Identification of Constrained Cancer Driver Genes Based on Mutation Timing

PubMed Central

Sakoparnig, Thomas; Fried, Patrick; Beerenwinkel, Niko

2015-01-01

Cancer drivers are genomic alterations that provide cells containing them with a selective advantage over their local competitors, whereas neutral passengers do not change the somatic fitness of cells. Cancer-driving mutations are usually discriminated from passenger mutations by their higher degree of recurrence in tumor samples. However, there is increasing evidence that many additional driver mutations may exist that occur at very low frequencies among tumors. This observation has prompted alternative methods for driver detection, including finding groups of mutually exclusive mutations and incorporating prior biological knowledge about gene function or network structure. Dependencies among drivers due to epistatic interactions can also result in low mutation frequencies, but this effect has been ignored in driver detection so far. Here, we present a new computational approach for identifying genomic alterations that occur at low frequencies because they depend on other events. Unlike passengers, these constrained mutations display punctuated patterns of occurrence in time. We test this driver–passenger discrimination approach based on mutation timing in extensive simulation studies, and we apply it to cross-sectional copy number alteration (CNA) data from ovarian cancer, CNA and single-nucleotide variant (SNV) data from breast tumors and SNV data from colorectal cancer. Among the top ranked predicted drivers, we find low-frequency genes that have already been shown to be involved in carcinogenesis, as well as many new candidate drivers. The mutation timing approach is orthogonal and complementary to existing driver prediction methods. It will help identifying from cancer genome data the alterations that drive tumor progression. PMID:25569148

Discovery of cancer common and specific driver gene sets

PubMed Central

2017-01-01

Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295

Discovering potential driver genes through an integrated model of somatic mutation profiles and gene functional information.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2017-09-26

The accumulating availability of next-generation sequencing data offers an opportunity to pinpoint driver genes that are causally implicated in oncogenesis through computational models. Despite previous efforts made regarding this challenging problem, there is still room for improvement in the driver gene identification accuracy. In this paper, we propose a novel integrated approach called IntDriver for prioritizing driver genes. Based on a matrix factorization framework, IntDriver can effectively incorporate functional information from both the interaction network and Gene Ontology similarity, and detect driver genes mutated in different sets of patients at the same time. When evaluated through known benchmarking driver genes, the top ranked genes of our result show highly significant enrichment for the known genes. Meanwhile, IntDriver also detects some known driver genes that are not found by the other competing approaches. When measured by precision, recall and F1 score, the performances of our approach are comparable or increased in comparison to the competing approaches.

Significant associations between driver gene mutations and DNA methylation alterations across many cancer types

PubMed Central

Chen, Yun-Ching; Margolin, Gennady

2017-01-01

Recent evidence shows that mutations in several driver genes can cause aberrant methylation patterns, a hallmark of cancer. In light of these findings, we hypothesized that the landscapes of tumor genomes and epigenomes are tightly interconnected. We measured this relationship using principal component analyses and methylation-mutation associations applied at the nucleotide level and with respect to genome-wide trends. We found that a few mutated driver genes were associated with genome-wide patterns of aberrant hypomethylation or CpG island hypermethylation in specific cancer types. In addition, we identified associations between 737 mutated driver genes and site-specific methylation changes. Moreover, using these mutation-methylation associations, we were able to distinguish between two uterine and two thyroid cancer subtypes. The driver gene mutation–associated methylation differences between the thyroid cancer subtypes were linked to differential gene expression in JAK-STAT signaling, NADPH oxidation, and other cancer-related pathways. These results establish that driver gene mutations are associated with methylation alterations capable of shaping regulatory network functions. In addition, the methodology presented here can be used to subdivide tumors into more homogeneous subsets corresponding to underlying molecular characteristics, which could improve treatment efficacy. PMID:29125844

SBCDDB: Sleeping Beauty Cancer Driver Database for gene discovery in mouse models of human cancers

PubMed Central

Mann, Michael B

2018-01-01

Abstract Large-scale oncogenomic studies have identified few frequently mutated cancer drivers and hundreds of infrequently mutated drivers. Defining the biological context for rare driving events is fundamentally important to increasing our understanding of the druggable pathways in cancer. Sleeping Beauty (SB) insertional mutagenesis is a powerful gene discovery tool used to model human cancers in mice. Our lab and others have published a number of studies that identify cancer drivers from these models using various statistical and computational approaches. Here, we have integrated SB data from primary tumor models into an analysis and reporting framework, the Sleeping Beauty Cancer Driver DataBase (SBCDDB, http://sbcddb.moffitt.org), which identifies drivers in individual tumors or tumor populations. Unique to this effort, the SBCDDB utilizes a single, scalable, statistical analysis method that enables data to be grouped by different biological properties. This allows for SB drivers to be evaluated (and re-evaluated) under different contexts. The SBCDDB provides visual representations highlighting the spatial attributes of transposon mutagenesis and couples this functionality with analysis of gene sets, enabling users to interrogate relationships between drivers. The SBCDDB is a powerful resource for comparative oncogenomic analyses with human cancer genomics datasets for driver prioritization. PMID:29059366

Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development

PubMed Central

Takeda, Haruna; Rust, Alistair G.; Ward, Jerrold M.; Yew, Christopher Chin Kuan; Jenkins, Nancy A.; Copeland, Neal G.

2016-01-01

Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4+/− mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC. PMID:27006499

Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development.

PubMed

Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G

2016-04-05

Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC.

Identifying core gene modules in glioblastoma based on multilayer factor-mediated dysfunctional regulatory networks through integrating multi-dimensional genomic data

PubMed Central

Ping, Yanyan; Deng, Yulan; Wang, Li; Zhang, Hongyi; Zhang, Yong; Xu, Chaohan; Zhao, Hongying; Fan, Huihui; Yu, Fulong; Xiao, Yun; Li, Xia

2015-01-01

The driver genetic aberrations collectively regulate core cellular processes underlying cancer development. However, identifying the modules of driver genetic alterations and characterizing their functional mechanisms are still major challenges for cancer studies. Here, we developed an integrative multi-omics method CMDD to identify the driver modules and their affecting dysregulated genes through characterizing genetic alteration-induced dysregulated networks. Applied to glioblastoma (GBM), the CMDD identified a core gene module of 17 genes, including seven known GBM drivers, and their dysregulated genes. The module showed significant association with shorter survival of GBM. When classifying driver genes in the module into two gene sets according to their genetic alteration patterns, we found that one gene set directly participated in the glioma pathway, while the other indirectly regulated the glioma pathway, mostly, via their dysregulated genes. Both of the two gene sets were significant contributors to survival and helpful for classifying GBM subtypes, suggesting their critical roles in GBM pathogenesis. Also, by applying the CMDD to other six cancers, we identified some novel core modules associated with overall survival of patients. Together, these results demonstrate integrative multi-omics data can identify driver modules and uncover their dysregulated genes, which is useful for interpreting cancer genome. PMID:25653168

Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

Identifying driver characteristics influencing overtaking crashes.

PubMed

Mohaymany, Afshin Shariat; Kashani, Ali Tavakoli; Ranjbari, Andishe

2010-08-01

To identify the most important driver characteristics influencing crash-causing overtaking maneuvers on 2-lane, 2-way rural roads of Iran. Based on the crash data for rural roads of Iran over 3 years from 2006 to 2008, the classification and regression tree (CART) method combined with the quasi-induced exposure concept was applied for 4 independent variables and one target variable of "driver status" with 2 classes of at fault and not at fault. The independent variables were vehicle type, driver's age, driving license, and driving experience of the driver-the latter 2 driver characteristics are relatively new in traffic safety studies. According to the data set, 16,809 drivers were involved in 2-lane, 2-way rural roads overtaking crashes. The analysis revealed that drivers who are younger than 28 years old, whose driving license is type 2--a common driving license that is for driving with passenger car and light vehicles--and whose driving experience is less than 2 years are most probably responsible for overtaking crashes. It was indicated that vehicle type is the most important factor associated with drivers being responsible for the crashes. The results also revealed that younger drivers (18-28 years) are most likely to be at fault in overtaking crashes. Therefore, enforcement and education should be more concentrated on this age group. Due to the incompliant nature of this group, changing the type and amount of traffic fines is essential for more preventing objectives. The research also found 2 relatively new factors of driving license and driving experience to have considerable effects on drivers being at fault, such that type 2 licensed drivers are more responsible compared to type 1 (a driving license for driving with all motor vehicles, which has some age and experience requirements) licensed drivers or drivers with a special license (a driving license with special vehicle types). Moreover, drivers with less than 2 years' driving experience are more

wtf genes are prolific dual poison-antidote meiotic drivers.

PubMed

Nuckolls, Nicole L; Bravo Núñez, María Angélica; Eickbush, Michael T; Young, Janet M; Lange, Jeffrey J; Yu, Jonathan S; Smith, Gerald R; Jaspersen, Sue L; Malik, Harmit S; Zanders, Sarah E

2017-06-20

Meiotic drivers are selfish genes that bias their transmission into gametes, defying Mendelian inheritance. Despite the significant impact of these genomic parasites on evolution and infertility, few meiotic drive loci have been identified or mechanistically characterized. Here, we demonstrate a complex landscape of meiotic drive genes on chromosome 3 of the fission yeasts Schizosaccharomyces kambucha and S. pombe . We identify S. kambucha wtf4 as one of these genes that acts to kill gametes (known as spores in yeast) that do not inherit the gene from heterozygotes. wtf4 utilizes dual, overlapping transcripts to encode both a gamete-killing poison and an antidote to the poison. To enact drive, all gametes are poisoned, whereas only those that inherit wtf4 are rescued by the antidote. Our work suggests that the wtf multigene family proliferated due to meiotic drive and highlights the power of selfish genes to shape genomes, even while imposing tremendous costs to fertility.

Functional annotation of rare gene aberration drivers of pancreatic cancer | Office of Cancer Genomics

Cancer.gov

As we enter the era of precision medicine, characterization of cancer genomes will directly influence therapeutic decisions in the clinic. Here we describe a platform enabling functionalization of rare gene mutations through their high-throughput construction, molecular barcoding and delivery to cancer models for in vivo tumour driver screens. We apply these technologies to identify oncogenic drivers of pancreatic ductal adenocarcinoma (PDAC).

wtf genes are prolific dual poison-antidote meiotic drivers

PubMed Central

Nuckolls, Nicole L; Bravo Núñez, María Angélica; Eickbush, Michael T; Young, Janet M; Lange, Jeffrey J; Yu, Jonathan S; Smith, Gerald R; Jaspersen, Sue L; Malik, Harmit S; Zanders, Sarah E

2017-01-01

Meiotic drivers are selfish genes that bias their transmission into gametes, defying Mendelian inheritance. Despite the significant impact of these genomic parasites on evolution and infertility, few meiotic drive loci have been identified or mechanistically characterized. Here, we demonstrate a complex landscape of meiotic drive genes on chromosome 3 of the fission yeasts Schizosaccharomyces kambucha and S. pombe. We identify S. kambucha wtf4 as one of these genes that acts to kill gametes (known as spores in yeast) that do not inherit the gene from heterozygotes. wtf4 utilizes dual, overlapping transcripts to encode both a gamete-killing poison and an antidote to the poison. To enact drive, all gametes are poisoned, whereas only those that inherit wtf4 are rescued by the antidote. Our work suggests that the wtf multigene family proliferated due to meiotic drive and highlights the power of selfish genes to shape genomes, even while imposing tremendous costs to fertility. DOI: http://dx.doi.org/10.7554/eLife.26033.001 PMID:28631612

Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma.

PubMed

Gu, Yunyan; Wang, Hongwei; Qin, Yao; Zhang, Yujing; Zhao, Wenyuan; Qi, Lishuang; Zhang, Yuannv; Wang, Chenguang; Guo, Zheng

2013-03-01

The heterogeneity of genetic alterations in human cancer genomes presents a major challenge to advancing our understanding of cancer mechanisms and identifying cancer driver genes. To tackle this heterogeneity problem, many approaches have been proposed to investigate genetic alterations and predict driver genes at the individual pathway level. However, most of these approaches ignore the correlation of alteration events between pathways and miss many genes with rare alterations collectively contributing to carcinogenesis. Here, we devise a network-based approach to capture the cooperative functional modules hidden in genome-wide somatic mutation and copy number alteration profiles of glioblastoma (GBM) from The Cancer Genome Atlas (TCGA), where a module is a set of altered genes with dense interactions in the protein interaction network. We identify 7 pairs of significantly co-altered modules that involve the main pathways known to be altered in GBM (TP53, RB and RTK signaling pathways) and highlight the striking co-occurring alterations among these GBM pathways. By taking into account the non-random correlation of gene alterations, the property of co-alteration could distinguish oncogenic modules that contain driver genes involved in the progression of GBM. The collaboration among cancer pathways suggests that the redundant models and aggravating models could shed new light on the potential mechanisms during carcinogenesis and provide new indications for the design of cancer therapeutic strategies.

Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data.

PubMed

Nabavi, Sheida

2016-08-15

With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues. To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies. The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate

PubMed Central

Juul, Malene; Bertl, Johanna; Guo, Qianyun; Nielsen, Morten Muhlig; Świtnicki, Michał; Hornshøj, Henrik; Madsen, Tobias; Hobolth, Asger; Pedersen, Jakob Skou

2017-01-01

Non-coding mutations may drive cancer development. Statistical detection of non-coding driver regions is challenged by a varying mutation rate and uncertainty of functional impact. Here, we develop a statistically founded non-coding driver-detection method, ncdDetect, which includes sample-specific mutational signatures, long-range mutation rate variation, and position-specific impact measures. Using ncdDetect, we screened non-coding regulatory regions of protein-coding genes across a pan-cancer set of whole-genomes (n = 505), which top-ranked known drivers and identified new candidates. For individual candidates, presence of non-coding mutations associates with altered expression or decreased patient survival across an independent pan-cancer sample set (n = 5454). This includes an antigen-presenting gene (CD1A), where 5’UTR mutations correlate significantly with decreased survival in melanoma. Additionally, mutations in a base-excision-repair gene (SMUG1) correlate with a C-to-T mutational-signature. Overall, we find that a rich model of mutational heterogeneity facilitates non-coding driver identification and integrative analysis points to candidates of potential clinical relevance. DOI: http://dx.doi.org/10.7554/eLife.21778.001 PMID:28362259

Evolutionary Origins of Cancer Driver Genes and Implications for Cancer Prognosis

PubMed Central

Chu, Xin-Yi; Zhou, Xiong-Hui; Cui, Ze-Jia; Zhang, Hong-Yu

2017-01-01

The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer. In addition, investigations based on multiple datasets revealed that cancer driver genes were enriched in genes originating from eukaryota, opisthokonta, and eumetazoa. These results have important implications for enhancing the robustness of cancer prognosis models through selecting the gene signatures by the gene age information. PMID:28708071

Evolutionary Origins of Cancer Driver Genes and Implications for Cancer Prognosis.

PubMed

Chu, Xin-Yi; Jiang, Ling-Han; Zhou, Xiong-Hui; Cui, Ze-Jia; Zhang, Hong-Yu

2017-07-14

The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer. In addition, investigations based on multiple datasets revealed that cancer driver genes were enriched in genes originating from eukaryota, opisthokonta, and eumetazoa. These results have important implications for enhancing the robustness of cancer prognosis models through selecting the gene signatures by the gene age information.

The valuation of nursing begins with identifying value drivers.

PubMed

Rutherford, Marcella M

2010-03-01

Adequate investment in a profession links to its ability to define and document its value. This requires identifying those elements or value drivers that demonstrate its worth. To completely identify nursing's value drivers requires meshing the economic, technical, and caring aspects of its profession. Nursing's valuation includes assessing nursing's tangible and intangible assets and documenting these assets. This information communicates nursing's worth and ensures adequate economic investment in its services.

Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins.

PubMed

Waks, Zeev; Weissbrod, Omer; Carmeli, Boaz; Norel, Raquel; Utro, Filippo; Goldschmidt, Yaara

2016-12-23

Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample size limitations by integrating tumor genomics data with a wide spectrum of gene-specific properties to search for rare drivers, functionally classify them, and detect features characteristic of driver genes. We show that our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of potentially novel drivers that eluded over a dozen pan-cancer/multi-tumor type studies. In particular, feature analysis reveals a highly concentrated pool of known and putative tumor suppressors among the <1% of genes that encode very large, chromatin-regulating proteins. Thus, our study highlights the need for deeper characterization of very large, epigenetic regulators in the context of cancer causality.

Mutation analysis of 13 driver genes of colorectal cancer-related pathways in Taiwanese patients.

PubMed

Chang, Yuli Christine; Chang, Jan-Gowth; Liu, Ta-Chih; Lin, Chien-Yu; Yang, Shu-Fen; Ho, Cheng-Mao; Chen, William Tzu-Liang; Chang, Ya-Sian

2016-02-21

To investigate the driver gene mutations associated with colorectal cancer (CRC) in the Taiwanese population. In this study, 103 patients with CRC were evaluated. The samples consisted of 66 men and 37 women with a median age of 59 years and an age range of 26-86 years. We used high-resolution melting analysis (HRM) and direct DNA sequencing to characterize the mutations in 13 driver genes of CRC-related pathways. The HRM assays were conducted using the LightCycler® 480 Instrument provided with the software LightCycler® 480 Gene Scanning Software Version 1.5. We also compared the clinicopathological data of CRC patients with the driver gene mutation status. Of the 103 patients evaluated, 73.79% had mutations in one of the 13 driver genes. We discovered 18 novel mutations in APC, MLH1, MSH2, PMS2, SMAD4 and TP53 that have not been previously reported. Additionally, we found 16 de novo mutations in APC, BMPR1A, MLH1, MSH2, MSH6, MUTYH and PMS2 in cancerous tissues previously reported in the dbSNP database; however, these mutations could not be detected in peripheral blood cells. The APC mutation correlates with lymph node metastasis (34.69% vs 12.96%, P = 0.009) and cancer stage (34.78% vs 14.04%, P = 0.013). No association was observed between other driver gene mutations and clinicopathological features. Furthermore, having two or more driver gene mutations correlates with the degree of lymph node metastasis (42.86% vs 24.07%, P = 0.043). Our findings confirm the importance of 13 CRC-related pathway driver genes in the development of CRC in Taiwanese patients.

Mutation analysis of 13 driver genes of colorectal cancer-related pathways in Taiwanese patients

PubMed Central

Chang, Yuli Christine; Chang, Jan-Gowth; Liu, Ta-Chih; Lin, Chien-Yu; Yang, Shu-Fen; Ho, Cheng-Mao; Chen, William Tzu-Liang; Chang, Ya-Sian

2016-01-01

AIM: To investigate the driver gene mutations associated with colorectal cancer (CRC) in the Taiwanese population. METHODS: In this study, 103 patients with CRC were evaluated. The samples consisted of 66 men and 37 women with a median age of 59 years and an age range of 26-86 years. We used high-resolution melting analysis (HRM) and direct DNA sequencing to characterize the mutations in 13 driver genes of CRC-related pathways. The HRM assays were conducted using the LightCycler® 480 Instrument provided with the software LightCycler® 480 Gene Scanning Software Version 1.5. We also compared the clinicopathological data of CRC patients with the driver gene mutation status. RESULTS: Of the 103 patients evaluated, 73.79% had mutations in one of the 13 driver genes. We discovered 18 novel mutations in APC, MLH1, MSH2, PMS2, SMAD4 and TP53 that have not been previously reported. Additionally, we found 16 de novo mutations in APC, BMPR1A, MLH1, MSH2, MSH6, MUTYH and PMS2 in cancerous tissues previously reported in the dbSNP database; however, these mutations could not be detected in peripheral blood cells. The APC mutation correlates with lymph node metastasis (34.69% vs 12.96%, P = 0.009) and cancer stage (34.78% vs 14.04%, P = 0.013). No association was observed between other driver gene mutations and clinicopathological features. Furthermore, having two or more driver gene mutations correlates with the degree of lymph node metastasis (42.86% vs 24.07%, P = 0.043). CONCLUSION: Our findings confirm the importance of 13 CRC-related pathway driver genes in the development of CRC in Taiwanese patients. PMID:26900293

Engineering and Functional Characterization of Fusion Genes Identifies Novel Oncogenic Drivers of Cancer.

PubMed

Lu, Hengyu; Villafane, Nicole; Dogruluk, Turgut; Grzeskowiak, Caitlin L; Kong, Kathleen; Tsang, Yiu Huen; Zagorodna, Oksana; Pantazi, Angeliki; Yang, Lixing; Neill, Nicholas J; Kim, Young Won; Creighton, Chad J; Verhaak, Roel G; Mills, Gordon B; Park, Peter J; Kucherlapati, Raju; Scott, Kenneth L

2017-07-01

Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK , and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in The Cancer Genome Atlas datasets. In addition to confirming oncogenic activity of the known fusion oncogenes engineered by our construction strategy, we validated five novel fusion genes involving MET, NTRK2 , and BRAF kinases that exhibited potent transforming activity and conferred sensitivity to FDA-approved kinase inhibitors. Our fusion construction strategy also enabled domain-function studies of BRAF fusion genes. Our results confirmed other reports that the transforming activity of BRAF fusions results from truncation-mediated loss of inhibitory domains within the N-terminus of the BRAF protein. BRAF mutations residing within this inhibitory region may provide a means for BRAF activation in cancer, therefore we leveraged the modular design of our fusion gene construction methodology to screen N-terminal domain mutations discovered in tumors that are wild-type at the BRAF mutation hotspot, V600. We identified an oncogenic mutation, F247L, whose expression robustly activated the MAPK pathway and sensitized cells to BRAF and MEK inhibitors. When applied broadly, these tools will facilitate rapid fusion gene construction for subsequent functional characterization and translation into personalized treatment strategies. Cancer Res; 77(13); 3502-12. ©2017 AACR . ©2017 American Association for Cancer Research.

Exome sequencing of oral squamous cell carcinoma in users of Arabian snuff reveals novel candidates for driver genes.

