    2015-02-02

    We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

  12. End-to-end deep neural network for optical inversion in quantitative photoacoustic imaging.

    PubMed

    Cai, Chuangjian; Deng, Kexin; Ma, Cheng; Luo, Jianwen

    2018-06-15

    An end-to-end deep neural network, ResU-net, is developed for quantitative photoacoustic imaging. A residual learning framework is used to facilitate optimization and to gain better accuracy from considerably increased network depth. The contracting and expanding paths enable ResU-net to extract comprehensive context information from multispectral initial pressure images and, subsequently, to infer a quantitative image of chromophore concentration or oxygen saturation (sO 2 ). According to our numerical experiments, the estimations of sO 2 and indocyanine green concentration are accurate and robust against variations in both optical property and object geometry. An extremely short reconstruction time of 22 ms is achieved.

  13. The adaptation rate of a quantitative trait in an environmental gradient

    NASA Astrophysics Data System (ADS)

    Hermsen, R.

    2016-12-01

    The spatial range of a species habitat is generally determined by the ability of the species to cope with biotic and abiotic variables that vary in space. Therefore, the species range is itself an evolvable property. Indeed, environmental gradients permit a mode of evolution in which range expansion and adaptation go hand in hand. This process can contribute to rapid evolution of drug resistant bacteria and viruses, because drug concentrations in humans and livestock treated with antibiotics are far from uniform. Here, we use a minimal stochastic model of discrete, interacting organisms evolving in continuous space to study how the rate of adaptation of a quantitative trait depends on the steepness of the gradient and various population parameters. We discuss analytical results for the mean-field limit as well as extensive stochastic simulations. These simulations were performed using an exact, event-driven simulation scheme that can deal with continuous time-, density- and coordinate-dependent reaction rates and could be used for a wide variety of stochastic systems. The results reveal two qualitative regimes. If the gradient is shallow, the rate of adaptation is limited by dispersion and increases linearly with the gradient slope. If the gradient is steep, the adaptation rate is limited by mutation. In this regime, the mean-field result is highly misleading: it predicts that the adaptation rate continues to increase with the gradient slope, whereas stochastic simulations show that it in fact decreases with the square root of the slope. This discrepancy underscores the importance of discreteness and stochasticity even at high population densities; mean-field results, including those routinely used in quantitative genetics, should be interpreted with care.

  14. The adaptation rate of a quantitative trait in an environmental gradient.

    PubMed

    Hermsen, R

    2016-11-30

    The spatial range of a species habitat is generally determined by the ability of the species to cope with biotic and abiotic variables that vary in space. Therefore, the species range is itself an evolvable property. Indeed, environmental gradients permit a mode of evolution in which range expansion and adaptation go hand in hand. This process can contribute to rapid evolution of drug resistant bacteria and viruses, because drug concentrations in humans and livestock treated with antibiotics are far from uniform. Here, we use a minimal stochastic model of discrete, interacting organisms evolving in continuous space to study how the rate of adaptation of a quantitative trait depends on the steepness of the gradient and various population parameters. We discuss analytical results for the mean-field limit as well as extensive stochastic simulations. These simulations were performed using an exact, event-driven simulation scheme that can deal with continuous time-, density- and coordinate-dependent reaction rates and could be used for a wide variety of stochastic systems. The results reveal two qualitative regimes. If the gradient is shallow, the rate of adaptation is limited by dispersion and increases linearly with the gradient slope. If the gradient is steep, the adaptation rate is limited by mutation. In this regime, the mean-field result is highly misleading: it predicts that the adaptation rate continues to increase with the gradient slope, whereas stochastic simulations show that it in fact decreases with the square root of the slope. This discrepancy underscores the importance of discreteness and stochasticity even at high population densities; mean-field results, including those routinely used in quantitative genetics, should be interpreted with care.

  15. Six quantitative trait loci influence task thresholds for hygienic behaviour in honeybees (Apis mellifera).

    PubMed

    Oxley, Peter R; Spivak, Marla; Oldroyd, Benjamin P

    2010-04-01

    Honeybee hygienic behaviour provides colonies with protection from many pathogens and is an important model system of the genetics of a complex behaviour. It is a textbook example of complex behaviour under simple genetic control: hygienic behaviour consists of two components--uncapping a diseased brood cell, followed by removal of the contents--each of which are thought to be modulated independently by a few loci of medium to large effect. A worker's genetic propensity to engage in hygienic tasks affects the intensity of the stimulus required before she initiates the behaviour. Genetic diversity within colonies leads to task specialization among workers, with a minority of workers performing the majority of nest-cleaning tasks. We identify three quantitative trait loci that influence the likelihood that workers will engage in hygienic behaviour and account for up to 30% of the phenotypic variability in hygienic behaviour in our population. Furthermore, we identify two loci that influence the likelihood that a worker will perform uncapping behaviour only, and one locus that influences removal behaviour. We report the first candidate genes associated with engaging in hygienic behaviour, including four genes involved in olfaction, learning and social behaviour, and one gene involved in circadian locomotion. These candidates will allow molecular characterization of this distinctive behavioural mode of disease resistance, as well as providing the opportunity for marker-assisted selection for this commercially significant trait.

  16. Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection.

    PubMed

    Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

    2013-11-01

    Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

  17. Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

    PubMed

    Dobata, Shigeto

    2012-12-01

    Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

  18. Discovery of quantitative trait loci for resistance to parasitic nematode infection in sheep: I. Analysis of outcross pedigrees

    PubMed Central

    Crawford, Allan M; Paterson, Korena A; Dodds, Ken G; Diez Tascon, Cristina; Williamson, Penny A; Roberts Thomson, Meredith; Bisset, Stewart A; Beattie, Anne E; Greer, Gordon J; Green, Richard S; Wheeler, Roger; Shaw, Richard J; Knowler, Kevin; McEwan, John C

    2006-01-01

    Background Currently most pastoral farmers rely on anthelmintic drenches to control gastrointestinal parasitic nematodes in sheep. Resistance to anthelmintics is rapidly increasing in nematode populations such that on some farms none of the drench families are now completely effective. It is well established that host resistance to nematode infection is a moderately heritable trait. This study was undertaken to identify regions of the genome, quantitative trait loci (QTL) that contain genes affecting resistance to parasitic nematodes. Results Rams obtained from crossing nematode parasite resistant and susceptible selection lines were used to derive five large half-sib families comprising between 348 and 101 offspring per sire. Total offspring comprised 940 lambs. Extensive measurements for a range of parasite burden and immune function traits in all offspring allowed each lamb in each pedigree to be ranked for relative resistance to nematode parasites. Initially the 22 most resistant and 22 most susceptible progeny from each pedigree were used in a genome scan that used 203 microsatellite markers spread across all sheep autosomes. This study identified 9 chromosomes with regions showing sufficient linkage to warrant the genotyping of all offspring. After genotyping all offspring with markers covering Chromosomes 1, 3, 4, 5, 8, 12, 13, 22 and 23, the telomeric end of chromosome 8 was identified as having a significant QTL for parasite resistance as measured by the number of Trichostrongylus spp. adults in the abomasum and small intestine at the end of the second parasite challenge. Two further QTL for associated immune function traits of total serum IgE and T. colubiformis specific serum IgG, at the end of the second parasite challenge, were identified on chromosome 23. Conclusion Despite parasite resistance being a moderately heritable trait, this large study was able to identify only a single significant QTL associated with it. The QTL concerned adult parasite

  19. Discovery of quantitative trait loci for resistance to parasitic nematode infection in sheep: I. Analysis of outcross pedigrees.

    PubMed

    Crawford, Allan M; Paterson, Korena A; Dodds, Ken G; Diez Tascon, Cristina; Williamson, Penny A; Roberts Thomson, Meredith; Bisset, Stewart A; Beattie, Anne E; Greer, Gordon J; Green, Richard S; Wheeler, Roger; Shaw, Richard J; Knowler, Kevin; McEwan, John C

    2006-07-18

    Currently most pastoral farmers rely on anthelmintic drenches to control gastrointestinal parasitic nematodes in sheep. Resistance to anthelmintics is rapidly increasing in nematode populations such that on some farms none of the drench families are now completely effective. It is well established that host resistance to nematode infection is a moderately heritable trait. This study was undertaken to identify regions of the genome, quantitative trait loci (QTL) that contain genes affecting resistance to parasitic nematodes. Rams obtained from crossing nematode parasite resistant and susceptible selection lines were used to derive five large half-sib families comprising between 348 and 101 offspring per sire. Total offspring comprised 940 lambs. Extensive measurements for a range of parasite burden and immune function traits in all offspring allowed each lamb in each pedigree to be ranked for relative resistance to nematode parasites. Initially the 22 most resistant and 22 most susceptible progeny from each pedigree were used in a genome scan that used 203 microsatellite markers spread across all sheep autosomes. This study identified 9 chromosomes with regions showing sufficient linkage to warrant the genotyping of all offspring. After genotyping all offspring with markers covering Chromosomes 1, 3, 4, 5, 8, 12, 13, 22 and 23, the telomeric end of chromosome 8 was identified as having a significant QTL for parasite resistance as measured by the number of Trichostrongylus spp. adults in the abomasum and small intestine at the end of the second parasite challenge. Two further QTL for associated immune function traits of total serum IgE and T. colubiformis specific serum IgG, at the end of the second parasite challenge, were identified on chromosome 23. Despite parasite resistance being a moderately heritable trait, this large study was able to identify only a single significant QTL associated with it. The QTL concerned adult parasite burdens at the end of the second

  20. Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L.).

    PubMed

    Zhou, Yong; Dong, Guichun; Tao, Yajun; Chen, Chen; Yang, Bin; Wu, Yue; Yang, Zefeng; Liang, Guohua; Wang, Baohe; Wang, Yulong

    2016-01-01

    Identification of quantitative trait loci (QTLs) associated with rice root morphology provides useful information for avoiding drought stress and maintaining yield production under the irrigation condition. In this study, a set of chromosome segment substitution lines derived from 9311 as the recipient and Nipponbare as donor, were used to analysis root morphology. By combining the resequencing-based bin-map with a multiple linear regression analysis, QTL identification was conducted on root number (RN), total root length (TRL), root dry weight (RDW), maximum root length (MRL), root thickness (RTH), total absorption area (TAA) and root vitality (RV), using the CSSL population grown under hydroponic conditions. A total of thirty-eight QTLs were identified: six for TRL, six for RDW, eight for the MRL, four for RTH, seven for RN, two for TAA, and five for RV. Phenotypic effect variance explained by these QTLs ranged from 2.23% to 37.08%, and four single QTLs had more than 10% phenotypic explanations on three root traits. We also detected the correlations between grain yield (GY) and root traits, and found that TRL, RTH and MRL had significantly positive correlations with GY. However, TRL, RDW and MRL had significantly positive correlations with biomass yield (BY). Several QTLs identified in our population were co-localized with some loci for grain yield or biomass. This information may be immediately exploited for improving rice water and fertilizer use efficiency for molecular breeding of root system architectures.

  1. The Role of Temporal Trends in Growing Networks

    PubMed Central

    Ruppin, Eytan; Shavitt, Yuval

    2016-01-01

    The rich get richer principle, manifested by the Preferential attachment (PA) mechanism, is widely considered one of the major factors in the growth of real-world networks. PA stipulates that popular nodes are bound to be more attractive than less popular nodes; for example, highly cited papers are more likely to garner further citations. However, it overlooks the transient nature of popularity, which is often governed by trends. Here, we show that in a wide range of real-world networks the recent popularity of a node, i.e., the extent by which it accumulated links recently, significantly influences its attractiveness and ability to accumulate further links. We proceed to model this observation with a natural extension to PA, named Trending Preferential Attachment (TPA), in which edges become less influential as they age. TPA quantitatively parametrizes a fundamental network property, namely the network’s tendency to trends. Through TPA, we find that real-world networks tend to be moderately to highly trendy. Networks are characterized by different susceptibilities to trends, which determine their structure to a large extent. Trendy networks display complex structural traits, such as modular community structure and degree-assortativity, occurring regularly in real-world networks. In summary, this work addresses an inherent trait of complex networks, which greatly affects their growth and structure, and develops a unified model to address its interaction with preferential attachment. PMID:27486847

  2. Comparison study on qualitative and quantitative risk assessment methods for urban natural gas pipeline network.

    PubMed

    Han, Z Y; Weng, W G

    2011-05-15

    In this paper, a qualitative and a quantitative risk assessment methods for urban natural gas pipeline network are proposed. The qualitative method is comprised of an index system, which includes a causation index, an inherent risk index, a consequence index and their corresponding weights. The quantitative method consists of a probability assessment, a consequences analysis and a risk evaluation. The outcome of the qualitative method is a qualitative risk value, and for quantitative method the outcomes are individual risk and social risk. In comparison with previous research, the qualitative method proposed in this paper is particularly suitable for urban natural gas pipeline network, and the quantitative method takes different consequences of accidents into consideration, such as toxic gas diffusion, jet flame, fire ball combustion and UVCE. Two sample urban natural gas pipeline networks are used to demonstrate these two methods. It is indicated that both of the two methods can be applied to practical application, and the choice of the methods depends on the actual basic data of the gas pipelines and the precision requirements of risk assessment. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

  3. Comparing Bayesian estimates of genetic differentiation of molecular markers and quantitative traits: an application to Pinus sylvestris.

    PubMed

    Waldmann, P; García-Gil, M R; Sillanpää, M J

    2005-06-01

    Comparison of the level of differentiation at neutral molecular markers (estimated as F(ST) or G(ST)) with the level of differentiation at quantitative traits (estimated as Q(ST)) has become a standard tool for inferring that there is differential selection between populations. We estimated Q(ST) of timing of bud set from a latitudinal cline of Pinus sylvestris with a Bayesian hierarchical variance component method utilizing the information on the pre-estimated population structure from neutral molecular markers. Unfortunately, the between-family variances differed substantially between populations that resulted in a bimodal posterior of Q(ST) that could not be compared in any sensible way with the unimodal posterior of the microsatellite F(ST). In order to avoid publishing studies with flawed Q(ST) estimates, we recommend that future studies should present heritability estimates for each trait and population. Moreover, to detect variance heterogeneity in frequentist methods (ANOVA and REML), it is of essential importance to check also that the residuals are normally distributed and do not follow any systematically deviating trends.

  4. QIN. Early experiences in establishing a regional quantitative imaging network for PET/CT clinical trials

    PubMed Central

    Doot, Robert K.; Thompson, Tove; Greer, Benjamin E.; Allberg, Keith C.; Linden, Hannah M.; Mankoff, David A.; Kinahan, Paul E.

    2012-01-01

    The Seattle Cancer Care Alliance (SCCA) is a Pacific Northwest regional network that enables patients from community cancer centers to participate in multicenter oncology clinical trials where patients can receive some trial-related procedures at their local center. Results of positron emission tomography (PET) scans performed at community cancer centers are not currently used in SCCA Network trials since clinical trials customarily accept results from only trial-accredited PET imaging centers located at academic and large hospitals. Oncologists would prefer the option of using standard clinical PET scans from Network sites in multicenter clinical trials to increase accrual of patients for whom additional travel requirements for imaging is a barrier to recruitment. In an effort to increase accrual of rural and other underserved populations to Network trials, researchers and clinicians at the University of Washington, SCCA and its Network are assessing feasibility of using PET scans from all Network sites in their oncology clinical trials. A feasibility study is required because the reproducibility of multicenter PET measurements ranges from approximately 3% to 40% at national academic centers. Early experiences from both national and local PET phantom imaging trials are discussed and next steps are proposed for including patient PET scans from the emerging regional quantitative imaging network in clinical trials. There are feasible methods to determine and characterize PET quantitation errors and improve data quality by either prospective scanner calibration or retrospective post hoc corrections. These methods should be developed and implemented in multicenter clinical trials employing quantitative PET imaging of patients. PMID:22795929

  5. P Element Transposition Contributes Substantial New Variation for a Quantitative Trait in Drosophila Melanogaster

    PubMed Central

    Torkamanzehi, A.; Moran, C.; Nicholas, F. W.

    1992-01-01

    The P-M system of transposition in Drosophila melanogaster is a powerful mutator for many visible and lethal loci. Experiments using crosses between unrelated P and M stocks to assess the importance of transposition-mediated mutations affecting quantitative loci and reponse to selection have yielded unrepeatable or ambiguous results. In a different approach, we have used a P stock produced by microinjection of the ry(506) M stock. Selection responses were compared between transposition lines that were initiated by crossing M strain females with males from the ``co-isogenic'' P strain, and ry(506) M control lines. Unlike previous attempts to quantify the effects of P element transposition, there is no possibility of P transposition in the controls. During 10 generations of selection for the quantitative trait abdominal bristle number, none of the four control lines showed any response to selection, indicative of isogenicity for those loci affecting abdominal bristle number. In contrast, three of the four transposition lines showed substantial response, with regression of cumulative response on cumulative selection differential ranging from 15% to 25%. Transposition of P elements has produced new additive genetic variance at a rate which is more than 30 times greater than the rate expected from spontaneous mutation. PMID:1317317

  6. A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

    PubMed

    Ficklin, Stephen P; Feltus, Frank Alex

    2013-01-01

    Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with

  7. Sticking with the nice guy: trait warmth information impairs learning and modulates person perception brain network activity.

    PubMed

    Lee, Victoria K; Harris, Lasana T

    2014-12-01

    Social learning requires inferring social information about another person, as well as evaluating outcomes. Previous research shows that prior social information biases decision making and reduces reliance on striatal activity during learning (Delgado, Frank, & Phelps, Nature Neuroscience 8 (11): 1611-1618, 2005). A rich literature in social psychology on person perception demonstrates that people spontaneously infer social information when viewing another person (Fiske & Taylor, 2013) and engage a network of brain regions, including the medial prefrontal cortex, temporal parietal junction, superior temporal sulcus, and precuneus (Amodio & Frith, Nature Reviews Neuroscience, 7(4), 268-277, 2006; Haxby, Gobbini, & Montgomery, 2004; van Overwalle Human Brain Mapping, 30, 829-858, 2009). We investigate the role of these brain regions during social learning about well-established dimensions of person perception-trait warmth and trait competence. We test the hypothesis that activity in person perception brain regions interacts with learning structures during social learning. Participants play an investment game where they must choose an agent to invest on their behalf. This choice is guided by cues signaling trait warmth or trait competence based on framing of monetary returns. Trait warmth information impairs learning about human but not computer agents, while trait competence information produces similar learning rates for human and computer agents. We see increased activation to warmth information about human agents in person perception brain regions. Interestingly, activity in person perception brain regions during the decision phase negatively predicts activity in the striatum during feedback for trait competence inferences about humans. These results suggest that social learning may engage additional processing within person perception brain regions that hampers learning in economic contexts.

  8. Quantitative trait loci mapping for Gibberella ear rot resistance and associated agronomic traits using genotyping-by-sequencing in maize.

    PubMed

    Kebede, Aida Z; Woldemariam, Tsegaye; Reid, Lana M; Harris, Linda J

    2016-01-01

    Unique and co-localized chromosomal regions affecting Gibberella ear rot disease resistance and correlated agronomic traits were identified in maize. Dissecting the mechanisms underlying resistance to Gibberella ear rot (GER) disease in maize provides insight towards more informed breeding. To this goal, we evaluated 410 recombinant inbred lines (RIL) for GER resistance over three testing years using silk channel and kernel inoculation techniques. RILs were also evaluated for agronomic traits like days to silking, husk cover, and kernel drydown rate. The RILs showed significant genotypic differences for all traits with above average to high heritability estimates. Significant (P < 0.01) but weak genotypic correlations were observed between disease severity and agronomic traits, indicating the involvement of agronomic traits in disease resistance. Common QTLs were detected for GER resistance and kernel drydown rate, suggesting the existence of pleiotropic genes that could be exploited to improve both traits at the same time. The QTLs identified for silk and kernel resistance shared some common regions on chromosomes 1, 2, and 8 and also had some regions specific to each tissue on chromosomes 9 and 10. Thus, effective GER resistance breeding could be achieved by considering screening methods that allow exploitation of tissue-specific disease resistance mechanisms and include kernel drydown rate either in an index or as indirect selection criterion.

  9. Introduction to focus issue: quantitative approaches to genetic networks.

    PubMed

    Albert, Réka; Collins, James J; Glass, Leon

    2013-06-01

    All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

  10. Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

    NASA Astrophysics Data System (ADS)

    Albert, Réka; Collins, James J.; Glass, Leon

    2013-06-01

    All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

  11. Two quantitative trait loci affect ACE activities in Mexican-Americans.

    PubMed

    Kammerer, Candace M; Gouin, Nicolas; Samollow, Paul B; VandeBerg, Jane F; Hixson, James E; Cole, Shelley A; MacCluer, Jean W; Atwood, Larry D

    2004-02-01

    Angiotensin-converting enzyme (ACE) activity is highly heritable and has been associated with cardiovascular disease. We are studying the effects of genes and environmental factors on hypertension and related phenotypes, such as ACE activity, in Mexican-American families. In the current study, we performed multipoint linkage analysis to search for quantitative trait loci (QTLs) that affect ACE activities on data from 793 individuals from 29 pedigrees from the San Antonio Family Heart Study. As expected, we obtained strong evidence (maximum log of the odds [LOD]=4.57, genomic P=0.003) that a QTL for ACE activity is located on chromosome 17 near the ACE structural locus. We subsequently performed linkage analyses conditional on the effect of this QTL and obtained strong evidence (LOD=3.34) for a second QTL on chromosome 4 near D4S1548. We next incorporated the ACEIns/Del genotypes in our analyses and removed the evidence for the chromosome 17 QTL (maximum LOD=0.60); however, we retained our evidence for the QTL on chromosome 4q. We conclude that the QTL on chromosome 17 is tightly linked to ACE and is in strong disequilibrium with the insertion/deletion polymorphism, which is consistent with other reports. We also have evidence that an additional QTL affects ACE activity. Identification of this additional QTL might lead to alternate means of prophylaxis.

  12. Genome-wide Association Study of a Quantitative Disordered Gambling Trait

    PubMed Central

    Lind, Penelope A.; Zhu, Gu; Montgomery, Grant W; Madden, Pamela A.F.; Heath, Andrew C.; Martin, Nicholas G.; Slutske, Wendy S.

    2012-01-01

    Disordered gambling is a moderately heritable trait, but the underlying genetic basis is largely unknown. We performed a genome-wide association study (GWAS) for disordered gambling using a quantitative factor score in 1,312 twins from 894 Australian families. Association was conducted for 2,381,914 single nucleotide polymorphisms (SNPs) using the family-based association test in Merlin followed by gene and pathway enrichment analyses. Although no SNP reached genome-wide significance, six achieved P-values < 1 × 10−5 with variants in three genes (MT1X, ATXN1 and VLDLR) implicated in disordered gambling. Secondary case-control analyses found two SNPs on chromosome 9 (rs1106076 and rs12305135 near VLDLR) and rs10812227 near FZD10 on chromosome 12 to be significantly associated with lifetime DSM-IV pathological gambling and SOGS classified probable pathological gambling status. Furthermore, several addiction-related pathways were enriched for SNPs associated with disordered gambling. Finally, gene-based analysis of 24 candidate genes for dopamine agonist induced gambling in individuals with Parkinson’s disease suggested an enrichment of SNPs associated with disordered gambling. We report the first GWAS of disordered gambling. While further replication is required, the identification of susceptibility loci and biological pathways will be important in characterizing the biological mechanisms that underpin disordered gambling. PMID:22780124

  13. A compilation of quantitative functional traits for marine and freshwater crustacean zooplankton.

    PubMed

    Hébert, Marie-Pier; Beisner, Beatrix E; Maranger, Roxane

    2016-04-01

    This data compilation synthesizes 8609 individual observations and ranges of 13 traits from 201 freshwater and 191 marine crustacean taxa belonging to either Copepoda or Cladocera, two important zooplankton groups across all major aquatic habitats. Most data were gathered from the literature, with the balance being provided by zooplankton ecologists. With the aim of more fully assessing zooplankton effects on elemental processes such as nitrogen (N), phosphorus (P) and carbon (C) stocks and fluxes in aquatic ecosystems, this data set provides information on the following traits: body size (length and mass), trophic group, elemental and biochemical corporal composition (N, P, C, lipid and protein content), respiration rates, N- and P-excretion rates, as well as stoichiometric ratios. Although relationships for zooplankton metabolism as a function of body mass or requirements have been explored in the past three decades, data have not been systematically compiled nor examined from an integrative and large-scale perspective across crustacean taxa and habitat types. While this contribution likely represents the most comprehensive assembly of traits for both marine and freshwater species, this data set is not exhaustive either. As a result, this compilation also identifies knowledge gaps: a fact that should encourage researchers to disclose information they may have to help complete such databases. This trait matrix is made available for the first time in this data paper; prior to its release, the data set has been analyzed in a meta-analysis published as a companion paper. This data set should prove extremely valuable for aquatic ecologists for trait-based characterization of plankton community structure as well as biogeochemical modeling. These data are also well-suited for deriving shortcut relationships that predict more difficult to measure trait values, most of which can be directly related to ecosystem properties (i.e., effect traits), from simpler traits (e

  14. Identification, Replication, and Functional Fine-Mapping of Expression Quantitative Trait Loci in Primary Human Liver Tissue

    PubMed Central

    Stanaway, Ian B.; Gamazon, Eric R.; Smith, Joshua D.; Mirkov, Snezana; Ramirez, Jacqueline; Liu, Wanqing; Lin, Yvonne S.; Moloney, Cliona; Aldred, Shelly Force; Trinklein, Nathan D.; Schuetz, Erin; Nickerson, Deborah A.; Thummel, Ken E.; Rieder, Mark J.; Rettie, Allan E.; Ratain, Mark J.; Cox, Nancy J.; Brown, Christopher D.