PubMed

Al-Hebshi, Nezar Noor; Li, Shiyong; Nasher, Akram Thabet; El-Setouhy, Maged; Alsanosi, Rashad; Blancato, Jan; Loffredo, Christopher

2016-07-15

The study sought to identify genetic aberrations driving oral squamous cell carcinoma (OSCC) development among users of shammah, an Arabian preparation of smokeless tobacco. Twenty archival OSCC samples, 15 of which with a history of shammah exposure, were whole-exome sequenced at an average depth of 127×. Somatic mutations were identified using a novel, matched controls-independent filtration algorithm. CODEX and Exomedepth coupled with a novel, Database of Genomic Variant-based filter were employed to call somatic gene-copy number variations. Significantly mutated genes were identified with Oncodrive FM and the Youn and Simon's method. Candidate driver genes were nominated based on Gene Set Enrichment Analysis. The observed mutational spectrum was similar to that reported by the TCGA project. In addition to confirming known genes of OSCC (TP53, CDKNA2, CASP8, PIK3CA, HRAS, FAT1, TP63, CCND1 and FADD) the analysis identified several candidate novel driver events including mutations of NOTCH3, CSMD3, CRB1, CLTCL1, OSMR and TRPM2, amplification of the proto-oncogenes FOSL1, RELA, TRAF6, MDM2, FRS2 and BAG1, and deletion of the recently described tumor suppressor SMARCC1. Analysis also revealed significantly altered pathways not previously implicated in OSCC including Oncostatin-M signalling pathway, AP-1 and C-MYB transcription networks and endocytosis. There was a trend for higher number of mutations, amplifications and driver events in samples with history of shammah exposure particularly those that tested EBV positive, suggesting an interaction between tobacco exposure and EBV. The work provides further evidence for the genetic heterogeneity of oral cancer and suggests shammah-associated OSCC is characterized by extensive amplification of oncogenes. © 2016 UICC.

Diagnostic tools for identifying sleepy drivers in the field.

DOT National Transportation Integrated Search

2013-05-06

The overarching goal of this project was to identify and evaluate cognitive and behavioral indices that are sensitive to sleep : deprivation and may help identify commercial motor vehicle drivers (CMV) who are at-risk for driving in a sleep deprived ...

Co-fuse: a new class discovery analysis tool to identify and prioritize recurrent fusion genes from RNA-sequencing data.

PubMed

Paisitkriangkrai, Sakrapee; Quek, Kelly; Nievergall, Eva; Jabbour, Anissa; Zannettino, Andrew; Kok, Chung Hoow

2018-06-07

Recurrent oncogenic fusion genes play a critical role in the development of various cancers and diseases and provide, in some cases, excellent therapeutic targets. To date, analysis tools that can identify and compare recurrent fusion genes across multiple samples have not been available to researchers. To address this deficiency, we developed Co-occurrence Fusion (Co-fuse), a new and easy to use software tool that enables biologists to merge RNA-seq information, allowing them to identify recurrent fusion genes, without the need for exhaustive data processing. Notably, Co-fuse is based on pattern mining and statistical analysis which enables the identification of hidden patterns of recurrent fusion genes. In this report, we show that Co-fuse can be used to identify 2 distinct groups within a set of 49 leukemic cell lines based on their recurrent fusion genes: a multiple myeloma (MM) samples-enriched cluster and an acute myeloid leukemia (AML) samples-enriched cluster. Our experimental results further demonstrate that Co-fuse can identify known driver fusion genes (e.g., IGH-MYC, IGH-WHSC1) in MM, when compared to AML samples, indicating the potential of Co-fuse to aid the discovery of yet unknown driver fusion genes through cohort comparisons. Additionally, using a 272 primary glioma sample RNA-seq dataset, Co-fuse was able to validate recurrent fusion genes, further demonstrating the power of this analysis tool to identify recurrent fusion genes. Taken together, Co-fuse is a powerful new analysis tool that can be readily applied to large RNA-seq datasets, and may lead to the discovery of new disease subgroups and potentially new driver genes, for which, targeted therapies could be developed. The Co-fuse R source code is publicly available at https://github.com/sakrapee/co-fuse .

Evolutionary analysis of vision genes identifies potential drivers of visual differences between giraffe and okapi

PubMed Central

Agaba, Morris; Cavener, Douglas R.

2017-01-01

Background The capacity of visually oriented species to perceive and respond to visual signal is integral to their evolutionary success. Giraffes are closely related to okapi, but the two species have broad range of phenotypic differences including their visual capacities. Vision studies rank giraffe’s visual acuity higher than all other artiodactyls despite sharing similar vision ecological determinants with many of them. The extent to which the giraffe’s unique visual capacity and its difference with okapi is reflected by changes in their vision genes is not understood. Methods The recent availability of giraffe and okapi genomes provided opportunity to identify giraffe and okapi vision genes. Multiple strategies were employed to identify thirty-six candidate mammalian vision genes in giraffe and okapi genomes. Quantification of selection pressure was performed by a combination of branch-site tests of positive selection and clade models of selection divergence through comparing giraffe and okapi vision genes and orthologous sequences from other mammals. Results Signatures of selection were identified in key genes that could potentially underlie giraffe and okapi visual adaptations. Importantly, some genes that contribute to optical transparency of the eye and those that are critical in light signaling pathway were found to show signatures of adaptive evolution or selection divergence. Comparison between giraffe and other ruminants identifies significant selection divergence in CRYAA and OPN1LW. Significant selection divergence was identified in SAG while positive selection was detected in LUM when okapi is compared with ruminants and other mammals. Sequence analysis of OPN1LW showed that at least one of the sites known to affect spectral sensitivity of the red pigment is uniquely divergent between giraffe and other ruminants. Discussion By taking a systemic approach to gene function in vision, the results provide the first molecular clues associated with

Evolutionary analysis of vision genes identifies potential drivers of visual differences between giraffe and okapi.

PubMed

Ishengoma, Edson; Agaba, Morris; Cavener, Douglas R

2017-01-01

The capacity of visually oriented species to perceive and respond to visual signal is integral to their evolutionary success. Giraffes are closely related to okapi, but the two species have broad range of phenotypic differences including their visual capacities. Vision studies rank giraffe's visual acuity higher than all other artiodactyls despite sharing similar vision ecological determinants with many of them. The extent to which the giraffe's unique visual capacity and its difference with okapi is reflected by changes in their vision genes is not understood. The recent availability of giraffe and okapi genomes provided opportunity to identify giraffe and okapi vision genes. Multiple strategies were employed to identify thirty-six candidate mammalian vision genes in giraffe and okapi genomes. Quantification of selection pressure was performed by a combination of branch-site tests of positive selection and clade models of selection divergence through comparing giraffe and okapi vision genes and orthologous sequences from other mammals. Signatures of selection were identified in key genes that could potentially underlie giraffe and okapi visual adaptations. Importantly, some genes that contribute to optical transparency of the eye and those that are critical in light signaling pathway were found to show signatures of adaptive evolution or selection divergence. Comparison between giraffe and other ruminants identifies significant selection divergence in CRYAA and OPN1LW . Significant selection divergence was identified in SAG while positive selection was detected in LUM when okapi is compared with ruminants and other mammals. Sequence analysis of OPN1LW showed that at least one of the sites known to affect spectral sensitivity of the red pigment is uniquely divergent between giraffe and other ruminants. By taking a systemic approach to gene function in vision, the results provide the first molecular clues associated with giraffe and okapi vision adaptations. At

Transposon mutagenesis identifies genes and cellular processes driving epithelial-mesenchymal transition in hepatocellular carcinoma

PubMed Central

Kodama, Takahiro; Newberg, Justin Y.; Kodama, Michiko; Rangel, Roberto; Yoshihara, Kosuke; Tien, Jean C.; Parsons, Pamela H.; Wu, Hao; Finegold, Milton J.; Copeland, Neal G.; Jenkins, Nancy A.

2016-01-01

Epithelial-mesenchymal transition (EMT) is thought to contribute to metastasis and chemoresistance in patients with hepatocellular carcinoma (HCC), leading to their poor prognosis. The genes driving EMT in HCC are not yet fully understood, however. Here, we show that mobilization of Sleeping Beauty (SB) transposons in immortalized mouse hepatoblasts induces mesenchymal liver tumors on transplantation to nude mice. These tumors show significant down-regulation of epithelial markers, along with up-regulation of mesenchymal markers and EMT-related transcription factors (EMT-TFs). Sequencing of transposon insertion sites from tumors identified 233 candidate cancer genes (CCGs) that were enriched for genes and cellular processes driving EMT. Subsequent trunk driver analysis identified 23 CCGs that are predicted to function early in tumorigenesis and whose mutation or alteration in patients with HCC is correlated with poor patient survival. Validation of the top trunk drivers identified in the screen, including MET (MET proto-oncogene, receptor tyrosine kinase), GRB2-associated binding protein 1 (GAB1), HECT, UBA, and WWE domain containing 1 (HUWE1), lysine-specific demethylase 6A (KDM6A), and protein-tyrosine phosphatase, nonreceptor-type 12 (PTPN12), showed that deregulation of these genes activates an EMT program in human HCC cells that enhances tumor cell migration. Finally, deregulation of these genes in human HCC was found to confer sorafenib resistance through apoptotic tolerance and reduced proliferation, consistent with recent studies showing that EMT contributes to the chemoresistance of tumor cells. Our unique cell-based transposon mutagenesis screen appears to be an excellent resource for discovering genes involved in EMT in human HCC and potentially for identifying new drug targets. PMID:27247392

An Australasian model license reassessment procedure for identifying potentially unsafe drivers.

PubMed

Fildes, Brian N; Charlton, Judith; Pronk, Nicola; Langford, Jim; Oxley, Jennie; Koppel, Sjaanie

2008-08-01

Most licensing jurisdictions in Australia currently employ age-based assessment programs as a means to manage older driver safety, yet available evidence suggests that these programs have no safety benefits. This paper describes a community referral-based model license re assessment procedure for identifying and assessing potentially unsafe drivers. While the model was primarily developed for assessing older driver fitness to drive, it could be applicable to other forms of driver impairment associated with increased crash risk. It includes a three-tier process of assessment, involving the use of validated and relevant assessment instruments. A case is argued that this process is a more systematic, transparent and effective process for managing older driver safety and thus more likely to be widely acceptable to the target community and licensing authorities than age-based practices.

A transposon-based genetic screen in mice identifies genes altered in colorectal cancer.

PubMed

Starr, Timothy K; Allaei, Raha; Silverstein, Kevin A T; Staggs, Rodney A; Sarver, Aaron L; Bergemann, Tracy L; Gupta, Mihir; O'Sullivan, M Gerard; Matise, Ilze; Dupuy, Adam J; Collier, Lara S; Powers, Scott; Oberg, Ann L; Asmann, Yan W; Thibodeau, Stephen N; Tessarollo, Lino; Copeland, Neal G; Jenkins, Nancy A; Cormier, Robert T; Largaespada, David A

2009-03-27

Human colorectal cancers (CRCs) display a large number of genetic and epigenetic alterations, some of which are causally involved in tumorigenesis (drivers) and others that have little functional impact (passengers). To help distinguish between these two classes of alterations, we used a transposon-based genetic screen in mice to identify candidate genes for CRC. Mice harboring mutagenic Sleeping Beauty (SB) transposons were crossed with mice expressing SB transposase in gastrointestinal tract epithelium. Most of the offspring developed intestinal lesions, including intraepithelial neoplasia, adenomas, and adenocarcinomas. Analysis of over 16,000 transposon insertions identified 77 candidate CRC genes, 60 of which are mutated and/or dysregulated in human CRC and thus are most likely to drive tumorigenesis. These genes include APC, PTEN, and SMAD4. The screen also identified 17 candidate genes that had not previously been implicated in CRC, including POLI, PTPRK, and RSPO2.

Transposon mutagenesis identifies genes that cooperate with mutant Pten in breast cancer progression

PubMed Central

Rangel, Roberto; Lee, Song-Choon; Hon-Kim Ban, Kenneth; Guzman-Rojas, Liliana; Mann, Michael B.; Newberg, Justin Y.; McNoe, Leslie A.; Selvanesan, Luxmanan; Ward, Jerrold M.; Rust, Alistair G.; Chin, Kuan-Yew; Black, Michael A.; Jenkins, Nancy A.; Copeland, Neal G.

2016-01-01

Triple-negative breast cancer (TNBC) has the worst prognosis of any breast cancer subtype. To better understand the genetic forces driving TNBC, we performed a transposon mutagenesis screen in a phosphatase and tensin homolog (Pten) mutant mice and identified 12 candidate trunk drivers and a much larger number of progression genes. Validation studies identified eight TNBC tumor suppressor genes, including the GATA-like transcriptional repressor TRPS1. Down-regulation of TRPS1 in TNBC cells promoted epithelial-to-mesenchymal transition (EMT) by deregulating multiple EMT pathway genes, in addition to increasing the expression of SERPINE1 and SERPINB2 and the subsequent migration, invasion, and metastasis of tumor cells. Transposon mutagenesis has thus provided a better understanding of the genetic forces driving TNBC and discovered genes with potential clinical importance in TNBC. PMID:27849608

Rare discrepancies in a driver gene alteration within histologically heterogeneous primary lung cancers.

PubMed

Zhong, Wen-zhao; Su, Jian; Xu, Fang-ping; Zhai, Hao-ran; Zhang, Xu-chao; Yang, Xue-ning; Chen, Zhi-yong; Chen, Zhi-hong; Li, Wei; Dong, Song; Zhou, Qing; Yang, Jin-ji; Liu, Yan-hui; Wu, Yi-long

2015-11-01

Most lung adenocarcinomas consist of mixtures of histological subtypes harboring different frequencies of driver gene mutations. However, little is known about intratumoral heterogeneity(ITH) within histologically heterogeneous primary lung cancers. Investigating key driver genes in respective morphological pattern is crucial to personalized treatment. Morphologically different areas within the same surgically resected adenocarcinomas were extracted from tissues to analyze gene status in each growth pattern. Driver genes, epidermal growth factor receptor (EGFR), KRAS and EML4-ALK, were assessed by assays with different sensitivities. Seventy-nine consecutive eligible patients harboring a driver gene (EGFR=65; KRAS=10; EML4-ALK=4) were enrolled. For EGFR mutations, ITH occurred in 13.3% (8/60) by direct sequencing (DS) and 1.7% (1/60) by amplification refractory mutation system (ARMS) (P=0.016) among adenocarcinomas, but consistent within five adeno-squamous cell carcinomas by both methods. ITH among KRAS mutations were detected in 20% (2/10) by DS, whereas consistent (10/10) by high resolution melting. No discrepancies in EML4-ALK rearrangements existed according to fluorescence in situ hybridization. Rare ITHs of EGFR/KRAS/EML4-ALK alterations within histologically heterogeneous primary lung adenocarcinomas existed by methods with higher sensitivity. Discrepancies might be due to abundance of mutant tumor cells and detection assays. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors.

PubMed

Walter, Vonn; Du, Ying; Danilova, Ludmila; Hayward, Michele C; Hayes, D Neil

2018-06-15

Integrated analyses of multiple genomic datatypes are now common in cancer profiling studies. Such data present opportunities for numerous computational experiments, yet analytic pipelines are limited. Tools such as the cBioPortal and Regulome Explorer, although useful, are not easy to access programmatically or to implement locally. Here, we introduce the MVisAGe R package, which allows users to quantify gene-level associations between two genomic datatypes to investigate the effect of genomic alterations (e.g., DNA copy number changes on gene expression). Visualizing Pearson/Spearman correlation coefficients according to the genomic positions of the underlying genes provides a powerful yet novel tool for conducting exploratory analyses. We demonstrate its utility by analyzing three publicly available cancer datasets. Our approach highlights canonical oncogenes in chr11q13 that displayed the strongest associations between expression and copy number, including CCND1 and CTTN , genes not identified by copy number analysis in the primary reports. We demonstrate highly concordant usage of shared oncogenes on chr3q, yet strikingly diverse oncogene usage on chr11q as a function of HPV infection status. Regions of chr19 that display remarkable associations between methylation and gene expression were identified, as were previously unreported miRNA-gene expression associations that may contribute to the epithelial-to-mesenchymal transition. Significance: This study presents an important bioinformatics tool that will enable integrated analyses of multiple genomic datatypes. Cancer Res; 78(12); 3375-85. ©2018 AACR . ©2018 American Association for Cancer Research.

Simultaneous Identification of Multiple Driver Pathways in Cancer

PubMed Central

Leiserson, Mark D. M.; Blokh, Dima

2013-01-01

Distinguishing the somatic mutations responsible for cancer (driver mutations) from random, passenger mutations is a key challenge in cancer genomics. Driver mutations generally target cellular signaling and regulatory pathways consisting of multiple genes. This heterogeneity complicates the identification of driver mutations by their recurrence across samples, as different combinations of mutations in driver pathways are observed in different samples. We introduce the Multi-Dendrix algorithm for the simultaneous identification of multiple driver pathways de novo in somatic mutation data from a cohort of cancer samples. The algorithm relies on two combinatorial properties of mutations in a driver pathway: high coverage and mutual exclusivity. We derive an integer linear program that finds set of mutations exhibiting these properties. We apply Multi-Dendrix to somatic mutations from glioblastoma, breast cancer, and lung cancer samples. Multi-Dendrix identifies sets of mutations in genes that overlap with known pathways – including Rb, p53, PI(3)K, and cell cycle pathways – and also novel sets of mutually exclusive mutations, including mutations in several transcription factors or other genes involved in transcriptional regulation. These sets are discovered directly from mutation data with no prior knowledge of pathways or gene interactions. We show that Multi-Dendrix outperforms other algorithms for identifying combinations of mutations and is also orders of magnitude faster on genome-scale data. Software available at: http://compbio.cs.brown.edu/software. PMID:23717195

Driver genes in non-small cell lung cancer: Characteristics, detection methods, and targeted therapies

PubMed Central

He, Bing; Zhang, Hu-Qin

2017-01-01

Lung cancer is one of the most common causes of cancer-related death in the world. The large number of lung cancer cases is non-small cell lung cancer (NSCLC), which approximately accounting for 75% of lung cancer. Over the past years, our comprehensive knowledge about the molecular biology of NSCLC has been rapidly enriching, which has promoted the discovery of driver genes in NSCLC and directed FDA-approved targeted therapies. Of course, the targeted therapies based on driver genes provide a more exact option for advanced non-small cell lung cancer, improving the survival rate of patients. Now, we will review the landscape of driver genes in NSCLC including the characteristics, detection methods, the application of target therapy and challenges. PMID:28915704

Isolation of Novel CreERT2-Driver Lines in Zebrafish Using an Unbiased Gene Trap Approach

PubMed Central

Jungke, Peggy; Hammer, Juliane; Hans, Stefan; Brand, Michael

2015-01-01

Gene manipulation using the Cre/loxP-recombinase system has been successfully employed in zebrafish to study gene functions and lineage relationships. Recently, gene trapping approaches have been applied to produce large collections of transgenic fish expressing conditional alleles in various tissues. However, the limited number of available cell- and tissue-specific Cre/CreERT2-driver lines still constrains widespread application in this model organism. To enlarge the pool of existing CreERT2-driver lines, we performed a genome-wide gene trap screen using a Tol2-based mCherry-T2a-CreERT2 (mCT2aC) gene trap vector. This cassette consists of a splice acceptor and a mCherry-tagged variant of CreERT2 which enables simultaneous labeling of the trapping event, as well as CreERT2 expression from the endogenous promoter. Using this strategy, we generated 27 novel functional CreERT2-driver lines expressing in a cell- and tissue-specific manner during development and adulthood. This study summarizes the analysis of the generated CreERT2-driver lines with respect to functionality, expression, integration, as well as associated phenotypes. Our results significantly enlarge the existing pool of CreERT2-driver lines in zebrafish and combined with Cre–dependent effector lines, the new CreERT2-driver lines will be important tools to manipulate the zebrafish genome. PMID:26083735

Identifying Immune Drivers of Gulf War Illness Using a Novel Daily Sampling Approach

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-12-1-0557 TITLE: Identifying Immune Drivers of Gulf War Illness Using a Novel Daily Sampling Approach PRINCIPAL...TITLE AND SUBTITLE Identifying Immune Drivers of Gulf War Illness Using A Novel 5a. CONTRACT NUMBER Daily Sampling Approach 5b. GRANT NUMBER...INTRODUCTION: The major aim of this research project is to identify aspects of the immune system that are dysregulated in veterans with Gulf War Illness

Somatic chromosomal engineering identifies BCAN-NTRK1 as a potent glioma driver and therapeutic target.

PubMed

Cook, Peter J; Thomas, Rozario; Kannan, Ram; de Leon, Esther Sanchez; Drilon, Alexander; Rosenblum, Marc K; Scaltriti, Maurizio; Benezra, Robert; Ventura, Andrea

2017-07-11

The widespread application of high-throughput sequencing methods is resulting in the identification of a rapidly growing number of novel gene fusions caused by tumour-specific chromosomal rearrangements, whose oncogenic potential remains unknown. Here we describe a strategy that builds upon recent advances in genome editing and combines ex vivo and in vivo chromosomal engineering to rapidly and effectively interrogate the oncogenic potential of genomic rearrangements identified in human brain cancers. We show that one such rearrangement, an microdeletion resulting in a fusion between Brevican (BCAN) and Neurotrophic Receptor Tyrosine Kinase 1 (NTRK1), is a potent oncogenic driver of high-grade gliomas and confers sensitivity to the experimental TRK inhibitor entrectinib. This work demonstrates that BCAN-NTRK1 is a bona fide human glioma driver and describes a general strategy to define the oncogenic potential of novel glioma-associated genomic rearrangements and to generate accurate preclinical models of this lethal human cancer.

Analysis of Bos taurus and Sus scrofa X and Y chromosome transcriptome highlights reproductive driver genes

PubMed Central

Khan, Faheem Ahmed; Liu, Hui; Zhou, Hao; Wang, Kai; Qamar, Muhammad Tahir Ul; Pandupuspitasari, Nuruliarizki Shinta; Shujun, Zhang

2017-01-01

The biology of sperm, its capability of fertilizing an egg and its role in sex ratio are the major biological questions in reproductive biology. To answer these question we integrated X and Y chromosome transcriptome across different species: Bos taurus and Sus scrofa and identified reproductive driver genes based on Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm. Our strategy resulted in 11007 and 10445 unique genes consisting of 9 and 11 reproductive modules in Bos taurus and Sus scrofa, respectively. The consensus module calculation yields an overall 167 overlapped genes which were mapped to 846 DEGs in Bos taurus to finally get a list of 67 dual feature genes. We develop gene co-expression network of selected 67 genes that consists of 58 nodes (27 down-regulated and 31 up-regulated genes) enriched to 66 GO biological process (BP) including 6 GO annotations related to reproduction and two KEGG pathways. Moreover, we searched significantly related TF (ISRE, AP1FJ, RP58, CREL) and miRNAs (bta-miR-181a, bta-miR-17-5p, bta-miR-146b, bta-miR-146a) which targeted the genes in co-expression network. In addition we performed genetic analysis including phylogenetic, functional domain identification, epigenetic modifications, mutation analysis of the most important reproductive driver genes PRM1, PPP2R2B and PAFAH1B1 and finally performed a protein docking analysis to visualize their therapeutic and gene expression regulation ability. PMID:28903352

How to identify the key factors that affect driver perception of accident risk. A comparison between Italian and Spanish driver behavior.

PubMed

de Oña, Juan; de Oña, Rocio; Eboli, Laura; Forciniti, Carmen; Mazzulla, Gabriella

2014-12-01

Road crashes can be caused by different factors, including infrastructure, vehicles, and human variables. Many research studies have focused solely on identifying the key factors that cause road crashes. From these studies, it emerged that human factors have the most relevant impact on accident severity. More specifically, accident severity depends on several factors related directly to the driver, i.e., driving experience, driver's socio-economic characteristics, and driving behavior and attitudes. In this paper, we investigate driver behaviors and attitudes while driving and specifically focus on different methods for identifying the factors that most affect the driver's perception of accident risk. To this end, we designed and conducted a survey in two different European contexts: the city of Cosenza, which is located in the south of Italy, and the city of Granada, which is located in the south of Spain. Samples of drivers were contacted for their opinions on certain aspects of driving rules and attitudes while driving, and different types of questions were addressed to the drivers to assess their judgments of these aspects. Consequently, different methods of data analysis were applied to determine the aspects that heavily influence driver perception of accident risk. An experiment based on the stated preferences (SP) was carried out with the drivers, and the SP data were analyzed using an ordered probit (OP) model. Interesting findings emerged from different analyses of the data and from the comparisons among the data collected in the two different territorial contexts. We found that both Italian and Spanish drivers consider driving in an altered psychophysical state and violating the overtaking rules to be the most risky behaviors. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mutation drivers of immunological responses to cancer

PubMed Central

Porta-Pardo, Eduard; Godzik, Adam

2016-01-01

In cancer immunology, somatic missense mutations have been mostly studied regarding their role in the generation of neoantigens. However, growing evidence suggests that mutations in certain genes, such as CASP8 or TP53, influence the immune response against a tumor by other mechanisms. Identifying these genes and mechanisms is important because, just as the identification of cancer driver genes led to the development of personalized cancer therapies, a comprehensive catalog of such cancer immunity drivers will aid in the development of therapies aimed at restoring antitumor immunity. Here we present an algorithm, domainXplorer, that can be used to identify potential cancer immunity drivers. To demonstrate its potential, we used it to analyze a dataset of 5,164 tumor samples from TCGA and to identify protein domains whose mutation status correlates with the presence of immune cells in cancer tissue (immune infiltrate). We identified 122 such protein regions including several that belong to proteins with known roles in immune response, such as C2, CD163L1, or FCγR2A. In several cases we show that mutations within the same protein can be associated with more or less immune cell infiltration, depending on the specific domain mutated. These results expand the catalog of potential cancer immunity drivers and highlight the importance of taking into account the structural context of somatic mutations when analyzing their potential association with immune phenotypes. PMID:27401919

Genome-wide methylation sequencing of paired primary and metastatic cell lines identifies common DNA methylation changes and a role for EBF3 as a candidate epigenetic driver of melanoma metastasis

PubMed Central

Chatterjee, Aniruddha; Stockwell, Peter A; Ahn, Antonio; Rodger, Euan J; Leichter, Anna L; Eccles, Michael R

2017-01-01

Epigenetic alterations are increasingly implicated in metastasis, whereas very few genetic mutations have been identified as authentic drivers of cancer metastasis. Yet, to date, few studies have identified metastasis-related epigenetic drivers, in part because a framework for identifying driver epigenetic changes in metastasis has not been established. Using reduced representation bisulfite sequencing (RRBS), we mapped genome-wide DNA methylation patterns in three cutaneous primary and metastatic melanoma cell line pairs to identify metastasis-related epigenetic drivers. Globally, metastatic melanoma cell lines were hypomethylated compared to the matched primary melanoma cell lines. Using whole genome RRBS we identified 75 shared (10 hyper- and 65 hypomethylated) differentially methylated fragments (DMFs), which were associated with 68 genes showing significant methylation differences. One gene, Early B Cell Factor 3 (EBF3), exhibited promoter hypermethylation in metastatic cell lines, and was validated with bisulfite sequencing and in two publicly available independent melanoma cohorts (n = 40 and 458 melanomas, respectively). We found that hypermethylation of the EBF3 promoter was associated with increased EBF3 mRNA levels in metastatic melanomas and subsequent inhibition of DNA methylation reduced EBF3 expression. RNAi-mediated knockdown of EBF3 mRNA levels decreased proliferation, migration and invasion in primary and metastatic melanoma cell lines. Overall, we have identified numerous epigenetic changes characterising metastatic melanoma cell lines, including EBF3-induced aggressive phenotypic behaviour with elevated EBF3 expression in metastatic melanoma, suggesting that EBF3 promoter hypermethylation may be a candidate epigenetic driver of metastasis. PMID:28030832

A Sleeping Beauty forward genetic screen identifies new genes and pathways driving osteosarcoma development and metastasis

PubMed Central

Moriarity, Branden S; Otto, George M; Rahrmann, Eric P; Rathe, Susan K; Wolf, Natalie K; Weg, Madison T; Manlove, Luke A; LaRue, Rebecca S; Temiz, Nuri A; Molyneux, Sam D; Choi, Kwangmin; Holly, Kevin J; Sarver, Aaron L; Scott, Milcah C; Forster, Colleen L; Modiano, Jaime F; Khanna, Chand; Hewitt, Stephen M; Khokha, Rama; Yang, Yi; Gorlick, Richard; Dyer, Michael A; Largaespada, David A

2016-01-01

Osteosarcomas are sarcomas of the bone, derived from osteoblasts or their precursors, with a high propensity to metastasize. Osteosarcoma is associated with massive genomic instability, making it problematic to identify driver genes using human tumors or prototypical mouse models, many of which involve loss of Trp53 function. To identify the genes driving osteosarcoma development and metastasis, we performed a Sleeping Beauty (SB) transposon-based forward genetic screen in mice with and without somatic loss of Trp53. Common insertion site (CIS) analysis of 119 primary tumors and 134 metastatic nodules identified 232 sites associated with osteosarcoma development and 43 sites associated with metastasis, respectively. Analysis of CIS-associated genes identified numerous known and new osteosarcoma-associated genes enriched in the ErbB, PI3K-AKT-mTOR and MAPK signaling pathways. Lastly, we identified several oncogenes involved in axon guidance, including Sema4d and Sema6d, which we functionally validated as oncogenes in human osteosarcoma. PMID:25961939

Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph

PubMed Central

Zhao, Shuai; Tong, Yunhai; Wang, Zitian; Tan, Shaohua

2016-01-01

In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks’ price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds. PMID:27893780

Identifying Key Drivers of Return Reversal with Dynamical Bayesian Factor Graph.

PubMed

Zhao, Shuai; Tong, Yunhai; Wang, Zitian; Tan, Shaohua

2016-01-01

In the stock market, return reversal occurs when investors sell overbought stocks and buy oversold stocks, reversing the stocks' price trends. In this paper, we develop a new method to identify key drivers of return reversal by incorporating a comprehensive set of factors derived from different economic theories into one unified dynamical Bayesian factor graph. We then use the model to depict factor relationships and their dynamics, from which we make some interesting discoveries about the mechanism behind return reversals. Through extensive experiments on the US stock market, we conclude that among the various factors, the liquidity factors consistently emerge as key drivers of return reversal, which is in support of the theory of liquidity effect. Specifically, we find that stocks with high turnover rates or high Amihud illiquidity measures have a greater probability of experiencing return reversals. Apart from the consistent drivers, we find other drivers of return reversal that generally change from year to year, and they serve as important characteristics for evaluating the trends of stock returns. Besides, we also identify some seldom discussed yet enlightening inter-factor relationships, one of which shows that stocks in Finance and Insurance industry are more likely to have high Amihud illiquidity measures in comparison with those in other industries. These conclusions are robust for return reversals under different thresholds.

Drivers of genetic diversity in secondary metabolic gene clusters within a fungal species

PubMed Central

Lind, Abigail L.; Wisecaver, Jennifer H.; Lameiras, Catarina; Wiemann, Philipp; Palmer, Jonathan M.; Keller, Nancy P.; Rodrigues, Fernando; Goldman, Gustavo H.

2017-01-01

Filamentous fungi produce a diverse array of secondary metabolites (SMs) critical for defense, virulence, and communication. The metabolic pathways that produce SMs are found in contiguous gene clusters in fungal genomes, an atypical arrangement for metabolic pathways in other eukaryotes. Comparative studies of filamentous fungal species have shown that SM gene clusters are often either highly divergent or uniquely present in one or a handful of species, hampering efforts to determine the genetic basis and evolutionary drivers of SM gene cluster divergence. Here, we examined SM variation in 66 cosmopolitan strains of a single species, the opportunistic human pathogen Aspergillus fumigatus. Investigation of genome-wide within-species variation revealed 5 general types of variation in SM gene clusters: nonfunctional gene polymorphisms; gene gain and loss polymorphisms; whole cluster gain and loss polymorphisms; allelic polymorphisms, in which different alleles corresponded to distinct, nonhomologous clusters; and location polymorphisms, in which a cluster was found to differ in its genomic location across strains. These polymorphisms affect the function of representative A. fumigatus SM gene clusters, such as those involved in the production of gliotoxin, fumigaclavine, and helvolic acid as well as the function of clusters with undefined products. In addition to enabling the identification of polymorphisms, the detection of which requires extensive genome-wide synteny conservation (e.g., mobile gene clusters and nonhomologous cluster alleles), our approach also implicated multiple underlying genetic drivers, including point mutations, recombination, and genomic deletion and insertion events as well as horizontal gene transfer from distant fungi. Finally, most of the variants that we uncover within A. fumigatus have been previously hypothesized to contribute to SM gene cluster diversity across entire fungal classes and phyla. We suggest that the drivers of genetic

[Correlation of clinicopathologic features and driver gene mutation in non-small cell lung cancer].

PubMed

Chen, L F; Chen, X Y; Yu, X B

2016-04-08

To study the relationship between mutations of well-known driver genes and clinicopathologic characteristics of non-small cell lung cancers (NSCLC). Scorpions amplification refractory mutation system (scorpions ARMS) fluorescence quantitative PCR was performed to investigate 205 driver gene mutation status in NSCLC in correlation with clinicopathological characteristics of the patients. Driver gene mutations were detected in 146 of 205 (71.2%) patients with NSCLC, including 81.7%(138/169) adenocarcinomas, in which mutations of nine genes were found: EGFR (63.3%, 107/169), KRAS (5.9%, 10/169), PIK3CA (4.1%, 7/169), ALK (4.1%, 7/169), ROS1 (3.0%, 5/169), RET (3.6%, 6/169), HER2 (1.8%, 3/169), NRAS (0.6%, 1/169) and BRAF (0.6%, 1/169). The frequencies of driver gene mutations were higher in adenocarcinomas, female patients and non-smokers (P<0.01, P=0.003, P<0.01, respectively). Driver gene mutation status showed no correlation with either the age or the clinical stage (P=0.281, P=0.490, respectively). However, EGFR mutations tended to occur in adenocarcinoma, female, non-smokers, and patients of ≥62 years of age (P<0.01, P<0.01, P=0.002, P=0.012, respectively). The frequency of EGFR mutation was positively correlated with the tumor histology of lepidic, acinar, papillary and micropapillary predominant growth patterns. There was no relationship between EGFR mutation and the clinical stage (P=0.237). The frequency of KRAS mutation was higher in solid predominant and invasive mucinous adenocarcinomas (P=0.015); that of PIK3CA mutation was higher in patients of ≥62 years of age, invasive mucinous adenocarcinoma and fetal adenocarcinoma (P=0.015, P=0.006, respectively). ALK, ROS1 or RET mutation positive NSCLC tended to occur in nonsmokers and have solid predominant tumors and invasive mucinous adenocarcinoma (P=0.012, P=0.017 respectively). The frequency of EML4-ALK mutation was higher in the early stage patients with solid predominant tumors and invasive mucinous

Comparison of algorithms for the detection of cancer-drivers at sub-gene resolution

PubMed Central

Porta-Pardo, Eduard; Kamburov, Atanas; Tamborero, David; Pons, Tirso; Grases, Daniela; Valencia, Alfonso; Lopez-Bigas, Nuria; Getz, Gad; Godzik, Adam

2018-01-01

Understanding genetic events that lead to cancer initiation and progression remains one of the biggest challenges in cancer biology. Traditionally most algorithms for cancer driver identification look for genes that have more mutations than expected from the average background mutation rate. However, there is now a wide variety of methods that look for non-random distribution of mutations within proteins as a signal they have a driving role in cancer. Here we classify and review the progress of such sub-gene resolution algorithms, compare their findings on four distinct cancer datasets from The Cancer Genome Atlas and discuss how predictions from these algorithms can be interpreted in the emerging paradigms that challenge the simple dichotomy between driver and passenger genes. PMID:28714987

Distinguishing between cancer driver and passenger gene alteration candidates via cross-species comparison: a pilot study.

PubMed

Ji, Xinglai; Tang, Jie; Halberg, Richard; Busam, Dana; Ferriera, Steve; Peña, Maria Marjorette O; Venkataramu, Chinnambally; Yeatman, Timothy J; Zhao, Shaying

2010-08-13

We are developing a cross-species comparison strategy to distinguish between cancer driver- and passenger gene alteration candidates, by utilizing the difference in genomic location of orthologous genes between the human and other mammals. As an initial test of this strategy, we conducted a pilot study with human colorectal cancer (CRC) and its mouse model C57BL/6J ApcMin/+, focusing on human 5q22.2 and 18q21.1-q21.2. We first performed bioinformatics analysis on the evolution of 5q22.2 and 18q21.1-q21.2 regions. Then, we performed exon-targeted sequencing, real time quantitative polymerase chain reaction (qPCR), and real time quantitative reverse transcriptase PCR (qRT-PCR) analyses on a number of genes of both regions with both human and mouse colon tumors. These two regions (5q22.2 and 18q21.1-q21.2) are frequently deleted in human CRCs and encode genuine colorectal tumor suppressors APC and SMAD4. They also encode genes such as MCC (mutated in colorectal cancer) with their role in CRC etiology unknown. We have discovered that both regions are evolutionarily unstable, resulting in genes that are clustered in each human region being found scattered at several distinct loci in the genome of many other species. For instance, APC and MCC are within 200 kb apart in human 5q22.2 but are 10 Mb apart in the mouse genome. Importantly, our analyses revealed that, while known CRC driver genes APC and SMAD4 were disrupted in both human colorectal tumors and tumors from ApcMin/+ mice, the questionable MCC gene was disrupted in human tumors but appeared to be intact in mouse tumors. These results indicate that MCC may not actually play any causative role in early colorectal tumorigenesis. We also hypothesize that its disruption in human CRCs is likely a mere result of its close proximity to APC in the human genome. Expanding this pilot study to the entire genome may identify more questionable genes like MCC, facilitating the discovery of new CRC driver gene candidates.

Environmental drivers of the distribution of nitrogen functional genes at a watershed scale.

PubMed

Tsiknia, Myrto; Paranychianakis, Nikolaos V; Varouchakis, Emmanouil A; Nikolaidis, Nikolaos P

2015-06-01

To date only few studies have dealt with the biogeography of microbial communities at large spatial scales, despite the importance of such information to understand and simulate ecosystem functioning. Herein, we describe the biogeographic patterns of microorganisms involved in nitrogen (N)-cycling (diazotrophs, ammonia oxidizers, denitrifiers) as well as the environmental factors shaping these patterns across the Koiliaris Critical Zone Observatory, a typical Mediterranean watershed. Our findings revealed that a proportion of variance ranging from 40 to 80% of functional genes abundance could be explained by the environmental variables monitored, with pH, soil texture, total organic carbon and potential nitrification rate being identified as the most important drivers. The spatial autocorrelation of N-functional genes ranged from 0.2 to 6.2 km and prediction maps, generated by cokriging, revealed distinct patterns of functional genes. The inclusion of functional genes in statistical modeling substantially improved the proportion of variance explained by the models, a result possibly due to the strong relationships that were identified among microbial groups. Significant relationships were set between functional groups, which were further mediated by land use (natural versus agricultural lands). These relationships, in combination with the environmental variables, allow us to provide insights regarding the ecological preferences of N-functional groups and among them the recently identified clade II of nitrous oxide reducers. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Engineering and Functional Characterization of Fusion Genes Identifies Novel Oncogenic Drivers of Cancer. | Office of Cancer Genomics

Cancer.gov

Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK, and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in TCGA datasets.

Obstructive sleep apnea among commercial motor vehicle drivers: using evidence-based practice to identify risk factors.

PubMed

Olszewski, Kimberly; Wolf, Debra

2013-11-01

Commercial motor vehicle driving is a hazardous occupation, having the third highest fatality rate among common U.S. jobs. Among the estimated 14 million U.S. commercial motor vehicle drivers, the prevalence of obstructive sleep apnea is reported to be 17% to 28%. Despite the identified increased prevalence of obstructive sleep apnea among commercial motor vehicle drivers, federal law does not require that they be screened for obstructive sleep apnea. This article presents an evidence-based practice change project; the authors developed, implemented, and evaluated a screening program to identify commercial motor vehicle drivers' risk for obstructive sleep apnea during commercial driver medical examinations. The results of this practice change indicated screening for obstructive sleep apnea during the commercial driver medical examination led to improved identification of obstructive sleep apnea risk among commercial motor vehicle drivers and should be a clinical standard in occupational health clinics. Copyright 2013, SLACK Incorporated.

Can vehicle longitudinal jerk be used to identify aggressive drivers? An examination using naturalistic driving data.

PubMed

Feng, Fred; Bao, Shan; Sayer, James R; Flannagan, Carol; Manser, Michael; Wunderlich, Robert

2017-07-01

This paper investigated the characteristics of vehicle longitudinal jerk (change rate of acceleration with respect to time) by using vehicle sensor data from an existing naturalistic driving study. The main objective was to examine whether vehicle jerk contains useful information that could be potentially used to identify aggressive drivers. Initial investigation showed that there are unique characteristics of vehicle jerk in drivers' gas and brake pedal operations. Thus two jerk-based metrics were examined: (1) driver's frequency of using large positive jerk when pressing the gas pedal, and (2) driver's frequency of using large negative jerk when pressing the brake pedal. To validate the performance of the two metrics, drivers were firstly divided into an aggressive group and a normal group using three classification methods (1) traveling at excessive speed (speeding), (2) following too closely to a front vehicle (tailgating), and (3) their association with crashes or near-crashes in the dataset. The results show that those aggressive drivers defined using any of the three methods above were associated with significantly higher values of the two jerk-based metrics. Between the two metrics the frequency of using large negative jerk seems to have better performance in identifying aggressive drivers. A sensitivity analysis shows the findings were largely consistent with varying parameters in the analysis. The potential applications of this work include developing quantitative surrogate safety measures to identify aggressive drivers and aggressive driving, which could be potentially used to, for example, provide real-time or post-ride performance feedback to the drivers, or warn the surrounding drivers or vehicles using the connected vehicle technologies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exome sequencing identifies putative drivers of progression of transient myeloproliferative disorder to AMKL in infants with Down syndrome.

PubMed

Nikolaev, Sergey I; Santoni, Federico; Vannier, Anne; Falconnet, Emilie; Giarin, Emanuela; Basso, Giuseppe; Hoischen, Alexander; Veltman, Joris A; Groet, Jurgen; Nizetic, Dean; Antonarakis, Stylianos E

2013-07-25

Some neonates with Down syndrome (DS) are diagnosed with self-regressing transient myeloproliferative disorder (TMD), and 20% to 30% of those progress to acute megakaryoblastic leukemia (AMKL). We performed exome sequencing in 7 TMD/AMKL cases and copy-number analysis in these and 10 additional cases. All TMD/AMKL samples contained GATA1 mutations. No exome-sequenced TMD/AMKL sample had other recurrently mutated genes. However, 2 of 5 TMD cases, and all AMKL cases, showed mutations/deletions other than GATA1, in genes proven as transformation drivers in non-DS leukemia (EZH2, APC, FLT3, JAK1, PARK2-PACRG, EXT1, DLEC1, and SMC3). One patient at the TMD stage revealed 2 clonal expansions with different GATA1 mutations, of which 1 clone had an additional driver mutation. Interestingly, it was the other clone that gave rise to AMKL after accumulating mutations in 7 other genes. Data suggest that GATA1 mutations alone are sufficient for clonal expansions, and additional driver mutations at the TMD stage do not necessarily predict AMKL progression. Later in infancy, leukemic progression requires "third-hit driver" mutations/somatic copy-number alterations found in non-DS leukemias. Putative driver mutations affecting WNT (wingless-related integration site), JAK-STAT (Janus kinase/signal transducer and activator of transcription), or MAPK/PI3K (mitogen-activated kinase/phosphatidylinositol-3 kinase) pathways were found in all cases, aberrant activation of which converges on overexpression of MYC.