    2011-01-01

    The discovery of expression quantitative trait loci (“eQTLs”) can help to unravel genetic contributions to complex traits. We identified genetic determinants of human liver gene expression variation using two independent collections of primary tissue profiled with Agilent (n = 206) and Illumina (n = 60) expression arrays and Illumina SNP genotyping (550K), and we also incorporated data from a published study (n = 266). We found that ∼30% of SNP-expression correlations in one study failed to replicate in either of the others, even at thresholds yielding high reproducibility in simulations, and we quantified numerous factors affecting reproducibility. Our data suggest that drug exposure, clinical descriptors, and unknown factors associated with tissue ascertainment and analysis have substantial effects on gene expression and that controlling for hidden confounding variables significantly increases replication rate. Furthermore, we found that reproducible eQTL SNPs were heavily enriched near gene starts and ends, and subsequently resequenced the promoters and 3′UTRs for 14 genes and tested the identified haplotypes using luciferase assays. For three genes, significant haplotype-specific in vitro functional differences correlated directly with expression levels, suggesting that many bona fide eQTLs result from functional variants that can be mechanistically isolated in a high-throughput fashion. Finally, given our study design, we were able to discover and validate hundreds of liver eQTLs. Many of these relate directly to complex traits for which liver-specific analyses are likely to be relevant, and we identified dozens of potential connections with disease-associated loci. These included previously characterized eQTL contributors to diabetes, drug response, and lipid levels, and they suggest novel candidates such as a role for NOD2 expression in leprosy risk and C2orf43 in prostate cancer. In general, the work presented here will be valuable for

  15. High Density Single Nucleotide Polymorphism (SNP) Mapping and Quantitative Trait Loci (QTL) Analysis in a Biparental Spring Triticale Population Localized Major and Minor Effect Fusarium Head Blight Resistance and Associated Traits QTL

    PubMed Central

    Dhariwal, Raman; Fedak, George; Dion, Yves; Pozniak, Curtis; Laroche, André; Eudes, François; Randhawa, Harpinder Singh

    2018-01-01

    Triticale (xTriticosecale Wittmack) is an important feed crop which suffers severe yield, grade and end-use quality losses due to Fusarium head blight (FHB). Development of resistant triticale cultivars is hindered by lack of effective genetic resistance sources. To dissect FHB resistance, a doubled haploid spring triticale population produced from the cross TMP16315/AC Ultima using a microspore culture method, was phenotyped for FHB incidence, severity, visual rating index (VRI), deoxynivalenol (DON) and some associated traits (ergot, grain protein content, test weight, yield, plant height and lodging) followed by single nucleotide polymorphism (SNP) genotyping. A high-density map consisting of 5274 SNPs, mapped on all 21 chromosomes with a map density of 0.48 cM/SNP, was constructed. Together, 17 major quantitative trait loci were identified for FHB on chromosomes 1A, 2B, 3A, 4A, 4R, 5A, 5R and 6B; two of incidence loci (on 2B and 5R) also co-located with loci for severity and VRI, and two other loci of VRI (on 1A and 4R) with DON accumulation. Major and minor loci were also identified for all other traits in addition to many epistasis loci. This study provides new insight into the genetic basis of FHB resistance and their association with other traits in triticale. PMID:29304028

  16. Fine mapping of quantitative trait loci underlying sensory meat quality traits in three French beef cattle breeds.

    PubMed

    Allais, S; Levéziel, H; Hocquette, J F; Rousset, S; Denoyelle, C; Journaux, L; Renand, G

    2014-10-01

    Improving the traits that underlie meat quality is a major challenge in the beef industry. The objective of this paper was to detect QTL linked to sensory meat quality traits in 3 French beef cattle breeds. We genotyped 1,059, 1,219, and 947 young bulls and their sires belonging to the Charolais, Limousin, and Blonde d'Aquitaine breeds, respectively, using the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). After estimating relevant genetic parameters using VCE software, we performed a linkage disequilibrium and linkage analysis on 4 meat traits: intramuscular fat content, muscle lightness, shear force, and tenderness score. Heritability coefficients largely ranged between 0.10 and 0.24; however, they reached a maximum of 0.44 and 0.50 for intramuscular fat content and tenderness score, respectively, in the Charolais breed. The 2 meat texture traits, shear force and tenderness score, were strongly genetically correlated (-0.91 in the Charolais and Limousin breed and -0.86 in the Blonde d'Aquitaine breed), indicating that they are 2 different measures of approximately the same trait. The genetic correlation between tenderness and intramuscular fat content differed across breeds. Using a significance threshold of 5 × 10(-4) for QTL detection, we found more than 200 significant positions across the 29 autosomal chromosomes for the 4 traits in the Charolais and Blonde d'Aquitaine breeds; in contrast, there were only 78 significant positions in the Limousin breed. Few QTL were common across breeds. We detected QTL for intramuscular fat content located near the myostatin gene in the Charolais and Blonde d'Aquitaine breeds. No mutation in this gene has been reported for the Blonde d'Aquitaine breed; therefore, it suggests that an unknown mutation could be segregating in this breed. We confirmed that, in certain breeds, markers in the calpastatin and calpain 1 gene regions affect tenderness. We also found new QTL as several QTL on chromosome 3 that are

  17. Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP-brain network associations.

    PubMed

    Kim, Junghi; Pan, Wei

    2017-04-01

    There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e.g., some quantitative and some binary, but it is also potentially more robust to the commonly adopted additive inheritance mode. More importantly, we develop an adaptive test in a POM so that it can maintain high power across many possible situations. Compared to the existing methods treating multiple traits as responses, e.g., in a generalized estimating equation (GEE) approach, the proposed method can be applied to a high dimensional setting where the number of phenotypes (p) can be larger than the sample size (n), in addition to a usual small P setting. The promising performance of the proposed method was demonstrated with applications to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which either structural MRI driven phenotypes or resting-state functional MRI (rs-fMRI) derived brain functional connectivity measures were used as phenotypes. The applications led to the identification of several top SNPs of biological interest. Furthermore, simulation studies showed competitive performance of the new method, especially for p>n. © 2017 WILEY PERIODICALS, INC.

  18. Building phenotype networks to improve QTL detection: a comparative analysis of fatty acid and fat traits in pigs.

    PubMed

    Yang, B; Navarro, N; Noguera, J L; Muñoz, M; Guo, T F; Yang, K X; Ma, J W; Folch, J M; Huang, L S; Pérez-Enciso, M

    2011-10-01

    Models in QTL mapping can be improved by considering all potential variables, i.e. we can use remaining traits other than the trait under study as potential predictors. QTL mapping is often conducted by correcting for a few fixed effects or covariates (e.g. sex, age), although many traits with potential causal relationships between them are recorded. In this work, we evaluate by simulation several procedures to identify optimum models in QTL scans: forward selection, undirected dependency graph and QTL-directed dependency graph (QDG). The latter, QDG, performed better in terms of power and false discovery rate and was applied to fatty acid (FA) composition and fat deposition traits in two pig F2 crosses from China and Spain. Compared with the typical QTL mapping, QDG approach revealed several new QTL. To the contrary, several FA QTL on chromosome 4 (e.g. Palmitic, C16:0; Stearic, C18:0) detected by typical mapping vanished after adjusting for phenotypic covariates in QDG mapping. This suggests that the QTL detected in typical mapping could be indirect. When a QTL is supported by both approaches, there is an increased confidence that the QTL have a primary effect on the corresponding trait. An example is a QTL for C16:1 on chromosome 8. In conclusion, mapping QTL based on causal phenotypic networks can increase power and help to make more biologically sound hypothesis on the genetic architecture of complex traits. © 2011 Blackwell Verlag GmbH.

  19. Investigation of four porcine candidate genes (H-FABP, MYOD1, UCP3 and MASTR) for meat quality traits in Large White pigs.

    PubMed

    Han, Xuelei; Jiang, Tengfei; Yang, Huawei; Zhang, Qingde; Wang, Weimin; Fan, Bin; Liu, Bang

    2012-06-01

    Meat quality traits are economically important traits of swine, and are controlled by multiple genes as complex quantitative traits. In the present study four genes, H-FABP (heart fatty acid-binding protein), MASTR (MEF2 activating motif and SAP domain containing transcriptional regulator), UCP3 (uncoupling protein 3) and MYOD1 (myogenic differentiation 1) were researched in Large White pigs. The polymorphisms H-FABP T/C of 5'UTR, MYOD1 g.257 A>C, UCP3 g.1406 G>A in exon 3 and MASTR c.187 C>T have been reported to be associated with meat quality traits in pigs. The aim of this study was to analyze the effect of single and multiple markers for single traits in Large White pigs. The single marker association analysis showed that the H-FABP and MASTR genes were associated with IMF (intramuscular fat content) (P < 0.05), and that the g.257 A>C of MYOD1 gene was most significantly related to muscle pH value (P < 0.01). The multiple markers for IMF were analyzed by combining the markers and quantitative trait modes into the linear regression. The results revealed that H-FABP and MASTR integrate gene networks for IMF. Thus, our study results suggested that H-FABP and MASTR polymorphisms could be used as genetic markers in the marker-assisted selection towards the improvement of IMF in Large White pigs.

  20. Genome-wide identification of expression quantitative trait loci for human telomerase.

    PubMed

    Kim, Hanseol; Ryu, Jihye; Lee, Chaeyoung

    2016-10-01

    A genome-wide association study was conducted to identify expression quantitative trait loci (eQTL) for human telomerase.We tested the genetic associations of nucleotide variants with expression of the genes encoding human telomerase reverse transcriptase (hTERT) and telomerase RNA components (TERC) in lymphoblastoid cell lines derived from 373 Europeans.Our results revealed 6 eQTLs associated with hTERT (P < 5 × 10). One eQTL (rs17755753) was located in the intron 1 of the gene encoding R-spondin-3 (RSPO3), a well-known Wnt signaling regulator. Transcriptome-wide association analysis for these eQTLs revealed their additional associations with the expression of 29 genes (P < 4.75 × 10), including prickle planar cell polarity protein 2 (PRICKLE2) gene important for the Wnt signaling pathway. This concurs with previous studies in which significant expressional relationships between hTERT and some genes (β-catenin and Wnt-3a) in the Wnt signaling pathway have been observed.This study suggested 6 novel eQTLs for hTERT and the association of hTERT with the Wnt signaling pathway. Further studies are needed to understand their underlying mechanisms to improve our understanding of the role of hTERT in cancer.

  1. Linkage disequilibrium fine mapping of quantitative trait loci: A simulation study

    PubMed Central

    Abdallah, Jihad M; Goffinet, Bruno; Cierco-Ayrolles, Christine; Pérez-Enciso, Miguel

    2003-01-01

    Recently, the use of linkage disequilibrium (LD) to locate genes which affect quantitative traits (QTL) has received an increasing interest, but the plausibility of fine mapping using linkage disequilibrium techniques for QTL has not been well studied. The main objectives of this work were to (1) measure the extent and pattern of LD between a putative QTL and nearby markers in finite populations and (2) investigate the usefulness of LD in fine mapping QTL in simulated populations using a dense map of multiallelic or biallelic marker loci. The test of association between a marker and QTL and the power of the test were calculated based on single-marker regression analysis. The results show the presence of substantial linkage disequilibrium with closely linked marker loci after 100 to 200 generations of random mating. Although the power to test the association with a frequent QTL of large effect was satisfactory, the power was low for the QTL with a small effect and/or low frequency. More powerful, multi-locus methods may be required to map low frequent QTL with small genetic effects, as well as combining both linkage and linkage disequilibrium information. The results also showed that multiallelic markers are more useful than biallelic markers to detect linkage disequilibrium and association at an equal distance. PMID:12939203

  2. Mapping eQTL Networks with Mixed Graphical Markov Models

    PubMed Central

    Tur, Inma; Roverato, Alberto; Castelo, Robert

    2014-01-01

    Expression quantitative trait loci (eQTL) mapping constitutes a challenging problem due to, among other reasons, the high-dimensional multivariate nature of gene-expression traits. Next to the expression heterogeneity produced by confounding factors and other sources of unwanted variation, indirect effects spread throughout genes as a result of genetic, molecular, and environmental perturbations. From a multivariate perspective one would like to adjust for the effect of all of these factors to end up with a network of direct associations connecting the path from genotype to phenotype. In this article we approach this challenge with mixed graphical Markov models, higher-order conditional independences, and q-order correlation graphs. These models show that additive genetic effects propagate through the network as function of gene–gene correlations. Our estimation of the eQTL network underlying a well-studied yeast data set leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes. Interestingly, it also reveals that eQTLs explain most of the expression variability of network hub genes. PMID:25271303

  3. Empirical evaluation of neutral interactions in host-parasite networks.

    PubMed

    Canard, E F; Mouquet, N; Mouillot, D; Stanko, M; Miklisova, D; Gravel, D

    2014-04-01

    While niche-based processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 host-parasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite host-parasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization.

  4. An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci

    PubMed Central

    Ju, Jin Hyun; Crystal, Ronald G.

    2017-01-01

    Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In

  5. An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci.

    PubMed

    Ju, Jin Hyun; Shenoy, Sushila A; Crystal, Ronald G; Mezey, Jason G

    2017-05-01

    Genome-wide expression Quantitative Trait Loci (eQTL) studies in humans have provided numerous insights into the genetics of both gene expression and complex diseases. While the majority of eQTL identified in genome-wide analyses impact a single gene, eQTL that impact many genes are particularly valuable for network modeling and disease analysis. To enable the identification of such broad impact eQTL, we introduce CONFETI: Confounding Factor Estimation Through Independent component analysis. CONFETI is designed to address two conflicting issues when searching for broad impact eQTL: the need to account for non-genetic confounding factors that can lower the power of the analysis or produce broad impact eQTL false positives, and the tendency of methods that account for confounding factors to model broad impact eQTL as non-genetic variation. The key advance of the CONFETI framework is the use of Independent Component Analysis (ICA) to identify variation likely caused by broad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed model. We show that CONFETI has better performance than other mixed model confounding factor methods when considering broad impact eQTL recovery from synthetic data. We also used the CONFETI framework and these same confounding factor methods to identify eQTL that replicate between matched twin pair datasets in the Multiple Tissue Human Expression Resource (MuTHER), the Depression Genes Networks study (DGN), the Netherlands Study of Depression and Anxiety (NESDA), and multiple tissue types in the Genotype-Tissue Expression (GTEx) consortium. These analyses identified both cis-eQTL and trans-eQTL impacting individual genes, and CONFETI had better or comparable performance to other mixed model confounding factor analysis methods when identifying such eQTL. In these analyses, we were able to identify and replicate a few broad impact eQTL although the overall number was small even when applying CONFETI. In

  6. Mapping quantitative trait loci controlling milk production in dairy cattle by exploiting progeny testing

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

    Georges, M.; Nielsen, D.; Mackinnon, M.

    1995-02-01

    We have exploited {open_quotes}progeny testing{close_quotes} to map quantitative trait loci (QTL) underlying the genetic variation of milk production in a selected dairy cattle population. A total of 1,518 sires, with progeny tests based on the milking performances of >150,000 daughters jointly, was genotyped for 159 autosomal microsatellites bracketing 1645 centimorgan or approximately two thirds of the bovine genome. Using a maximum likelihood multilocus linkage analysis accounting for variance heterogeneity of the phenotypes, we identified five chromosomes giving very strong evidence (LOD score {ge} 3) for the presence of a QTL controlling milk production: chromosomes 1, 6, 9, 10 and 20.more » These findings demonstrate that loci with considerable effects on milk production are still segregating in highly selected populations and pave the way toward marker-assisted selection in dairy cattle breeding. 44 refs., 4 figs., 3 tabs.« less

  7. Differential contribution of genomic regions to marked genetic variation and prediction of quantitative traits in broiler chickens.

    PubMed

    Abdollahi-Arpanahi, Rostam; Morota, Gota; Valente, Bruno D; Kranis, Andreas; Rosa, Guilherme J M; Gianola, Daniel

    2016-02-03

    phenotypic variation for the three traits studied. Overall, the contribution of additive genetic variance to the total genetic variance was much greater than that of dominance variance. Our results show that all genomic regions are important for the prediction of the targeted traits, and the whole-genome approach was reaffirmed as the best tool for genome-enabled prediction of quantitative traits.

  8. Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

    PubMed

    Feltus, F Alex

    2014-06-01

    Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  9. Epistasis analysis for quantitative traits by functional regression model.

    PubMed

    Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao

    2014-06-01

    The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.

  10. Quantitative trait loci affecting lactose and total solids on chromosome 6 in Brazilian Gir dairy cattle.

    PubMed

    Silva, A A; Azevedo, A L S; Gasparini, K; Verneque, R S; Peixoto, M G C D; Panetto, B R; Guimarães, S E F; Machado, M A

    2011-10-31

    Fourteen Brazilian Gir sire families with 657 daughters were analyzed for quantitative trait loci (QTL) on chromosome 6 affecting lactose and total solids. Cows and sires were genotyped with 27 microsatellites with a mean spacing between markers of 4.9 cM. We used a 1% chromosome-wide threshold for QTL qualification. A QTL for lactose yield was found close to marker MNB66 in three families. A QTL for total solid yield was identified close to marker BMS2508 in three families. A QTL for lactose percentage, close to marker DIK1182, was identified in two families. A QTL for total solid percentage, close to marker MNB208, was identified in four families. These QTLs could be used for selection of animals in dairy production systems.

  11. A trait database for marine copepods

    NASA Astrophysics Data System (ADS)

    Brun, Philipp; Payne, Mark R.; Kiørboe, Thomas

    2017-02-01

    The trait-based approach is gaining increasing popularity in marine plankton ecology but the field urgently needs more and easier accessible trait data to advance. We compiled trait information on marine pelagic copepods, a major group of zooplankton, from the published literature and from experts and organized the data into a structured database. We collected 9306 records for 14 functional traits. Particular attention was given to body size, feeding mode, egg size, spawning strategy, respiration rate, and myelination (presence of nerve sheathing). Most records were reported at the species level, but some phylogenetically conserved traits, such as myelination, were reported at higher taxonomic levels, allowing the entire diversity of around 10 800 recognized marine copepod species to be covered with a few records. Aside from myelination, data coverage was highest for spawning strategy and body size, while information was more limited for quantitative traits related to reproduction and physiology. The database may be used to investigate relationships between traits, to produce trait biogeographies, or to inform and validate trait-based marine ecosystem models. The data can be downloaded from PANGAEA, doi:10.1594/PANGAEA.862968.

  12. Alterations of Brain Functional Architecture Associated with Psychopathic Traits in Male Adolescents with Conduct Disorder.

    PubMed

    Pu, Weidan; Luo, Qiang; Jiang, Yali; Gao, Yidian; Ming, Qingsen; Yao, Shuqiao

    2017-09-12

    Psychopathic traits of conduct disorder (CD) have a core callous-unemotional (CU) component and an impulsive-antisocial component. Previous task-driven fMRI studies have suggested that psychopathic traits are associated with dysfunction of several brain areas involved in different cognitive functions (e.g., empathy, reward, and response inhibition etc.), but the relationship between psychopathic traits and intrinsic brain functional architecture has not yet been explored in CD. Using a holistic brain-wide functional connectivity analysis, this study delineated the alterations in brain functional networks in patients with conduct disorder. Compared with matched healthy controls, we found decreased anti-synchronization between the fronto-parietal network (FPN) and default mode network (DMN), and increased intra-network synchronization within the frontothalamic-basal ganglia, right frontoparietal, and temporal/limbic/visual networks in CD patients. Correlation analysis showed that the weakened FPN-DMN interaction was associated with CU traits, while the heightened intra-network functional connectivity was related to impulsivity traits in CD patients. Our findings suggest that decoupling of cognitive control (FPN) with social understanding of others (DMN) is associated with the CU traits, and hyper-functions of the reward and motor inhibition systems elevate impulsiveness in CD.

  13. Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

    DOE PAGES

    Baldwin, Nicole E.; Chesler, Elissa J.; Kirov, Stefan; ...

    2005-01-01

    Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis -regulatory element discovery. Themore » causal basis for co-regulation is detected through the use of quantitative trait locus mapping.« less

  14. Deletion in a quantitative trait gene qPE9-1 associated with panicle erectness improves plant architecture during rice domestication.

    PubMed

    Zhou, Yong; Zhu, Jinyan; Li, Zhengyi; Yi, Chuandeng; Liu, Jun; Zhang, Honggen; Tang, Shuzhu; Gu, Minghong; Liang, Guohua

    2009-09-01

    Rice plant architecture is an important agronomic trait and a major determinant in high productivity. Panicle erectness is the preferred plant architecture in japonica rice, but the molecular mechanism underlying domestication of the erect panicle remains elusive. Here we report the map-based cloning of a major quantitative trait locus, qPE9-1, which plays an integral role in regulation of rice plant architecture including panicle erectness. The R6547 qPE9-1 gene encodes a 426-amino-acid protein, homologous to the keratin-associated protein 5-4 family. The gene is composed of three Von Willebrand factor type C domains, one transmembrane domain, and one 4-disulfide-core domain. Phenotypic comparisons of a set of near-isogenic lines and transgenic lines reveal that the functional allele (qPE9-1) results in drooping panicles, and the loss-of-function mutation (qpe9-1) leads to more erect panicles. In addition, the qPE9-1 locus regulates panicle and grain length, grain weight, and consequently grain yield. We propose that the panicle erectness trait resulted from a natural random loss-of-function mutation for the qPE9-1 gene and has subsequently been the target of artificial selection during japonica rice breeding.

  15. A journey from a SSR-based low density map to a SNP-based high density map for identification of disease resistance quantitative trait loci in peanut

    USDA-ARS?s Scientific Manuscript database

    Mapping and identification of quantitative trait loci (QTLs) are important for efficient marker-assisted breeding. Diseases such as leaf spots and Tomato spotted wilt virus (TSWV) cause significant loses to peanut growers. The U.S. Peanut Genome Initiative (PGI) was launched in 2004, and expanded to...

  16. Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

    PubMed Central

    2015-01-01

    Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN2 vs immediate flash freezing (iFF) in LN2 on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen. PMID:24927040

  17. Quantitative genetic correlation between trait and preference supports a sexually selected sperm process

    PubMed Central

    Simmons, Leigh W.; Kotiaho, Janne S.

    2007-01-01

    Sperm show patterns of rapid and divergent evolution that are characteristic of sexual selection. Sperm competition has been proposed as an important selective agent in the evolution of sperm morphology. However, several comparative analyses have revealed evolutionary associations between sperm length and female reproductive tract morphology that suggest patterns of male–female coevolution. In the dung beetle Onthophagus taurus, males with short sperm have a fertilization advantage that depends on the size of the female's sperm storage organ, the spermatheca; large spermathecae select for short sperm. Sperm length is heritable and is genetically correlated with male condition. Here we report significant additive genetic variation and heritability for spermatheca size and genetic covariance between spermatheca size and sperm length predicted by both the “good-sperm” and “sexy-sperm” models of postcopulatory female preference. Our data thus provide quantitative genetic support for the role of a sexually selected sperm process in the evolutionary divergence of sperm morphology, in much the same manner as precopulatory female preferences drive the evolutionary divergence of male secondary sexual traits. PMID:17921254

  18. SNP by SNP by environment interaction network of alcoholism.

    PubMed

    Zollanvari, Amin; Alterovitz, Gil

    2017-03-14

    Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP [Formula: see text]SNP[Formula: see text]E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits.