A framework for identifying carbon hotspots and forest management drivers

Treesearch

Nilesh Timilsina; Francisco J. Escobedo; Wendell P. Cropper; Amr Abd-Elrahman; Thomas Brandeis; Sonia Delphin; Samuel Lambert

2013-01-01

Spatial analyses of ecosystem system services that are directly relevant to both forest management decision making and conservation in the subtropics are rare. Also, frameworks that identify and map carbon stocks and corresponding forest management drivers using available regional, national, and international-level forest inventory datasets could provide insights into...

Comprehensive Ex Vivo Transposon Mutagenesis Identifies Genes That Promote Growth Factor Independence and Leukemogenesis.

PubMed

Guo, Yabin; Updegraff, Barrett L; Park, Sunho; Durakoglugil, Deniz; Cruz, Victoria H; Maddux, Sarah; Hwang, Tae Hyun; O'Donnell, Kathryn A

2016-02-15

Aberrant signaling through cytokine receptors and their downstream signaling pathways is a major oncogenic mechanism underlying hematopoietic malignancies. To better understand how these pathways become pathologically activated and to potentially identify new drivers of hematopoietic cancers, we developed a high-throughput functional screening approach using ex vivo mutagenesis with the Sleeping Beauty transposon. We analyzed over 1,100 transposon-mutagenized pools of Ba/F3 cells, an IL3-dependent pro-B-cell line, which acquired cytokine independence and tumor-forming ability. Recurrent transposon insertions could be mapped to genes in the JAK/STAT and MAPK pathways, confirming the ability of this strategy to identify known oncogenic components of cytokine signaling pathways. In addition, recurrent insertions were identified in a large set of genes that have been found to be mutated in leukemia or associated with survival, but were not previously linked to the JAK/STAT or MAPK pathways nor shown to functionally contribute to leukemogenesis. Forced expression of these novel genes resulted in IL3-independent growth in vitro and tumorigenesis in vivo, validating this mutagenesis-based approach for identifying new genes that promote cytokine signaling and leukemogenesis. Therefore, our findings provide a broadly applicable approach for classifying functionally relevant genes in diverse malignancies and offer new insights into the impact of cytokine signaling on leukemia development. ©2015 American Association for Cancer Research.

Profound Tissue Specificity in Proliferation Control Underlies Cancer Drivers and Aneuploidy Patterns.

PubMed

Sack, Laura Magill; Davoli, Teresa; Li, Mamie Z; Li, Yuyang; Xu, Qikai; Naxerova, Kamila; Wooten, Eric C; Bernardi, Ronald J; Martin, Timothy D; Chen, Ting; Leng, Yumei; Liang, Anthony C; Scorsone, Kathleen A; Westbrook, Thomas F; Wong, Kwok-Kin; Elledge, Stephen J

2018-04-05

Genomics has provided a detailed structural description of the cancer genome. Identifying oncogenic drivers that work primarily through dosage changes is a current challenge. Unrestrained proliferation is a critical hallmark of cancer. We constructed modular, barcoded libraries of human open reading frames (ORFs) and performed screens for proliferation regulators in multiple cell types. Approximately 10% of genes regulate proliferation, with most performing in an unexpectedly highly tissue-specific manner. Proliferation drivers in a given cell type showed specific enrichment in somatic copy number changes (SCNAs) from cognate tumors and helped predict aneuploidy patterns in those tumors, implying that tissue-type-specific genetic network architectures underlie SCNA and driver selection in different cancers. In vivo screening confirmed these results. We report a substantial contribution to the catalog of SCNA-associated cancer drivers, identifying 147 amplified and 107 deleted genes as potential drivers, and derive insights about the genetic network architecture of aneuploidy in tumors. Copyright © 2018 Elsevier Inc. All rights reserved.

Contributions to the Nutrient Toolbox: Identifying Drivers, Nutrient Sources, and Attribution of Exceedances

EPA Science Inventory

Nutrients are a leading cause of impairments in the United States, and as a result tools are needed to identify drivers of nutrients and response variables (such as chlorophyll a), nutrient sources, and identify causes of exceedances of water quality thresholds. This presentatio...

Mutations in the Kinase Domain of the HER2/ERBB2 Gene Identified in a Wide Variety of Human Cancers.

PubMed

Wen, Wenhsiang; Chen, Wangjuh Sting; Xiao, Nick; Bender, Ryan; Ghazalpour, Anatole; Tan, Zheng; Swensen, Jeffrey; Millis, Sherri Z; Basu, Gargi; Gatalica, Zoran; Press, Michael F

2015-09-01

The HER2 (official name ERBB2) gene encodes a membrane receptor in the epidermal growth factor receptor family amplified and overexpressed in adenocarcinoma. Activating mutations also occur in several cancers. We report mutation analyses of the HER2 kinase domain in 7497 histologically diverse cancers. Forty-five genes, including the kinase domain of HER2 with HER2 IHC and dual in situ hybridization, were analyzed in tumors from 7497 patients with cancer, including 850 breast, 770 colorectal, 910 non-small cell lung, 823 uterine or cervical, 1372 ovarian, and 297 pancreatic cancers, as well as 323 melanomas and 2152 other solid tumors. Sixty-nine HER2 kinase domain mutations were identified in tumors from 68 patients (approximately 1% of all cases, ranging from absent in sarcomas to 4% in urothelial cancers), which included previously published activating mutations and 13 novel mutations. Fourteen cases with coexisting HER2 mutation and amplification and/or overexpression were identified. Fifty-two of 68 patients had additional mutations in other analyzed genes, whereas 16 patients (23%) had HER2 mutations identified as the sole driver mutation. HER2 mutations coexisted with HER2 gene amplification and overexpression and with mutations in other functionally important genes. HER2 mutations were identified as the only driver mutation in a significant proportion of solid cancers. Evaluation of anti-HER2 therapies in nonamplified, HER2-mutated cancers is warranted. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

The Cancer Genome Atlas Clinical Explorer: a web and mobile interface for identifying clinical-genomic driver associations.

PubMed

Lee, HoJoon; Palm, Jennifer; Grimes, Susan M; Ji, Hanlee P

2015-10-27

The Cancer Genome Atlas (TCGA) project has generated genomic data sets covering over 20 malignancies. These data provide valuable insights into the underlying genetic and genomic basis of cancer. However, exploring the relationship among TCGA genomic results and clinical phenotype remains a challenge, particularly for individuals lacking formal bioinformatics training. Overcoming this hurdle is an important step toward the wider clinical translation of cancer genomic/proteomic data and implementation of precision cancer medicine. Several websites such as the cBio portal or University of California Santa Cruz genome browser make TCGA data accessible but lack interactive features for querying clinically relevant phenotypic associations with cancer drivers. To enable exploration of the clinical-genomic driver associations from TCGA data, we developed the Cancer Genome Atlas Clinical Explorer. The Cancer Genome Atlas Clinical Explorer interface provides a straightforward platform to query TCGA data using one of the following methods: (1) searching for clinically relevant genes, micro RNAs, and proteins by name, cancer types, or clinical parameters; (2) searching for genomic/proteomic profile changes by clinical parameters in a cancer type; or (3) testing two-hit hypotheses. SQL queries run in the background and results are displayed on our portal in an easy-to-navigate interface according to user's input. To derive these associations, we relied on elastic-net estimates of optimal multiple linear regularized regression and clinical parameters in the space of multiple genomic/proteomic features provided by TCGA data. Moreover, we identified and ranked gene/micro RNA/protein predictors of each clinical parameter for each cancer. The robustness of the results was estimated by bootstrapping. Overall, we identify associations of potential clinical relevance among genes/micro RNAs/proteins using our statistical analysis from 25 cancer types and 18 clinical parameters that

Clonal status of actionable driver events and the timing of mutational processes in cancer evolution

PubMed Central

McGranahan, Nicholas; Favero, Francesco; de Bruin, Elza C.; Birkbak, Nicolai Juul; Szallasi, Zoltan; Swanton, Charles

2015-01-01

Deciphering whether actionable driver mutations are found in all or a subset of tumor cells will likely be required to improve drug development and precision medicine strategies. We analyzed nine cancer types to determine the subclonal frequencies of driver events, to time mutational processes during cancer evolution, and to identify drivers of subclonal expansions. Although mutations in known driver genes typically occurred early in cancer evolution, we also identified later subclonal “actionable” mutations, including BRAF(V600E), IDH1(R132H), PIK3CA(E545K), EGFR(L858R), and KRAS(G12D), which may compromise the efficacy of targeted therapy approaches. More than 20% of IDH1 mutations in glioblastomas, and 15% of mutations in genes in the PI3K(phosphatidylinositol 3-kinase)–AKT–mTOR (mammalian target of rapamycin) signaling axis across all tumor types were subclonal. Mutations in the RAS–MEK (mitogen-activated protein kinase kinase) signaling axis were less likely to be subclonal than mutations in genes associated with PI3K-AKT-mTORsignaling. Analysis of late mutations revealed a link between APOBEC-mediated mutagenesis and the acquisition of subclonal driver mutations and uncovered putative cancer genes involved in subclonal expansions, including CTNNA2 and ATXN1. Our results provide a pan-cancer census of driver events within the context of intratumor heterogeneity and reveal patterns of tumor evolution across cancers. The frequent presence of subclonal driver mutations suggests the need to stratify targeted therapy response according to the proportion of tumor cells in which the driver is identified. PMID:25877892

Clonal status of actionable driver events and the timing of mutational processes in cancer evolution.

PubMed

McGranahan, Nicholas; Favero, Francesco; de Bruin, Elza C; Birkbak, Nicolai Juul; Szallasi, Zoltan; Swanton, Charles

2015-04-15

Deciphering whether actionable driver mutations are found in all or a subset of tumor cells will likely be required to improve drug development and precision medicine strategies. We analyzed nine cancer types to determine the subclonal frequencies of driver events, to time mutational processes during cancer evolution, and to identify drivers of subclonal expansions. Although mutations in known driver genes typically occurred early in cancer evolution, we also identified later subclonal "actionable" mutations, including BRAF (V600E), IDH1 (R132H), PIK3CA (E545K), EGFR (L858R), and KRAS (G12D), which may compromise the efficacy of targeted therapy approaches. More than 20% of IDH1 mutations in glioblastomas, and 15% of mutations in genes in the PI3K (phosphatidylinositol 3-kinase)-AKT-mTOR (mammalian target of rapamycin) signaling axis across all tumor types were subclonal. Mutations in the RAS-MEK (mitogen-activated protein kinase kinase) signaling axis were less likely to be subclonal than mutations in genes associated with PI3K-AKT-mTOR signaling. Analysis of late mutations revealed a link between APOBEC-mediated mutagenesis and the acquisition of subclonal driver mutations and uncovered putative cancer genes involved in subclonal expansions, including CTNNA2 and ATXN1. Our results provide a pan-cancer census of driver events within the context of intratumor heterogeneity and reveal patterns of tumor evolution across cancers. The frequent presence of subclonal driver mutations suggests the need to stratify targeted therapy response according to the proportion of tumor cells in which the driver is identified. Copyright © 2015, American Association for the Advancement of Science.

Motor vehicle accident or driver suicide? Identifying cases of failed driver suicide in the trauma setting.

PubMed

Henderson, Antony F; Joseph, Anthony P

2012-01-01

Many authors have suggested that some road traffic crashes are disguised suicide attempts. A case report and literature review is used to explore this claim and to examine the frequency and risk factors associated with driver suicide. The author concludes the methodological difficulty of establishing the driver's intent of suicide accounts for an under-estimation of the frequency of this event and that many cases of driver suicide go unrecognised. Familiarity with the risk factors associated with driver suicide may assist in the identification of cases of failed driver suicide and referral to psychiatric services. Copyright © 2011 Elsevier Ltd. All rights reserved.

Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival.

PubMed

Suo, Chen; Hrydziuszko, Olga; Lee, Donghwan; Pramana, Setia; Saputra, Dhany; Joshi, Himanshu; Calza, Stefano; Pawitan, Yudi

2015-08-15

Genome and transcriptome analyses can be used to explore cancers comprehensively, and it is increasingly common to have multiple omics data measured from each individual. Furthermore, there are rich functional data such as predicted impact of mutations on protein coding and gene/protein networks. However, integration of the complex information across the different omics and functional data is still challenging. Clinical validation, particularly based on patient outcomes such as survival, is important for assessing the relevance of the integrated information and for comparing different procedures. An analysis pipeline is built for integrating genomic and transcriptomic alterations from whole-exome and RNA sequence data and functional data from protein function prediction and gene interaction networks. The method accumulates evidence for the functional implications of mutated potential driver genes found within and across patients. A driver-gene score (DGscore) is developed to capture the cumulative effect of such genes. To contribute to the score, a gene has to be frequently mutated, with high or moderate mutational impact at protein level, exhibiting an extreme expression and functionally linked to many differentially expressed neighbors in the functional gene network. The pipeline is applied to 60 matched tumor and normal samples of the same patient from The Cancer Genome Atlas breast-cancer project. In clinical validation, patients with high DGscores have worse survival than those with low scores (P = 0.001). Furthermore, the DGscore outperforms the established expression-based signatures MammaPrint and PAM50 in predicting patient survival. In conclusion, integration of mutation, expression and functional data allows identification of clinically relevant potential driver genes in cancer. The documented pipeline including annotated sample scripts can be found in http://fafner.meb.ki.se/biostatwiki/driver-genes/. yudi.pawitan@ki.se Supplementary data are

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2018-06-05

Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods incorporate interaction network as prior information. However, the prior information of mRNA expression patterns are not exploited by these existing network-based methods, which is also proven to be highly informative of cancer progressions. To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from mutation data. Furthermore, our framework also conducts Frobenius norm regularization to overcome overfitting issue. Sparsity-inducing penalty is employed to obtain sparse scores in gene representations, of which the top scored genes are selected as driver candidates. Evaluation experiments by known benchmarking genes indicate that the performance of our method benefits from the two type of prior information. Our method also outperforms the existing network-based methods, and detect some driver genes that are not predicted by the competing methods. In summary, our proposed method can improve the performance of driver gene discovery by effectively incorporating prior information from interaction network and mRNA expression patterns into a robust and sparse co-regularized matrix factorization framework.

A CRISPR-Based Screen Identifies Genes Essential for West-Nile-Virus-Induced Cell Death.

PubMed

Ma, Hongming; Dang, Ying; Wu, Yonggan; Jia, Gengxiang; Anaya, Edgar; Zhang, Junli; Abraham, Sojan; Choi, Jang-Gi; Shi, Guojun; Qi, Ling; Manjunath, N; Wu, Haoquan

2015-07-28

West Nile virus (WNV) causes an acute neurological infection attended by massive neuronal cell death. However, the mechanism(s) behind the virus-induced cell death is poorly understood. Using a library containing 77,406 sgRNAs targeting 20,121 genes, we performed a genome-wide screen followed by a second screen with a sub-library. Among the genes identified, seven genes, EMC2, EMC3, SEL1L, DERL2, UBE2G2, UBE2J1, and HRD1, stood out as having the strongest phenotype, whose knockout conferred strong protection against WNV-induced cell death with two different WNV strains and in three cell lines. Interestingly, knockout of these genes did not block WNV replication. Thus, these appear to be essential genes that link WNV replication to downstream cell death pathway(s). In addition, the fact that all of these genes belong to the ER-associated protein degradation (ERAD) pathway suggests that this might be the primary driver of WNV-induced cell death. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A network-based, integrative study to identify core biological pathways that drive breast cancer clinical subtypes

PubMed Central

Dutta, B; Pusztai, L; Qi, Y; André, F; Lazar, V; Bianchini, G; Ueno, N; Agarwal, R; Wang, B; Shiang, C Y; Hortobagyi, G N; Mills, G B; Symmans, W F; Balázsi, G

2012-01-01

Background: The rapid collection of diverse genome-scale data raises the urgent need to integrate and utilise these resources for biological discovery or biomedical applications. For example, diverse transcriptomic and gene copy number variation data are currently collected for various cancers, but relatively few current methods are capable to utilise the emerging information. Methods: We developed and tested a data-integration method to identify gene networks that drive the biology of breast cancer clinical subtypes. The method simultaneously overlays gene expression and gene copy number data on protein–protein interaction, transcriptional-regulatory and signalling networks by identifying coincident genomic and transcriptional disturbances in local network neighborhoods. Results: We identified distinct driver-networks for each of the three common clinical breast cancer subtypes: oestrogen receptor (ER)+, human epidermal growth factor receptor 2 (HER2)+, and triple receptor-negative breast cancers (TNBC) from patient and cell line data sets. Driver-networks inferred from independent datasets were significantly reproducible. We also confirmed the functional relevance of a subset of randomly selected driver-network members for TNBC in gene knockdown experiments in vitro. We found that TNBC driver-network members genes have increased functional specificity to TNBC cell lines and higher functional sensitivity compared with genes selected by differential expression alone. Conclusion: Clinical subtype-specific driver-networks identified through data integration are reproducible and functionally important. PMID:22343619

A Pooled Sequencing Approach Identifies a Candidate Meiotic Driver in Drosophila

PubMed Central

Wei, Kevin H.-C.; Reddy, Hemakumar M.; Rathnam, Chandramouli; Lee, Jimin; Lin, Deanna; Ji, Shuqing; Mason, James M.; Clark, Andrew G.; Barbash, Daniel A.

2017-01-01

Meiotic drive occurs when a selfish element increases its transmission frequency above the Mendelian ratio by hijacking the asymmetric divisions of female meiosis. Meiotic drive causes genomic conflict and potentially has a major impact on genome evolution, but only a few drive loci of large effect have been described. New methods to reliably detect meiotic drive are therefore needed, particularly for discovering moderate-strength drivers that are likely to be more prevalent in natural populations than strong drivers. Here, we report an efficient method that uses sequencing of large pools of backcross (BC1) progeny to test for deviations from Mendelian segregation genome-wide with single-nucleotide polymorphisms (SNPs) that distinguish the parental strains. We show that meiotic drive can be detected by a characteristic pattern of decay in distortion of SNP frequencies, caused by recombination unlinking the driver from distal loci. We further show that control crosses allow allele-frequency distortion caused by meiotic drive to be distinguished from distortion resulting from developmental effects. We used this approach to test whether chromosomes with extreme telomere-length differences segregate at Mendelian ratios, as telomeric regions are a potential hotspot for meiotic drive due to their roles in meiotic segregation and multiple observations of high rates of telomere sequence evolution. Using four different pairings of long and short telomere strains, we find no evidence that extreme telomere-length variation causes meiotic drive in Drosophila. However, we identify one candidate meiotic driver in a centromere-linked region that shows an ∼8% increase in transmission frequency, corresponding to a ∼54:46 segregation ratio. Our results show that candidate meiotic drivers of moderate strength can be readily detected and localized in pools of BC1 progeny. PMID:28258181

Circuits of cancer drivers revealed by convergent misregulation of transcription factor targets across tumor types.

PubMed

Gonzalez-Perez, Abel

2016-01-20

Large tumor genome sequencing projects have now uncovered a few hundred genes involved in the onset of tumorigenesis, or drivers, in some two dozen malignancies. One of the main challenges emerging from this catalog of drivers is how to make sense of their heterogeneity in most cancer types. This is key not only to understand how carcinogenesis appears and develops in these malignancies to be able to early diagnose them, but also to open up the possibility to employ therapeutic strategies targeting a driver protein to counteract the alteration of another connected driver. Here, I focus on driver transcription factors and their connection to tumorigensis in several tumor types through the alteration of the expression of their targets. First, I explore their involvement in tumorigenesis as mutational drivers in 28 different tumor types. Then, I collect a list of downstream targets of the all driver transcription factors (TFs), and identify which of them exhibit a differential expression upon alterations of driver transcription factors. I identify the subset of targets of each TF most likely mediating the tumorigenic effect of their driver alterations in each tumor type, and explore their overlap. Furthermore, I am able to identify other driver genes that cause tumorigenesis through the alteration of very similar sets of targets. I thus uncover these circuits of connected drivers which cause tumorigenesis through the perturbation of overlapping cellular pathways in a pan-cancer manner across 15 malignancies. The systematic detection of these circuits may be key to propose novel therapeutic strategies indirectly targeting driver alterations in tumors.

Identifying mismatches between institutional perceptions of water-related risk drivers and water management strategies in three river basin areas

NASA Astrophysics Data System (ADS)

Räsänen, Aleksi; Juhola, Sirkku; Monge Monge, Adrián; Käkönen, Mira; Kanninen, Markku; Nygren, Anja

2017-07-01

Water-related risks and vulnerabilities are driven by variety of stressors, including climate and land use change, as well as changes in socio-economic positions and political landscapes. Hence, water governance, which addresses risks and vulnerabilities, should target multiple stressors. We analyze the institutional perceptions of the drivers and strategies for managing water-related risks and vulnerabilities in three regionally important river basin areas located in Finland, Mexico, and Laos. Our analysis is based on data gathered through participatory workshops and complemented by qualitative content analysis of relevant policy documents. The identified drivers and proposed risk reduction strategies showed the multidimensionality and context-specificity of water-related risks and vulnerabilities across study areas. Most of the identified drivers were seen to increase risks, but some of the drivers were positive trends, and drivers also included also policy instruments that can both increase or decrease risks. Nevertheless, all perceived drivers were not addressed with suggested risk reduction strategies. In particular, most of the risk reduction strategies were incremental adjustments, although many of the drivers classified as most important were large-scale trends, such as climate change, land use changes and increase in foreign investments. We argue that there is a scale mismatch between the identified drivers and suggested strategies, which questions the opportunity to manage the drivers by single-scale incremental adjustments. Our study suggests that for more sustainable risk and vulnerability reduction, the root causes of water-related risks and vulnerabilities should be addressed through adaptive multi-scale governance that carefully considers the context-specificity and the multidimensionality of the associated drivers and stressors.

Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma.

PubMed

Walker, Brian A; Mavrommatis, Konstantinos; Wardell, Christopher P; Ashby, T Cody; Bauer, Michael; Davies, Faith E; Rosenthal, Adam; Wang, Hongwei; Qu, Pingping; Hoering, Antje; Samur, Mehmet; Towfic, Fadi; Ortiz, Maria; Flynt, Erin; Yu, Zhinuan; Yang, Zhihong; Rozelle, Dan; Obenauer, John; Trotter, Matthew; Auclair, Daniel; Keats, Jonathan; Bolli, Niccolo; Fulciniti, Mariateresa; Szalat, Raphael; Moreau, Philippe; Durie, Brian; Stewart, A Keith; Goldschmidt, Hartmut; Raab, Marc S; Einsele, Hermann; Sonneveld, Pieter; San Miguel, Jesus; Lonial, Sagar; Jackson, Graham H; Anderson, Kenneth C; Avet-Loiseau, Herve; Munshi, Nikhil; Thakurta, Anjan; Morgan, Gareth J

2018-06-08

Understanding the profile of oncogene and tumor suppressor gene mutations with their interactions and impact on the prognosis of multiple myeloma (MM) can improve the definition of disease subsets and identify pathways important in disease pathobiology. Using integrated genomics of 1,273 newly diagnosed patients with multiple myeloma we identify 63 driver genes, some of which are novel including IDH1 , IDH2 , HUWE1 , KLHL6 , and PTPN11 Oncogene mutations are significantly more clonal than tumor suppressor mutations, indicating they may exert a bigger selective pressure. Patients with more mutations in driver genes are associated with a worse outcome, as are those with identified mechanisms of genomic instability. Oncogenic dependencies were identified between mutations in driver genes, common regions of copy number change, and primary translocation and hyperdiploidy events. These dependencies included associations with t(4;14) and mutations in FGFR3 , DIS3 and PRKD2 ; t(11;14) with mutations in CCND1 and IRF4 ; t(14;16) with mutations in MAF , BRAF , DIS3 and ATM ; and hyperdiploidy with gain 11q, mutations in FAM46C and MYC rearrangements. These associations indicate that the genomic landscape of myeloma is pre-determined by the primary events upon which further dependencies are built, giving rise to a non-random accumulation of genetic hits. Understanding these dependencies may elucidate potential evolutionary patterns and lead to better treatment regimens. Copyright © 2018 American Society of Hematology.

SNP array profiling of childhood adrenocortical tumors reveals distinct pathways of tumorigenesis and highlights candidate driver genes.

PubMed

Letouzé, Eric; Rosati, Roberto; Komechen, Heloisa; Doghman, Mabrouka; Marisa, Laetitia; Flück, Christa; de Krijger, Ronald R; van Noesel, Max M; Mas, Jean-Christophe; Pianovski, Mara A D; Zambetti, Gerard P; Figueiredo, Bonald C; Lalli, Enzo

2012-07-01

Childhood adrenocortical tumors (ACT) are rare malignancies, except in southern Brazil, where a higher incidence rate is associated to a high frequency of the founder R337H TP53 mutation. To date, copy number alterations in these tumors have only been analyzed by low-resolution comparative genomic hybridization. We analyzed an international series of 25 childhood ACT using high-resolution single nucleotide polymorphism arrays to: 1) detect focal copy number alterations highlighting candidate driver genes; and 2) compare genetic alterations between Brazilian patients carrying the R337H TP53 mutation and non-Brazilian patients. We identified 16 significantly recurrent chromosomal alterations (q-value < 0.05), the most frequent being -4q34, +9q33-q34, +19p, loss of heterozygosity (LOH) of chromosome 17 and 11p15. Focal amplifications and homozygous deletions comprising well-known oncogenes (MYC, MDM2, PDGFRA, KIT, MCL1, BCL2L1) and tumor suppressors (TP53, RB1, RPH3AL) were identified. In addition, eight focal deletions were detected at 4q34, defining a sharp peak region around the noncoding RNA LINC00290 gene. Although non-Brazilian tumors with a mutated TP53 were similar to Brazilian tumors, those with a wild-type TP53 displayed distinct genomic profiles, with significantly fewer rearrangements (P = 0.019). In particular, three alterations (LOH of chromosome 17, +9q33-q34, and -4q34) were significantly more frequent in TP53-mutated samples. Finally, two of four TP53 wild-type tumors displayed as sole rearrangement a copy-neutral LOH of the imprinted region at 11p15, supporting a major role for this region in ACT development. Our findings highlight potential driver genes and cellular pathways implicated in childhood ACT and demonstrate the existence of different oncogenic routes in this pathology.

Targeted deletion and lipidomic analysis identify epithelial cell COX-2 as a major driver of chemically induced skin cancer.

PubMed

Jiao, Jing; Ishikawa, Tomo-O; Dumlao, Darren S; Norris, Paul C; Magyar, Clara E; Mikulec, Carol; Catapang, Art; Dennis, Edward A; Fischer, Susan M; Herschman, Harvey R

2014-11-01

Pharmacologic and global gene deletion studies demonstrate that cyclooxygenase-2 (PTGS2/COX-2) plays a critical role in DMBA/TPA-induced skin tumor induction. Although many cell types in the tumor microenvironment express COX-2, the cell types in which COX-2 expression is required for tumor promotion are not clearly established. Here, cell type-specific Cox-2 gene deletion reveals a vital role for skin epithelial cell COX-2 expression in DMBA/TPA tumor induction. In contrast, myeloid Cox-2 gene deletion has no effect on DMBA/TPA tumorigenesis. The infrequent, small tumors that develop on mice with an epithelial cell-specific Cox-2 gene deletion have decreased proliferation and increased cell differentiation properties. Blood vessel density is reduced in tumors with an epithelial cell-specific Cox-2 gene deletion, compared with littermate control tumors, suggesting a reciprocal relationship in tumor progression between COX-2-expressing tumor epithelial cells and microenvironment endothelial cells. Lipidomics analysis of skin and tumors from DMBA/TPA-treated mice suggests that the prostaglandins PGE2 and PGF2α are likely candidates for the epithelial cell COX-2-dependent eicosanoids that mediate tumor progression. This study both illustrates the value of cell type-specific gene deletions in understanding the cellular roles of signal-generating pathways in complex microenvironments and emphasizes the benefit of a systems-based lipidomic analysis approach to identify candidate lipid mediators of biologic responses. Cox-2 gene deletion demonstrates that intrinsic COX-2 expression in initiated keratinocytes is a principal driver of skin carcinogenesis; lipidomic analysis identifies likely prostanoid effectors. ©2014 American Association for Cancer Research.

Characterization of potential driver mutations involved in human breast cancer by computational approaches

PubMed Central

Rajendran, Barani Kumar; Deng, Chu-Xia

2017-01-01

Breast cancer is the second most frequently occurring form of cancer and is also the second most lethal cancer in women worldwide. A genetic mutation is one of the key factors that alter multiple cellular regulatory pathways and drive breast cancer initiation and progression yet nature of these cancer drivers remains elusive. In this article, we have reviewed various computational perspectives and algorithms for exploring breast cancer driver mutation genes. Using both frequency based and mutational exclusivity based approaches, we identified 195 driver genes and shortlisted 63 of them as candidate drivers for breast cancer using various computational approaches. Finally, we conducted network and pathway analysis to explore their functions in breast tumorigenesis including tumor initiation, progression, and metastasis. PMID:28477017

Identification of mutated driver pathways in cancer using a multi-objective optimization model.

PubMed

Zheng, Chun-Hou; Yang, Wu; Chong, Yan-Wen; Xia, Jun-Feng

2016-05-01

New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context. Copyright © 2016 Elsevier Ltd. All rights reserved.

NIH Researchers Identify OCD Risk Gene

MedlinePlus

... News From NIH NIH Researchers Identify OCD Risk Gene Past Issues / Summer 2006 Table of Contents For ... and Alcoholism (NIAAA) have identified a previously unknown gene variant that doubles an individual's risk for obsessive- ...

Inferring causal genomic alterations in breast cancer using gene expression data

PubMed Central

2011-01-01

Background One of the primary objectives in cancer research is to identify causal genomic alterations, such as somatic copy number variation (CNV) and somatic mutations, during tumor development. Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies. Results We developed a framework for identifying recurrent regions of CNV and distinguishing the cancer driver genes from the passenger genes in the regions. By inferring CNV regions across many datasets we were able to identify 109 recurrent amplified/deleted CNV regions. Many of these regions are enriched for genes involved in many important processes associated with tumorigenesis and cancer progression. Genes in these recurrent CNV regions were then examined in the context of gene regulatory networks to prioritize putative cancer driver genes. The cancer driver genes uncovered by the framework include not only well-known oncogenes but also a number of novel cancer susceptibility genes validated via siRNA experiments. Conclusions To our knowledge, this is the first effort to systematically identify and validate drivers for expression based CNV regions in breast cancer. The framework where the wavelet analysis of copy number alteration based on expression coupled with the gene regulatory network analysis, provides a blueprint for leveraging genomic data to identify key regulatory components and gene targets. This integrative approach can be applied to many other large-scale gene expression studies and other novel types of cancer data such as next-generation sequencing based expression (RNA-Seq) as well as CNV data. PMID:21806811

Dimensions of aberrant driving behaviours in Tunisia: identifying the relation between Driver Behaviour Questionnaire results and accident data.

PubMed

Mohamed, Dhibi; Lotfi, Belkacem

2016-12-01

In this study, the Manchester Driver Behaviour Questionnaire (DBQ) was used to examine the self-reported driving behaviours of a group of Tunisian drivers (N = 900) and to collect socio-demographic data, driver behaviours and DBQ items. A sample of Tunisian drivers above 18 years was selected. The aim of the present study was to investigate the factorial structure of the DBQ in Tunisia. The principal component analysis identified three factor solutions: inattention errors, dangerous errors and dangerous violations. Logistic regression analysis showed that dangerous errors, dangerous violations and speeding preference factors predicted crash involvement in Tunisia. Speeding is the most common form of aberrant behaviour reported by drivers in the current sample. It remains one of the major road safety concerns.

Identification of FGF19 as a prognostic marker and potential driver gene of lung squamous cell carcinomas in Chinese smoking patients.

PubMed

Tan, Qiang; Li, Fan; Wang, Guan; Xia, Weiliang; Li, Ziming; Niu, Xiaomin; Ji, Wenxiang; Yuan, Hong; Xu, Qiang; Luo, Qingquan; Zhang, Jie; Lu, Shun

2016-04-05

Comprehensive genomic characterizations of lung squamous cell carcinoma (LSCC) have been performed, but the differences between smokers (S-LSCC) and never smokers (NS-LSCC) are not clear, as NS-LSCC could be considered as a different disease from S-LSCC. In this study we delineated genomic alterations in a cohort of 21 NS-LSCC and 16 S-LSCC patients, and identified common gene mutations and amplifications as previously reported. Inclusion of more NS-LSCC patients enabled us to identify unreported S-LSCC- or NS-LSCC-specific alterations. Importantly, an amplification region containing FGF19, FGF3, FGF4 and CCND1 was found five-times more frequent in S-LSCC than in NS-LSCC. Amplification of FGF19 was validated in independent LSCC samples. Furthermore, FGF19 stimulated LSCC cell growth in vitro. These data implicate FGF19 as a potential driver gene in LSCC with clinic characteristics as smoking.

Frameshift mutational target gene analysis identifies similarities and differences in constitutional mismatch repair-deficiency and Lynch syndrome.

PubMed

Maletzki, Claudia; Huehns, Maja; Bauer, Ingrid; Ripperger, Tim; Mork, Maureen M; Vilar, Eduardo; Klöcking, Sabine; Zettl, Heike; Prall, Friedrich; Linnebacher, Michael

2017-07-01

Mismatch-repair deficient (MMR-D) malignancies include Lynch Syndrome (LS), which is secondary to germline mutations in one of the MMR genes, and the rare childhood-form of constitutional mismatch repair-deficiency (CMMR-D); caused by bi-allelic MMR gene mutations. A hallmark of LS-associated cancers is microsatellite instability (MSI), characterized by coding frameshift mutations (cFSM) in target genes. By contrast, tumors arising in CMMR-D patients are thought to display a somatic mutation pattern differing from LS. This study has the main goal to identify cFSM in MSI target genes relevant in CMMR-D and to compare the spectrum of common somatic mutations, including alterations in DNA polymerases POLE and D1 between LS and CMMR-D. CMMR-D-associated tumors harbored more somatic mutations compared to LS cases, especially in the TP53 gene and in POLE and POLD1, where novel mutations were additionally identified. Strikingly, MSI in classical mononucleotide markers BAT40 and CAT25 was frequent in CMMR-D cases. MSI-target gene analysis revealed mutations in CMMR-D-associated tumors, some of them known to be frequently hit in LS, such as RNaseT2, HT001, and TGFβR2. Our results imply a general role for these cFSM as potential new drivers of MMR-D tumorigenesis. © 2017 Wiley Periodicals, Inc.

"It drives us to do it": pregnant adolescents identify drivers for sexual risk-taking.

PubMed

King Jones, Tammy C

2010-01-01

Sexual risk-taking behaviors have a negative effect on the heath and future of American adolescents. To gain insight into these behaviors and preventative efforts, this study explored the experiences and perceptions of 15 pregnant adolescents using a qualitative feminist approach and in-depth interviews. As participants discussed sex education, each identified influences on sexual decision-making that often overpowered the information received. Content analysis and constant comparison of this data led to the overarching theme "Drivers for Sexual Risk-taking." Drivers were categorized as internal and external and each demonstrated a significant influence on adolescent sexual decision-making. Results of this study can inform the development of educational efforts, reform of social policy, and the focus of future research.

Integrated Molecular Profiling of Human Gastric Cancer Identifies DDR2 as a Potential Regulator of Peritoneal Dissemination.

PubMed

Kurashige, Junji; Hasegawa, Takanori; Niida, Atsushi; Sugimachi, Keishi; Deng, Niantao; Mima, Kosuke; Uchi, Ryutaro; Sawada, Genta; Takahashi, Yusuke; Eguchi, Hidetoshi; Inomata, Masashi; Kitano, Seigo; Fukagawa, Takeo; Sasako, Mitsuru; Sasaki, Hiroki; Sasaki, Shin; Mori, Masaki; Yanagihara, Kazuyoshi; Baba, Hideo; Miyano, Satoru; Tan, Patrick; Mimori, Koshi

2016-03-03

Peritoneal dissemination is the most frequent, incurable metastasis occurring in patients with advanced gastric cancer (GC). However, molecular mechanisms driving peritoneal dissemination still remain poorly understood. Here, we aimed to provide novel insights into the molecular mechanisms that drive the peritoneal dissemination of GC. We performed combined expression analysis with in vivo-selected metastatic cell lines and samples from 200 GC patients to identify driver genes of peritoneal dissemination. The driver-gene functions associated with GC dissemination were examined using a mouse xenograft model. We identified a peritoneal dissemination-associated expression signature, whose profile correlated with those of genes related to development, focal adhesion, and the extracellular matrix. Among the genes comprising the expression signature, we identified that discoidin-domain receptor 2 (DDR2) as a potential regulator of peritoneal dissemination. The DDR2 was upregulated by the loss of DNA methylation and that DDR2 knockdown reduced peritoneal metastasis in a xenograft model. Dasatinib, an inhibitor of the DDR2 signaling pathway, effectively suppressed peritoneal dissemination. DDR2 was identified as a driver gene for GC dissemination from the combined expression signature and can potentially serve as a novel therapeutic target for inhibiting GC peritoneal dissemination.

Identification of FGF19 as a prognostic marker and potential driver gene of lung squamous cell carcinomas in Chinese smoking patients

PubMed Central

Xia, Weiliang; Li, Ziming; Niu, Xiaomin; Ji, Wenxiang; Yuan, Hong; Xu, Qiang; Luo, Qingquan; Zhang, Jie; Lu, Shun

2016-01-01

Comprehensive genomic characterizations of lung squamous cell carcinoma (LSCC) have been performed, but the differences between smokers (S-LSCC) and never smokers (NS-LSCC) are not clear, as NS-LSCC could be considered as a different disease from S-LSCC. In this study we delineated genomic alterations in a cohort of 21 NS-LSCC and 16 S-LSCC patients, and identified common gene mutations and amplifications as previously reported. Inclusion of more NS-LSCC patients enabled us to identify unreported S-LSCC- or NS-LSCC-specific alterations. Importantly, an amplification region containing FGF19, FGF3, FGF4 and CCND1 was found five-times more frequent in S-LSCC than in NS-LSCC. Amplification of FGF19 was validated in independent LSCC samples. Furthermore, FGF19 stimulated LSCC cell growth in vitro. These data implicate FGF19 as a potential driver gene in LSCC with clinic characteristics as smoking. PMID:26943773

HIT'nDRIVE: patient-specific multidriver gene prioritization for precision oncology

PubMed Central

Hodzic, Ermin; Sauerwald, Thomas; Dao, Phuong; Wang, Kendric; Yeung, Jake; Anderson, Shawn; Vandin, Fabio; Haffari, Gholamreza; Collins, Colin C.; Sahinalp, S. Cenk

2017-01-01

Prioritizing molecular alterations that act as drivers of cancer remains a crucial bottleneck in therapeutic development. Here we introduce HIT'nDRIVE, a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with sufficient collective influence over dysregulated transcripts. HIT'nDRIVE aims to solve the “random walk facility location” (RWFL) problem in a gene (or protein) interaction network, which differs from the standard facility location problem by its use of an alternative distance measure: “multihitting time,” the expected length of the shortest random walk from any one of the set of sequence-altered genes to an expression-altered target gene. When applied to 2200 tumors from four major cancer types, HIT'nDRIVE revealed many potentially clinically actionable driver genes. We also demonstrated that it is possible to perform accurate phenotype prediction for tumor samples by only using HIT'nDRIVE-seeded driver gene modules from gene interaction networks. In addition, we identified a number of breast cancer subtype-specific driver modules that are associated with patients’ survival outcome. Furthermore, HIT'nDRIVE, when applied to a large panel of pan-cancer cell lines, accurately predicted drug efficacy using the driver genes and their seeded gene modules. Overall, HIT'nDRIVE may help clinicians contextualize massive multiomics data in therapeutic decision making, enabling widespread implementation of precision oncology. PMID:28768687

Anthropogenic and natural drivers of gene flow in a temperate wild fruit tree: a basis for conservation and breeding programs in apples

PubMed Central

Cornille, Amandine; Feurtey, Alice; Gélin, Uriel; Ropars, Jeanne; Misvanderbrugge, Kristine; Gladieux, Pierre; Giraud, Tatiana

2015-01-01

Gene flow is an essential component of population adaptation and species evolution. Understanding of the natural and anthropogenic factors affecting gene flow is also critical for the development of appropriate management, breeding, and conservation programs. Here, we explored the natural and anthropogenic factors impacting crop-to-wild and within wild gene flow in apples in Europe using an unprecedented dense sampling of 1889 wild apple (Malus sylvestris) from European forests and 339 apple cultivars (Malus domestica). We made use of genetic, environmental, and ecological data (microsatellite markers, apple production across landscapes and records of apple flower visitors, respectively). We provide the first evidence that both human activities, through apple production, and human disturbance, through modifications of apple flower visitor diversity, have had a significant impact on crop-to-wild interspecific introgression rates. Our analysis also revealed the impact of previous natural climate change on historical gene flow in the nonintrogressed wild apple M. sylvestris, by identifying five distinct genetic groups in Europe and a north–south gradient of genetic diversity. These findings identify human activities and climate as key drivers of gene flow in a wild temperate fruit tree and provide a practical basis for conservation, agroforestry, and breeding programs for apples in Europe. PMID:25926882

Utilizing Gene Tree Variation to Identify Candidate Effector Genes in Zymoseptoria tritici

PubMed Central

McDonald, Megan C.; McGinness, Lachlan; Hane, James K.; Williams, Angela H.; Milgate, Andrew; Solomon, Peter S.

2016-01-01

Zymoseptoria tritici is a host-specific, necrotrophic pathogen of wheat. Infection by Z. tritici is characterized by its extended latent period, which typically lasts 2 wks, and is followed by extensive host cell death, and rapid proliferation of fungal biomass. This work characterizes the level of genomic variation in 13 isolates, for which we have measured virulence on 11 wheat cultivars with differential resistance genes. Between the reference isolate, IPO323, and the 13 Australian isolates we identified over 800,000 single nucleotide polymorphisms, of which ∼10% had an effect on the coding regions of the genome. Furthermore, we identified over 1700 probable presence/absence polymorphisms in genes across the Australian isolates using de novo assembly. Finally, we developed a gene tree sorting method that quickly identifies groups of isolates within a single gene alignment whose sequence haplotypes correspond with virulence scores on a single wheat cultivar. Using this method, we have identified < 100 candidate effector genes whose gene sequence correlates with virulence toward a wheat cultivar carrying a major resistance gene. PMID:26837952

Recurrent chromosomal gains and heterogeneous driver mutations characterise papillary renal cancer evolution

PubMed Central

Kovac, Michal; Navas, Carolina; Horswell, Stuart; Salm, Max; Bardella, Chiara; Rowan, Andrew; Stares, Mark; Castro-Giner, Francesc; Fisher, Rosalie; de Bruin, Elza C.; Kovacova, Monika; Gorman, Maggie; Makino, Seiko; Williams, Jennet; Jaeger, Emma; Jones, Angela; Howarth, Kimberley; Larkin, James; Pickering, Lisa; Gore, Martin; Nicol, David L.; Hazell, Steven; Stamp, Gordon; O’Brien, Tim; Challacombe, Ben; Matthews, Nik; Phillimore, Benjamin; Begum, Sharmin; Rabinowitz, Adam; Varela, Ignacio; Chandra, Ashish; Horsfield, Catherine; Polson, Alexander; Tran, Maxine; Bhatt, Rupesh; Terracciano, Luigi; Eppenberger-Castori, Serenella; Protheroe, Andrew; Maher, Eamonn; El Bahrawy, Mona; Fleming, Stewart; Ratcliffe, Peter; Heinimann, Karl; Swanton, Charles; Tomlinson, Ian

2015-01-01

Papillary renal cell carcinoma (pRCC) is an important subtype of kidney cancer with a problematic pathological classification and highly variable clinical behaviour. Here we sequence the genomes or exomes of 31 pRCCs, and in four tumours, multi-region sequencing is undertaken. We identify BAP1, SETD2, ARID2 and Nrf2 pathway genes (KEAP1, NHE2L2 and CUL3) as probable drivers, together with at least eight other possible drivers. However, only ~10% of tumours harbour detectable pathogenic changes in any one driver gene, and where present, the mutations are often predicted to be present within cancer sub-clones. We specifically detect parallel evolution of multiple SETD2 mutations within different sub-regions of the same tumour. By contrast, large copy number gains of chromosomes 7, 12, 16 and 17 are usually early, monoclonal changes in pRCC evolution. The predominance of large copy number variants as the major drivers for pRCC highlights an unusual mode of tumorigenesis that may challenge precision medicine approaches. PMID:25790038

Finding cancer driver mutations in the era of big data research.