  19. Identifying gene networks underlying the neurobiology of ethanol and alcoholism.

    PubMed

    Wolen, Aaron R; Miles, Michael F

    2012-01-01

    For complex disorders such as alcoholism, identifying the genes linked to these diseases and their specific roles is difficult. Traditional genetic approaches, such as genetic association studies (including genome-wide association studies) and analyses of quantitative trait loci (QTLs) in both humans and laboratory animals already have helped identify some candidate genes. However, because of technical obstacles, such as the small impact of any individual gene, these approaches only have limited effectiveness in identifying specific genes that contribute to complex diseases. The emerging field of systems biology, which allows for analyses of entire gene networks, may help researchers better elucidate the genetic basis of alcoholism, both in humans and in animal models. Such networks can be identified using approaches such as high-throughput molecular profiling (e.g., through microarray-based gene expression analyses) or strategies referred to as genetical genomics, such as the mapping of expression QTLs (eQTLs). Characterization of gene networks can shed light on the biological pathways underlying complex traits and provide the functional context for identifying those genes that contribute to disease development.

  20. Quantitative trait loci and metabolic pathways: genetic control of the concentration of maysin, a corn earworm resistance factor, in maize silks.

    PubMed Central

    Byrne, P F; McMullen, M D; Snook, M E; Musket, T A; Theuri, J M; Widstrom, N W; Wiseman, B R; Coe, E H

    1996-01-01

    Interpretation of quantitative trait locus (QTL) studies of agronomic traits is limited by lack of knowledge of biochemical pathways leading to trait expression. To more fully elucidate the biological significance of detected QTL, we chose a trait that is the product of a well-characterized pathway, namely the concentration of maysin, a C-glycosyl flavone, in silks of maize, Zea mays L. Maysin is a host-plant resistance factor against the corn earworm, Helicoverpa zea (Boddie). We determined silk maysin concentrations and restriction fragment length polymorphism genotypes at flavonoid pathway loci or linked markers for 285 F2 plants derived from the cross of lines GT114 and GT119. Single-factor analysis of variance indicated that the p1 region on chromosome 1 accounted for 58.0% of the phenotypic variance and showed additive gene action. The p1 locus is a transcription activator for portions of the flavonoid pathway. A second QTL, represented by marker umc 105a near the brown pericarp1 locus on chromosome 9, accounted for 10.8% of the variance. Gene action of this region was dominant for low maysin, but was only expressed in the presence of a functional p1 allele. The model explaining the greatest proportion of phenotypic variance (75.9%) included p1, umc105a, umc166b (chromosome 1), r1 (chromosome 10), and two epistatic interaction terms, p1 x umc105a and p1 x r1. Our results provide evidence that regulatory loci have a central role and that there is a complex interplay among different branches of the flavonoid pathway in the expression of this trait. PMID:11607699

  1. A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

    PubMed Central

    Ficklin, Stephen P.; Feltus, Frank Alex

    2013-01-01

    Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with

  2. Measuring quantitative autism traits in families: informant effect or intergenerational transmission?

    PubMed

    De la Marche, Wouter; Noens, Ilse; Kuppens, Sofie; Spilt, Jantine L; Boets, Bart; Steyaert, Jean

    2015-04-01

    Autism spectrum disorders (ASD) have a high degree of heritability, but there is still much debate about specific causal genes and pathways. To gain insight into patterns of transmission, research has focused on the relatedness of quantitative autism traits (QAT) between family members, mostly using questionnaires. Yet, different kinds of bias may influence research results. In this paper, we focus on possible informant effects and, taking these into account, on possible intergenerational transmission of QAT. This study used multiple informant data retrieved via the Social Responsiveness Scale from 170 families with at least one member with ASD. Using intraclass correlations (ICCs) and mixed model analyses, we investigated inter-informant agreement and differences between parent and teacher reports on children and between self- and other-reports on adults. Using structural equation modelling (SEM), we investigated the relatedness of QAT between family members in ASD families. Parent-teacher agreement about social responsiveness was poor, especially for children with ASD, though agreement between parents was moderate to strong for affected and unaffected children. Agreement between self- and other-report in adult men was good, but only moderate in women. Agreement did not differ between adults with and without ASD. While accounting for informant effects, our SEM results corroborated the assortative mating theory and the intergenerational transmission of QAT from both fathers and mothers to their offspring.

  3. High-Density Genetic Linkage Map Construction and Quantitative Trait Locus Mapping for Hawthorn (Crataegus pinnatifida Bunge).

    PubMed

    Zhao, Yuhui; Su, Kai; Wang, Gang; Zhang, Liping; Zhang, Jijun; Li, Junpeng; Guo, Yinshan

    2017-07-14

    Genetic linkage maps are an important tool in genetic and genomic research. In this study, two hawthorn cultivars, Qiujinxing and Damianqiu, and 107 progenies from a cross between them were used for constructing a high-density genetic linkage map using the 2b-restriction site-associated DNA (2b-RAD) sequencing method, as well as for mapping quantitative trait loci (QTL) for flavonoid content. In total, 206,411,693 single-end reads were obtained, with an average sequencing depth of 57× in the parents and 23× in the progeny. After quality trimming, 117,896 high-quality 2b-RAD tags were retained, of which 42,279 were polymorphic; of these, 12,951 markers were used for constructing the genetic linkage map. The map contained 17 linkage groups and 3,894 markers, with a total map length of 1,551.97 cM and an average marker interval of 0.40 cM. QTL mapping identified 21 QTLs associated with flavonoid content in 10 linkage groups, which explained 16.30-59.00% of the variance. This is the first high-density linkage map for hawthorn, which will serve as a basis for fine-scale QTL mapping and marker-assisted selection of important traits in hawthorn germplasm and will facilitate chromosome assignment for hawthorn whole-genome assemblies in the future.

  4. Detection of quantitative trait loci causing abnormal spermatogenesis and reduced testis weight in the small testis (Smt) mutant mouse.

    PubMed

    Bolor, Hasbaira; Wakasugi, Noboru; Zhao, Wei Dong; Ishikawa, Akira

    2006-04-01

    The small testis (Smt) mutant mouse is characterized by a small testis of one third to one half the size of a normal testis, and its spermatogenesis is mostly arrested at early stages of meiosis, although a small number of spermatocytes at the late prophase of meiosis and a few spermatids can sometimes be seen. We performed quantitative trait locus (QTL) analysis of these spermatogenic traits and testis weight using 221 F2 males obtained from a cross between Smt and MOM (Mus musculus molossinus) mice. At the genome-wide 5% level, we detected two QTLs affecting meiosis on chromosomes 4 and 13, and two QTLs for paired testis weight as a percentage of body weight on chromosomes 4 and X. In addition, we found several QTLs for degenerated germ cells and multinuclear giant cells on chromosomes 4, 7 and 13. Interestingly, for cell degeneration, the QTL on chromosome 13 interacted epistatically with the QTL on chromosome 4. These results reveal polygenic participation in the abnormal spermatogenesis and small testis size in the Smt mutant.

  5. A genome scan for quantitative trait loci affecting cyanogenic potential of cassava root in an outbred population.

    PubMed

    Whankaew, Sukhuman; Poopear, Supannee; Kanjanawattanawong, Supanath; Tangphatsornruang, Sithichoke; Boonseng, Opas; Lightfoot, David A; Triwitayakorn, Kanokporn

    2011-05-25

    Cassava (Manihot esculenta Crantz) can produce cyanide, a toxic compound, without self-injury. That ability was called the cyanogenic potential (CN). This project aimed to identify quantitative trait loci (QTL) associated with the CN in an outbred population derived from 'Hanatee' × 'Huay Bong 60', two contrasting cultivars. CN was evaluated in 2008 and in 2009 at Rayong province, and in 2009 at Lop Buri province, Thailand. CN was measured using a picrate paper kit. QTL analysis affecting CN was performed with 303 SSR markers. The phenotypic values showed continuous variation with transgressive segregation events with more (115 ppm) and less CN (15 ppm) than either parent ('Hanatee' had 33 ppm and 'Huay Bong 60' had 95 ppm). The linkage map consisted of 303 SSR markers, on 27 linkage groups with a map that encompassed 1,328 cM. The average marker interval was 5.8 cM. Five QTL underlying CN were detected. CN08R1from 2008 at Rayong, CN09R1and CN09R2 from 2009 at Rayong, and CN09L1 and CN09L2 from 2009 at Lop Buri were mapped on linkage group 2, 5, 10 and 11, respectively. Among all the identified QTL, CN09R1 was the most significantly associated with the CN trait with LOD score 5.75 and explained the greatest percentage of phenotypic variation (%Expl.) of 26%. Five new QTL affecting CN were successfully identified from 4 linkage groups. Discovery of these QTL can provide useful markers to assist in cassava breeding and studying genes affecting the trait.

  6. A genome scan for quantitative trait loci affecting cyanogenic potential of cassava root in an outbred population

    PubMed Central

    2011-01-01

    Background Cassava (Manihot esculenta Crantz) can produce cyanide, a toxic compound, without self-injury. That ability was called the cyanogenic potential (CN). This project aimed to identify quantitative trait loci (QTL) associated with the CN in an outbred population derived from 'Hanatee' × 'Huay Bong 60', two contrasting cultivars. CN was evaluated in 2008 and in 2009 at Rayong province, and in 2009 at Lop Buri province, Thailand. CN was measured using a picrate paper kit. QTL analysis affecting CN was performed with 303 SSR markers. Results The phenotypic values showed continuous variation with transgressive segregation events with more (115 ppm) and less CN (15 ppm) than either parent ('Hanatee' had 33 ppm and 'Huay Bong 60' had 95 ppm). The linkage map consisted of 303 SSR markers, on 27 linkage groups with a map that encompassed 1,328 cM. The average marker interval was 5.8 cM. Five QTL underlying CN were detected. CN08R1from 2008 at Rayong, CN09R1and CN09R2 from 2009 at Rayong, and CN09L1 and CN09L2 from 2009 at Lop Buri were mapped on linkage group 2, 5, 10 and 11, respectively. Among all the identified QTL, CN09R1 was the most significantly associated with the CN trait with LOD score 5.75 and explained the greatest percentage of phenotypic variation (%Expl.) of 26%. Conclusions Five new QTL affecting CN were successfully identified from 4 linkage groups. Discovery of these QTL can provide useful markers to assist in cassava breeding and studying genes affecting the trait. PMID:21609492

  7. Ensemble learning of QTL models improves prediction of complex traits

    USDA-ARS?s Scientific Manuscript database

    Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability, but are less useful for genetic prediction due to difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage ...

  8. Improvement of baking quality traits through a diverse soft winter wheat population

    USDA-ARS?s Scientific Manuscript database

    Breeding baking quality improvements into soft winter wheat (SWW) entails crossing lines based on quality traits, assessing new lines, and repeating several times as little is known about the genetics of these traits. Previous research on SWW baking quality focused on quantitative trait locus and ge...

  9. Adjusting for treatment effects in studies of quantitative traits: antihypertensive therapy and systolic blood pressure.

    PubMed

    Tobin, Martin D; Sheehan, Nuala A; Scurrah, Katrina J; Burton, Paul R

    2005-10-15

    A population-based study of a quantitative trait may be seriously compromised when the trait is subject to the effects of a treatment. For example, in a typical study of quantitative blood pressure (BP) 15 per cent or more of middle-aged subjects may take antihypertensive treatment. Without appropriate correction, this can lead to substantial shrinkage in the estimated effect of aetiological determinants of scientific interest and a marked reduction in statistical power. Correction relies upon imputation, in treated subjects, of the underlying BP from the observed BP having invoked one or more assumptions about the bioclinical setting. There is a range of different assumptions that may be made, and a number of different analytical models that may be used. In this paper, we motivate an approach based on a censored normal regression model and compare it with a range of other methods that are currently used or advocated. We compare these methods in simulated data sets and assess the estimation bias and the loss of power that ensue when treatment effects are not appropriately addressed. We also apply the same methods to real data and demonstrate a pattern of behaviour that is consistent with that in the simulation studies. Although all approaches to analysis are necessarily approximations, we conclude that two of the adjustment methods appear to perform well across a range of realistic settings. These are: (1) the addition of a sensible constant to the observed BP in treated subjects; and (2) the censored normal regression model. A third, non-parametric, method based on averaging ordered residuals may also be advocated in some settings. On the other hand, three approaches that are used relatively commonly are fundamentally flawed and should not be used at all. These are: (i) ignoring the problem altogether and analysing observed BP in treated subjects as if it was underlying BP; (ii) fitting a conventional regression model with treatment as a binary covariate; and (iii

  10. Quantitative Trait Loci for High-Temperature Adult-Plant Resistance to Stripe Rust (Puccinia Striiformis f. sp. tritici) in a Hard Red Winter Wheat Germplasm IDO444

    USDA-ARS?s Scientific Manuscript database

    High-temperature adult-plant (HTAP) resistance to stripe rust (Puccinia striiformis f. sp. tritici) is a durable type of resistance in wheat. The objective of this study was to identify quantitative trait loci (QTL) conferring the HTAP resistance to stripe rust in a population consisted of 179 F7:8...

  11. Genome-wide QTL analysis for anxiety trait in bipolar disorder type I.

    PubMed

    Contreras, J; Hare, E; Chavarría-Soley, G; Raventós, H

    2018-07-01

    Genetic studies have been consistent that bipolar disorder type I (BPI) runs in families and that this familial aggregation is strongly influenced by genes. In a preliminary study, we proved that anxiety trait meets endophenotype criteria for BPI. We assessed 619 individuals from the Central Valley of Costa Rica (CVCR) who have received evaluation for anxiety following the same methodological procedure used for the initial pilot study. Our goal was to conduct a multipoint quantitative trait linkage analysis to identify quantitative trait loci (QTLs) related to anxiety trait in subjects with BPI. We conducted the statistical analyses using Quantitative Trait Loci method (Variance-components models), implemented in Sequential Oligogenic Linkage Analysis Routines (SOLAR), using 5606 single nucleotide polymorphism (SNPs). We identified a suggestive linkage signal with a LOD score of 2.01 at chromosome 2 (2q13-q14). Since confounding factors such as substance abuse, medical illness and medication history were not assessed in our study, these conclusions should be taken as preliminary. We conclude that region 2q13-q14 may harbor a candidate gene(s) with an important role in the pathophysiology of BPI and anxiety. Published by Elsevier B.V.

  12. Technical Note: Quantitative dynamic contrast-enhanced MRI of a 3-dimensional artificial capillary network.

    PubMed

    Gaass, Thomas; Schneider, Moritz Jörg; Dietrich, Olaf; Ingrisch, Michael; Dinkel, Julien

    2017-04-01

    Variability across devices, patients, and time still hinders widespread recognition of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as quantitative biomarker. The purpose of this work was to introduce and characterize a dedicated microchannel phantom as a model for quantitative DCE-MRI measurements. A perfusable, MR-compatible microchannel network was constructed on the basis of sacrificial melt-spun sugar fibers embedded in a block of epoxy resin. Structural analysis was performed on the basis of light microscopy images before DCE-MRI experiments. During dynamic acquisition the capillary network was perfused with a standard contrast agent injection system. Flow-dependency, as well as inter- and intrascanner reproducibility of the computed DCE parameters were evaluated using a 3.0 T whole-body MRI. Semi-quantitative and quantitative flow-related parameters exhibited the expected proportionality to the set flow rate (mean Pearson correlation coefficient: 0.991, P < 2.5e-5). The volume fraction was approximately independent from changes of the applied flow rate through the phantom. Repeatability and reproducibility experiments yielded maximum intrascanner coefficients of variation (CV) of 4.6% for quantitative parameters. All evaluated parameters were well in the range of known in vivo results for the applied flow rates. The constructed phantom enables reproducible, flow-dependent, contrast-enhanced MR measurements with the potential to facilitate standardization and comparability of DCE-MRI examinations. © 2017 American Association of Physicists in Medicine.

  13. The effectiveness of clinical networks in improving quality of care and patient outcomes: a systematic review of quantitative and qualitative studies.

    PubMed

    Brown, Bernadette Bea; Patel, Cyra; McInnes, Elizabeth; Mays, Nicholas; Young, Jane; Haines, Mary

    2016-08-08

    Reorganisation of healthcare services into networks of clinical experts is increasing as a strategy to promote the uptake of evidence based practice and to improve patient care. This is reflected in significant financial investment in clinical networks. However, there is still some question as to whether clinical networks are effective vehicles for quality improvement. The aim of this systematic review was to ascertain the effectiveness of clinical networks and identify how successful networks improve quality of care and patient outcomes. A systematic search was undertaken in accordance with the PRISMA approach in Medline, Embase, CINAHL and PubMed for relevant papers between 1 January 1996 and 30 September 2014. Established protocols were used separately to examine and assess the evidence from quantitative and qualitative primary studies and then integrate findings. A total of 22 eligible studies (9 quantitative; 13 qualitative) were included. Of the quantitative studies, seven focused on improving quality of care and two focused on improving patient outcomes. Quantitative studies were limited by a lack of rigorous experimental design. The evidence indicates that clinical networks can be effective vehicles for quality improvement in service delivery and patient outcomes across a range of clinical disciplines. However, there was variability in the networks' ability to make meaningful network- or system-wide change in more complex processes such as those requiring intensive professional education or more comprehensive redesign of care pathways. Findings from qualitative studies indicated networks that had a positive impact on quality of care and patients outcomes were those that had adequate resources, credible leadership and efficient management coupled with effective communication strategies and collaborative trusting relationships. There is evidence that clinical networks can improve the delivery of healthcare though there are few high quality quantitative

  14. Case-Deletion Diagnostics for Maximum Likelihood Multipoint Quantitative Trait Locus Linkage Analysis

    PubMed Central

    Mendoza, Maria C.B.; Burns, Trudy L.; Jones, Michael P.

    2009-01-01

    Objectives Case-deletion diagnostic methods are tools that allow identification of influential observations that may affect parameter estimates and model fitting conclusions. The goal of this paper was to develop two case-deletion diagnostics, the exact case deletion (ECD) and the empirical influence function (EIF), for detecting outliers that can affect results of sib-pair maximum likelihood quantitative trait locus (QTL) linkage analysis. Methods Subroutines to compute the ECD and EIF were incorporated into the maximum likelihood QTL variance estimation components of the linkage analysis program MAPMAKER/SIBS. Performance of the diagnostics was compared in simulation studies that evaluated the proportion of outliers correctly identified (sensitivity), and the proportion of non-outliers correctly identified (specificity). Results Simulations involving nuclear family data sets with one outlier showed EIF sensitivities approximated ECD sensitivities well for outlier-affected parameters. Sensitivities were high, indicating the outlier was identified a high proportion of the time. Simulations also showed the enormous computational time advantage of the EIF. Diagnostics applied to body mass index in nuclear families detected observations influential on the lod score and model parameter estimates. Conclusions The EIF is a practical diagnostic tool that has the advantages of high sensitivity and quick computation. PMID:19172086

  15. Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI.

    PubMed

    Li, Zhengjun; Vidorreta, Marta; Katchmar, Natalie; Alsop, David C; Wolf, Daniel H; Detre, John A

    2018-06-01

    Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Whole-genome scan to detect quantitative trait loci associated with milk protein composition in 3 French dairy cattle breeds.

    PubMed

    Sanchez, M P; Govignon-Gion, A; Ferrand, M; Gelé, M; Pourchet, D; Amigues, Y; Fritz, S; Boussaha, M; Capitan, A; Rocha, D; Miranda, G; Martin, P; Brochard, M; Boichard, D

    2016-10-01

    In the context of the PhénoFinLait project, a genome-wide analysis was performed to detect quantitative trait loci (QTL) that affect milk protein composition estimated using mid-infrared spectrometry in the Montbéliarde (MO), Normande (NO), and Holstein (HO) French dairy cattle breeds. The 6 main milk proteins (α-lactalbumin, β-lactoglobulin, and αS1-, αS2-, β-, and κ-caseins) expressed as grams per 100g of milk (% of milk) or as grams per 100g of protein (% of protein) were estimated in 848,068 test-day milk samples from 156,660 cows. Genotyping was performed for 2,773 MO, 2,673 NO, and 2,208 HO cows using the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). Individual test-day records were adjusted for environmental effects and then averaged per cow to define the phenotypes analyzed. Quantitative trait loci detection was performed within each breed using a linkage disequilibrium and linkage analysis approach. A total of 39 genomic regions distributed on 20 of the 29 Bos taurus autosomes (BTA) were significantly associated with milk protein composition at a genome-wide level of significance in at least 1 of the 3 breeds. The 9 most significant QTL were located on BTA2 (133 Mbp), BTA6 (38, 47, and 87 Mbp), BTA11 (103 Mbp), BTA14 (1.8 Mbp), BTA20 (32 and 58 Mbp), and BTA29 (8 Mbp). The BTA6 (87 Mbp), BTA11, and BTA20 (58 Mbp) QTL were found in all 3 breeds, and they had highly significant effects on κ-casein, β-lactoglobulin, and α-lactalbumin, expressed as a percentage of protein, respectively. Each of these QTL explained between 13% (BTA14) and 51% (BTA11) of the genetic variance of the trait. Many other QTL regions were also identified in at least one breed. They were located on 14 additional chromosomes (1, 3, 4, 5, 7, 15, 17, 19, 21, 22, 24, 25, 26, and 27), and they explained 2 to 8% of the genetic variance of 1 or more protein composition traits. Concordance analyses, performed between QTL status and sequence-derived polymorphisms from

  17. Better Cognitive Performance Is Associated With the Combination of High Trait Mindfulness and Low Trait Anxiety.

    PubMed

    Jaiswal, Satish; Tsai, Shao-Yang; Juan, Chi-Hung; Liang, Wei-Kuang; Muggleton, Neil G

    2018-01-01

    There are several ways in which cognitive and neurophysiological parameters have been consistently used to explain the variability in cognitive ability between people. However, little has been done to explore how such cognitive abilities are influenced by differences in personality traits. Dispositional mindfulness and anxiety are two inversely linked traits that have been independently attributed to a range of cognitive functions. The current study investigated these two traits in combination along with measures of the attentional network, cognitive inhibition, and visual working memory (VWM) capacity. A total of 392 prospective participants were screened to select two experimental groups each of 30 healthy young adults, with one having high mindfulness and low anxiety (HMLA) and the second having low mindfulness and high anxiety (LMHA). The groups performed an attentional network task, a color Stroop task, and a change detection test of VWM capacity. Results showed that the HMLA group was more accurate than the LMHA group on the Stroop and change detection tasks. Additionally, the HMLA group was more sensitive in detecting changes and had a higher WMC than the LMHA group. This research adds to the literature that has investigated mindfulness and anxiety independently with a comprehensive investigation of the effects of these two traits in conjunction on executive function.

  18. A Network Neuroscience of Human Learning: Potential To Inform Quantitative Theories of Brain and Behavior

    PubMed Central

    Bassett, Danielle S.; Mattar, Marcelo G.

    2017-01-01

    Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. PMID:28259554

  19. A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

    PubMed

    Bassett, Danielle S; Mattar, Marcelo G

    2017-04-01

    Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Associating quantitative behavioral traits with gene expression in the brain: searching for diamonds in the hay.

    PubMed

    Reiner-Benaim, Anat; Yekutieli, Daniel; Letwin, Noah E; Elmer, Gregory I; Lee, Norman H; Kafkafi, Neri; Benjamini, Yoav

    2007-09-01

    Gene expression and phenotypic functionality can best be associated when they are measured quantitatively within the same experiment. The analysis of such a complex experiment is presented, searching for associations between measures of exploratory behavior in mice and gene expression in brain regions. The analysis of such experiments raises several methodological problems. First and foremost, the size of the pool of potential discoveries being screened is enormous yet only few biologically relevant findings are expected, making the problem of multiple testing especially severe. We present solutions based on screening by testing related hypotheses, then testing the hypotheses of interest. In one variant the subset is selected directly, in the other one a tree of hypotheses is tested hierarchical; both variants control the False Discovery Rate (FDR). Other problems in such experiments are in the fact that the level of data aggregation may be different for the quantitative traits (one per animal) and gene expression measurements (pooled across animals); in that the association may not be linear; and in the resolution of interest only few replications exist. We offer solutions to these problems as well. The hierarchical FDR testing strategies presented here can serve beyond the structure of our motivating example study to any complex microarray study. Supplementary data are available at Bioinformatics online.