PubMed

Poulos, Rebecca C; Wong, Jason W H

2018-04-02

In the last decade, the costs of genome sequencing have decreased considerably. The commencement of large-scale cancer sequencing projects has enabled cancer genomics to join the big data revolution. One of the challenges still facing cancer genomics research is determining which are the driver mutations in an individual cancer, as these contribute only a small subset of the overall mutation profile of a tumour. Focusing primarily on somatic single nucleotide mutations in this review, we consider both coding and non-coding driver mutations, and discuss how such mutations might be identified from cancer sequencing datasets. We describe some of the tools and database that are available for the annotation of somatic variants and the identification of cancer driver genes. We also address the use of genome-wide variation in mutation load to establish background mutation rates from which to identify driver mutations under positive selection. Finally, we describe the ways in which mutational signatures can act as clues for the identification of cancer drivers, as these mutations may cause, or arise from, certain mutational processes. By defining the molecular changes responsible for driving cancer development, new cancer treatment strategies may be developed or novel preventative measures proposed.

Identifying training needs of logging truck drivers using a skill inventory.

PubMed

Carnahan, B J

2004-11-01

The purpose of this research was to determine if the Driver Skill Inventory (DSI) could be used to characterize the self-assessed driving performance of commercial logging truck drivers. The DSI requires respondents to subjectively evaluate their own ability in regard to 15 different driving skills. The DSI responses of 1000 logging truck drivers were collected across three southeastern states. The underlying hypothesis in the current study was that DSI responses of these drivers would have similar reliability and factor structure as those DSI responses collected from non-commercial drivers in previous studies. Factor analysis of the data confirmed this hypothesis. Statistical analysis revealed that low self-ratings on various safety skill items within the DSI inventory were associated with: (1) inconsistency in using seat belts, (2) inconsistency in performing pre-trip inspections on logging trucks, and (3) committing moving violations. Conversely, high self-ratings ratings on various perceptual-motor skill items were associated with these same at-risk behaviors. The perceptual-motor skill items were also positively associated with negative attitudes toward driving regulations and the number of moving violations incurred over a three-year period. Non-parametric statistical analysis revealed that self-assessments were lowest for DSI skills pertaining to controlling one's anger while driving and managing the truck through a skid or slide. Results of the study confirmed that the DSI can be successfully applied to commercial logging truck drivers as part of an overall comprehensive training needs assessment.

Genome-wide DNA methylation analysis identifies MEGF10 as a novel epigenetically repressed candidate tumor suppressor gene in neuroblastoma.

PubMed

Charlet, Jessica; Tomari, Ayumi; Dallosso, Anthony R; Szemes, Marianna; Kaselova, Martina; Curry, Thomas J; Almutairi, Bader; Etchevers, Heather C; McConville, Carmel; Malik, Karim T A; Brown, Keith W

2017-04-01

Neuroblastoma is a childhood cancer in which many children still have poor outcomes, emphasising the need to better understand its pathogenesis. Despite recent genome-wide mutation analyses, many primary neuroblastomas do not contain recognizable driver mutations, implicating alternate molecular pathologies such as epigenetic alterations. To discover genes that become epigenetically deregulated during neuroblastoma tumorigenesis, we took the novel approach of comparing neuroblastomas to neural crest precursor cells, using genome-wide DNA methylation analysis. We identified 93 genes that were significantly differentially methylated of which 26 (28%) were hypermethylated and 67 (72%) were hypomethylated. Concentrating on hypermethylated genes to identify candidate tumor suppressor loci, we found the cell engulfment and adhesion factor gene MEGF10 to be epigenetically repressed by DNA hypermethylation or by H3K27/K9 methylation in neuroblastoma cell lines. MEGF10 showed significantly down-regulated expression in neuroblastoma tumor samples; furthermore patients with the lowest-expressing tumors had reduced relapse-free survival. Our functional studies showed that knock-down of MEGF10 expression in neuroblastoma cell lines promoted cell growth, consistent with MEGF10 acting as a clinically relevant, epigenetically deregulated neuroblastoma tumor suppressor gene. © 2016 The Authors. Molecular Carcinogenesis Published by Wiley Periodicals, Inc. © 2016 The Authors. Molecular Carcinogenesis Published by Wiley Periodicals, Inc.

Genome‐wide DNA methylation analysis identifies MEGF10 as a novel epigenetically repressed candidate tumor suppressor gene in neuroblastoma

PubMed Central

Charlet, Jessica; Tomari, Ayumi; Dallosso, Anthony R.; Szemes, Marianna; Kaselova, Martina; Curry, Thomas J.; Almutairi, Bader; Etchevers, Heather C.; McConville, Carmel; Malik, Karim T. A.

2016-01-01

Neuroblastoma is a childhood cancer in which many children still have poor outcomes, emphasising the need to better understand its pathogenesis. Despite recent genome‐wide mutation analyses, many primary neuroblastomas do not contain recognizable driver mutations, implicating alternate molecular pathologies such as epigenetic alterations. To discover genes that become epigenetically deregulated during neuroblastoma tumorigenesis, we took the novel approach of comparing neuroblastomas to neural crest precursor cells, using genome‐wide DNA methylation analysis. We identified 93 genes that were significantly differentially methylated of which 26 (28%) were hypermethylated and 67 (72%) were hypomethylated. Concentrating on hypermethylated genes to identify candidate tumor suppressor loci, we found the cell engulfment and adhesion factor gene MEGF10 to be epigenetically repressed by DNA hypermethylation or by H3K27/K9 methylation in neuroblastoma cell lines. MEGF10 showed significantly down‐regulated expression in neuroblastoma tumor samples; furthermore patients with the lowest‐expressing tumors had reduced relapse‐free survival. Our functional studies showed that knock‐down of MEGF10 expression in neuroblastoma cell lines promoted cell growth, consistent with MEGF10 acting as a clinically relevant, epigenetically deregulated neuroblastoma tumor suppressor gene. © 2016 The Authors. Molecular Carcinogenesis Published by Wiley Periodicals, Inc. PMID:27862318

SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering.

PubMed

Van den Eynden, Jimmy; Fierro, Ana Carolina; Verbeke, Lieven P C; Marchal, Kathleen

2015-04-23

With the advances in high throughput technologies, increasing amounts of cancer somatic mutation data are being generated and made available. Only a small number of (driver) mutations occur in driver genes and are responsible for carcinogenesis, while the majority of (passenger) mutations do not influence tumour biology. In this study, SomInaClust is introduced, a method that accurately identifies driver genes based on their mutation pattern across tumour samples and then classifies them into oncogenes or tumour suppressor genes respectively. SomInaClust starts from the observation that oncogenes mainly contain mutations that, due to positive selection, cluster at similar positions in a gene across patient samples, whereas tumour suppressor genes contain a high number of protein-truncating mutations throughout the entire gene length. The method was shown to prioritize driver genes in 9 different solid cancers. Furthermore it was found to be complementary to existing similar-purpose methods with the additional advantages that it has a higher sensitivity, also for rare mutations (occurring in less than 1% of all samples), and it accurately classifies candidate driver genes in putative oncogenes and tumour suppressor genes. Pathway enrichment analysis showed that the identified genes belong to known cancer signalling pathways, and that the distinction between oncogenes and tumour suppressor genes is biologically relevant. SomInaClust was shown to detect candidate driver genes based on somatic mutation patterns of inactivation and clustering and to distinguish oncogenes from tumour suppressor genes. The method could be used for the identification of new cancer genes or to filter mutation data for further data-integration purposes.

Kin-Driver: a database of driver mutations in protein kinases.

PubMed

Simonetti, Franco L; Tornador, Cristian; Nabau-Moretó, Nuria; Molina-Vila, Miguel A; Marino-Buslje, Cristina

2014-01-01

Somatic mutations in protein kinases (PKs) are frequent driver events in many human tumors, while germ-line mutations are associated with hereditary diseases. Here we present Kin-driver, the first database that compiles driver mutations in PKs with experimental evidence demonstrating their functional role. Kin-driver is a manual expert-curated database that pays special attention to activating mutations (AMs) and can serve as a validation set to develop new generation tools focused on the prediction of gain-of-function driver mutations. It also offers an easy and intuitive environment to facilitate the visualization and analysis of mutations in PKs. Because all mutations are mapped onto a multiple sequence alignment, analogue positions between kinases can be identified and tentative new mutations can be proposed for studying by transferring annotation. Finally, our database can also be of use to clinical and translational laboratories, helping them to identify uncommon AMs that can correlate with response to new antitumor drugs. The website was developed using PHP and JavaScript, which are supported by all major browsers; the database was built using MySQL server. Kin-driver is available at: http://kin-driver.leloir.org.ar/ © The Author(s) 2014. Published by Oxford University Press.

Exome-wide Sequencing Shows Low Mutation Rates and Identifies Novel Mutated Genes in Seminomas.

PubMed

Cutcutache, Ioana; Suzuki, Yuka; Tan, Iain Beehuat; Ramgopal, Subhashini; Zhang, Shenli; Ramnarayanan, Kalpana; Gan, Anna; Lee, Heng Hong; Tay, Su Ting; Ooi, Aikseng; Ong, Choon Kiat; Bolthouse, Jonathan T; Lane, Brian R; Anema, John G; Kahnoski, Richard J; Tan, Patrick; Teh, Bin Tean; Rozen, Steven G

2015-07-01

Testicular germ cell tumors are the most common cancer diagnosed in young men, and seminomas are the most common type of these cancers. There have been no exome-wide examinations of genes mutated in seminomas or of overall rates of nonsilent somatic mutations in these tumors. The objective was to analyze somatic mutations in seminomas to determine which genes are affected and to determine rates of nonsilent mutations. Eight seminomas and matched normal samples were surgically obtained from eight patients. DNA was extracted from tissue samples and exome sequenced on massively parallel Illumina DNA sequencers. Single-nucleotide polymorphism chip-based copy number analysis was also performed to assess copy number alterations. The DNA sequencing read data were analyzed to detect somatic mutations including single-nucleotide substitutions and short insertions and deletions. The detected mutations were validated by independent sequencing and further checked for subclonality. The rate of nonsynonymous somatic mutations averaged 0.31 mutations/Mb. We detected nonsilent somatic mutations in 96 genes that were not previously known to be mutated in seminomas, of which some may be driver mutations. Many of the mutations appear to have been present in subclonal populations. In addition, two genes, KIT and KRAS, were affected in two tumors each with mutations that were previously observed in other cancers and are presumably oncogenic. Our study, the first report on exome sequencing of seminomas, detected somatic mutations in 96 new genes, several of which may be targetable drivers. Furthermore, our results show that seminoma mutation rates are five times higher than previously thought, but are nevertheless low compared to other common cancers. Similar low rates are seen in other cancers that also have excellent rates of remission achieved with chemotherapy. We examined the DNA sequences of seminomas, the most common type of testicular germ cell cancer. Our study identified 96

Genetic Drivers of Kidney Defects in the DiGeorge Syndrome.

PubMed

Lopez-Rivera, Esther; Liu, Yangfan P; Verbitsky, Miguel; Anderson, Blair R; Capone, Valentina P; Otto, Edgar A; Yan, Zhonghai; Mitrotti, Adele; Martino, Jeremiah; Steers, Nicholas J; Fasel, David A; Vukojevic, Katarina; Deng, Rong; Racedo, Silvia E; Liu, Qingxue; Werth, Max; Westland, Rik; Vivante, Asaf; Makar, Gabriel S; Bodria, Monica; Sampson, Matthew G; Gillies, Christopher E; Vega-Warner, Virginia; Maiorana, Mariarosa; Petrey, Donald S; Honig, Barry; Lozanovski, Vladimir J; Salomon, Rémi; Heidet, Laurence; Carpentier, Wassila; Gaillard, Dominique; Carrea, Alba; Gesualdo, Loreto; Cusi, Daniele; Izzi, Claudia; Scolari, Francesco; van Wijk, Joanna A E; Arapovic, Adela; Saraga-Babic, Mirna; Saraga, Marijan; Kunac, Nenad; Samii, Ali; McDonald-McGinn, Donna M; Crowley, Terrence B; Zackai, Elaine H; Drozdz, Dorota; Miklaszewska, Monika; Tkaczyk, Marcin; Sikora, Przemyslaw; Szczepanska, Maria; Mizerska-Wasiak, Malgorzata; Krzemien, Grazyna; Szmigielska, Agnieszka; Zaniew, Marcin; Darlow, John M; Puri, Prem; Barton, David; Casolari, Emilio; Furth, Susan L; Warady, Bradley A; Gucev, Zoran; Hakonarson, Hakon; Flogelova, Hana; Tasic, Velibor; Latos-Bielenska, Anna; Materna-Kiryluk, Anna; Allegri, Landino; Wong, Craig S; Drummond, Iain A; D'Agati, Vivette; Imamoto, Akira; Barasch, Jonathan M; Hildebrandt, Friedhelm; Kiryluk, Krzysztof; Lifton, Richard P; Morrow, Bernice E; Jeanpierre, Cecile; Papaioannou, Virginia E; Ghiggeri, Gian Marco; Gharavi, Ali G; Katsanis, Nicholas; Sanna-Cherchi, Simone

2017-02-23

The DiGeorge syndrome, the most common of the microdeletion syndromes, affects multiple organs, including the heart, the nervous system, and the kidney. It is caused by deletions on chromosome 22q11.2; the genetic driver of the kidney defects is unknown. We conducted a genomewide search for structural variants in two cohorts: 2080 patients with congenital kidney and urinary tract anomalies and 22,094 controls. We performed exome and targeted resequencing in samples obtained from 586 additional patients with congenital kidney anomalies. We also carried out functional studies using zebrafish and mice. We identified heterozygous deletions of 22q11.2 in 1.1% of the patients with congenital kidney anomalies and in 0.01% of population controls (odds ratio, 81.5; P=4.5×10 -14 ). We localized the main drivers of renal disease in the DiGeorge syndrome to a 370-kb region containing nine genes. In zebrafish embryos, an induced loss of function in snap29, aifm3, and crkl resulted in renal defects; the loss of crkl alone was sufficient to induce defects. Five of 586 patients with congenital urinary anomalies had newly identified, heterozygous protein-altering variants, including a premature termination codon, in CRKL. The inactivation of Crkl in the mouse model induced developmental defects similar to those observed in patients with congenital urinary anomalies. We identified a recurrent 370-kb deletion at the 22q11.2 locus as a driver of kidney defects in the DiGeorge syndrome and in sporadic congenital kidney and urinary tract anomalies. Of the nine genes at this locus, SNAP29, AIFM3, and CRKL appear to be critical to the phenotype, with haploinsufficiency of CRKL emerging as the main genetic driver. (Funded by the National Institutes of Health and others.).

Genetic Drivers of Kidney Defects in the DiGeorge Syndrome

PubMed Central

Lopez-Rivera, E.; Liu, Y.P.; Verbitsky, M.; Anderson, B.R.; Capone, V.P.; Otto, E.A.; Yan, Z.; Mitrotti, A.; Martino, J.; Steers, N.J.; Fasel, D.A.; Vukojevic, K.; Deng, R.; Racedo, S.E.; Liu, Q.; Werth, M.; Westland, R.; Vivante, A.; Makar, G.S.; Bodria, M.; Sampson, M.G.; Gillies, C.E.; Vega-Warner, V.; Maiorana, M.; Petrey, D.S.; Honig, B.; Lozanovski, V.J.; Salomon, R.; Heidet, L.; Carpentier, W.; Gaillard, D.; Carrea, A.; Gesualdo, L.; Cusi, D.; Izzi, C.; Scolari, F.; van Wijk, J.A.E.; Arapovic, A.; Saraga-Babic, M.; Saraga, M.; Kunac, N.; Samii, A.; McDonald-McGinn, D.M.; Crowley, T.B.; Zackai, E.H.; Drozdz, D.; Miklaszewska, M.; Tkaczyk, M.; Sikora, P.; Szczepanska, M.; Mizerska-Wasiak, M.; Krzemien, G.; Szmigielska, A.; Zaniew, M.; Darlow, J.M.; Puri, P.; Barton, D.; Casolari, E.; Furth, S.L.; Warady, B.A.; Gucev, Z.; Hakonarson, H.; Flogelova, H.; Tasic, V.; Latos-Bielenska, A.; Materna-Kiryluk, A.; Allegri, L.; Wong, C.S.; Drummond, I.A.; D’Agati, V.; Imamoto, A.; Barasch, J.M.; Hildebrandt, F.; Kiryluk, K.; Lifton, R.P.; Morrow, B.E.; Jeanpierre, C.; Papaioannou, V.E.; Ghiggeri, G.M.; Gharavi, A.G.; Katsanis, N.; Sanna-Cherchi, S.

2017-01-01

BACKGROUND The DiGeorge syndrome, the most common of the microdeletion syndromes, affects multiple organs, including the heart, the nervous system, and the kidney. It is caused by deletions on chromosome 22q11.2; the genetic driver of the kidney defects is unknown. METHODS We conducted a genomewide search for structural variants in two cohorts: 2080 patients with congenital kidney and urinary tract anomalies and 22,094 controls. We performed exome and targeted resequencing in samples obtained from 586 additional patients with congenital kidney anomalies. We also carried out functional studies using zebrafish and mice. RESULTS We identified heterozygous deletions of 22q11.2 in 1.1% of the patients with congenital kidney anomalies and in 0.01% of population controls (odds ratio, 81.5; P=4.5×10−14). We localized the main drivers of renal disease in the DiGeorge syndrome to a 370-kb region containing nine genes. In zebrafish embryos, an induced loss of function in snap29, aifm3, and crkl resulted in renal defects; the loss of crkl alone was sufficient to induce defects. Five of 586 patients with congenital urinary anomalies had newly identified, heterozygous protein-altering variants, including a premature termination codon, in CRKL. The inactivation of Crkl in the mouse model induced developmental defects similar to those observed in patients with congenital urinary anomalies. CONCLUSIONS We identified a recurrent 370-kb deletion at the 22q11.2 locus as a driver of kidney defects in the DiGeorge syndrome and in sporadic congenital kidney and urinary tract anomalies. Of the nine genes at this locus, SNAP29, AIFM3, and CRKL appear to be critical to the phenotype, with haploinsufficiency of CRKL emerging as the main genetic driver. (Funded by the National Institutes of Health and others.) PMID:28121514

Microarray analysis and scale-free gene networks identify candidate regulators in drought-stressed roots of loblolly pine (P. taeda L.)

PubMed Central

2011-01-01

genes identified are known to be up-regulated in response to osmotic stress in pine and other plant species and encode proteins involved in both signal transduction and stress tolerance. Gene expression levels returned to control values within a 48-hour recovery period in all but 76 transcripts. Correlation network analysis indicates a scale-free network topology for the pine root transcriptome and identifies central nodes that may serve as drivers of drought-responsive transcriptome dynamics in the roots of loblolly pine. PMID:21609476

Candidate genes for panhypopituitarism identified by gene expression profiling

PubMed Central

Mortensen, Amanda H.; MacDonald, James W.; Ghosh, Debashis

2011-01-01

Mutations in the transcription factors PROP1 and PIT1 (POU1F1) lead to pituitary hormone deficiency and hypopituitarism in mice and humans. The dysmorphology of developing Prop1 mutant pituitaries readily distinguishes them from those of Pit1 mutants and normal mice. This and other features suggest that Prop1 controls the expression of genes besides Pit1 that are important for pituitary cell migration, survival, and differentiation. To identify genes involved in these processes we used microarray analysis of gene expression to compare pituitary RNA from newborn Prop1 and Pit1 mutants and wild-type littermates. Significant differences in gene expression were noted between each mutant and their normal littermates, as well as between Prop1 and Pit1 mutants. Otx2, a gene critical for normal eye and pituitary development in humans and mice, exhibited elevated expression specifically in Prop1 mutant pituitaries. We report the spatial and temporal regulation of Otx2 in normal mice and Prop1 mutants, and the results suggest Otx2 could influence pituitary development by affecting signaling from the ventral diencephalon and regulation of gene expression in Rathke's pouch. The discovery that Otx2 expression is affected by Prop1 deficiency provides support for our hypothesis that identifying molecular differences in mutants will contribute to understanding the molecular mechanisms that control pituitary organogenesis and lead to human pituitary disease. PMID:21828248

Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

PubMed

Songhurst, Anna; Coulson, Tim

2014-03-01

Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

Comparison of Expression Profiles in Ovarian Epithelium In Vivo and Ovarian Cancer Identifies Novel Candidate Genes Involved in Disease Pathogenesis

PubMed Central

Emmanuel, Catherine; Gava, Natalie; Kennedy, Catherine; Balleine, Rosemary L.; Sharma, Raghwa; Wain, Gerard; Brand, Alison; Hogg, Russell; Etemadmoghadam, Dariush; George, Joshy; Birrer, Michael J.; Clarke, Christine L.; Chenevix-Trench, Georgia; Bowtell, David D. L.; Harnett, Paul R.; deFazio, Anna

2011-01-01

Molecular events leading to epithelial ovarian cancer are poorly understood but ovulatory hormones and a high number of life-time ovulations with concomitant proliferation, apoptosis, and inflammation, increases risk. We identified genes that are regulated during the estrous cycle in murine ovarian surface epithelium and analysed these profiles to identify genes dysregulated in human ovarian cancer, using publically available datasets. We identified 338 genes that are regulated in murine ovarian surface epithelium during the estrous cycle and dysregulated in ovarian cancer. Six of seven candidates selected for immunohistochemical validation were expressed in serous ovarian cancer, inclusion cysts, ovarian surface epithelium and in fallopian tube epithelium. Most were overexpressed in ovarian cancer compared with ovarian surface epithelium and/or inclusion cysts (EpCAM, EZH2, BIRC5) although BIRC5 and EZH2 were expressed as highly in fallopian tube epithelium as in ovarian cancer. We prioritised the 338 genes for those likely to be important for ovarian cancer development by in silico analyses of copy number aberration and mutation using publically available datasets and identified genes with established roles in ovarian cancer as well as novel genes for which we have evidence for involvement in ovarian cancer. Chromosome segregation emerged as an important process in which genes from our list of 338 were over-represented including two (BUB1, NCAPD2) for which there is evidence of amplification and mutation. NUAK2, upregulated in ovarian surface epithelium in proestrus and predicted to have a driver mutation in ovarian cancer, was examined in a larger cohort of serous ovarian cancer where patients with lower NUAK2 expression had shorter overall survival. In conclusion, defining genes that are activated in normal epithelium in the course of ovulation that are also dysregulated in cancer has identified a number of pathways and novel candidate genes that may contribute

Profiling of potential driver mutations in sarcomas by targeted next generation sequencing.