  1. Intercontinental convergence of stream fish community traits along geomorphic and hydraulic gradients

    USGS Publications Warehouse

    Lamouroux, N.; Poff, N.L.; Angermeier, P.L.

    2002-01-01

    Community convergence across biogeographically distinct regions suggests the existence of key, repeated, evolutionary mechanisms relating community characteristics to the environment. However, convergence studies at the community level often involve only qualitative comparisons of the environment and may fail to identify which environmental variables drive community structure. We tested the hypothesis that the biological traits of fish communities on two continents (Europe and North America) are similarly related to environmental conditions. Specifically, from observations of individual fish made at the microhabitat scale (a few square meters) within French streams, we generated habitat preference models linking traits of fish species to local scale hydraulic conditions (Froude number), Using this information, we then predicted how hydraulics and geomorphology at the larger scale of stream reaches (several pool-riffle sequences) should quantitatively influence the trait composition of fish communities. Trait composition for fishes in stream reaches with low Froude number at low flow or high proportion of pools was predicted as nonbenthic, large, fecund, long-lived, nonstreamlined, and weak swimmers. We tested our predictions in contrasting stream reaches in France (n = 11) and Virginia, USA (n = 76), using analyses of covariance to quantify the relative influence of continent vs. physical habitat variables on fish traits. The reach-scale convergence analysis indicated that trait proportions in the communities differed between continents (up to 55% of the variance in each trait was explained by "continent"), partly due to distinct evolutionary histories. However, within continents, trait proportions were comparably related to the hydraulic and geomorphic variables (up to 54% of the variance within continents explained). In particular, a synthetic measure of fish traits in reaches was well explained (50% of its variance) by the Froude number independently of the

  2. Spontaneous Trait Inferences on Social Media.

    PubMed

    Levordashka, Ana; Utz, Sonja

    2017-01-01

    The present research investigates whether spontaneous trait inferences occur under conditions characteristic of social media and networking sites: nonextreme, ostensibly self-generated content, simultaneous presentation of multiple cues, and self-paced browsing. We used an established measure of trait inferences (false recognition paradigm) and a direct assessment of impressions. Without being asked to do so, participants spontaneously formed impressions of people whose status updates they saw. Our results suggest that trait inferences occurred from nonextreme self-generated content, which is commonly found in social media updates (Experiment 1) and when nine status updates from different people were presented in parallel (Experiment 2). Although inferences did occur during free browsing, the results suggest that participants did not necessarily associate the traits with the corresponding status update authors (Experiment 3). Overall, the findings suggest that spontaneous trait inferences occur on social media. We discuss implications for online communication and research on spontaneous trait inferences.

  3. Composite Interval Mapping Based on Lattice Design for Error Control May Increase Power of Quantitative Trait Locus Detection.

    PubMed

    He, Jianbo; Li, Jijie; Huang, Zhongwen; Zhao, Tuanjie; Xing, Guangnan; Gai, Junyi; Guan, Rongzhan

    2015-01-01

    Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively.

  4. Validating the Adult Playfulness Trait Scale (APTS): An Examination of Personality, Behavior, Attitude, and Perception in the Nomological Network of Playfulness

    ERIC Educational Resources Information Center

    Shen, Xiangyou Sharon; Chick, Garry; Zinn, Harry

    2014-01-01

    The authors discuss the Adult Playfulness Trait Scale (APTS), a measurement that they developed along with a conceptualization of playfulness based on a synthesis of personality research and play literature. They assert the research they conducted, which examined the nomological network of playfulness and involved relevant constructs of…

  5. Genetic dissection of quantitative trait locus for ethanol sensitivity in long- and short-sleep mice.

    PubMed

    Bennett, B; Carosone-Link, P; Beeson, M; Gordon, L; Phares-Zook, N; Johnson, T E

    2008-08-01

    Interval-specific congenic strains (ISCS) allow fine mapping of a quantitative trait locus (QTL), narrowing its confidence interval by an order of magnitude or more. In earlier work, we mapped four QTL specifying differential ethanol sensitivity, assessed by loss of righting reflex because of ethanol (LORE), in the inbred long-sleep (ILS) and inbred short-sleep (ISS) strains, accounting for approximately 50% of the genetic variance for this trait. Subsequently, we generated reciprocal congenic strains in which each full QTL interval from ILS was bred onto the ISS background and vice versa. An earlier paper reported construction and results of the ISCS on the ISS background; here, we describe this process and report results on the ILS background. We developed multiple ISCS for each Lore QTL in which the QTL interval was broken into a number of smaller intervals. For each of the four QTL regions (chromosomes 1, 2, 11 and 15), we were successful in reducing the intervals significantly. Multiple, positive strains were overlapped to generate a single, reduced interval. Subsequently, this reduced region was overlaid on previous reductions from the ISS background congenics, resulting in substantial reductions in all QTL regions by approximately 75% from the initial mapping study. Genes with sequence or expression polymorphisms in the reduced intervals are potential candidates; evidence for these is presented. Genetic background effects can be important in detection of single QTL; combining this information with the generation of congenics on both backgrounds, as described here, is a powerful approach for fine mapping QTL.

  6. Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants.

    PubMed

    Iso-Touru, T; Sahana, G; Guldbrandtsen, B; Lund, M S; Vilkki, J

    2016-03-22

    The Nordic Red Cattle consisting of three different populations from Finland, Sweden and Denmark are under a joint breeding value estimation system. The long history of recording of production and health traits offers a great opportunity to study production traits and identify causal variants behind them. In this study, we used whole genome sequence level data from 4280 progeny tested Nordic Red Cattle bulls to scan the genome for loci affecting milk, fat and protein yields. Using a genome-wise significance threshold, regions on Bos taurus chromosomes 5, 14, 23, 25 and 26 were associated with fat yield. Regions on chromosomes 5, 14, 16, 19, 20 and 25 were associated with milk yield and chromosomes 5, 14 and 25 had regions associated with protein yield. Significantly associated variations were found in 227 genes for fat yield, 72 genes for milk yield and 30 genes for protein yield. Ingenuity Pathway Analysis was used to identify networks connecting these genes displaying significant hits. When compared to previously mapped genomic regions associated with fertility, significantly associated variations were found in 5 genes common for fat yield and fertility, thus linking these two traits via biological networks. This is the first time when whole genome sequence data is utilized to study genomic regions affecting milk production in the Nordic Red Cattle population. Sequence level data offers the possibility to study quantitative traits in detail but still cannot unambiguously reveal which of the associated variations is causative. Linkage disequilibrium creates difficulties to pinpoint the causative genes and variations. One solution to overcome these difficulties is the identification of the functional gene networks and pathways to reveal important interacting genes as candidates for the observed effects. This information on target genomic regions may be exploited to improve genomic prediction.

  7. Quantitative analysis of volatile organic compounds using ion mobility spectra and cascade correlation neural networks

    NASA Technical Reports Server (NTRS)

    Harrington, Peter DEB.; Zheng, Peng

    1995-01-01

    Ion Mobility Spectrometry (IMS) is a powerful technique for trace organic analysis in the gas phase. Quantitative measurements are difficult, because IMS has a limited linear range. Factors that may affect the instrument response are pressure, temperature, and humidity. Nonlinear calibration methods, such as neural networks, may be ideally suited for IMS. Neural networks have the capability of modeling complex systems. Many neural networks suffer from long training times and overfitting. Cascade correlation neural networks train at very fast rates. They also build their own topology, that is a number of layers and number of units in each layer. By controlling the decay parameter in training neural networks, reproducible and general models may be obtained.

  8. Two Quantitative Trait Loci Influence Whipworm (Trichuris trichiura) Infection in a Nepalese Population

    PubMed Central

    Williams-Blangero, Sarah; VandeBerg, John L.; Subedi, Janardan; Jha, Bharat; Dyer, T.D.; Blangero, John

    2014-01-01

    Background Whipworm (Trichuris trichiura) is a soil-transmitted helminth which infects over a billion people. It is a serious public health problem in many developing countries and can result in deficits in growth and cognitive development. In a follow-up study of a significant heritability for whipworm infection, we conducted the first genome scan for susceptibility to this important parasitic disease. Methods We assessed whipworm eggs per gram of feces in 1253 members of the Jirel population of eastern Nepal. All sampled individuals belonged to a single pedigree containing over 26,000 relative pairs that are informative for genetic analysis. Results Linkage analysis of genome scan data generated for the pedigree provided unambiguous evidence for two quantitative trait loci influencing susceptibility to whipworm infection, one located on chromosome 9 (LOD = 3.35, genome-wide p = 0.0138) and the other located on chromosome 18 (LOD = 3.29, genome-wide p = 0.0159). There was also suggestive evidence for two loci located on chromosomes 12 and 13 influencing whipworm infection. Conclusion The results of this first genome scan for susceptibility to whipworm infection may ultimately lead to the identification of novel targets for vaccine and drug development efforts. PMID:18462166

  9. Quantitative evaluation of simulated functional brain networks in graph theoretical analysis.

    PubMed

    Lee, Won Hee; Bullmore, Ed; Frangou, Sophia

    2017-02-01

    There is increasing interest in the potential of whole-brain computational models to provide mechanistic insights into resting-state brain networks. It is therefore important to determine the degree to which computational models reproduce the topological features of empirical functional brain networks. We used empirical connectivity data derived from diffusion spectrum and resting-state functional magnetic resonance imaging data from healthy individuals. Empirical and simulated functional networks, constrained by structural connectivity, were defined based on 66 brain anatomical regions (nodes). Simulated functional data were generated using the Kuramoto model in which each anatomical region acts as a phase oscillator. Network topology was studied using graph theory in the empirical and simulated data. The difference (relative error) between graph theory measures derived from empirical and simulated data was then estimated. We found that simulated data can be used with confidence to model graph measures of global network organization at different dynamic states and highlight the sensitive dependence of the solutions obtained in simulated data on the specified connection densities. This study provides a method for the quantitative evaluation and external validation of graph theory metrics derived from simulated data that can be used to inform future study designs. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  10. Detection of expression quantitative trait Loci in complex mouse crosses: impact and alleviation of data quality and complex population substructure.

    PubMed

    Iancu, Ovidiu D; Darakjian, Priscila; Kawane, Sunita; Bottomly, Daniel; Hitzemann, Robert; McWeeney, Shannon

    2012-01-01

    Complex Mus musculus crosses, e.g., heterogeneous stock (HS), provide increased resolution for quantitative trait loci detection. However, increased genetic complexity challenges detection methods, with discordant results due to low data quality or complex genetic architecture. We quantified the impact of theses factors across three mouse crosses and two different detection methods, identifying procedures that greatly improve detection quality. Importantly, HS populations have complex genetic architectures not fully captured by the whole genome kinship matrix, calling for incorporating chromosome specific relatedness information. We analyze three increasingly complex crosses, using gene expression levels as quantitative traits. The three crosses were an F(2) intercross, a HS formed by crossing four inbred strains (HS4), and a HS (HS-CC) derived from the eight lines found in the collaborative cross. Brain (striatum) gene expression and genotype data were obtained using the Illumina platform. We found large disparities between methods, with concordance varying as genetic complexity increased; this problem was more acute for probes with distant regulatory elements (trans). A suite of data filtering steps resulted in substantial increases in reproducibility. Genetic relatedness between samples generated overabundance of detected eQTLs; an adjustment procedure that includes the kinship matrix attenuates this problem. However, we find that relatedness between individuals is not evenly distributed across the genome; information from distinct chromosomes results in relatedness structure different from the whole genome kinship matrix. Shared polymorphisms from distinct chromosomes collectively affect expression levels, confounding eQTL detection. We suggest that considering chromosome specific relatedness can result in improved eQTL detection.

  11. Quantitative trait loci mapping of the mouse plasma proteome (pQTL).

    PubMed

    Holdt, Lesca M; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

    2013-02-01

    A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F(2) intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins.

  12. Evidence of a novel quantitative-trait locus for obesity on chromosome 4p in Mexican Americans.

    PubMed

    Arya, Rector; Duggirala, Ravindranath; Jenkinson, Christopher P; Almasy, Laura; Blangero, John; O'Connell, Peter; Stern, Michael P

    2004-02-01

    Although several genomewide scans have identified quantitative-trait loci influencing several obesity-related traits in humans, genes influencing normal variation in obesity phenotypes have not yet been identified. We therefore performed a genome scan of body mass index (BMI) on Mexican Americans, a population prone to obesity and diabetes, using a variance-components linkage analysis to identify loci that influence BMI. We used phenotypic data from 430 individuals (26% diabetics, 59% females, mean age +/- SD = 43 +/- 17 years, mean BMI +/- SD = 30.0 +/- 6.7, mean leptin (ng/ml) +/- SD = 22.1 +/- 17.1) distributed across 27 low-income Mexican American pedigrees who participated in the San Antonio Family Diabetes Study (SAFDS) for whom a 10-15-cM map is available. In this genomewide search, after accounting for the covariate effects of age, sex, diabetes, and leptin, we identified a genetic region exhibiting the most highly significant evidence for linkage (LOD 4.5) with BMI on chromosome 4p (4p15.1) at 42 cM, near marker D4S2912. This linkage result has been confirmed in an independent linkage study of severe obesity in Utah pedigrees. Two strong positional candidates, the human peroxisome proliferator-activated receptor gamma coactivator 1 (PPARGC1) and cholecystokinin A receptor (CCKAR) with major roles in the development of obesity, are located in this region. In conclusion, we identified a major genetic locus influencing BMI on chromosome 4p in Mexican Americans.

  13. Neural Basis of Interpersonal Traits in Neurodegenerative Diseases

    PubMed Central

    Sollberger, Marc; Stanley, Christine M.; Wilson, Stephen M.; Gyurak, Anett; Beckman, Victoria; Growdon, Matthew; Jang, Jung; Weiner, Michael W.; Miller, Bruce L.; Rankin, Katherine P.

    2009-01-01

    Several functional and structural imaging studies have investigated the neural basis of personality in healthy adults, but human lesions studies are scarce. Personality changes are a common symptom in patients with neurodegenerative diseases like frontotemporal dementia (FTD) and semantic dementia (SD), allowing a unique window into the neural basis of personality. In this study, we used the Interpersonal Adjective Scales to investigate the structural basis of eight interpersonal traits (dominance, arrogance, coldness, introversion, submissiveness, ingenuousness, warmth, and extraversion) in 257 subjects: 214 patients with neurodegenerative diseases such as FTD, SD, progressive non-fluent aphasia, Alzheimer’s disease, amnestic mild cognitive impairment, corticobasal degeneration, and progressive supranuclear palsy and 43 healthy elderly people. Measures of interpersonal traits were correlated with regional atrophy pattern using voxel-based morphometry (VBM) analysis of structural MR images. Interpersonal traits mapped onto distinct brain regions depending on the degree to which they involved agency and affiliation. Interpersonal traits high in agency related to left dorsolateral prefrontal and left lateral frontopolar regions, whereas interpersonal traits high in affiliation related to right ventromedial prefrontal and right anteromedial temporal regions. Consistent with the existing literature on neural networks underlying social cognition, these results indicate that brain regions related to externally-focused, executive control-related processes underlie agentic interpersonal traits such as dominance, whereas brain regions related to internally-focused, emotion- and reward-related processes underlie affiliative interpersonal traits such as warmth. In addition, these findings indicate that interpersonal traits are subserved by complex neural networks rather than discrete anatomic areas. PMID:19540253

  14. Quantitative trait loci analyses and RNA-seq identify genes affecting stress response in rainbow trout

    USDA-ARS?s Scientific Manuscript database

    Genomic analyses have the potential to impact aquaculture production traits by identifying markers as proxies for traits which are expensive or difficult to measure and characterizing genetic variation and biochemical mechanisms underlying phenotypic variation. One such trait is the response of rai...

  15. Genetic basis of climatic adaptation in scots pine by bayesian quantitative trait locus analysis.

    PubMed Central

    Hurme, P; Sillanpää, M J; Arjas, E; Repo, T; Savolainen, O

    2000-01-01

    We examined the genetic basis of large adaptive differences in timing of bud set and frost hardiness between natural populations of Scots pine. As a mapping population, we considered an "open-pollinated backcross" progeny by collecting seeds of a single F(1) tree (cross between trees from southern and northern Finland) growing in southern Finland. Due to the special features of the design (no marker information available on grandparents or the father), we applied a Bayesian quantitative trait locus (QTL) mapping method developed previously for outcrossed offspring. We found four potential QTL for timing of bud set and seven for frost hardiness. Bayesian analyses detected more QTL than ANOVA for frost hardiness, but the opposite was true for bud set. These QTL included alleles with rather large effects, and additionally smaller QTL were supported. The largest QTL for bud set date accounted for about a fourth of the mean difference between populations. Thus, natural selection during adaptation has resulted in selection of at least some alleles of rather large effect. PMID:11063704

  16. Over-seasons analysis of quantitative trait loci affecting phenolic content and antioxidant capacity in raspberry.

    PubMed

    Dobson, Patricia; Graham, Julie; Stewart, D; Brennan, Rex; Hackett, Christine A; McDougall, Gordon J

    2012-05-30

    This study examined the total phenol content (TPC) and total anthocyanin content (TAC) in ripe fruit of progeny of a mapping population generated from a cross between the European red raspberry cv. Glen Moy ( Rubus ideaus var. idaeus) and the North American red raspberry cv. Latham ( Rubus ideaus var. strigosus) over five seasons in two different growing environments. Measurements of antioxidant capacity (FRAP and TEAC) were also carried out. TPC was highly correlated with TEAC and FRAP across the entire data set. The subset of anthocyanin content was genotype-dependent but also correlated with TPC, although the proportion of anthocyanin compounds varied between progeny. Quantitative trait locus (QTL) analysis was carried out, and key markers were tested for consistency of effects over sites and years. Four regions, on linkage groups 2, 3, 5, and 6, were identified. These agree with QTLs from a previous study over a single season and indicate that QTL effects were robust over seasons.

  17. PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies.

    PubMed

    Zhang, Wenchao; Dai, Xinbin; Wang, Qishan; Xu, Shizhong; Zhao, Patrick X

    2016-05-01

    The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.

  18. Quantitative petri net model of gene regulated metabolic networks in the cell.

    PubMed

    Chen, Ming; Hofestädt, Ralf

    2011-01-01

    A method to exploit hybrid Petri nets (HPN) for quantitatively modeling and simulating gene regulated metabolic networks is demonstrated. A global kinetic modeling strategy and Petri net modeling algorithm are applied to perform the bioprocess functioning and model analysis. With the model, the interrelations between pathway analysis and metabolic control mechanism are outlined. Diagrammatical results of the dynamics of metabolites are simulated and observed by implementing a HPN tool, Visual Object Net ++. An explanation of the observed behavior of the urea cycle is proposed to indicate possibilities for metabolic engineering and medical care. Finally, the perspective of Petri nets on modeling and simulation of metabolic networks is discussed.

  19. Linking imaging spectroscopy and trait data to better understand spatial and temporal variability in functional traits

    NASA Astrophysics Data System (ADS)

    Townsend, Philip; Kruger, Eric; Wang, Zhihui; Singh, Aditya

    2017-04-01

    Imaging spectroscopy exhibits great potential for mapping foliar functional traits that are impractical or expensive to regularly measure on the ground, and are essentially impossible to characterize comprehensively across space. Specifically, the high information content in spectroscopic data enables us to identify narrow spectral feature that are associated with vegetation primary and secondary biochemistry (nutrients, pigments, defensive compounds), leaf structure (e.g., leaf mass per area), canopy structure, and physiological capacity. Ultimately, knowledge of the variability in such traits is critical to understanding vegetation productivity, as well as responses to climatic variability, disturbances, pests and pathogens. The great challenge to the use of imaging spectroscopy to supplement trait databases is the development of trait retrieval approaches that are broadly applicable within and between ecosystem types. Here, we outline how we are using the US National Ecological Observatory Network (NEON) to prototype the scaling and comparison of trait distributions derived from field measurements and imagery. We find that algorithms to map traits from imagery are robust across ecosystem types, when controlling for physiognomy and vegetation percent cover, and that among all vegetation types, the chemometric algorithms utilize similar features for mapping of traits.

  20. The Strategic Environment Assessment bibliographic network: A quantitative literature review analysis

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

    Caschili, Simone, E-mail: s.caschili@ucl.ac.uk; De Montis, Andrea; Ganciu, Amedeo

    2014-07-01

    Academic literature has been continuously growing at such a pace that it can be difficult to follow the progression of scientific achievements; hence, the need to dispose of quantitative knowledge support systems to analyze the literature of a subject. In this article we utilize network analysis tools to build a literature review of scientific documents published in the multidisciplinary field of Strategic Environment Assessment (SEA). The proposed approach helps researchers to build unbiased and comprehensive literature reviews. We collect information on 7662 SEA publications and build the SEA Bibliographic Network (SEABN) employing the basic idea that two publications are interconnectedmore » if one cites the other. We apply network analysis at macroscopic (network architecture), mesoscopic (sub graph) and microscopic levels (node) in order to i) verify what network structure characterizes the SEA literature, ii) identify the authors, disciplines and journals that are contributing to the international discussion on SEA, and iii) scrutinize the most cited and important publications in the field. Results show that the SEA is a multidisciplinary subject; the SEABN belongs to the class of real small world networks with a dominance of publications in Environmental studies over a total of 12 scientific sectors. Christopher Wood, Olivia Bina, Matthew Cashmore, and Andrew Jordan are found to be the leading authors while Environmental Impact Assessment Review is by far the scientific journal with the highest number of publications in SEA studies. - Highlights: • We utilize network analysis to analyze scientific documents in the SEA field. • We build the SEA Bibliographic Network (SEABN) of 7662 publications. • We apply network analysis at macroscopic, mesoscopic and microscopic network levels. • We identify SEABN architecture, relevant publications, authors, subjects and journals.« less

  1. Identification of bioconversion quantitative trait loci in the interspecific cross Sorghum bicolor × Sorghum propinquum.

    PubMed

    Vandenbrink, Joshua P; Goff, Valorie; Jin, Huizhe; Kong, Wenqian; Paterson, Andrew H; Feltus, F Alex

    2013-09-01

    For lignocellulosic bioenergy to be economically viable, genetic improvements must be made in feedstock quality including both biomass total yield and conversion efficiency. Toward this goal, multiple studies have considered candidate genes and discovered quantitative trait loci (QTL) associated with total biomass accumulation and/or grain production in bioenergy grass species including maize and sorghum. However, very little research has been focused on genes associated with increased biomass conversion efficiency. In this study, Trichoderma viride fungal cellulase hydrolysis activity was measured for lignocellulosic biomass (leaf and stem tissue) obtained from individuals in a F5 recombinant inbred Sorghum bicolor × Sorghum propinquum mapping population. A total of 49 QTLs (20 leaf, 29 stem) were associated with enzymatic conversion efficiency. Interestingly, six high-density QTL regions were identified in which four or more QTLs overlapped. In addition to enzymatic conversion efficiency QTLs, two QTLs were identified for biomass crystallinity index, a trait which has been shown to be inversely correlated with conversion efficiency in bioenergy grasses. The identification of these QTLs provides an important step toward identifying specific genes relevant to increasing conversion efficiency of bioenergy feedstocks. DNA markers linked to these QTLs could be useful in marker-assisted breeding programs aimed at increasing overall bioenergy yields concomitant with selection of high total biomass genotypes.

  2. A traits-based approach for prioritizing species for monitoring and surrogacy selection

    DOE PAGES

    Pracheil, Brenda M.; McManamay, Ryan A.; Bevelhimer, Mark S.; ...