PubMed

Andersson, Carola; Fagman, Henrik; Hansson, Magnus; Enlund, Fredrik

2016-04-01

Comprehensive genetic profiling by massively parallel sequencing, commonly known as next generation sequencing (NGS), is becoming the foundation of personalized oncology. For sarcomas very few targeted treatments are currently in routine use. In clinical practice the preoperative diagnostic workup of soft tissue tumours largely relies on core needle biopsies. Although mostly sufficient for histopathological diagnosis, only very limited amounts of formalin fixated paraffin embedded tissue are often available for predictive mutation analysis. Targeted NGS may thus open up new possibilities for comprehensive characterization of scarce biopsies. We therefore set out to search for driver mutations by NGS in a cohort of 55 clinically and morphologically well characterized sarcomas using low input of DNA from formalin fixated paraffin embedded tissues. The aim was to investigate if there are any recurrent or targetable aberrations in cancer driver genes in addition to known chromosome translocations in different types of sarcomas. We employed a panel covering 207 mutation hotspots in 50 cancer-associated genes to analyse DNA from nine gastrointestinal stromal tumours, 14 synovial sarcomas, seven myxoid liposarcomas, 22 Ewing sarcomas and three Ewing-like small round cell tumours at a large sequencing depth to detect also mutations that are subclonal or occur at low allele frequencies. We found nine mutations in eight different potential driver genes, some of which are potentially actionable by currently existing targeted therapies. Even though no recurrent mutations in driver genes were found in the different sarcoma groups, we show that targeted NGS-based sequencing is clearly feasible in a diagnostic setting with very limited amounts of paraffin embedded tissue and may provide novel insights into mesenchymal cell signalling and potentially druggable targets. Interestingly, we also identify five non-synonymous sequence variants in 4 established cancer driver genes in DNA

Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

PubMed Central

Xu, Pingzhen

2018-01-01

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

Drivers Are More Physically Active Than Non-Drivers in Older Adults.

PubMed

Amagasa, Shiho; Fukushima, Noritoshi; Kikuchi, Hiroyuki; Takamiya, Tomoko; Odagiri, Yuko; Oka, Koichiro; Inoue, Shigeru

2018-05-28

Car use has been identified as sedentary behavior, although it may enhance mobility, particularly in the older population. This cross-sectional study aimed to compare the time spent in objectively determined sedentary behavior (SB) and physical activity (PA) between older drivers and non-drivers. Four hundred and fifty Japanese older adults (74.3 ± 2.9 years) who had valid accelerometer data were included. They were asked to respond to a questionnaire and wear an accelerometer (HJA-350IT, Omron Healthcare) on their waist for 7 consecutive days in 2015. To compare activity time between drivers and non-drivers, we calculated estimated means using analysis of covariance, adjusting for sociodemographic, physical, and psychological factors and accelerometer wear time. Compared to non-drivers, drivers engaged in more light-intensity PA (LPA) (drivers: 325.0 vs. non-drivers: 289.0 min/day) and moderate-to-vigorous PA (drivers: 37.5 vs. non-drivers: 30.0 min/day) and less SB (drivers: 493.4 vs. non-drivers: 535.9 min/day) (all p < 0.05). After stratification by age, sex, and residential area, larger effect of driving on PA time was found in older-older adults, in men, and in rural residents. Older drivers were found to be more physically active than non-drivers, suggesting more access to outdoor activities or expanding social network.

Snowball: resampling combined with distance-based regression to discover transcriptional consequences of a driver mutation

PubMed Central

Xu, Yaomin; Guo, Xingyi; Sun, Jiayang; Zhao, Zhongming

2015-01-01

Motivation: Large-scale cancer genomic studies, such as The Cancer Genome Atlas (TCGA), have profiled multidimensional genomic data, including mutation and expression profiles on a variety of cancer cell types, to uncover the molecular mechanism of cancerogenesis. More than a hundred driver mutations have been characterized that confer the advantage of cell growth. However, how driver mutations regulate the transcriptome to affect cellular functions remains largely unexplored. Differential analysis of gene expression relative to a driver mutation on patient samples could provide us with new insights in understanding driver mutation dysregulation in tumor genome and developing personalized treatment strategies. Results: Here, we introduce the Snowball approach as a highly sensitive statistical analysis method to identify transcriptional signatures that are affected by a recurrent driver mutation. Snowball utilizes a resampling-based approach and combines a distance-based regression framework to assign a robust ranking index of genes based on their aggregated association with the presence of the mutation, and further selects the top significant genes for downstream data analyses or experiments. In our application of the Snowball approach to both synthesized and TCGA data, we demonstrated that it outperforms the standard methods and provides more accurate inferences to the functional effects and transcriptional dysregulation of driver mutations. Availability and implementation: R package and source code are available from CRAN at http://cran.r-project.org/web/packages/DESnowball, and also available at http://bioinfo.mc.vanderbilt.edu/DESnowball/. Contact: zhongming.zhao@vanderbilt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25192743

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

PubMed Central

Vinayagam, Arunachalam; Gibson, Travis E.; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

2016-01-01

The protein–protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as “indispensable,” “neutral,” or “dispensable,” which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990

Identifying key genes in rheumatoid arthritis by weighted gene co-expression network analysis.

PubMed

Ma, Chunhui; Lv, Qi; Teng, Songsong; Yu, Yinxian; Niu, Kerun; Yi, Chengqin

2017-08-01

This study aimed to identify rheumatoid arthritis (RA) related genes based on microarray data using the WGCNA (weighted gene co-expression network analysis) method. Two gene expression profile datasets GSE55235 (10 RA samples and 10 healthy controls) and GSE77298 (16 RA samples and seven healthy controls) were downloaded from Gene Expression Omnibus database. Characteristic genes were identified using metaDE package. WGCNA was used to find disease-related networks based on gene expression correlation coefficients, and module significance was defined as the average gene significance of all genes used to assess the correlation between the module and RA status. Genes in the disease-related gene co-expression network were subject to functional annotation and pathway enrichment analysis using Database for Annotation Visualization and Integrated Discovery. Characteristic genes were also mapped to the Connectivity Map to screen small molecules. A total of 599 characteristic genes were identified. For each dataset, characteristic genes in the green, red and turquoise modules were most closely associated with RA, with gene numbers of 54, 43 and 79, respectively. These genes were enriched in totally enriched in 17 Gene Ontology terms, mainly related to immune response (CD97, FYB, CXCL1, IKBKE, CCR1, etc.), inflammatory response (CD97, CXCL1, C3AR1, CCR1, LYZ, etc.) and homeostasis (C3AR1, CCR1, PLN, CCL19, PPT1, etc.). Two small-molecule drugs sanguinarine and papaverine were predicted to have a therapeutic effect against RA. Genes related to immune response, inflammatory response and homeostasis presumably have critical roles in RA pathogenesis. Sanguinarine and papaverine have a potential therapeutic effect against RA. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

A Visual Analytics Framework for Identifying Topic Drivers in Media Events.

PubMed

Lu, Yafeng; Wang, Hong; Landis, Steven; Maciejewski, Ross

2017-09-14

Media data has been the subject of large scale analysis with applications of text mining being used to provide overviews of media themes and information flows. Such information extracted from media articles has also shown its contextual value of being integrated with other data, such as criminal records and stock market pricing. In this work, we explore linking textual media data with curated secondary textual data sources through user-guided semantic lexical matching for identifying relationships and data links. In this manner, critical information can be identified and used to annotate media timelines in order to provide a more detailed overview of events that may be driving media topics and frames. These linked events are further analyzed through an application of causality modeling to model temporal drivers between the data series. Such causal links are then annotated through automatic entity extraction which enables the analyst to explore persons, locations, and organizations that may be pertinent to the media topic of interest. To demonstrate the proposed framework, two media datasets and an armed conflict event dataset are explored.

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.

RET fusion as a novel driver of medullary thyroid carcinoma.

PubMed

Grubbs, Elizabeth G; Ng, Patrick Kwok-Shing; Bui, Jacquelin; Busaidy, Naifa L; Chen, Ken; Lee, Jeffrey E; Lu, Xinyan; Lu, Hengyu; Meric-Bernstam, Funda; Mills, Gordon B; Palmer, Gary; Perrier, Nancy D; Scott, Kenneth L; Shaw, Kenna R; Waguespack, Steven G; Williams, Michelle D; Yelensky, Roman; Cote, Gilbert J

2015-03-01

Oncogenic RET tyrosine kinase gene fusions and activating mutations have recently been identified in lung cancers, prompting initiation of targeted therapy trials in this disease. Although RET point mutation has been identified as a driver of tumorigenesis in medullary thyroid carcinoma (MTC), no fusions have been described to date. We evaluated the role of RET fusion as an oncogenic driver in MTC. We describe a patient who died from aggressive sporadic MTC < 10 months after diagnosis. Her tumor was evaluated by means of next-generation sequencing, including an intronic capture strategy. A reciprocal translocation involving RET intron 12 was identified. The fusion was validated using a targeted break apart fluorescence in situ hybridization probe, and RNA sequencing confirmed the existence of an in-frame fusion transcript joining MYH13 exon 35 with RET exon 12. Ectopic expression of fusion product in a murine Ba/F3 cell reporter model established strong oncogenicity. Three tyrosine kinase inhibitors currently used to treat MTC in clinical practice blocked tumorigenic cell growth. This finding represents the report of a novel RET fusion, the first of its kind described in MTC. The finding of this potential novel oncogenic mechanism has clear implications for sporadic MTC, which in the majority of cases has no driver mutation identified. The presence of a RET fusion also provides a plausible target for RET tyrosine kinase inhibitor therapies.

Identifying key genes in glaucoma based on a benchmarked dataset and the gene regulatory network.

PubMed

Chen, Xi; Wang, Qiao-Ling; Zhang, Meng-Hui

2017-10-01

The current study aimed to identify key genes in glaucoma based on a benchmarked dataset and gene regulatory network (GRN). Local and global noise was added to the gene expression dataset to produce a benchmarked dataset. Differentially-expressed genes (DEGs) between patients with glaucoma and normal controls were identified utilizing the Linear Models for Microarray Data (Limma) package based on benchmarked dataset. A total of 5 GRN inference methods, including Zscore, GeneNet, context likelihood of relatedness (CLR) algorithm, Partial Correlation coefficient with Information Theory (PCIT) and GEne Network Inference with Ensemble of Trees (Genie3) were evaluated using receiver operating characteristic (ROC) and precision and recall (PR) curves. The interference method with the best performance was selected to construct the GRN. Subsequently, topological centrality (degree, closeness and betweenness) was conducted to identify key genes in the GRN of glaucoma. Finally, the key genes were validated by performing reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A total of 176 DEGs were detected from the benchmarked dataset. The ROC and PR curves of the 5 methods were analyzed and it was determined that Genie3 had a clear advantage over the other methods; thus, Genie3 was used to construct the GRN. Following topological centrality analysis, 14 key genes for glaucoma were identified, including IL6 , EPHA2 and GSTT1 and 5 of these 14 key genes were validated by RT-qPCR. Therefore, the current study identified 14 key genes in glaucoma, which may be potential biomarkers to use in the diagnosis of glaucoma and aid in identifying the molecular mechanism of this disease.

Comprehensive profiling of DNA repair defects in breast cancer identifies a novel class of endocrine therapy resistance drivers.

PubMed

Anurag, Meenakshi; Punturi, Nindo; Hoog, Jeremy; Bainbridge, Matthew N; Ellis, Matthew J; Haricharan, Svasti

2018-05-23

This study was undertaken to conduct a comprehensive investigation of the role of DNA damage repair (DDR) defects in poor outcome ER+ disease. Expression and mutational status of DDR genes in ER+ breast tumors were correlated with proliferative response in neoadjuvant aromatase inhibitor therapy trials (discovery data set), with outcomes in METABRIC, TCGA and Loi data sets (validation data sets), and in patient derived xenografts. A causal relationship between candidate DDR genes and endocrine treatment response, and the underlying mechanism, was then tested in ER+ breast cancer cell lines. Correlations between loss of expression of three genes: CETN2 (p<0.001) and ERCC1 (p=0.01) from the nucleotide excision repair (NER) and NEIL2 (p=0.04) from the base excision repair (BER) pathways were associated with endocrine treatment resistance in discovery data sets, and subsequently validated in independent patient cohorts. Complementary mutation analysis supported associations between mutations in NER and BER pathways and reduced endocrine treatment response. A causal role for CETN2, NEIL2 and ERCC1 loss in intrinsic endocrine resistance was experimentally validated in ER+ breast cancer cell lines, and in ER+ patient-derived xenograft models. Loss of CETN2, NEIL2 or ERCC1 induced endocrine treatment response by dysregulating G1/S transition, and therefore, increased sensitivity to CDK4/6 inhibitors. A combined DDR signature score was developed that predicted poor outcome in multiple patient cohorts. This report identifies DDR defects as a new class of endocrine treatment resistance drivers and indicates new avenues for predicting efficacy of CDK4/6 inhibition in the adjuvant treatment setting. Copyright ©2018, American Association for Cancer Research.

Diametrical clustering for identifying anti-correlated gene clusters.

PubMed

Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

2003-09-01

Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

Comprehensive Characterization of Oncogenic Drivers in Asian Lung Adenocarcinoma.

PubMed

Li, Shiyong; Choi, Yoon-La; Gong, Zhuolin; Liu, Xiao; Lira, Maruja; Kan, Zhengyan; Oh, Ensel; Wang, Jian; Ting, Jason C; Ye, Xiangsheng; Reinhart, Christoph; Liu, Xiaoqiao; Pei, Yunfei; Zhou, Wei; Chen, Ronghua; Fu, Shijun; Jin, Gang; Jiang, Awei; Fernandez, Julio; Hardwick, James; Kang, Min Woong; I, Hoseok; Zheng, Hancheng; Kim, Jhingook; Mao, Mao

2016-12-01

The incidence rate of lung adenocarcinoma (LUAD), the predominant histological subtype of lung cancer, is elevated in Asians, particularly in female nonsmokers. The mutation patterns in LUAD in Asians might be distinct from those in LUAD in whites. We profiled 271 resected LUAD tumors (mainly stage I) to characterize the genomic landscape of LUAD in Asians with a focus on female nonsmokers. Mutations in EGFR, KRAS, erb-b2 receptor tyrosine kinase 2 gene (ERBB2), and BRAF; gene fusions involving anaplastic lymphoma receptor tyrosine kinase gene (ALK), ROS1, and ret proto-oncogene (RET); and Met Proto-Oncogene Tyrosine Kinase (MET) exon 14 skipping were the major drivers in LUAD in Asians, exhibiting mutually exclusive and differing prevalence from those reported in studies of LUAD in non-Asians. In addition, we identified a novel mutational signature of XNX (the mutated base N in the middle flanked by two identical bases at the 5' and 3' positions) that was overrepresented in LUAD tumors in nonsmokers and negatively correlated with the overall mutational frequency. In this cohort, approximately 85% of individuals have known driver mutations (EGFR 59.4%, KRAS 7.4%, ALK 7.4%, ERBB2 2.6%, ROS1 2.2%, RET 2.2%, MET 1.8%, BRAF 1.1%, and NRAS 0.4%). Seventy percent of smokers and 90% of nonsmokers had defined oncogenic drivers matching the U.S. Food and Drug Administration-approved targeted therapies. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes.

PubMed

Cheng, Feixiong; Zhao, Junfei; Zhao, Zhongming

2016-07-01

Cancer is often driven by the accumulation of genetic alterations, including single nucleotide variants, small insertions or deletions, gene fusions, copy-number variations, and large chromosomal rearrangements. Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data and catalog somatic mutations in both common and rare cancer types. So far, the somatic mutation landscapes and signatures of >10 major cancer types have been reported; however, pinpointing driver mutations and cancer genes from millions of available cancer somatic mutations remains a monumental challenge. To tackle this important task, many methods and computational tools have been developed during the past several years and, thus, a review of its advances is urgently needed. Here, we first summarize the main features of these methods and tools for whole-exome, whole-genome and whole-transcriptome sequencing data. Then, we discuss major challenges like tumor intra-heterogeneity, tumor sample saturation and functionality of synonymous mutations in cancer, all of which may result in false-positive discoveries. Finally, we highlight new directions in studying regulatory roles of noncoding somatic mutations and quantitatively measuring circulating tumor DNA in cancer. This review may help investigators find an appropriate tool for detecting potential driver or actionable mutations in rapidly emerging precision cancer medicine. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

ENU Mutagenesis in Mice Identifies Candidate Genes For Hypogonadism

PubMed Central

Weiss, Jeffrey; Hurley, Lisa A.; Harris, Rebecca M.; Finlayson, Courtney; Tong, Minghan; Fisher, Lisa A.; Moran, Jennifer L.; Beier, David R.; Mason, Christopher; Jameson, J. Larry

2012-01-01

Genome-wide mutagenesis was performed in mice to identify candidate genes for male infertility, for which the predominant causes remain idiopathic. Mice were mutagenized using N-ethyl-N-nitrosourea (ENU), bred, and screened for phenotypes associated with the male urogenital system. Fifteen heritable lines were isolated and chromosomal loci were assigned using low density genome-wide SNP arrays. Ten of the fifteen lines were pursued further using higher resolution SNP analysis to narrow the candidate gene regions. Exon sequencing of candidate genes identified mutations in mice with cystic kidneys (Bicc1), cryptorchidism (Rxfp2), restricted germ cell deficiency (Plk4), and severe germ cell deficiency (Prdm9). In two other lines with severe hypogonadism candidate sequencing failed to identify mutations, suggesting defects in genes with previously undocumented roles in gonadal function. These genomic intervals were sequenced in their entirety and a candidate mutation was identified in SnrpE in one of the two lines. The line harboring the SnrpE variant retains substantial spermatogenesis despite small testis size, an unusual phenotype. In addition to the reproductive defects, heritable phenotypes were observed in mice with ataxia (Myo5a), tremors (Pmp22), growth retardation (unknown gene), and hydrocephalus (unknown gene). These results demonstrate that the ENU screen is an effective tool for identifying potential causes of male infertility. PMID:22258617

Changing drivers' minds: the evaluation of an advanced driver coaching system.

PubMed

Stanton, N A; Walker, G H; Young, M S; Kazi, T; Salmon, P M

2007-08-01

This paper reports on the study of an advanced driver coaching system. The study distinguishes between different types of post-licensure programmes in order to explore a system based on a model of identifying and responding to hazards, called 'information, position, speed, gear and acceleration' (IPSGA). Previous literature has been sceptical about the benefits of advanced driver education; thus, the current study was designed to control for the effects of coaching drivers in the 'IPSGA' system (the treatment group) against the effects of being accompanied (control group 1), as well as the mere effects of time (control group 2). Measures were taken before the driver coaching began (as a baseline measure) and again after 8 weeks (to see if any changes had occurred). These measures included driver knowledge via a post-drive interview, observations of driving skill and driver attitude using a locus of control scale. The results suggest that advanced driver coaching using the IPSGA system had a beneficial effect on all of these measures. Drivers in the coaching condition improved their situation awareness, driving skills and reduced attributions of external locus of control. The study lends support to the case for one-to-one individualized driver coaching using a systematic model of driving.

Driving fatigue in professional drivers: a survey of truck and taxi drivers.

PubMed

Meng, Fanxing; Li, Shuling; Cao, Lingzhi; Li, Musen; Peng, Qijia; Wang, Chunhui; Zhang, Wei

2015-01-01

Fatigue among truck drivers has been studied extensively; however, less is known regarding the fatigue experience of taxi drivers in heavily populated metropolitan areas. This study aimed to compare the differences and similarities between truck and taxi driver fatigue to provide implications for the fatigue management and education of professional drivers. A sample of 274 truck drivers and 286 taxi drivers in Beijing was surveyed via a questionnaire, which included items regarding work characteristics, fatigue experience, accident information, attitude toward fatigue, and methods of counteracting fatigue. Driver fatigue was prevalent among professional drivers, and it was even more serious for taxi drivers. Taxi drivers reported more frequent fatigue experiences and were involved in more accidents. Among the contributing factors to fatigue, prolonged driving time was the most important factor identified by both driver groups. Importantly, the reason for the engagement in prolonged driving was neither due to the lack of awareness concerning the serious outcome of fatigue driving nor because of their poor detection of fatigue. The most probable reason was the optimism bias, as a result of which these professional drivers thought that fatigue was more serious for other drivers than for themselves, and they thought that they were effective in counteracting the effect of fatigue on their driving performance. Moreover, truck drivers tended to employ methods that require stopping to counteract fatigue, whereas taxi drivers preferred methods that were simultaneous with driving. Although both driver groups considered taking a nap as one of the most effective means to address fatigue, this method was not commonly used. Interestingly, these drivers were aware that the methods they frequently used were not the most effective means to counteract fatigue. This study provides knowledge on truck and taxi drivers' characteristics in fatigue experience, fatigue attitude, and

Identifying key genes associated with acute myocardial infarction.

PubMed

Cheng, Ming; An, Shoukuan; Li, Junquan

2017-10-01

This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P < .05 was used as the cutoff for a differentially expressed gene (DEG). The expression data matrices of DEGs were imported in ReactomeFIViz to construct a gene functional interaction (FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21-5p and hsa-miR-30c-5p were obviously decreased in AMI. A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs.