    2016-11-28

    The bar for justifying the use of vertebrate animals for study is being increasingly raised, thus requiring increased rigor for species selection and study design. Although we have power analyses to provide quantitative backing for the numbers of organisms used, quantitative backing for selection of study species is not frequently employed. This can be especially important when measuring the impacts of ecosystem alteration, when study species must be chosen that are both sensitive to the alteration and of sufficient abundance for study. Just as important is providing justification for designation of surrogate species for study, especially when the species ofmore » interest is rare or of conservation concern and selection of an appropriate surrogate can have legal implications. In this study, we use a combination of GIS, a fish traits database and multivariate statistical analyses to quantitatively prioritize species for study and to determine potential study surrogate species. We provide two case studies to illustrate our quantitative, traits-based approach for designating study species and surrogate species. In the first case study, we select broadly representative fish species to understand the effects of turbine passage on adult fishes based on traits that suggest sensitivity to turbine passage. In our second case study, we present a framework for selecting a surrogate species for an endangered species. Lastly, we suggest that our traits-based framework can provide quantitative backing and added justification to selection of study species while expanding the inference space of study results.« less

  3. A traits-based approach for prioritizing species for monitoring and surrogacy selection

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

    Pracheil, Brenda M.; McManamay, Ryan A.; Bevelhimer, Mark S.

    The bar for justifying the use of vertebrate animals for study is being increasingly raised, thus requiring increased rigor for species selection and study design. Although we have power analyses to provide quantitative backing for the numbers of organisms used, quantitative backing for selection of study species is not frequently employed. This can be especially important when measuring the impacts of ecosystem alteration, when study species must be chosen that are both sensitive to the alteration and of sufficient abundance for study. Just as important is providing justification for designation of surrogate species for study, especially when the species ofmore » interest is rare or of conservation concern and selection of an appropriate surrogate can have legal implications. In this study, we use a combination of GIS, a fish traits database and multivariate statistical analyses to quantitatively prioritize species for study and to determine potential study surrogate species. We provide two case studies to illustrate our quantitative, traits-based approach for designating study species and surrogate species. In the first case study, we select broadly representative fish species to understand the effects of turbine passage on adult fishes based on traits that suggest sensitivity to turbine passage. In our second case study, we present a framework for selecting a surrogate species for an endangered species. Lastly, we suggest that our traits-based framework can provide quantitative backing and added justification to selection of study species while expanding the inference space of study results.« less

  4. Identification of Quantitative Trait Loci Conditioning the Main Biomass Yield Components and Resistance to Melampsora spp. in Salix viminalis × Salix schwerinii Hybrids

    PubMed Central

    Sulima, Paweł; Przyborowski, Jerzy A.; Kuszewska, Anna; Załuski, Dariusz; Jędryczka, Małgorzata; Irzykowski, Witold

    2017-01-01

    The biomass of Salix viminalis is the most highly valued source of green energy, followed by S. schwerinii, S. dasyclados and other species. Significant variability in productivity and leaf rust resistance are noted both within and among willow species, which creates new opportunities for improving willow yield parameters through selection of desirable recombinants supported with molecular markers. The aim of this study was to identify quantitative trait loci (QTLs) linked with biomass yield-related traits and the resistance/susceptibility of Salix mapping population to leaf rust. The experimental material comprised a mapping population developed based on S. viminalis × S. schwerinii hybrids. Phenotyping was performed on plants grown in a field experiment that had a balanced incomplete block design with 10 replications. Based on a genetic map, 11 QTLs were identified for plant height, 9 for shoot diameter, 3 for number of shoots and 11 for resistance/susceptibility to leaf rust. The QTLs identified in our study explained 3%–16% of variability in the analyzed traits. Our findings make significant contributions to the development of willow breeding programs and research into shrubby willow crops grown for energy. PMID:28327519

  5. Detection of QTL for forage yield, lodging resistance and spring vigor traits in alfalfa (Medicago sativa L.)

    USDA-ARS?s Scientific Manuscript database

    Alfalfa (Medicago sativa L.) is an internationally significant forage crop. Forage yield, lodging resistance and spring vigor are important agronomic traits conditioned by quantitative genetic and environmental effects. The objective of this study was to identify quantitative trait loci (QTL) and mo...

  6. Analysis of Sequence Data Under Multivariate Trait-Dependent Sampling.

    PubMed

    Tao, Ran; Zeng, Donglin; Franceschini, Nora; North, Kari E; Boerwinkle, Eric; Lin, Dan-Yu

    2015-06-01

    High-throughput DNA sequencing allows for the genotyping of common and rare variants for genetic association studies. At the present time and for the foreseeable future, it is not economically feasible to sequence all individuals in a large cohort. A cost-effective strategy is to sequence those individuals with extreme values of a quantitative trait. We consider the design under which the sampling depends on multiple quantitative traits. Under such trait-dependent sampling, standard linear regression analysis can result in bias of parameter estimation, inflation of type I error, and loss of power. We construct a likelihood function that properly reflects the sampling mechanism and utilizes all available data. We implement a computationally efficient EM algorithm and establish the theoretical properties of the resulting maximum likelihood estimators. Our methods can be used to perform separate inference on each trait or simultaneous inference on multiple traits. We pay special attention to gene-level association tests for rare variants. We demonstrate the superiority of the proposed methods over standard linear regression through extensive simulation studies. We provide applications to the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study and the National Heart, Lung, and Blood Institute Exome Sequencing Project.

  7. Chromosomal mapping of quantitative trait loci controlling elastin content in rat aorta.

    PubMed

    Gauguier, Dominique; Behmoaras, Jacques; Argoud, Karène; Wilder, Steven P; Pradines, Christelle; Bihoreau, Marie Thérèse; Osborne-Pellegrin, Mary; Jacob, Marie Paule

    2005-03-01

    Extracellular matrix molecules such as elastin and collagens provide mechanical support to the vessel wall. In addition to its structural role, elastin is a regulator that maintains homeostasis through biologic signaling. Genetically determined minor modifications in elastin and collagen in the aorta could influence the onset and evolution of arterial pathology, such as hypertension and its complications. We previously demonstrated that the inbred Brown Norway (BN) rat shows an aortic elastin deficit in both abdominal and thoracic segments, partly because of a decrease in tropoelastin synthesis when compared with the LOU rat, that elastin gene polymorphisms in these strains do not significantly account for. After a genome-wide search for quantitative trait loci (QTL) influencing the aortic elastin, collagen, and cell protein contents in an F2 population derived from BN and LOU rats, we identified on chromosomes 2 and 14, 3 QTL specifically controlling elastin levels, and a further highly significant QTL on chromosome 17 linked to the level of cell proteins. We also mapped 3 highly significant QTL linked to body weight (on chromosomes 1 and 3) and heart weight (on chromosome 1) in the cross. This study demonstrates the polygenic control of the content of key components of the arterial wall. Such information represents a first step in understanding possible mechanisms involved in dysregulation of these parameters in arterial pathology.

  8. Boron toxicity in rice (Oryza sativa L.). I. Quantitative trait locus (QTL) analysis of tolerance to boron toxicity.

    PubMed

    Ochiai, K; Uemura, S; Shimizu, A; Okumoto, Y; Matoh, T

    2008-06-01

    Boron toxicity tolerance of rice plants was studied. Modern japonica subspecies such as Koshihikari, Nipponbare, and Sasanishiki were tolerant, whereas indica subspecies such as Kasalath and IR36 were intolerant to excessive application of boron (B), even though their shoot B contents under B toxicity were not significantly different. Recombinant inbred lines (RILs) of japonica Nekken-1 and indica IR36 were used for quantitative trait locus (QTL) analysis to identify the gene responsible for B toxicity tolerance. A major QTL that could explain 45% of the phenotypic variation was detected in chromosome 4. The QTL was confirmed using a population derived from a recombinant inbred line which is heterogenic at the QTL region. The QTL was also confirmed in other chromosome segment substitution lines (CSSLs).

  9. Comparison of gene-based rare variant association mapping methods for quantitative traits in a bovine population with complex familial relationships.

    PubMed

    Zhang, Qianqian; Guldbrandtsen, Bernt; Calus, Mario P L; Lund, Mogens Sandø; Sahana, Goutam

    2016-08-17

    There is growing interest in the role of rare variants in the variation of complex traits due to increasing evidence that rare variants are associated with quantitative traits. However, association methods that are commonly used for mapping common variants are not effective to map rare variants. Besides, livestock populations have large half-sib families and the occurrence of rare variants may be confounded with family structure, which makes it difficult to disentangle their effects from family mean effects. We compared the power of methods that are commonly applied in human genetics to map rare variants in cattle using whole-genome sequence data and simulated phenotypes. We also studied the power of mapping rare variants using linear mixed models (LMM), which are the method of choice to account for both family relationships and population structure in cattle. We observed that the power of the LMM approach was low for mapping a rare variant (defined as those that have frequencies lower than 0.01) with a moderate effect (5 to 8 % of phenotypic variance explained by multiple rare variants that vary from 5 to 21 in number) contributing to a QTL with a sample size of 1000. In contrast, across the scenarios studied, statistical methods that are specialized for mapping rare variants increased power regardless of whether multiple rare variants or a single rare variant underlie a QTL. Different methods for combining rare variants in the test single nucleotide polymorphism set resulted in similar power irrespective of the proportion of total genetic variance explained by the QTL. However, when the QTL variance is very small (only 0.1 % of the total genetic variance), these specialized methods for mapping rare variants and LMM generally had no power to map the variants within a gene with sample sizes of 1000 or 5000. We observed that the methods that combine multiple rare variants within a gene into a meta-variant generally had greater power to map rare variants compared

  10. Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: I. egg production traits.

    PubMed

    Goraga, Z S; Nassar, M K; Brockmann, G A

    2012-04-01

    A genome scan was performed to detect chromosomal regions that affect egg production traits in reciprocal crosses between two genetically and phenotypically extreme chicken lines: the partially inbred line New Hampshire (NHI) and the inbred line White Leghorn (WL77). The NHI line had been selected for high growth and WL77 for low egg weight before inbreeding. The result showed a highly significant region on chromosome 4 with multiple QTL for egg production traits between 19.2 and 82.1 Mb. This QTL region explained 4.3 and 16.1% of the phenotypic variance for number of eggs and egg weight in the F(2) population, respectively. The egg weight QTL effects are dependent on the direction of the cross. In addition, genome-wide suggestive QTL for egg weight were found on chromosomes 1, 5, and 9, and for number of eggs on chromosomes 5 and 7. A genome-wide significant QTL affecting age at first egg was mapped on chromosome 1. The difference between the parental lines and the highly significant QTL effects on chromosome 4 will further support fine mapping and candidate gene identification for egg production traits in chicken. © 2011 The Authors, Animal Genetics © 2011 Stichting International Foundation for Animal Genetics.

  11. Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)

    PubMed Central

    Holdt, Lesca M.; von Delft, Annette; Nicolaou, Alexandros; Baumann, Sven; Kostrzewa, Markus; Thiery, Joachim; Teupser, Daniel

    2013-01-01

    A current challenge in the era of genome-wide studies is to determine the responsible genes and mechanisms underlying newly identified loci. Screening of the plasma proteome by high-throughput mass spectrometry (MALDI-TOF MS) is considered a promising approach for identification of metabolic and disease processes. Therefore, plasma proteome screening might be particularly useful for identifying responsible genes when combined with analysis of variation in the genome. Here, we describe a proteomic quantitative trait locus (pQTL) study of plasma proteome screens in an F2 intercross of 455 mice mapped with 177 genetic markers across the genome. A total of 69 of 176 peptides revealed significant LOD scores (≥5.35) demonstrating strong genetic regulation of distinct components of the plasma proteome. Analyses were confirmed by mechanistic studies and MALDI-TOF/TOF, liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of the two strongest pQTLs: A pQTL for mass-to-charge ratio (m/z) 3494 (LOD 24.9, D11Mit151) was identified as the N-terminal 35 amino acids of hemoglobin subunit A (Hba) and caused by genetic variation in Hba. Another pQTL for m/z 8713 (LOD 36.4; D1Mit111) was caused by variation in apolipoprotein A2 (Apoa2) and cosegregated with HDL cholesterol. Taken together, we show that genome-wide plasma proteome profiling in combination with genome-wide genetic screening aids in the identification of causal genetic variants affecting abundance of plasma proteins. PMID:23172855

  12. Early Life Stress, FKBP5 Polymorphisms, and Quantitative Glycemic Traits.

    PubMed

    Suarez, Anna; Lahti, Jari; Kajantie, Eero; Eriksson, Johan G; Räikkönen, Katri

    2017-06-01

    Early life stress (ELS) has been shown to influence health later in life. Functioning of the hypothalamic-pituitary-adrenal axis, regulated partly by FKBP5 gene, may moderate these effects. We examined whether FKBP5 single-nucleotide polymorphisms (SNPs) interact with ELS on Type 2 diabetes, cardiovascular disease, and quantitative glycemic traits. A total of 1728 Helsinki Birth Cohort Study participants born from 1934 to 1944 were genotyped for FKBP5 SNPs (rs1360780, rs9394309, rs9470080) and were administered a 2-hour (75 g) oral glucose tolerance test and a questionnaire on physician-diagnosed and medication use for chronic diseases at a mean age of 61.5 years. Of the participants, 273 had been exposed to ELS, operationalized as separation from their parents, at a mean age of 4.7 years due to evacuations during World War II. ELS interacted with FKBP5 SNPs in the analyses of fasting (rs1360780, p = .015), 30-minute (rs1360780, p = .031; rs9394309, p = .041) and incremental insulin (rs1360780, p = .032; rs9394309, p = .028; rs9470080, p = .043), insulin area under the curve (rs1360780, p = .044), and impaired fasting glucose (rs9470080, p = .049); among carriers of at least one copy of minor allele, but not among major allele homozygotes, insulin values were higher, as were the odds for impaired fasting glucose if they had been separated compared with if they had not. Corresponding associations were found with a haplotype formed by minor alleles in all three SNPs for fasting, 30-minute, and incremental insulin (p < .05). FKBP5 polymorphisms in combination with ELS exposure predict higher insulin and glucose values in midlife. Our findings support the role for hypothalamic-pituitary-adrenal axis dysregulation in health-related metabolic outcomes.

  13. Evidence of a Novel Quantitative-Trait Locus for Obesity on Chromosome 4p in Mexican Americans

    PubMed Central

    Arya, Rector; Duggirala, Ravindranath; Jenkinson, Christopher P.; Almasy, Laura; Blangero, John; O’Connell, Peter; Stern, Michael P.

    2004-01-01

    Although several genomewide scans have identified quantitative-trait loci influencing several obesity-related traits in humans, genes influencing normal variation in obesity phenotypes have not yet been identified. We therefore performed a genome scan of body mass index (BMI) on Mexican Americans, a population prone to obesity and diabetes, using a variance-components linkage analysis to identify loci that influence BMI. We used phenotypic data from 430 individuals (26% diabetics, 59% females, mean age ± SD = 43 ± 17 years, mean BMI ± SD = 30.0 ± 6.7, mean leptin (ng/ml) ± SD = 22.1 ± 17.1) distributed across 27 low-income Mexican American pedigrees who participated in the San Antonio Family Diabetes Study (SAFDS) for whom a 10–15-cM map is available. In this genomewide search, after accounting for the covariate effects of age, sex, diabetes, and leptin, we identified a genetic region exhibiting the most highly significant evidence for linkage (LOD 4.5) with BMI on chromosome 4p (4p15.1) at 42 cM, near marker D4S2912. This linkage result has been confirmed in an independent linkage study of severe obesity in Utah pedigrees. Two strong positional candidates, the human peroxisome proliferator-activated receptor gamma coactivator 1 (PPARGC1) and cholecystokinin A receptor (CCKAR) with major roles in the development of obesity, are located in this region. In conclusion, we identified a major genetic locus influencing BMI on chromosome 4p in Mexican Americans. PMID:14740316

  14. Fifteen years of quantitative trait loci studies in fish: challenges and future directions.

    PubMed

    Ashton, David T; Ritchie, Peter A; Wellenreuther, Maren

    2017-03-01

    Understanding the genetic basis of phenotypic variation is a major challenge in biology. Here, we systematically evaluate 146 quantitative trait loci (QTL) studies on teleost fish over the last 15 years to investigate (i) temporal trends and (ii) factors affecting QTL detection and fine-mapping. The number of fish QTL studies per year increased over the review period and identified a cumulative number of 3632 putative QTLs. Most studies used linkage-based mapping approaches and were conducted on nonmodel species with limited genomic resources. A gradual and moderate increase in the size of the mapping population and a sharp increase in marker density from 2011 onwards were observed; however, the number of QTLs and variance explained by QTLs changed only minimally over the review period. Based on these findings, we discuss the causative factors and outline how larger sample sizes, phenomics, comparative genomics, epigenetics and software development could improve both the quantity and quality of QTLs in future genotype-phenotype studies. Given that the technical limitations on DNA sequencing have mostly been overcome in recent years, a renewed focus on these and other study design factors will likely lead to significant improvements in QTL studies in the future. © 2016 John Wiley & Sons Ltd.

  15. Two quantitative trait loci influence whipworm (Trichuris trichiura) infection in a Nepalese population.

    PubMed

    Williams-Blangero, Sarah; Vandeberg, John L; Subedi, Janardan; Jha, Bharat; Dyer, Tom D; Blangero, John

    2008-04-15

    Whipworm (Trichuris trichiura) infection is a soil-transmitted helminth infection that affects >1 billion people. It is a serious public health problem in many developing countries and can result in deficits in growth and cognitive development. In a follow-up study of significant heritability for whipworm infection, we conducted the first genome scan for quantitative trait loci (QTL) influencing the heritability of susceptibility to this important parasitic disease. Whipworm egg counts were determined for 1,253 members of the Jirel population of eastern Nepal. All individuals in the study sample belonged to a single pedigree including >26,000 pairs of relatives that are informative for genetic analysis. Linkage analysis of genome scan data generated for the pedigree provided unambiguous evidence for 2 QTL influencing susceptibility to whipworm infection, one located on chromosome 9 (logarithm of the odds ratio [LOD] score, 3.35; genomewide P = .0138) and the other located on chromosome 18 (LOD score, 3.29; genomewide P = .0159). There was also suggestive evidence that 2 loci located on chromosomes 12 and 13 influenced whipworm infection. The results of this first genome scan for T. trichiura egg counts provides new information on the determinants of genetic predisposition to whipworm infection.

  16. Networks of plants: how to measure similarity in vegetable species.

    PubMed

    Vivaldo, Gianna; Masi, Elisa; Pandolfi, Camilla; Mancuso, Stefano; Caldarelli, Guido

    2016-06-07

    Despite the common misconception of nearly static organisms, plants do interact continuously with the environment and with each other. It is fair to assume that during their evolution they developed particular features to overcome similar problems and to exploit possibilities from environment. In this paper we introduce various quantitative measures based on recent advancements in complex network theory that allow to measure the effective similarities of various species. By using this approach on the similarity in fruit-typology ecological traits we obtain a clear plant classification in a way similar to traditional taxonomic classification. This result is not trivial, since a similar analysis done on the basis of diaspore morphological properties do not provide any clear parameter to classify plants species. Complex network theory can then be used in order to determine which feature amongst many can be used to distinguish scope and possibly evolution of plants. Future uses of this approach range from functional classification to quantitative determination of plant communities in nature.

  17. Quantitative trait loci identified for blood chemistry components of an advanced intercross line of chickens under heat stress.

    PubMed

    Van Goor, Angelica; Ashwell, Christopher M; Persia, Michael E; Rothschild, Max F; Schmidt, Carl J; Lamont, Susan J

    2016-04-14

    Heat stress in poultry results in considerable economic losses and is a concern for both animal health and welfare. Physiological changes occur during periods of heat stress, including changes in blood chemistry components. A highly advanced intercross line, created from a broiler (heat susceptible) by Fayoumi (heat resistant) cross, was exposed to daily heat cycles for seven days starting at 22 days of age. Blood components measured pre-heat treatment and on the seventh day of heat treatment included pH, pCO2, pO2, base excess, HCO3, TCO2, K, Na, ionized Ca, hematocrit, hemoglobin, sO2, and glucose. A genome-wide association study (GWAS) for these traits and their calculated changes was conducted to identify quantitative trait loci (QTL) using a 600 K SNP panel. There were significant increases in pH, base excess, HCO3, TCO2, ionized Ca, hematocrit, hemoglobin, and sO2, and significant decreases in pCO2 and glucose after 7 days of heat treatment. Heritabilities ranged from 0.01-0.21 for pre-heat measurements, 0.01-0.23 for measurements taken during heat, and 0.00-0.10 for the calculated change due to heat treatment. All blood components were highly correlated within measurement days, but not correlated between measurement days. The GWAS revealed 61 QTL for all traits, located on GGA (Gallus gallus chromosome) 1, 3, 6, 9, 10, 12-14, 17, 18, 21-28, and Z. A functional analysis of the genes in these QTL regions identified the Angiopoietin pathway as significant. The QTL that co-localized for three or more traits were on GGA10, 22, 26, 28, and Z and revealed candidate genes for birds' response to heat stress. The results of this study contribute to our knowledge of levels and heritabilities of several blood components of chickens under thermoneutral and heat stress conditions. Most components responded to heat treatment. Mapped QTL may serve as markers for genomic selection to enhance heat tolerance in poultry. The Angiopoietin pathway is likely involved in the

  18. A new method of linkage analysis using LOD scores for quantitative traits supports linkage of monoamine oxidase activity to D17S250 in the Collaborative Study on the Genetics of Alcoholism pedigrees.

    PubMed

    Curtis, David; Knight, Jo; Sham, Pak C

    2005-09-01

    Although LOD score methods have been applied to diseases with complex modes of inheritance, linkage analysis of quantitative traits has tended to rely on non-parametric methods based on regression or variance components analysis. Here, we describe a new method for LOD score analysis of quantitative traits which does not require specification of a mode of inheritance. The technique is derived from the MFLINK method for dichotomous traits. A range of plausible transmission models is constructed, constrained to yield the correct population mean and variance for the trait but differing with respect to the contribution to the variance due to the locus under consideration. Maximized LOD scores under homogeneity and admixture are calculated, as is a model-free LOD score which compares the maximized likelihoods under admixture assuming linkage and no linkage. These LOD scores have known asymptotic distributions and hence can be used to provide a statistical test for linkage. The method has been implemented in a program called QMFLINK. It was applied to data sets simulated using a variety of transmission models and to a measure of monoamine oxidase activity in 105 pedigrees from the Collaborative Study on the Genetics of Alcoholism. With the simulated data, the results showed that the new method could detect linkage well if the true allele frequency for the trait was close to that specified. However, it performed poorly on models in which the true allele frequency was much rarer. For the Collaborative Study on the Genetics of Alcoholism data set only a modest overlap was observed between the results obtained from the new method and those obtained when the same data were analysed previously using regression and variance components analysis. Of interest is that D17S250 produced a maximized LOD score under homogeneity and admixture of 2.6 but did not indicate linkage using the previous methods. However, this region did produce evidence for linkage in a separate data set

  19. Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

    PubMed

    Dumas, Marc-Emmanuel; Domange, Céline; Calderari, Sophie; Martínez, Andrea Rodríguez; Ayala, Rafael; Wilder, Steven P; Suárez-Zamorano, Nicolas; Collins, Stephan C; Wallis, Robert H; Gu, Quan; Wang, Yulan; Hue, Christophe; Otto, Georg W; Argoud, Karène; Navratil, Vincent; Mitchell, Steve C; Lindon, John C; Holmes, Elaine; Cazier, Jean-Baptiste; Nicholson, Jeremy K; Gauguier, Dominique

    2016-09-30

    The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by 1 H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of

  20. Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts

    NASA Astrophysics Data System (ADS)

    Meng, T.-T.; Wang, H.; Harrison, S. P.; Prentice, I. C.; Ni, J.; Wang, G.

    2015-09-01

    Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature

  1. Effects of P Element Insertions on Quantitative Traits in Drosophila Melanogaster

    PubMed Central

    Mackay, TFC.; Lyman, R. F.; Jackson, M. S.

    1992-01-01

    P element mutagenesis was used to construct 94 third chromosome lines of Drosophila melanogaster which contained on average 3.1 stable P element inserts, in an inbred host strain background previously free of P elements. The homozygous and heterozygous effects of the inserts on viability and abdominal and sternopleural bristle number were ascertained by comparing the chromosome lines with inserts to insert-free control lines of the inbred host strain. P elements reduced average homozygous viability by 12.2% per insert and average heterozygous viability by 5.5% per insert, and induced recessive lethal mutations at a rate of 3.8% per insert. Mutational variation for the bristle traits averaged over both sexes was 0.03V(e) per homozygous P insert and 0.003V(e) per heterozygous P insert, where V(e) is the environmental variance. Mutational variation was greater for the sexes considered separately because inserts had large pleiotropic effects on sex dimorphism of bristle characters. The distributions of homozygous effects of inserts on the bristle traits were asymmetrical, with the largest effects in the direction of reducing bristle number; and highly leptokurtic, with most of the increase in variance contributed by a few lines with large effects. The inserts had partially recessive effects on the bristle traits. Insert lines with extreme bristle effects had on average greatly reduced viability. PMID:1311697

  2. The Role of Technologies, Behaviors, Gender, and Gender Stereotype Traits in Adolescents' Cyber Aggression.

    PubMed

    Wright, Michelle F

    2017-03-01

    The present study focused on the impact of gender and gender stereotype traits (i.e., masculinity, femininity) on cyber aggression perpetration utilizing different technologies (i.e., social-networking sites, gaming consoles, mobile phones) and behaviors (i.e., cyber relational aggression, cyber verbal aggression, hacking). Participants included 233 eighth graders (108 female; M age = 13.26, SD = 0.36) from two middle schools in the Midwestern United States. Adolescents completed questionnaires on their endorsement of masculinity and femininity traits as well as how often they engaged in cyber aggression perpetration (i.e., cyber relational aggression, cyber verbal aggression, hacking) through mobile phones, social-networking sites, and gaming consoles. Findings indicated that boys and girls with more feminine traits engaged in more cyber relational aggression through social-networking sites and mobile phones, while boys and girls who endorsed more masculine traits perpetrated this behavior and cyber verbal aggression more often through online gaming. In addition, these boys and girls engaged in more hacking through all technologies when compared with girls and boys who reported more feminine traits. Results of this study indicate the importance of delineating gender stereotype traits, behaviors, and technologies when examining cyber aggression perpetration.

  3. Sex chromosome linked genetic variance and the evolution of sexual dimorphism of quantitative traits.

    PubMed

    Husby, Arild; Schielzeth, Holger; Forstmeier, Wolfgang; Gustafsson, Lars; Qvarnström, Anna

    2013-03-01

    Theory predicts that sex chromsome linkage should reduce intersexual genetic correlations thereby allowing the evolution of sexual dimorphism. Empirical evidence for sex linkage has come largely from crosses and few studies have examined how sexual dimorphism and sex linkage are related within outbred populations. Here, we use data on an array of different traits measured on over 10,000 individuals from two pedigreed populations of birds (collared flycatcher and zebra finch) to estimate the amount of sex-linked genetic variance (h(2)z ). Of 17 traits examined, eight showed a nonzero h(2)Z estimate but only four were significantly different from zero (wing patch size and tarsus length in collared flycatchers, wing length and beak color in zebra finches). We further tested how sexual dimorphism and the mode of selection operating on the trait relate to the proportion of sex-linked genetic variance. Sexually selected traits did not show higher h(2)Z than morphological traits and there was only a weak positive relationship between h(2)Z and sexual dimorphism. However, given the relative scarcity of empirical studies, it is premature to make conclusions about the role of sex chromosome linkage in the evolution of sexual dimorphism. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

  4. The study on the core personality trait words of Chinese medical university students based on social network analysis.

    PubMed

    Wu, Ying; Xue, Yunzhen; Xue, Zhanling

    2017-09-01

    The medical university students in China whose school work is relatively heavy and educational system is long are a special professional group. Many students have psychological problems more or less. So, to understand their personality characteristics will provide a scientific basis for the intervention of psychological health.We selected top 30 personality trait words according to the order of frequency. Additionally, some methods such as social network analysis (SNA) and visualization technology of mapping knowledge domain were used in this study.Among these core personality trait words Family conscious had the 3 highest centralities and possessed the largest core status and influence. From the analysis of core-peripheral structure, we can see polarized core-perpheral structure was quite obvious. From the analysis of K-plex, there were in total 588 "K-2"K-plexs. From the analysis of Principal Components, we selected the 11 principal components.This study of personality not only can prevent disease, but also provide a scientific basis for students' psychological healthy education. In addition, we have adopted SNA to pay more attention to the relationship between personality trait words and the connection among personality dimensions. This study may provide the new ideas and methods for the research of personality structure.

  5. The study on the core personality trait words of Chinese medical university students based on social network analysis

    PubMed Central

    Wu, Ying; Xue, Yunzhen; Xue, Zhanling

    2017-01-01

    Abstract The medical university students in China whose school work is relatively heavy and educational system is long are a special professional group. Many students have psychological problems more or less. So, to understand their personality characteristics will provide a scientific basis for the intervention of psychological health. We selected top 30 personality trait words according to the order of frequency. Additionally, some methods such as social network analysis (SNA) and visualization technology of mapping knowledge domain were used in this study. Among these core personality trait words Family conscious had the 3 highest centralities and possessed the largest core status and influence. From the analysis of core-peripheral structure, we can see polarized core-perpheral structure was quite obvious. From the analysis of K-plex, there were in total 588 “K-2”K-plexs. From the analysis of Principal Components, we selected the 11 principal components. This study of personality not only can prevent disease, but also provide a scientific basis for students’ psychological healthy education. In addition, we have adopted SNA to pay more attention to the relationship between personality trait words and the connection among personality dimensions. This study may provide the new ideas and methods for the research of personality structure. PMID:28906409

  6. Analysis of quantitative lipid traits in the genetics of NIDDM (GENNID) study.

    PubMed

    Malhotra, Alka; Wolford, Johanna K

    2005-10-01

    Coronary heart disease (CHD) is the leading cause of death among individuals with type 2 diabetes. Dyslipidemia contributes significantly to CHD in diabetic patients, in whom lipid abnormalities include hypertriglyceridemia, low HDL cholesterol, and increased levels of small, dense LDL particles. To identify genes for lipid-related traits, we performed genome-wide linkage analyses for levels of triglycerides and HDL, LDL, and total cholesterol in Caucasian, Hispanic, and African-American families from the Genetics of NIDDM (GENNID) study. Most lipid traits showed significant estimates of heritability (P < 0.001) with the exception of triglycerides and the triglyceride/HDL ratio in African Americans. Variance components analysis identified linkage on chromosome 3p12.1-3q13.31 for the triglyceride/HDL ratio (logarithm of odds [LOD] = 3.36) and triglyceride (LOD = 3.27) in Caucasian families. Statistically significant evidence for linkage was identified for the triglyceride/HDL ratio (LOD = 2.45) on 11p in Hispanic families in a region that showed suggestive evidence for linkage (LOD = 2.26) for triglycerides in this population. In African Americans, the strongest evidence for linkage (LOD = 2.26) was found on 19p13.2-19q13.42 for total cholesterol. Our findings provide strong support for previous reports of linkage for lipid-related traits, suggesting the presence of genes on 3p12.1-3q13.31, 11p15.4-11p11.3, and 19p13.2-19q13.42 that may influence traits underlying lipid abnormalities associated with type 2 diabetes.

  7. Mapping and validation of major quantitative trait loci for kernel length in wild barley (Hordeum vulgare ssp. spontaneum).

    PubMed

    Zhou, Hong; Liu, Shihang; Liu, Yujiao; Liu, Yaxi; You, Jing; Deng, Mei; Ma, Jian; Chen, Guangdeng; Wei, Yuming; Liu, Chunji; Zheng, Youliang

    2016-09-13

    Kernel length is an important target trait in barley (Hordeum vulgare L.) breeding programs. However, the number of known quantitative trait loci (QTLs) controlling kernel length is limited. In the present study, we aimed to identify major QTLs for kernel length, as well as putative candidate genes that might influence kernel length in wild barley. A recombinant inbred line (RIL) population derived from the barley cultivar Baudin (H. vulgare ssp. vulgare) and the long-kernel wild barley genotype Awcs276 (H.vulgare ssp. spontaneum) was evaluated at one location over three years. A high-density genetic linkage map was constructed using 1,832 genome-wide diversity array technology (DArT) markers, spanning a total of 927.07 cM with an average interval of approximately 0.49 cM. Two major QTLs for kernel length, LEN-3H and LEN-4H, were detected across environments and further validated in a second RIL population derived from Fleet (H. vulgare ssp. vulgare) and Awcs276. In addition, a systematic search of public databases identified four candidate genes and four categories of proteins related to LEN-3H and LEN-4H. This study establishes a fundamental research platform for genomic studies and marker-assisted selection, since LEN-3H and LEN-4H could be used for accelerating progress in barley breeding programs that aim to improve kernel length.

  8. Mapping quantitative trait loci for lint yield and fiber quality across environments in a Gossypium hirsutum × Gossypium barbadense backcross inbred line population.

    PubMed

    Yu, Jiwen; Zhang, Ke; Li, Shuaiyang; Yu, Shuxun; Zhai, Honghong; Wu, Man; Li, Xingli; Fan, Shuli; Song, Meizhen; Yang, Daigang; Li, Yunhai; Zhang, Jinfa

    2013-01-01

    Identification of stable quantitative trait loci (QTLs) across different environments and mapping populations is a prerequisite for marker-assisted selection (MAS) for cotton yield and fiber quality. To construct a genetic linkage map and to identify QTLs for fiber quality and yield traits, a backcross inbred line (BIL) population of 146 lines was developed from a cross between Upland cotton (Gossypium hirsutum) and Egyptian cotton (Gossypium barbadense) through two generations of backcrossing using Upland cotton as the recurrent parent followed by four generations of self pollination. The BIL population together with its two parents was tested in five environments representing three major cotton production regions in China. The genetic map spanned a total genetic distance of 2,895 cM and contained 392 polymorphic SSR loci with an average genetic distance of 7.4 cM per marker. A total of 67 QTLs including 28 for fiber quality and 39 for yield and its components were detected on 23 chromosomes, each of which explained 6.65-25.27% of the phenotypic variation. Twenty-nine QTLs were located on the At subgenome originated from a cultivated diploid cotton, while 38 were on the Dt subgenome from an ancestor that does not produce spinnable fibers. Of the eight common QTLs (12%) detected in more than two environments, two were for fiber quality traits including one for fiber strength and one for uniformity, and six for yield and its components including three for lint yield, one for seedcotton yield, one for lint percentage and one for boll weight. QTL clusters for the same traits or different traits were also identified. This research represents one of the first reports using a permanent advanced backcross inbred population of an interspecific hybrid population to identify QTLs for fiber quality and yield traits in cotton across diverse environments. It provides useful information for transferring desirable genes from G. barbadense to G. hirsutum using MAS.

  9. Mapping the functional connectome traits of levels of consciousness.

    PubMed

    Amico, Enrico; Marinazzo, Daniele; Di Perri, Carol; Heine, Lizette; Annen, Jitka; Martial, Charlotte; Dzemidzic, Mario; Kirsch, Murielle; Bonhomme, Vincent; Laureys, Steven; Goñi, Joaquín

    2017-03-01

    Examining task-free functional connectivity (FC) in the human brain offers insights on how spontaneous integration and segregation of information relate to human cognition, and how this organization may be altered in different conditions, and neurological disorders. This is particularly relevant for patients in disorders of consciousness (DOC) following severe acquired brain damage and coma, one of the most devastating conditions in modern medical care. We present a novel data-driven methodology, connICA, which implements Independent Component Analysis (ICA) for the extraction of robust independent FC patterns (FC-traits) from a set of individual functional connectomes, without imposing any a priori data stratification into groups. We here apply connICA to investigate associations between network traits derived from task-free FC and cognitive/clinical features that define levels of consciousness. Three main independent FC-traits were identified and linked to consciousness-related clinical features. The first one represents the functional configuration of a "resting" human brain, and it is associated to a sedative (sevoflurane), the overall effect of the pathology and the level of arousal. The second FC-trait reflects the disconnection of the visual and sensory-motor connectivity patterns. It also relates to the time since the insult and to the ability of communicating with the external environment. The third FC-trait isolates the connectivity pattern encompassing the fronto-parietal and the default-mode network areas as well as the interaction between left and right hemispheres, which are also associated to the awareness of the self and its surroundings. Each FC-trait represents a distinct functional process with a role in the degradation of conscious states of functional brain networks, shedding further light on the functional sub-circuits that get disrupted in severe brain-damage. Copyright © 2017. Published by Elsevier Inc.

  10. Analysis of quantitative trait loci affecting chlorophyll content of rice leaves in a double haploid population and two backcross populations.

    PubMed

    Jiang, Gonghao; Zeng, Jing; He, Yuqing

    2014-02-25

    Chlorophyll content, one of the most important physiological parameters related to plant photosynthesis, is usually used to predict yield potential. To map the quantitative trait loci (QTLs) underlying the chlorophyll content of rice leaves, a double haploid (DH) population was developed from an indica/japonica (Zhenshan 97/Wuyujing 2) crossing and two backcross populations were established subsequently by backcrossing DH lines with each of their parents. The contents of chlorophyll a and chlorophyll b were determined by using a spectrophotometer to directly measure the leaf chlorophyll extracts. To determine the leaf chlorophyll retention along with maturation, all measurements were performed on the day of heading and were repeated 30 days later. A total of 60 QTLs were resolved for all the traits using these three populations. These QTLs were distributed on 10 rice chromosomes, except chromosomes 5 and 10; the closer the traits, the more clustering of the QTLs residing on common rice chromosomal regions. In general, the majority of QTLs that specify chlorophyll a content also play a role in determining chlorophyll b content. Strangely, chlorophyll content in this study was found mostly to be lacking or to have a negative correlation with yield. In both backcross F1 populations, overdominant (or underdominant) loci were more important than complete or partially dominant loci for main-effect QTLs and epistatic QTLs, thereby supporting previous findings that overdominant effects are the primary genetic basis for depression in inbreeding and heterosis in rice. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. Characterisation of a novel quantitative trait locus, GN4-1, for grain number and yield in rice (Oryza sativa L.).

    PubMed

    Zhou, Yong; Tao, Yajun; Yuan, Yuan; Zhang, Yanzhou; Miao, Jun; Zhang, Ron; Yi, Chuandeng; Gong, Zhiyun; Yang, Zefeng; Liang, Guohua

    2018-03-01

    A novel QTL for grain number, GN4-1, was identified and fine-mapped to an ~ 190-kb region on the long arm of rice chromosome 4. Rice grain yield is primarily determined by three components: number of panicles per plant, grain number per panicle and grain weight. Among these traits, grain number per panicle is the major contributor to grain yield formation and is a crucial trait for yield improvement. In this study, we identified a major quantitative trait locus (QTL) responsible for rice grain number on chromosome 4, designated GN4-1 (a QTL for Grain Number on chromosome 4), using advanced segregating populations derived from the crosses between an elite indica cultivar 'Zhonghui 8006' (ZH8006) and a japonica rice 'Wuyunjing 8' (WYJ8). GN4-1 was delimited to an ~ 190-kb region on chromosome 4. The genetic effect of GN4-1 was estimated using a pair of near-isogenic lines. The GN4-1 gene from WYJ8 promoted accumulation of cytokinins in the inflorescence and increased grain number per panicle by ~ 17%. More importantly, introduction of the WYJ8 GN4-1 gene into ZH8006 increased grain yield by ~ 14.3 and ~ 11.5% in the experimental plots in 2014 and 2015, respectively. In addition, GN4-1 promoted thickening of the culm and may enhance resistance to lodging. These results demonstrate that GN4-1 is a potentially valuable gene for improvement of yield and lodging resistance in rice breeding.

  12. Novel Applications of Multi-task Learning and Multiple Output Regression to Multiple Genetic Trait Prediction

    USDA-ARS?s Scientific Manuscript database

    Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait predicti...

  13. Quantitative trait locus mapping under irrigated and drought treatments based on a novel genetic linkage map in mungbean (Vigna radiata L.).

    PubMed

    Liu, Changyou; Wu, Jing; Wang, Lanfen; Fan, Baojie; Cao, Zhimin; Su, Qiuzhu; Zhang, Zhixiao; Wang, Yan; Tian, Jing; Wang, Shumin

    2017-11-01

    A novel genetic linkage map was constructed using SSR markers and stable QTLs were identified for six drought tolerance related-traits using single-environment analysis under irrigation and drought treatments. Mungbean (Vigna radiata L.) is one of the most important leguminous food crops. However, mungbean production is seriously constrained by drought. Isolation of drought-responsive genetic elements and marker-assisted selection breeding will benefit from the detection of quantitative trait locus (QTLs) for traits related to drought tolerance. In this study, we developed a full-coverage genetic linkage map based on simple sequence repeat (SSR) markers using a recombinant inbred line (RIL) population derived from an intra-specific cross between two drought-resistant varieties. This novel map was anchored with 313 markers. The total map length was 1010.18 cM across 11 linkage groups, covering the entire genome of mungbean with a saturation of one marker every 3.23 cM. We subsequently detected 58 QTLs for plant height (PH), maximum leaf area (MLA), biomass (BM), relative water content, days to first flowering, and seed yield (Yield) and 5 for the drought tolerance index of 3 traits in irrigated and drought environments at 2 locations. Thirty-eight of these QTLs were consistently detected two or more times at similar linkage positions. Notably, qPH5A and qMLA2A were consistently identified in marker intervals from GMES5773 to MUS128 in LG05 and from Mchr11-34 to the HAAS_VR_1812 region in LG02 in four environments, contributing 6.40-20.06% and 6.97-7.94% of the observed phenotypic variation, respectively. None of these QTLs shared loci with previously identified drought-related loci from mungbean. The results of these analyses might facilitate the isolation of drought-related genes and help to clarify the mechanism of drought tolerance in mungbean.

  14. Quantitative trait loci controlling leaf appearance and curd initiation of cauliflower in relation to temperature.

    PubMed

    Hasan, Yaser; Briggs, William; Matschegewski, Claudia; Ordon, Frank; Stützel, Hartmut; Zetzsche, Holger; Groen, Simon; Uptmoor, Ralf

    2016-07-01

    QTL regions on chromosomes C06 and C09 are involved in temperature dependent time to curd induction in cauliflower. Temperature is the main environmental factor influencing curding time of cauliflower (Brassica oleracea var. botrytis). Temperatures above 20-22 °C inhibit development towards curding even in many summer cultivars. To identify quantitative trait loci (QTL) controlling curding time and its related traits in a wide range of different temperature regimes from 12 to 27 °C, a doubled haploid (DH) mapping population segregating for curding time was developed and days to curd initiation (DCI), leaf appearance rate (LAR), and final leaf number (FLN) were measured. The population was genotyped with 176 single nucleotide polymorphism (SNP) markers. Composite interval mapping (CIM) revealed repeatedly detected QTL for DCI on C06 and C09. The estimated additive effect increased at high temperatures. Significant QTL × environment interactions (Q × E) for FLN and DCI on C06 and C09 suggest that these hotspot regions have major influences on temperature mediated curd induction. 25 % of the DH lines did not induce curds at temperatures higher than 22 °C. Applying a binary model revealed a QTL with LOD >15 on C06. Nearly all lines carrying the allele of the reliable early maturing parental line (PL) on that locus induced curds at high temperatures while only half of the DH lines carrying the allele of the unreliable PL reached the generative phase during the experiment. Large variation in LAR was observed. QTL for LAR were detected repeatedly in several environments on C01, C04 and C06. Negative correlations between LAR and DCI and QTL co-localizations on C04 and C06 suggest that LAR has also effects on development towards curd induction.

  15. Quantitative trait locus analysis of heterosis for plant height and ear height in an elite maize hybrid zhengdan 958 by design III.

    PubMed

    Li, Hongjian; Yang, Qingsong; Fan, Nannan; Zhang, Ming; Zhai, Huijie; Ni, Zhongfu; Zhang, Yirong

    2017-04-17

    Plant height (PH) and ear height (EH) are two important agronomic traits in maize selection breeding. F 1 hybrid exhibit significant heterosis for PH and EH as compared to their parental inbred lines. To understand the genetic basis of heterosis controlling PH and EH, we conducted quantitative trait locus (QTL) analysis using a recombinant inbreed line (RIL) based design III population derived from the elite maize hybrid Zhengdan 958 in five environments. A total of 14 environmentally stable QTLs were identified, and the number of QTLs for Z 1 and Z 2 populations was six and eight, respectively. Notably, all the eight environmentally stable QTLs for Z 2 were characterized by overdominance effect (OD), suggesting that overdominant QTLs were the most important contributors to heterosis for PH and EH. Furthermore, 14 environmentally stable QTLs were anchored on six genomic regions, among which four are trait-specific QTLs, suggesting that the genetic basis for PH and EH is partially different. Additionally, qPH.A-1.3, modifying about 10 centimeters of PH, was further validated in backcross populations. The genetic basis for PH and EH is partially different, and overdominant QTLs are important factors for heterosis of PH and EH. A major QTL qPH.A-1.3 may be a desired target for genetic improvement of maize plant height.

  16. Accounting for trait architecture in genomic predictions of US Holstein cattle using a weighted realized relationship matrix.

    PubMed

    Tiezzi, Francesco; Maltecca, Christian

    2015-04-02

    Genomic BLUP (GBLUP) can predict breeding values for non-phenotyped individuals based on the identity-by-state genomic relationship matrix (G). The G matrix can be constructed from thousands of markers spread across the genome. The strongest assumption of G and consequently of GBLUP is that all markers contribute equally to the genetic variance of a trait. This assumption is violated for traits that are controlled by a small number of quantitative trait loci (QTL) or individual QTL with large effects. In this paper, we investigate the performance of using a weighted genomic relationship matrix (wG) that takes into consideration the genetic architecture of the trait in order to improve predictive ability for a wide range of traits. Multiple methods were used to calculate weights for several economically relevant traits in US Holstein dairy cattle. Predictive performance was tested by k-means cross-validation. Relaxing the GBLUP assumption of equal marker contribution by increasing the weight that is given to a specific marker in the construction of the trait-specific G resulted in increased predictive performance. The increase was strongest for traits that are controlled by a small number of QTL (e.g. fat and protein percentage). Furthermore, bias in prediction estimates was reduced compared to that resulting from the use of regular G. Even for traits with low heritability and lower general predictive performance (e.g. calving ease traits), weighted G still yielded a gain in accuracy. Genomic relationship matrices weighted by marker realized variance yielded more accurate and less biased predictions for traits regulated by few QTL. Genome-wide association analyses were used to derive marker weights for creating weighted genomic relationship matrices. However, this can be cumbersome and prone to low stability over generations because of erosion of linkage disequilibrium between markers and QTL. Future studies may include other sources of information, such as

  17. The Relationship Between Online Social Networking and Depression: A Systematic Review of Quantitative Studies.

    PubMed

    Baker, David A; Algorta, Guillermo Perez

    2016-11-01

    Online social networking sites (SNSs) such as Facebook, Twitter, and MySpace are used by billions of people every day to communicate and interact with others. There has been increasing interest in the potential impact of online social networking on wellbeing, with a broadening body of new research into factors associated with both positive and negative mental health outcomes such as depression. This systematic review of empirical studies (n = 30) adds to existing research in this field by examining current quantitative studies focused on the relationship between online social networking and symptoms of depression. The academic databases PsycINFO, Web of Science, CINAHL, MEDLINE, and EMBASE were searched systematically using terms related to online social networking and depression. Reporting quality was critically appraised and the findings discussed with reference to their wider implications. The findings suggest that the relationship between online social networking and symptoms of depression may be complex and associated with multiple psychological, social, behavioral, and individual factors. Furthermore, the impact of online social networking on wellbeing may be both positive and negative, highlighting the need for future research to determine the impact of candidate mediators and moderators underlying these heterogeneous outcomes across evolving networks.

  18. A simple model clarifies the complicated relationships of complex networks

    PubMed Central

    Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi

    2014-01-01

    Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation. PMID:25160506

  19. Identification of genotyping-by-sequencing sequence tags associated with milling performance and end-use quality traits in hard red spring wheat (Triticum aestivum L.)

    USDA-ARS?s Scientific Manuscript database

    Wheat quality is defined by culinary end-uses and processing characteristics. Wheat breeders are interested to identify quantitative trait loci for grain, milling, and end-use quality traits because it is imperative to understand the genetic complexity underlying quantitatively inherited traits to ...

  20. Using avian functional traits to assess the impact of land-cover change on ecosystem processes linked to resilience in tropical forests.

    PubMed

    Bregman, Tom P; Lees, Alexander C; MacGregor, Hannah E A; Darski, Bianca; de Moura, Nárgila G; Aleixo, Alexandre; Barlow, Jos; Tobias, Joseph A

    2016-12-14

    Vertebrates perform key roles in ecosystem processes via trophic interactions with plants and insects, but the response of these interactions to environmental change is difficult to quantify in complex systems, such as tropical forests. Here, we use the functional trait structure of Amazonian forest bird assemblages to explore the impacts of land-cover change on two ecosystem processes: seed dispersal and insect predation. We show that trait structure in assemblages of frugivorous and insectivorous birds remained stable after primary forests were subjected to logging and fire events, but that further intensification of human land use substantially reduced the functional diversity and dispersion of traits, and resulted in communities that occupied a different region of trait space. These effects were only partially reversed in regenerating secondary forests. Our findings suggest that local extinctions caused by the loss and degradation of tropical forest are non-random with respect to functional traits, thus disrupting the network of trophic interactions regulating seed dispersal by forest birds and herbivory by insects, with important implications for the structure and resilience of human-modified tropical forests. Furthermore, our results illustrate how quantitative functional traits for specific guilds can provide a range of metrics for estimating the contribution of biodiversity to ecosystem processes, and the response of such processes to land-cover change. © 2016 The Author(s).

  1. Using avian functional traits to assess the impact of land-cover change on ecosystem processes linked to resilience in tropical forests

    PubMed Central

    Bregman, Tom P.; Lees, Alexander C.; MacGregor, Hannah E. A.; Darski, Bianca; de Moura, Nárgila G.; Aleixo, Alexandre; Barlow, Jos

    2016-01-01

    Vertebrates perform key roles in ecosystem processes via trophic interactions with plants and insects, but the response of these interactions to environmental change is difficult to quantify in complex systems, such as tropical forests. Here, we use the functional trait structure of Amazonian forest bird assemblages to explore the impacts of land-cover change on two ecosystem processes: seed dispersal and insect predation. We show that trait structure in assemblages of frugivorous and insectivorous birds remained stable after primary forests were subjected to logging and fire events, but that further intensification of human land use substantially reduced the functional diversity and dispersion of traits, and resulted in communities that occupied a different region of trait space. These effects were only partially reversed in regenerating secondary forests. Our findings suggest that local extinctions caused by the loss and degradation of tropical forest are non-random with respect to functional traits, thus disrupting the network of trophic interactions regulating seed dispersal by forest birds and herbivory by insects, with important implications for the structure and resilience of human-modified tropical forests. Furthermore, our results illustrate how quantitative functional traits for specific guilds can provide a range of metrics for estimating the contribution of biodiversity to ecosystem processes, and the response of such processes to land-cover change. PMID:27928045

  2. A Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients

    PubMed Central

    Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

    2016-01-01

    Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1) they are susceptible to subjective factors; (2) they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information. PMID:26861337

  3. A Compressed Sensing-Based Wearable Sensor Network for Quantitative Assessment of Stroke Patients.

    PubMed

    Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

    2016-02-05

    Clinical rehabilitation assessment is an important part of the therapy process because it is the premise for prescribing suitable rehabilitation interventions. However, the commonly used assessment scales have the following two drawbacks: (1) they are susceptible to subjective factors; (2) they only have several rating levels and are influenced by a ceiling effect, making it impossible to exactly detect any further improvement in the movement. Meanwhile, energy constraints are a primary design consideration in wearable sensor network systems since they are often battery-operated. Traditionally, for wearable sensor network systems that follow the Shannon/Nyquist sampling theorem, there are many data that need to be sampled and transmitted. This paper proposes a novel wearable sensor network system to monitor and quantitatively assess the upper limb motion function, based on compressed sensing technology. With the sparse representation model, less data is transmitted to the computer than with traditional systems. The experimental results show that the accelerometer signals of Bobath handshake and shoulder touch exercises can be compressed, and the length of the compressed signal is less than 1/3 of the raw signal length. More importantly, the reconstruction errors have no influence on the predictive accuracy of the Brunnstrom stage classification model. It also indicated that the proposed system can not only reduce the amount of data during the sampling and transmission processes, but also, the reconstructed accelerometer signals can be used for quantitative assessment without any loss of useful information.

  4. Mapping of Quantitative Trait Locus (QTLs) that Contribute to Germination and Early Seedling Drought Tolerance in the Interspecific Cross Setaria italica×Setaria viridis

    PubMed Central

    Qie, Lufeng; Jia, Guanqing; Zhang, Wenying; Schnable, James; Shang, Zhonglin; Li, Wei; Liu, Binhui; Li, Mingzhe; Chai, Yang; Zhi, Hui; Diao, Xianmin

    2014-01-01

    Drought tolerance is an important breeding target for enhancing the yields of grain crop species in arid and semi-arid regions of the world. Two species of Setaria, domesticated foxtail millet (S. italica) and its wild ancestor green foxtail (S. viridis) are becoming widely adopted as models for functional genomics studies in the Panicoid grasses. In this study, the genomic regions controlling germination and early seedling drought tolerance in Setaria were identified using 190 F7 lines derived from a cross between Yugu1, a S. italica cultivar developed in China, and a wild S. viridis genotype collected from Uzbekistan. Quantitative trait loci were identified which contribute to a number of traits including promptness index, radical root length, coleoptile length and lateral root number at germinating stage and seedling survival rate was characterized by the ability of desiccated seedlings to revive after rehydration. A genetic map with 128 SSR markers which spans 1293.9 cM with an average of 14 markers per linkage group of the 9 linkage groups was constructed. A total of eighteen QTLs were detected which included nine that explained over 10% of the phenotypic variance for a given trait. Both the wild green foxtail genotype and the foxtail millet cultivar contributed the favorite alleles for traits detected in this trial, indicating that wild Setaria viridis populations may serve as a reservoir for novel stress tolerance alleles which could be employed in foxtail millet breeding. PMID:25033201

  5. Mapping of quantitative trait locus (QTLs) that contribute to germination and early seedling drought tolerance in the interspecific cross Setaria italica×Setaria viridis.

    PubMed

    Qie, Lufeng; Jia, Guanqing; Zhang, Wenying; Schnable, James; Shang, Zhonglin; Li, Wei; Liu, Binhui; Li, Mingzhe; Chai, Yang; Zhi, Hui; Diao, Xianmin

    2014-01-01

    Drought tolerance is an important breeding target for enhancing the yields of grain crop species in arid and semi-arid regions of the world. Two species of Setaria, domesticated foxtail millet (S. italica) and its wild ancestor green foxtail (S. viridis) are becoming widely adopted as models for functional genomics studies in the Panicoid grasses. In this study, the genomic regions controlling germination and early seedling drought tolerance in Setaria were identified using 190 F7 lines derived from a cross between Yugu1, a S. italica cultivar developed in China, and a wild S. viridis genotype collected from Uzbekistan. Quantitative trait loci were identified which contribute to a number of traits including promptness index, radical root length, coleoptile length and lateral root number at germinating stage and seedling survival rate was characterized by the ability of desiccated seedlings to revive after rehydration. A genetic map with 128 SSR markers which spans 1293.9 cM with an average of 14 markers per linkage group of the 9 linkage groups was constructed. A total of eighteen QTLs were detected which included nine that explained over 10% of the phenotypic variance for a given trait. Both the wild green foxtail genotype and the foxtail millet cultivar contributed the favorite alleles for traits detected in this trial, indicating that wild Setaria viridis populations may serve as a reservoir for novel stress tolerance alleles which could be employed in foxtail millet breeding.

  6. Quantitative Trait Locus Analysis of SIX1-SIX6 with Retinal Nerve Fiber Layer Thickness in Individuals of European Descent

    PubMed Central

    Kuo, Jane Z.; Zangwill, Linda M.; Medeiros, Felipe A.; Liebmann, Jeffery M.; Girkin, Christopher A.; Hammel, Na’ama; Rotter, Jerome I.; Weinreb, Robert N.

    2015-01-01

    Purpose To perform a quantitative trait locus (QTL) analysis and evaluate whether a locus between SIX1 and SIX6 is associated with retinal nerve fiber layer (RNFL) thickness in individuals of European descent. Design Observational, multi-center, cross-sectional study. Methods 231 participants were recruited from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study. Association of rs10483727 in SIX1-SIX6 with global and sectoral RNFL thickness was performed. Quantitative trait analysis with the additive model of inheritance was analyzed using linear regression. Trend analysis was performed to evaluate the mean global and sectoral RNFL thickness with 3 genotypes of interest (T/T, C/T, C/C). All models were adjusted for age and gender. Results Direction of association between T allele and RNFL thickness was consistent in the global and different sectoral RNFL regions. Each copy of the T risk allele in rs10483727 was associated with −0.16 μm thinner global RNFL thickness (β=−0.16, 95% CI: −0.28 to −0.03; P=0.01). Similar patterns were found for the sectoral regions, including inferior (P=0.03), inferior-nasal (P=0.017), superior-nasal (P=0.0025), superior (P=0.002) and superior-temporal (P=0.008). The greatest differences were observed in the superior and inferior quadrants, supporting clinical observations for RNFL thinning in glaucoma. Thinner global RNFL was found in subjects with T/T genotypes compared to subjects with C/T and C/C genotypes (P=0.044). Conclusions Each copy of the T risk allele has an additive effect and was associated with thinner global and sectoral RNFL. Findings from this QTL analysis further support a genetic contribution to glaucoma pathophysiology. PMID:25849520

  7. Genome-wide association mapping of quantitative traits in a breeding population of sugarcane.

    PubMed

    Racedo, Josefina; Gutiérrez, Lucía; Perera, María Francisca; Ostengo, Santiago; Pardo, Esteban Mariano; Cuenya, María Inés; Welin, Bjorn; Castagnaro, Atilio Pedro

    2016-06-24

    Molecular markers associated with relevant agronomic traits could significantly reduce the time and cost involved in developing new sugarcane varieties. Previous sugarcane genome-wide association analyses (GWAS) have found few molecular markers associated with relevant traits at plant-cane stage. The aim of this study was to establish an appropriate GWAS to find molecular markers associated with yield related traits consistent across harvesting seasons in a breeding population. Sugarcane clones were genotyped with DArT (Diversity Array Technology) and TRAP (Target Region Amplified Polymorphism) markers, and evaluated for cane yield (CY) and sugar content (SC) at two locations during three successive crop cycles. GWAS mapping was applied within a novel mixed-model framework accounting for population structure with Principal Component Analysis scores as random component. A total of 43 markers significantly associated with CY in plant-cane, 42 in first ratoon, and 41 in second ratoon were detected. Out of these markers, 20 were associated with CY in 2 years. Additionally, 38 significant associations for SC were detected in plant-cane, 34 in first ratoon, and 47 in second ratoon. For SC, one marker-trait association was found significant for the 3 years of the study, while twelve markers presented association for 2 years. In the multi-QTL model several markers with large allelic substitution effect were found. Sequences of four DArT markers showed high similitude and e-value with coding sequences of Sorghum bicolor, confirming the high gene microlinearity between sorghum and sugarcane. In contrast with other sugarcane GWAS studies reported earlier, the novel methodology to analyze multi-QTLs through successive crop cycles used in the present study allowed us to find several markers associated with relevant traits. Combining existing phenotypic trial data and genotypic DArT and TRAP marker characterizations within a GWAS approach including population structure as

  8. Quantitative trait loci for maternal performance for offspring survival in mice.

    PubMed Central

    Peripato, Andréa C; De Brito, Reinaldo A; Vaughn, Ty T; Pletscher, L Susan; Matioli, Sergio R; Cheverud, James M

    2002-01-01

    Maternal performance refers to the effect that the environment provided by mothers has on their offspring's phenotypes, such as offspring survival and growth. Variations in maternal behavior and physiology are responsible for variations in maternal performance, which in turn affects offspring survival. In our study we found females that failed to nurture their offspring and showed abnormal maternal behaviors. The genetic architecture of maternal performance for offspring survival was investigated in 241 females of an F(2) intercross of the SM/J and LG/J inbred mouse strains. Using interval-mapping methods we found two quantitative trait loci (QTL) affecting maternal performance at D2Mit17 + 6 cM and D7Mit21 + 2 cM on chromosomes 2 and 7, respectively. In a two-way genome-wide epistasis scan we found 15 epistatic interactions involving 23 QTL distributed across all chromosomes except 12, 16, and 17. These loci form several small sets of interacting QTL, suggesting a complex set of mechanisms operating to determine maternal performance for offspring survival. Taken all together and correcting for the large number of significant factors, QTL and their interactions explain almost 35% of the phenotypic variation for maternal performance for offspring survival in this cross. This study allowed the identification of many possible candidate genes, as well as the relative size of gene effects and patterns of gene action affecting maternal performance in mice. Detailed behavior observation of mothers from later generations suggests that offspring survival in the first week is related to maternal success in building nests, grooming their pups, providing milk, and/or manifesting aggressive behavior against intruders. PMID:12454078

  9. The genetic architecture of sexually selected traits in two natural populations of Drosophila montana

    PubMed Central

    Veltsos, P; Gregson, E; Morrissey, B; Slate, J; Hoikkala, A; Butlin, R K; Ritchie, M G

    2015-01-01

    We investigated the genetic architecture of courtship song and cuticular hydrocarbon traits in two phygenetically distinct populations of Drosophila montana. To study natural variation in these two important traits, we analysed within-population crosses among individuals sampled from the wild. Hence, the genetic variation analysed should represent that available for natural and sexual selection to act upon. In contrast to previous between-population crosses in this species, no major quantitative trait loci (QTLs) were detected, perhaps because the between-population QTLs were due to fixed differences between the populations. Partitioning the trait variation to chromosomes suggested a broadly polygenic genetic architecture of within-population variation, although some chromosomes explained more variation in one population compared with the other. Studies of natural variation provide an important contrast to crosses between species or divergent lines, but our analysis highlights recent concerns that segregating variation within populations for important quantitative ecological traits may largely consist of small effect alleles, difficult to detect with studies of moderate power. PMID:26198076

  10. VARIATIONS AT A QUANTITATIVE TRAIT LOCUS (QTL) AFFECT DEVELOPMENT OF BEHAVIOR IN LEAD-EXPOSED DROSOPHILA MELANOGASTER

    PubMed Central

    Hirsch, Helmut V. B.; Possidente, Debra; Averill, Sarah; Despain, Tamira Palmetto; Buytkins, Joel; Thomas, Valerie; Goebel, W. Paul; Shipp-Hilts, Asante; Wilson, Diane; Hollocher, Kurt; Possidente, Bernard; Lnenicka, Greg; Ruden, Douglas M.

    2009-01-01

    We developed Drosophila melanogaster as a model to study correlated behavioral, neuronal and genetic effects of the neurotoxin lead, known to affect cognitive and behavioral development in children. We showed that, as in vertebrates, lead affects both synaptic development and complex behaviors (courtship, fecundity, locomotor activity) in Drosophila. By assessing differential behavioral responses to developmental lead exposure among recombinant inbred Drosophila lines (RI), derived from parental lines Oregon R and Russian 2b, we have now identified a genotype by environment interaction (GEI) for a behavioral trait affected by lead. Drosophila Activity Monitors (TriKinetics, Waltham, MA), which measure activity by counting the number of times a single fly in a small glass tube walks through an infrared beam aimed at the middle of the tube, were used to measure activity of flies, reared from eggs to 4 days of adult age on either control or lead-contaminated medium, from each of 75 RI lines. We observed a significant statistical association between the effect of lead on average daytime activity across lines and one marker locus, 30AB, on chromosome 2; we define this as a Quantitative Trait Locus (QTL) associated with behavioral effects of developmental lead exposure. When 30AB was from Russian 2b, lead significantly increased locomotor activity, whereas, when 30AB was from Oregon R, lead decreased it. 30AB contains about 125 genes among which are likely “candidate genes” for the observed lead-dependent behavioral changes. Drosophila are thus a useful, underutilized model for studying behavioral, synaptic and genetic changes following chronic exposure to lead or other neurotoxins during development. PMID:19428504

  11. Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.

    PubMed

    Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J; Murcray, Cassandra Elizabeth; Conti, David

    2011-12-01

    Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. © 2011 Wiley Periodicals, Inc.

  12. Using Extreme Phenotype Sampling to Identify the Rare Causal Variants of Quantitative Traits in Association Studies

    PubMed Central

    Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J.; Murcray, Cassandra Elizabeth; Conti, David

    2014-01-01

    Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. PMID:21922541

  13. A Conserved Developmental Patterning Network Produces Quantitatively Different Output in Multiple Species of Drosophila

    PubMed Central

    Meyer, Miriah; Wunderlich, Zeba; Simirenko, Lisa; Luengo Hendriks, Cris L.; Keränen, Soile V. E.; Henriquez, Clara; Knowles, David W.; Biggin, Mark D.; Eisen, Michael B.; DePace, Angela H.

    2011-01-01

    Differences in the level, timing, or location of gene expression can contribute to alternative phenotypes at the molecular and organismal level. Understanding the origins of expression differences is complicated by the fact that organismal morphology and gene regulatory networks could potentially vary even between closely related species. To assess the scope of such changes, we used high-resolution imaging methods to measure mRNA expression in blastoderm embryos of Drosophila yakuba and Drosophila pseudoobscura and assembled these data into cellular resolution atlases, where expression levels for 13 genes in the segmentation network are averaged into species-specific, cellular resolution morphological frameworks. We demonstrate that the blastoderm embryos of these species differ in their morphology in terms of size, shape, and number of nuclei. We present an approach to compare cellular gene expression patterns between species, while accounting for varying embryo morphology, and apply it to our data and an equivalent dataset for Drosophila melanogaster. Our analysis reveals that all individual genes differ quantitatively in their spatio-temporal expression patterns between these species, primarily in terms of their relative position and dynamics. Despite many small quantitative differences, cellular gene expression profiles for the whole set of genes examined are largely similar. This suggests that cell types at this stage of development are conserved, though they can differ in their relative position by up to 3–4 cell widths and in their relative proportion between species by as much as 5-fold. Quantitative differences in the dynamics and relative level of a subset of genes between corresponding cell types may reflect altered regulatory functions between species. Our results emphasize that transcriptional networks can diverge over short evolutionary timescales and that even small changes can lead to distinct output in terms of the placement and number of

  14. Quantitative implementation of the endogenous molecular-cellular network hypothesis in hepatocellular carcinoma.

    PubMed

    Wang, Gaowei; Zhu, Xiaomei; Gu, Jianren; Ao, Ping

    2014-06-06

    A quantitative hypothesis for cancer genesis and progression-the endogenous molecular-cellular network hypothesis, intended to include both genetic and epigenetic causes of cancer-has been proposed recently. Using this hypothesis, here we address the molecular basis for maintaining normal liver and hepatocellular carcinoma (HCC), and the potential strategy to cure or relieve HCC. First, we elaborate the basic assumptions of the hypothesis and establish a core working network of HCC according to the hypothesis. Second, we quantify the working network by a nonlinear dynamical system. We show that the working network reproduces the main known features of normal liver and HCC at both the modular and molecular levels. Lastly, the validated working network reveals that (i) specific positive feedback loops are responsible for the maintenance of normal liver and HCC; (ii) inhibiting proliferation and inflammation-related positive feedback loops and simultaneously inducing a liver-specific positive feedback loop is predicated as a potential strategy to cure or relieve HCC; and (iii) the genesis and regression of HCC are asymmetric. In light of the characteristic properties of the nonlinear dynamical system, we demonstrate that positive feedback loops must exist as a simple and general molecular basis for the maintenance of heritable phenotypes, such as normal liver and HCC, and regulating the positive feedback loops directly or indirectly provides potential strategies to cure or relieve HCC.

  15. Quantitative system drift compensates for altered maternal inputs to the gap gene network of the scuttle fly Megaselia abdita

    PubMed Central

    Wotton, Karl R; Jiménez-Guri, Eva; Crombach, Anton; Janssens, Hilde; Alcaine-Colet, Anna; Lemke, Steffen; Schmidt-Ott, Urs; Jaeger, Johannes

    2015-01-01

    The segmentation gene network in insects can produce equivalent phenotypic outputs despite differences in upstream regulatory inputs between species. We investigate the mechanistic basis of this phenomenon through a systems-level analysis of the gap gene network in the scuttle fly Megaselia abdita (Phoridae). It combines quantification of gene expression at high spatio-temporal resolution with systematic knock-downs by RNA interference (RNAi). Initiation and dynamics of gap gene expression differ markedly between M. abdita and Drosophila melanogaster, while the output of the system converges to equivalent patterns at the end of the blastoderm stage. Although the qualitative structure of the gap gene network is conserved, there are differences in the strength of regulatory interactions between species. We term such network rewiring ‘quantitative system drift’. It provides a mechanistic explanation for the developmental hourglass model in the dipteran lineage. Quantitative system drift is likely to be a widespread mechanism for developmental evolution. DOI: http://dx.doi.org/10.7554/eLife.04785.001 PMID:25560971

  16. Quantitative genetics and sex-specific selection on sexually dimorphic traits in bighorn sheep

    PubMed Central

    Poissant, Jocelyn; Wilson, Alastair J; Festa-Bianchet, Marco; Hogg, John T; Coltman, David W

    2008-01-01

    Sexual conflict at loci influencing traits shared between the sexes occurs when sex-specific selection pressures are antagonistic relative to the genetic correlation between the sexes. To assess whether there is sexual conflict over shared traits, we estimated heritability and intersexual genetic correlations for highly sexually dimorphic traits (horn volume and body mass) in a wild population of bighorn sheep (Ovis canadensis) and quantified sex-specific selection using estimates of longevity and lifetime reproductive success. Body mass and horn volume showed significant additive genetic variance in both sexes, and intersexual genetic correlations were 0.24±0.28 for horn volume and 0.63±0.30 for body mass. For horn volume, selection coefficients did not significantly differ from zero in either sex. For body weight, selection coefficients were positive in females but did not differ from zero in males. The absence of detectable sexually antagonistic selection suggests that currently there are no sexual conflicts at loci influencing horn volume and body mass. PMID:18211870

  17. Quantitative analysis of chaperone network throughput in budding yeast

    PubMed Central

    Brownridge, Philip; Lawless, Craig; Payapilly, Aishwarya B; Lanthaler, Karin; Holman, Stephen W; Harman, Victoria M; Grant, Christopher M; Beynon, Robert J; Hubbard, Simon J

    2013-01-01

    The network of molecular chaperones mediates the folding and translocation of the many proteins encoded in the genome of eukaryotic organisms, as well as a response to stress. It has been particularly well characterised in the budding yeast, Saccharomyces cerevisiae, where 63 known chaperones have been annotated and recent affinity purification and MS/MS experiments have helped characterise the attendant network of chaperone targets to a high degree. In this study, we apply our QconCAT methodology to directly quantify the set of yeast chaperones in absolute terms (copies per cell) via SRM MS. Firstly, we compare these to existing quantitative estimates of these yeast proteins, highlighting differences between approaches. Secondly, we cast the results into the context of the chaperone target network and show a distinct relationship between abundance of individual chaperones and their targets. This allows us to characterise the ‘throughput’ of protein molecules passing through individual chaperones and their groups on a proteome-wide scale in an unstressed model eukaryote for the first time. The results demonstrate specialisations of the chaperone classes, which display different overall workloads, efficiencies and preference for the sub-cellular localisation of their targets. The novel integration of the interactome data with quantification supports re-estimates of the level of protein throughout going through molecular chaperones. Additionally, although chaperones target fewer than 40% of annotated proteins we show that they mediate the folding of the majority of protein molecules (∼62% of the total protein flux in the cell), highlighting their importance. PMID:23420633

  18. Comparative mapping of Raphanus sativus genome using Brassica markers and quantitative trait loci analysis for the Fusarium wilt resistance trait.

    PubMed

    Yu, Xiaona; Choi, Su Ryun; Ramchiary, Nirala; Miao, Xinyang; Lee, Su Hee; Sun, Hae Jeong; Kim, Sunggil; Ahn, Chun Hee; Lim, Yong Pyo

    2013-10-01

    Fusarium wilt (FW), caused by the soil-borne fungal pathogen Fusarium oxysporum is a serious disease in cruciferous plants, including the radish (Raphanus sativus). To identify quantitative trait loci (QTL) or gene(s) conferring resistance to FW, we constructed a genetic map of R. sativus using an F2 mapping population derived by crossing the inbred lines '835' (susceptible) and 'B2' (resistant). A total of 220 markers distributed in 9 linkage groups (LGs) were mapped in the Raphanus genome, covering a distance of 1,041.5 cM with an average distance between adjacent markers of 4.7 cM. Comparative analysis of the R. sativus genome with that of Arabidopsis thaliana and Brassica rapa revealed 21 and 22 conserved syntenic regions, respectively. QTL mapping detected a total of 8 loci conferring FW resistance that were distributed on 4 LGs, namely, 2, 3, 6, and 7 of the Raphanus genome. Of the detected QTL, 3 QTLs (2 on LG 3 and 1 on LG 7) were constitutively detected throughout the 2-year experiment. QTL analysis of LG 3, flanked by ACMP0609 and cnu_mBRPGM0085, showed a comparatively higher logarithm of the odds (LOD) value and percentage of phenotypic variation. Synteny analysis using the linked markers to this QTL showed homology to A. thaliana chromosome 3, which contains disease-resistance gene clusters, suggesting conservation of resistance genes between them.

  19. Magnetic resonance imaging traits in siblings discordant for Alzheimer disease.

    PubMed

    Cuenco, Karen T; Green, Robert C; Zhang, J; Lunetta, Kathryn; Erlich, Porat M; Cupples, L Adrienne; Farrer, Lindsay A; DeCarli, Charles

    2008-07-01

    Magnetic resonance imaging (MRI) can aid clinical assessment of brain changes potentially correlated with Alzheimer disease (AD). MRI traits may improve our ability to identify genes associated with AD-outcomes. We evaluated semi-quantitative MRI measures as endophenotypes for genetic studies by assessing their association with AD in families from the Multi-Institutional Research in Alzheimer Genetic Epidemiology (MIRAGE) Study. Discordant siblings from multiple ethnicities were ascertained through a single affected proband. Semi-quantitative MRI measures were obtained for each individual. The association between continuous/ordinal MRI traits and AD were analyzed using generalized estimating equations. Medical history and Apolipoprotein E (APOE)epsilon4 status were evaluated as potential confounders. Comparisons of 214 affected and 234 unaffected subjects from 229 sibships revealed that general cerebral atrophy, white matter hyperintensities (WMH), and mediotemporal atrophy differed significantly between groups (each at P < .0001) and varied by ethnicity. Age at MRI and duration of AD confounded all associations between AD and MRI traits. Among unaffected sibs, the presence of at least one APOEepsilon4 allele and MRI infarction was associated with more WMH after adjusting for age at MRI. The strong association between MRI traits and AD suggests that MRI traits may be informative endophenotypes for basic and clinical studies of AD. In particular, WMH may be a marker of vascular disease that contributes to AD pathogenesis.

  20. Morphological Variation and Inter-Relationships of Quantitative Traits in Enset (Ensete ventricosum (welw.) Cheesman) Germplasm from South and South-Western Ethiopia

    PubMed Central

    Yemataw, Zerihun; Chala, Alemayehu; Grant, Murray R.

    2017-01-01

    Enset (Ensete ventricosum (Welw.) Cheesman) is Ethiopia’s most important root crop. A total of 387 accessions collected from nine different regions of Ethiopia were evaluated for 15 quantitative traits at Areka Agricultural Research Centre to determine the extent and pattern of distribution of morphological variation. The variations among the accessions and regions were significant (p ≤ 0.01) for all the 15 traits studied. Mean for plant height, central shoot weight before grating, and fermented squeezed kocho yield per hectare per year showed regional variation along an altitude gradient and across cultural differences related to the origin of the collection. Furthermore, there were significant correlations among most of the characters. This included the correlation among agronomic characteristics of primary interest in enset breeding such as plant height, pseudostem height, and fermented squeezed kocho yield per hectare per year. Altitude of the collection sites also significantly impacted the various characteristics studied. These results reveal the existence of significant phenotypic variations among the 387 accessions as a whole. Regional differentiations were also evident among the accessions. The implication of the current results for plant breeding, germplasm collection, and in situ and ex situ genetic resource conservation are discussed. PMID:29210979

  1. Using chromosome introgression lines to map quantitative trait loci for photosynthesis parameters in rice (Oryza sativa L.) leaves under drought and well-watered field conditions

    PubMed Central

    Gu, Junfei; Yin, Xinyou; Struik, Paul C.; Stomph, Tjeerd Jan; Wang, Huaqi

    2012-01-01

    Photosynthesis is fundamental to biomass production, but sensitive to drought. To understand the genetics of leaf photosynthesis, especially under drought, upland rice cv. Haogelao, lowland rice cv. Shennong265, and 94 of their introgression lines (ILs) were studied at flowering and grain filling under drought and well-watered field conditions. Gas exchange and chlorophyll fluorescence measurements were conducted to evaluate eight photosynthetic traits. Since these traits are very sensitive to fluctuations in microclimate during measurements under field conditions, observations were adjusted for microclimatic differences through both a statistical covariant model and a physiological approach. Both approaches identified leaf-to-air vapour pressure difference as the variable influencing the traits most. Using the simple sequence repeat (SSR) linkage map for the IL population, 1–3 quantitative trait loci (QTLs) were detected per trait–stage–treatment combination, which explained between 7.0% and 30.4% of the phenotypic variance of each trait. The clustered QTLs near marker RM410 (the interval from 57.3 cM to 68.4 cM on chromosome 9) were consistent over both development stages and both drought and well-watered conditions. This QTL consistency was verified by a greenhouse experiment under a controlled environment. The alleles from the upland rice at this interval had positive effects on net photosynthetic rate, stomatal conductance, transpiration rate, quantum yield of photosystem II (PSII), and the maximum efficiency of light-adapted open PSII. However, the allele of another main QTL from upland rice was associated with increased drought sensitivity of photosynthesis. These results could potentially be used in breeding programmes through marker-assisted selection to improve drought tolerance and photosynthesis simultaneously. PMID:21984650

  2. Confirmatory factor analytic structure and measurement invariance of quantitative autistic traits measured by the social responsiveness scale-2.

    PubMed

    Frazier, Thomas W; Ratliff, Kristin R; Gruber, Chris; Zhang, Yi; Law, Paul A; Constantino, John N

    2014-01-01

    Understanding the factor structure of autistic symptomatology is critical to the discovery and interpretation of causal mechanisms in autism spectrum disorder. We applied confirmatory factor analysis and assessment of measurement invariance to a large (N = 9635) accumulated collection of reports on quantitative autistic traits using the Social Responsiveness Scale, representing a broad diversity of age, severity, and reporter type. A two-factor structure (corresponding to social communication impairment and restricted, repetitive behavior) as elaborated in the updated Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) criteria for autism spectrum disorder exhibited acceptable model fit in confirmatory factor analysis. Measurement invariance was appreciable across age, sex, and reporter (self vs other), but somewhat less apparent between clinical and nonclinical populations in this sample comprised of both familial and sporadic autism spectrum disorders. The statistical power afforded by this large sample allowed relative differentiation of three factors among items encompassing social communication impairment (emotion recognition, social avoidance, and interpersonal relatedness) and two factors among items encompassing restricted, repetitive behavior (insistence on sameness and repetitive mannerisms). Cross-trait correlations remained extremely high, that is, on the order of 0.66-0.92. These data clarify domains of statistically significant factoral separation that may relate to partially-but not completely-overlapping biological mechanisms, contributing to variation in human social competency. Given such robust intercorrelations among symptom domains, understanding their co-emergence remains a high priority in conceptualizing common neural mechanisms underlying autistic syndromes.

  3. A Novel Quantitative Trait Locus on Mouse Chromosome 18, “era1,” Modifies the Entrainment of Circadian Rhythms

    PubMed Central

    Wisor, Jonathan P.; Striz, Martin; DeVoss, Jason; Murphy, Greer M.; Edgar, Dale M.; O'Hara, Bruce F.

    2007-01-01

    Study Objectives: The mammalian circadian clock in the suprachiasmatic nuclei (SCN) of the hypothalamus conveys 24-h rhythmicity to sleep-wake cycles, locomotor activity, and other behavioral and physiological processes. The timing of rhythms relative to the light/dark (LD12:12) cycle is influenced in part by the endogenous circadian period and the time of day specific sensitivity of the clock to light. We now describe a novel circadian rhythm phenotype, and a locus influencing that phenotype, in a segregating population of mice. Methods: By crossbreeding 2 genetically distinct nocturnal strains of mice (Cast/Ei and C57BL/6J) and backcrossing the resulting progeny to Cast/Ei, we have produced a novel circadian phenotype, called early runner mice. Results: Early runner mice entrain to a light/dark cycle at an advanced phase, up to 9 hours before dark onset. This phenotype is not significantly correlated with circadian period in constant darkness and is not associated with disruption of molecular circadian rhythms in the SCN, as assessed by analysis of period gene expression. We have identified a genomic region that regulates this phenotype—a major quantitative trait locus on chromosome 18 (near D18Mit184) that we have named era1 for Early Runner Activity locus one. Phase delays caused by light exposure early in the subjective night were of smaller magnitude in backcross offspring that were homozygous Cast/Ei at D18Mit184 than in those that were heterozygous at this locus. Conclusion: Genetic variability in the circadian response to light may, in part, explain the variance in phase angle of entrainment in this segregating mouse population. Citation: Wisor JP; Striz M; DeVoss J; Murphy GM; Edgar DM; O'Hara BF. A novel quantitative trait locus on mouse chromosome 18, “era1,” modifies the entrainment of circadian rhythms. SLEEP 2007;30(10):1255-1263. PMID:17969459

  4. Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: II. Muscle weight and carcass composition.

    PubMed

    Nassar, M K; Goraga, Z S; Brockmann, G A

    2012-12-01

    In order to identify genetic factors influencing muscle weight and carcass composition in chicken, a linkage analysis was performed with 278 F(2) males of reciprocal crosses between the extremely different inbred lines New Hampshire (NHI) and White Leghorn (WL77). The NHI line had been selected for high meat yield and the WL77 for low egg weight before inbreeding. Highly significant quantitative trait loci (QTL) controlling body weight and the weights of carcass, breast muscle, drumsticks-thighs and wings were identified on GGA4 between 151.5 and 160.5 cM and on GGA27 between 4 and 52 cM. These genomic regions explained 13.7-40.2% and 5.3-13.8% of the phenotypic F(2) variances of the corresponding traits respectively. Additional genome-wide highly significant QTL for the weight of drumsticks-thighs were mapped on GGA1, 5 and 7. Moreover, significant QTL controlling body weight were found on GGA2 and 11. The data obtained in this study can be used for increasing the mapping resolution and subsequent gene targeting on GGA4 and 27 by combining data with other crosses where the same QTL were found. © 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.

  5. Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

    PubMed

    Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L

    2009-12-01

    Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

  6. Clines in quantitative traits: The role of migration patterns and selection scenarios

    PubMed Central

    Geroldinger, Ludwig; Bürger, Reinhard

    2015-01-01

    The existence, uniqueness, and shape of clines in a quantitative trait under selection toward a spatially varying optimum is studied. The focus is on deterministic diploid two-locus n-deme models subject to various migration patterns and selection scenarios. Migration patterns may exhibit isolation by distance, as in the stepping-stone model, or random dispersal, as in the island model. The phenotypic optimum may change abruptly in a single environmental step, more gradually, or not at all. Symmetry assumptions are imposed on phenotypic optima and migration rates. We study clines in the mean, variance, and linkage disequilibrium (LD). Clines result from polymorphic equilibria. The possible equilibrium configurations are determined as functions of the migration rate. Whereas for weak migration, many polymorphic equilibria may be simultaneously stable, their number decreases with increasing migration rate. Also for intermediate migration rates polymorphic equilibria are in general not unique, however, for loci of equal effects the corresponding clines in the mean, variance, and LD are unique. For sufficiently strong migration, no polymorphism is maintained. Both migration pattern and selection scenario exert strong influence on the existence and shape of clines. The results for discrete demes are compared with those from models in which space varies continuously and dispersal is modeled by diffusion. Comparisons with previous studies, which investigated clines under neutrality or under linkage equilibrium, are performed. If there is no long-distance migration, the environment does not change abruptly, and linkage is not very tight, populations are almost everywhere close to linkage equilibrium. PMID:25446959

  7. Two-phase designs for joint quantitative-trait-dependent and genotype-dependent sampling in post-GWAS regional sequencing.

    PubMed

    Espin-Garcia, Osvaldo; Craiu, Radu V; Bull, Shelley B

    2018-02-01

    We evaluate two-phase designs to follow-up findings from genome-wide association study (GWAS) when the cost of regional sequencing in the entire cohort is prohibitive. We develop novel expectation-maximization-based inference under a semiparametric maximum likelihood formulation tailored for post-GWAS inference. A GWAS-SNP (where SNP is single nucleotide polymorphism) serves as a surrogate covariate in inferring association between a sequence variant and a normally distributed quantitative trait (QT). We assess test validity and quantify efficiency and power of joint QT-SNP-dependent sampling and analysis under alternative sample allocations by simulations. Joint allocation balanced on SNP genotype and extreme-QT strata yields significant power improvements compared to marginal QT- or SNP-based allocations. We illustrate the proposed method and evaluate the sensitivity of sample allocation to sampling variation using data from a sequencing study of systolic blood pressure. © 2017 The Authors. Genetic Epidemiology Published by Wiley Periodicals, Inc.

  8. A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways

    PubMed Central

    Taipale, Mikko; Tucker, George; Peng, Jian; Krykbaeva, Irina; Lin, Zhen-Yuan; Larsen, Brett; Choi, Hyungwon; Berger, Bonnie; Gingras, Anne-Claude; Lindquist, Susan

    2014-01-01

    Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of co-factors (co-chaperones) that regulate their specificity and function. However, how these co-chaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We have combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone/co-chaperone/client interaction network in human cells. We uncover hundreds of novel chaperone clients, delineate their participation in specific co-chaperone complexes, and establish a surprisingly distinct network of protein/protein interactions for co-chaperones. As a salient example of the power of such analysis, we establish that NUDC family co-chaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network, its regulation in development and disease, and expand the use of chaperones as sensors for drug/target engagement. PMID:25036637

  9. Gene-Based Testing of Interactions in Association Studies of Quantitative Traits

    PubMed Central

    Ma, Li; Clark, Andrew G.; Keinan, Alon

    2013-01-01

    Various methods have been developed for identifying gene–gene interactions in genome-wide association studies (GWAS). However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene–gene interaction (GGG) tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein–protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies. PMID:23468652

  10. Mapping genomic features to functional traits through microbial whole genome sequences.

    PubMed

    Zhang, Wei; Zeng, Erliang; Liu, Dan; Jones, Stuart E; Emrich, Scott

    2014-01-01

    Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.

  11. Combining Quantitative Genetic Footprinting and Trait Enrichment Analysis to Identify Fitness Determinants of a Bacterial Pathogen

    PubMed Central

    Wiles, Travis J.; Norton, J. Paul; Russell, Colin W.; Dalley, Brian K.; Fischer, Kael F.; Mulvey, Matthew A.

    2013-01-01

    Strains of Extraintestinal Pathogenic Escherichia c oli (ExPEC) exhibit an array of virulence strategies and are a major cause of urinary tract infections, sepsis and meningitis. Efforts to understand ExPEC pathogenesis are challenged by the high degree of genetic and phenotypic variation that exists among isolates. Determining which virulence traits are widespread and which are strain-specific will greatly benefit the design of more effective therapies. Towards this goal, we utilized a quantitative genetic footprinting technique known as transposon insertion sequencing (Tn-seq) in conjunction with comparative pathogenomics to functionally dissect the genetic repertoire of a reference ExPEC isolate. Using Tn-seq and high-throughput zebrafish infection models, we tracked changes in the abundance of ExPEC variants within saturated transposon mutant libraries following selection within distinct host niches. Nine hundred and seventy bacterial genes (18% of the genome) were found to promote pathogen fitness in either a niche-dependent or independent manner. To identify genes with the highest therapeutic and diagnostic potential, a novel Trait Enrichment Analysis (TEA) algorithm was developed to ascertain the phylogenetic distribution of candidate genes. TEA revealed that a significant portion of the 970 genes identified by Tn-seq have homologues more often contained within the genomes of ExPEC and other known pathogens, which, as suggested by the first axiom of molecular Koch's postulates, is considered to be a key feature of true virulence determinants. Three of these Tn-seq-derived pathogen-associated genes—a transcriptional repressor, a putative metalloendopeptidase toxin and a hypothetical DNA binding protein—were deleted and shown to independently affect ExPEC fitness in zebrafish and mouse models of infection. Together, the approaches and observations reported herein provide a resource for future pathogenomics-based research and highlight the diversity of

  12. Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE

    NASA Astrophysics Data System (ADS)

    Correa, R.; Chesta, M. A.; Morales, J. R.; Dinator, M. I.; Requena, I.; Vila, I.

    2006-08-01

    An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced emission) spectra of organic substances. Following the training stage ANN was applied to a subset of similar samples thus obtaining the elemental concentrations in muscle, liver and gills of Cyprinus carpio. Concentrations obtained with the ANN method are in full agreement with results from one standard analytical procedure, showing the high potentiality of ANN in PIXE quantitative analyses.

  13. Brain functional connectivity changes in children that differ in impulsivity temperamental trait

    PubMed Central

    Inuggi, Alberto; Sanz-Arigita, Ernesto; González-Salinas, Carmen; Valero-García, Ana V.; García-Santos, Jose M.; Fuentes, Luis J.

    2014-01-01

    Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN) whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents' report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior. PMID:24834038

  14. Brain functional connectivity changes in children that differ in impulsivity temperamental trait.

    PubMed

    Inuggi, Alberto; Sanz-Arigita, Ernesto; González-Salinas, Carmen; Valero-García, Ana V; García-Santos, Jose M; Fuentes, Luis J

    2014-01-01

    Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN) whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents' report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior.

  15. Violent peer influence: The roles of self-esteem and psychopathic traits.

    PubMed

    Van Zalk, Maarten Herman Walter; Van Zalk, Nejra

    2015-11-01

    Evidence for the risks of psychopathic personality traits for adolescent antisocial behavior are well documented in the literature. Little is known, however, about who the peers of adolescents with these traits are and to what extent they influence one another. In the current study, three dimensions of psychopathic traits were distinguished: grandiose-manipulative traits, callous-unemotional traits, and impulsive-irresponsible traits. A dynamic social network approach was used with three waves of longitudinal data from 1,772 adolescents (51.1% girls, M age = 13.03 at first measurement). Results showed that adolescents with grandiose-manipulative and callous-unemotional traits formed peer relationships with adolescents who had low self-esteem. Furthermore, peers' violence predicted stronger increases in violence for adolescents with low self-esteem than for other adolescents, and peers' violence predicted stronger increases in adolescent violence for peers with high psychopathic traits than for other peers. Thus, findings indicate that adolescents with low self-esteem are vulnerable to deviant peer influence from peers with psychopathic traits.

  16. 3D quantitative phase imaging of neural networks using WDT

    NASA Astrophysics Data System (ADS)

    Kim, Taewoo; Liu, S. C.; Iyer, Raj; Gillette, Martha U.; Popescu, Gabriel

    2015-03-01

    White-light diffraction tomography (WDT) is a recently developed 3D imaging technique based on a quantitative phase imaging system called spatial light interference microscopy (SLIM). The technique has achieved a sub-micron resolution in all three directions with high sensitivity granted by the low-coherence of a white-light source. Demonstrations of the technique on single cell imaging have been presented previously; however, imaging on any larger sample, including a cluster of cells, has not been demonstrated using the technique. Neurons in an animal body form a highly complex and spatially organized 3D structure, which can be characterized by neuronal networks or circuits. Currently, the most common method of studying the 3D structure of neuron networks is by using a confocal fluorescence microscope, which requires fluorescence tagging with either transient membrane dyes or after fixation of the cells. Therefore, studies on neurons are often limited to samples that are chemically treated and/or dead. WDT presents a solution for imaging live neuron networks with a high spatial and temporal resolution, because it is a 3D imaging method that is label-free and non-invasive. Using this method, a mouse or rat hippocampal neuron culture and a mouse dorsal root ganglion (DRG) neuron culture have been imaged in order to see the extension of processes between the cells in 3D. Furthermore, the tomogram is compared with a confocal fluorescence image in order to investigate the 3D structure at synapses.

  17. Quantitative Risk Mapping of Urban Gas Pipeline Networks Using GIS

    NASA Astrophysics Data System (ADS)

    Azari, P.; Karimi, M.

    2017-09-01

    Natural gas is considered an important source of energy in the world. By increasing growth of urbanization, urban gas pipelines which transmit natural gas from transmission pipelines to consumers, will become a dense network. The increase in the density of urban pipelines will influence probability of occurring bad accidents in urban areas. These accidents have a catastrophic effect on people and their property. Within the next few years, risk mapping will become an important component in urban planning and management of large cities in order to decrease the probability of accident and to control them. Therefore, it is important to assess risk values and determine their location on urban map using an appropriate method. In the history of risk analysis of urban natural gas pipeline networks, the pipelines has always been considered one by one and their density in urban area has not been considered. The aim of this study is to determine the effect of several pipelines on the risk value of a specific grid point. This paper outlines a quantitative risk assessment method for analysing the risk of urban natural gas pipeline networks. It consists of two main parts: failure rate calculation where the EGIG historical data are used and fatal length calculation that involves calculation of gas release and fatality rate of consequences. We consider jet fire, fireball and explosion for investigating the consequences of gas pipeline failure. The outcome of this method is an individual risk and is shown as a risk map.

  18. A network-based approach for semi-quantitative knowledge mining and its application to yield variability

    NASA Astrophysics Data System (ADS)

    Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

    2016-12-01

    Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

  19. Gastrointestinal Traits: Individualizing Therapy for Obesity with Drugs and Devices

    PubMed Central

    Camilleri, Michael; Acosta, Andres

    2015-01-01

    Objectives The objectives were to review the discrepancy between numbers of people requiring weight loss treatment and results, and to assess the potential effects of pharmacological treatments (recently approved for obesity) and endoscopically deployed devices on quantitative gastrointestinal traits in development for obesity treatment. Methods We conducted a review of relevant literature to achieve our objectives. Results The 2013 guidelines increased the number of adults recommended for weight loss treatment by 20.9% (116.0 million to 140.2 million). There is an imbalance between efficacy and costs of commercial weight loss programs and drug therapy (average weight loss ~5 kg). The number of bariatric procedures performed in the United States has doubled in the past decade. The efficacy of bariatric surgery is attributed to reduction in the volume of the stomach, nutrient malabsorption with some types of surgery, increased postprandial incretin responses, and activation of farnesoid X receptor mechanisms. These gastrointestinal and behavioral traits identify sub-phenotypes of obesity based on recent research. Conclusions The mechanisms or traits targeted by drug and device treatments include centrally mediated alterations of appetite or satiation, diversion of nutrients, and alteration of stomach capacity, gastric emptying, or incretin hormones. Future treatment may be individualized based on quantitative gastrointestinal and behavioral traits measured in obese patients. PMID:26271184

  20. A Temperature-Responsive Network Links Cell Shape and Virulence Traits in a Primary Fungal Pathogen

    PubMed Central

    Beyhan, Sinem; Gutierrez, Matias; Voorhies, Mark; Sil, Anita

    2013-01-01

    Survival at host temperature is a critical trait for pathogenic microbes of humans. Thermally dimorphic fungal pathogens, including Histoplasma capsulatum, are soil fungi that undergo dramatic changes in cell shape and virulence gene expression in response to host temperature. How these organisms link changes in temperature to both morphologic development and expression of virulence traits is unknown. Here we elucidate a temperature-responsive transcriptional network in H. capsulatum, which switches from a filamentous form in the environment to a pathogenic yeast form at body temperature. The circuit is driven by three highly conserved factors, Ryp1, Ryp2, and Ryp3, that are required for yeast-phase growth at 37°C. Ryp factors belong to distinct families of proteins that control developmental transitions in fungi: Ryp1 is a member of the WOPR family of transcription factors, and Ryp2 and Ryp3 are both members of the Velvet family of proteins whose molecular function is unknown. Here we provide the first evidence that these WOPR and Velvet proteins interact, and that Velvet proteins associate with DNA to drive gene expression. Using genome-wide chromatin immunoprecipitation studies, we determine that Ryp1, Ryp2, and Ryp3 associate with a large common set of genomic loci that includes known virulence genes, indicating that the Ryp factors directly control genes required for pathogenicity in addition to their role in regulating cell morphology. We further dissect the Ryp regulatory circuit by determining that a fourth transcription factor, which we name Ryp4, is required for yeast-phase growth and gene expression, associates with DNA, and displays interdependent regulation with Ryp1, Ryp2, and Ryp3. Finally, we define cis-acting motifs that recruit the Ryp factors to their interwoven network of temperature-responsive target genes. Taken together, our results reveal a positive feedback circuit that directs a broad transcriptional switch between environmental and