Identifying drivers for consumer acceptance and purchase intent of corn tortilla.

PubMed

Herrera-Corredor, J A; Saidu, J E P; Khachatryan, A; Prinyawiwatkul, W; Carballo-Carballo, A; Zepeda-Bautista, R

2007-11-01

The traditional production of corn tortilla has been modified by new processing technologies to make possible a commercial-scale production; this practice has resulted in products having sensory properties different from those produced by the traditional method. There is no published information on sensory attributes driving acceptance and purchase intent of corn tortillas. Identifying sensory drivers for acceptance and purchase intent of corn tortillas will help commercially produce products that satisfy consumers' expectations. A consumer study was conducted to evaluate acceptance and purchase intent of corn tortillas and determine drivers of acceptance and purchase intent of the products. Ten samples of corn tortillas were selected to represent a variety of corn tortillas available in the Mexican market. Three hundred Mexican consumers evaluated acceptability of appearance, color, thickness, rollability, resistance to tearing, aroma, chewiness, taste and aftertaste, and overall liking using a 9-point hedonic scale. Overall acceptance and purchase intent were determined with a yes/no scale. Analysis of variance and multivariate analysis of variance revealed that consumers were able to differentiate differences in sensory acceptability among 10 samples. For example, 2 homemade and 1 small commercial-scale samples, with an overall liking score of 6.6 to 6.7, were more acceptable than others. Rollability, resistance to tearing, and chewiness were attributes underlying overall differences among 10 samples. Attributes determining overall acceptance of corn tortillas were chewiness and overall liking. Purchase intent was influenced by overall appearance, rollability, chewiness, taste, and overall liking. This study revealed critical sensory attributes and their weights given by Mexican consumers when making decisions for acceptance and purchase intent of corn tortilla.

SPIDER: A Framework for Understanding Driver Distraction.

PubMed

Strayer, David L; Fisher, Donald L

2016-02-01

The objective was to identify key cognitive processes that are impaired when drivers divert attention from driving. Driver distraction is increasingly recognized as a significant source of injuries and fatalities on the roadway. A "SPIDER" model is developed that identifies key cognitive processes that are impaired when drivers divert attention from driving. SPIDER is an acronym standing for scanning, predicting, identifying, decision making, and executing a response. When drivers engage in secondary activities unrelated to the task of driving, SPIDER-related processes are impaired, situation awareness is degraded, and the ability to safely operate a motor vehicle may be compromised. The pattern of interference helps to illuminate the sources of driver distraction and may help guide the integration of new technology into the automobile. © 2015, Human Factors and Ergonomics Society.

A genomic approach to identify hybrid incompatibility genes.

PubMed

Cooper, Jacob C; Phadnis, Nitin

2016-07-02

Uncovering the genetic and molecular basis of barriers to gene flow between populations is key to understanding how new species are born. Intrinsic postzygotic reproductive barriers such as hybrid sterility and hybrid inviability are caused by deleterious genetic interactions known as hybrid incompatibilities. The difficulty in identifying these hybrid incompatibility genes remains a rate-limiting step in our understanding of the molecular basis of speciation. We recently described how whole genome sequencing can be applied to identify hybrid incompatibility genes, even from genetically terminal hybrids. Using this approach, we discovered a new hybrid incompatibility gene, gfzf, between Drosophila melanogaster and Drosophila simulans, and found that it plays an essential role in cell cycle regulation. Here, we discuss the history of the hunt for incompatibility genes between these species, discuss the molecular roles of gfzf in cell cycle regulation, and explore how intragenomic conflict drives the evolution of fundamental cellular mechanisms that lead to the developmental arrest of hybrids.

A genomic approach to identify hybrid incompatibility genes

PubMed Central

Cooper, Jacob C.; Phadnis, Nitin

2016-01-01

ABSTRACT Uncovering the genetic and molecular basis of barriers to gene flow between populations is key to understanding how new species are born. Intrinsic postzygotic reproductive barriers such as hybrid sterility and hybrid inviability are caused by deleterious genetic interactions known as hybrid incompatibilities. The difficulty in identifying these hybrid incompatibility genes remains a rate-limiting step in our understanding of the molecular basis of speciation. We recently described how whole genome sequencing can be applied to identify hybrid incompatibility genes, even from genetically terminal hybrids. Using this approach, we discovered a new hybrid incompatibility gene, gfzf, between Drosophila melanogaster and Drosophila simulans, and found that it plays an essential role in cell cycle regulation. Here, we discuss the history of the hunt for incompatibility genes between these species, discuss the molecular roles of gfzf in cell cycle regulation, and explore how intragenomic conflict drives the evolution of fundamental cellular mechanisms that lead to the developmental arrest of hybrids. PMID:27230814

Relationship of driver oncogenes to long term pemetrexed response in non-small cell lung cancer

PubMed Central

Liang, Ying; Wakelee, Heather A.; Neal, Joel W.

2015-01-01

Background Pemetrexed is approved in the treatment of advanced stage non-squamous non-small-cell lung cancer (NSCLC). The length of response is variable, and we thus sought to identify which clinicopathologic characteristics are associated with long term disease control with pemetrexed. Methods Patients with metastatic NSCLC were identified who received pemetrexed (with or without bevacizumab) for 12 months or longer, either as maintenance treatment after first-line platinum-based chemotherapy or as subsequent treatment. Clinical and pathological characteristics were collected. Results Of a total of 196 patients who received pemetrexed starting in 2007, 25 patients were identified who received pemetrexed for over one year. Of these, 15 patients received pemetrexed with or without bevacizumab as maintenance treatment and 10 patients received pemetrexed as subsequent treatment. Fifteen of the 25 patients (60%) had an oncogenic driver mutation as follows: five (20%) had ROS1 gene rearrangements, four (16%) had ALK gene rearrangements, three (12%) had KRAS mutations, two (8%) had epidermal growth factor receptor (EGFR) mutations, and one (4%) had an NRAS mutation. The median overall survival (OS) was 42.2 months (95% confidence interval [CI]: 37.4–61.3) and median progression free survival (PFS) was 22.1 months (95% CI: 15.1–29.1). Patients with an oncogenic driver mutation had significantly better PFS (p=0.006) and OS (p=0.001). Conclusions Among patients with NSCLC who received pemetrexed for an extended time, those with ALK and ROS1 gene rearrangements are proportionally overrepresented compared with that anticipated in a general non-squamous NSCLC population, and patients with oncogenic driver mutations had improved outcomes. PMID:25665893

Novice drivers' individual trajectories of driver behavior over the first three years of driving.

PubMed

Roman, Gabriela D; Poulter, Damian; Barker, Edward; McKenna, Frank P; Rowe, Richard

2015-09-01

Identifying the changes in driving behavior that underlie the decrease in crash risk over the first few months of driving is key to efforts to reduce injury and fatality risk in novice drivers. This study represented a secondary data analysis of 1148 drivers who participated in the UK Cohort II study. The Driver Behavior Questionnaire was completed at 6 months and 1, 2 and 3 years after licensure. Linear latent growth models indicated significant increases across development in all four dimensions of aberrant driving behavior under scrutiny: aggressive violations, ordinary violations, errors and slips. Unconditional and conditional latent growth class analyses showed that the observed heterogeneity in individual trajectories was explained by the presence of multiple homogeneous groups of drivers, each exhibiting specific trajectories of aberrant driver behavior. Initial levels of aberrant driver behavior were important in identifying sub-groups of drivers. All classes showed positive slopes; there was no evidence of a group of drivers whose aberrant behavior decreased over time that might explain the decrease in crash involvement observed over this period. Male gender and younger age predicted membership of trajectories with higher levels of aberrant behavior. These findings highlight the importance of early intervention for improving road safety. We discuss the implications of our findings for understanding the behavioral underpinnings of the decrease in crash involvement observed in the early months of driving. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A scenario elicitation methodology to identify the drivers of electricity infrastructure cost in South America

NASA Astrophysics Data System (ADS)

Moksnes, Nandi; Taliotis, Constantinos; Broad, Oliver; de Moura, Gustavo; Howells, Mark

2017-04-01

Developing a set of scenarios to assess a proposed policy or future development pathways requires a certain level of information, as well as establishing the socio-economic context. As the future is difficult to predict, great care in defining the selected scenarios is needed. Even so it can be difficult to assess if the selected scenario is covering the possible solution space. Instead, this paper's methodology develops a large set of scenarios (324) in OSeMOSYS using the SAMBA 2.0 (South America Model Base) model to assess long-term electricity supply scenarios and applies a scenario-discovery statistical data mining algorithm, Patient Rule Induction Method (PRIM). By creating a multidimensional space, regions related to high and low cost can be identified as well as their key driver. The six key drivers are defined a priori in three (high, medium, low) or two levers (high, low): 1) Demand projected from GDP, population, urbanization and transport, 2) Fossil fuel price, 3) Climate change impact on hydropower, 4) Renewable technology learning rate, 5) Discount rate, 6) CO2 emission targets.

Identifying a gene expression signature of cluster headache in blood

PubMed Central

Eising, Else; Pelzer, Nadine; Vijfhuizen, Lisanne S.; Vries, Boukje de; Ferrari, Michel D.; ‘t Hoen, Peter A. C.; Terwindt, Gisela M.; van den Maagdenberg, Arn M. J. M.

2017-01-01

Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Gene expression data were analysed by gene and by module of co-expressed genes with particular attention to previously implicated disease pathways including hypocretin dysregulation. Only moderate gene expression differences were identified and no associations were found with previously reported pathogenic mechanisms. At the level of functional gene sets, associations were observed for genes involved in several brain-related mechanisms such as GABA receptor function and voltage-gated channels. In addition, genes and modules of co-expressed genes showed a role for intracellular signalling cascades, mitochondria and inflammation. Although larger study samples may be required to identify the full range of involved pathways, these results indicate a role for mitochondria, intracellular signalling and inflammation in cluster headache. PMID:28074859

Identifying key genes associated with acute myocardial infarction

PubMed Central

Cheng, Ming; An, Shoukuan; Li, Junquan

2017-01-01

Abstract Background: This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Methods: Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P < .05 was used as the cutoff for a differentially expressed gene (DEG). The expression data matrices of DEGs were imported in ReactomeFIViz to construct a gene functional interaction (FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. Result: A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21–5p and hsa-miR-30c-5p were obviously decreased in AMI. Conclusion: A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs. PMID:29049183

Gene-based rare allele analysis identified a risk gene of Alzheimer's disease.

PubMed

Kim, Jong Hun; Song, Pamela; Lim, Hyunsun; Lee, Jae-Hyung; Lee, Jun Hong; Park, Sun Ah

2014-01-01

Alzheimer's disease (AD) has a strong propensity to run in families. However, the known risk genes excluding APOE are not clinically useful. In various complex diseases, gene studies have targeted rare alleles for unsolved heritability. Our study aims to elucidate previously unknown risk genes for AD by targeting rare alleles. We used data from five publicly available genetic studies from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the database of Genotypes and Phenotypes (dbGaP). A total of 4,171 cases and 9,358 controls were included. The genotype information of rare alleles was imputed using 1,000 genomes. We performed gene-based analysis of rare alleles (minor allele frequency≤3%). The genome-wide significance level was defined as meta P<1.8×10(-6) (0.05/number of genes in human genome = 0.05/28,517). ZNF628, which is located at chromosome 19q13.42, showed a genome-wide significant association with AD. The association of ZNF628 with AD was not dependent on APOE ε4. APOE and TREM2 were also significantly associated with AD, although not at genome-wide significance levels. Other genes identified by targeting common alleles could not be replicated in our gene-based rare allele analysis. We identified that rare variants in ZNF628 are associated with AD. The protein encoded by ZNF628 is known as a transcription factor. Furthermore, the associations of APOE and TREM2 with AD were highly significant, even in gene-based rare allele analysis, which implies that further deep sequencing of these genes is required in AD heritability studies.

Towards setting credible speed limits: Identifying factors that affect driver compliance on urban roads.

PubMed

Gargoum, Suliman A; El-Basyouny, Karim; Kim, Amy

2016-10-01

Road geometry, vehicle characteristics, and weather conditions are all factors that impact a driver's perception of a safe or credible speed and, consequently, the driver's decision on whether or not to comply with the posted speed limit. In fact, the role a road's environment plays in a driver's perception of a credible speed limit is a topic that has attracted the interest of many researchers in recent years. Despite that, not many studies have considered using empirical data to investigate what features of the road environment influence a driver's compliance choice. This paper aims to address this matter by exploring the relationships between features of the road surroundings (geometric, temporal factors, and weather conditions) and driver compliance with speed limits. The paper uses data from almost 600 different urban roads in the city of Edmonton, at which over 35 million vehicle spot speeds were collected. Compliance was represented using a categorical ordered response variable, and mixed-effects-logistic-regression models were fitted. Two different models were built, one for arterials and another for collector roads. In general, the findings show that the more restricted drivers become, particularly on arterials, the more likely drivers are to comply with speed limits; potential restrictions include on-street parking and the absence of lateral shoulders. Furthermore, higher traffic activity during peak hours, and presumably on shoulder weekdays, both increase the likelihood of compliance on arterials. Similarly, posted speed limits and traffic volume are both positively correlated with compliance on both arterial and collector roads. The findings of this research provide evidence of the existence of an empirical relationship between road features and compliance, highlighting the importance of setting credible speed limits on roads and the possibility of achieving higher compliance rates through modifications to the road environment. Copyright © 2016

Identifying ecological and fishing drivers of bycatch in a U.S. groundfish fishery.

PubMed

Jannot, Jason E; Holland, Daniel S

2013-10-01

Fisheries bycatch is driven by both ecological (e.g., area, season) and social (e.g., fisher behavior) factors that are often difficult to disentangle. We demonstrate a method for comparing fishery-dependent bycatch to fishery-independent catch to delineate the influence of ecological and social factors on bycatch and provide insights for bycatch management. We used data from commercial fishing vessels in the U.S. west coast trawl groundfish fishery (fishery-dependent data collected by fisheries observers) and scientific data from the U.S. west coast bottom trawl groundfish survey (fishery-independent data) to compare the relative effects of season, time of day, target group, depth, and latitude on the expected catch of 12 bycatch species of management interest. This comparison highlights two important relationships that help identify drivers of bycatch. First, when the effect of season, time of day, depth, or latitude on bycatch in both the commercial and scientific data is positive, ecological processes are likely strong drivers of bycatch, suggesting technical approaches (e.g., temporal or spatial closures, gear modifications) might effectively control bycatch. Alternatively, when the effects of season, time of day, depth, latitude, or target group appear only in the commercial data (but not in survey data), fisher behavior is likely the stronger driver of bycatch, suggesting a need to strengthen incentives for fishers to change behavior to avoid bycatch (e.g., regulatory quotas). Two other patterns emerge that suggest that fishery bycatch is not associated with temporal, target, or spatial variables, implying that either current incentives to avoid bycatch are working (i.e., when survey expected catch is positively correlated with variables, but fishery catch is not) or bycatch is a product of unstudied or stochastic processes (i.e., variables are not correlated with expected catch in either data set) and continued monitoring is recommended. Our analysis

Gene expression meta-analysis identifies chromosomal regions and candidate genes involved in breast cancer metastasis.

PubMed

Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2009-01-01

Breast cancer cells exhibit complex karyotypic alterations causing deregulation of numerous genes. Some of these genes are probably causal for cancer formation and local growth whereas others are causal for the various steps of metastasis. In a fraction of tumors deregulation of the same genes might be caused by epigenetic modulations, point mutations or the influence of other genes. We have investigated the relation of gene expression and chromosomal position, using eight datasets including more than 1200 breast tumors, to identify chromosomal regions and candidate genes possibly causal for breast cancer metastasis. By use of "Gene Set Enrichment Analysis" we have ranked chromosomal regions according to their relation to metastasis. Overrepresentation analysis identified regions with increased expression for chromosome 1q41-42, 8q24, 12q14, 16q22, 16q24, 17q12-21.2, 17q21-23, 17q25, 20q11, and 20q13 among metastasizing tumors and reduced gene expression at 1p31-21, 8p22-21, and 14q24. By analysis of genes with extremely imbalanced expression in these regions we identified DIRAS3 at 1p31, PSD3, LPL, EPHX2 at 8p21-22, and FOS at 14q24 as candidate metastasis suppressor genes. Potential metastasis promoting genes includes RECQL4 at 8q24, PRMT7 at 16q22, GINS2 at 16q24, and AURKA at 20q13.

Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach

NASA Astrophysics Data System (ADS)

Chen, Lei; Huang, Tao; Zhang, Yu-Hang; Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong

2016-07-01

Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.

Factors associated with self-reported driver sleepiness and incidents in city bus drivers

PubMed Central

ANUND, Anna; IHLSTRÖM, Jonas; FORS, Carina; KECKLUND, Göran; FILTNESS, Ashleigh

2016-01-01

Driver fatigue has received increased attention during recent years and is now considered to be a major contributor to approximately 15–30% of all crashes. However, little is known about fatigue in city bus drivers. It is hypothesized that city bus drivers suffer from sleepiness, which is due to a combination of working conditions, lack of health and reduced sleep quantity and quality. The overall aim with the current study is to investigate if severe driver sleepiness, as indicated by subjective reports of having to fight sleep while driving, is a problem for city based bus drivers in Sweden and if so, to identify the determinants related to working conditions, health and sleep which contribute towards this. The results indicate that driver sleepiness is a problem for city bus drivers, with 19% having to fight to stay awake while driving the bus 2–3 times each week or more and nearly half experiencing this at least 2–4 times per month. In conclusion, severe sleepiness, as indicated by having to fight sleep during driving, was common among the city bus drivers. Severe sleepiness correlated with fatigue related safety risks, such as near crashes. PMID:27098307

Factors associated with self-reported driver sleepiness and incidents in city bus drivers.

PubMed

Anund, Anna; Ihlström, Jonas; Fors, Carina; Kecklund, Göran; Filtness, Ashleigh

2016-08-05

Driver fatigue has received increased attention during recent years and is now considered to be a major contributor to approximately 15-30% of all crashes. However, little is known about fatigue in city bus drivers. It is hypothesized that city bus drivers suffer from sleepiness, which is due to a combination of working conditions, lack of health and reduced sleep quantity and quality. The overall aim with the current study is to investigate if severe driver sleepiness, as indicated by subjective reports of having to fight sleep while driving, is a problem for city based bus drivers in Sweden and if so, to identify the determinants related to working conditions, health and sleep which contribute towards this. The results indicate that driver sleepiness is a problem for city bus drivers, with 19% having to fight to stay awake while driving the bus 2-3 times each week or more and nearly half experiencing this at least 2-4 times per month. In conclusion, severe sleepiness, as indicated by having to fight sleep during driving, was common among the city bus drivers. Severe sleepiness correlated with fatigue related safety risks, such as near crashes.

The landscape of cancer genes and mutational processes in breast cancer

PubMed Central

Stephens, Philip J.; Tarpey, Patrick S.; Davies, Helen; Loo, Peter Van; Greenman, Chris; Wedge, David C.; Nik-Zainal, Serena; Martin, Sancha; Varela, Ignacio; Bignell, Graham R.; Yates, Lucy R.; Papaemmanuil, Elli; Beare, David; Butler, Adam; Cheverton, Angela; Gamble, John; Hinton, Jonathan; Jia, Mingming; Jayakumar, Alagu; Jones, David; Latimer, Calli; Lau, King Wai; McLaren, Stuart; McBride, David J.; Menzies, Andrew; Mudie, Laura; Raine, Keiran; Rad, Roland; Chapman, Michael Spencer; Teague, Jon; Easton, Douglas; Langerød, Anita; OSBREAC; Lee, Ming Ta Michael; Shen, Chen-Yang; Tee, Benita Tan Kiat; Huimin, Bernice Wong; Broeks, Annegien; Vargas, Ana Cristina; Turashvili, Gulisa; Martens, John; Fatima, Aquila; Miron, Penelope; Chin, Suet-Feung; Thomas, Gilles; Boyault, Sandrine; Mariani, Odette; Lakhani, Sunil R.; van de Vijver, Marc; van ’t Veer, Laura; Foekens, John; Desmedt, Christine; Sotiriou, Christos; Tutt, Andrew; Caldas, Carlos; Reis-Filho, Jorge S.; Aparicio, Samuel A. J. R.; Salomon, Anne Vincent; Børresen-Dale, Anne-Lise; Richardson, Andrea L.; Campbell, Peter J.; Futreal, P. Andrew; Stratton, Michael R.

2012-01-01

All cancers carry somatic mutations in their genomes. A subset, known as driver mutations, confer clonal selective advantage on cancer cells and are causally implicated in oncogenesis1, and the remainder are passenger mutations. The driver mutations and mutational processes operative in breast cancer have not yet been comprehensively explored. Here we examine the genomes of 100 tumours for somatic copy number changes and mutations in the coding exons of protein-coding genes. The number of somatic mutations varied markedly between individual tumours. We found strong correlations between mutation number, age at which cancer was diagnosed and cancer histological grade, and observed multiple mutational signatures, including one present in about ten per cent of tumours characterized by numerous mutations of cytosine at TpC dinucleotides. Driver mutations were identified in several new cancer genes including AKT2, ARID1B, CASP8, CDKN1B, MAP3K1, MAP3K13, NCOR1, SMARCD1 and TBX3. Among the 100 tumours, we found driver mutations in at least 40 cancer genes and 73 different combinations of mutated cancer genes. The results highlight the substantial genetic diversity underlying this common disease. PMID:22722201

The strength of graduated drivers license programs and fatalities among teen drivers and passengers.

PubMed

Morrisey, Michael A; Grabowski, David C; Dee, Thomas S; Campbell, Christine

2006-01-01

The purpose of this study is to investigate the effects of differentially stringent graduated drivers license programs on teen driver fatalities, day-time and night-time teen driver fatalities, fatalities of teen drivers with passengers present, and fatalities among teen passengers. The study uses 1992-2002 data on motor vehicle fatalities among 15-17-year-old drivers from the Fatality Analysis Reporting System to identify the effects of "good", "fair", and "marginal" GDL programs based upon designations by the Insurance Institute for Highway Safety. Analysis is conducted using conditional negative binomial regressions with fixed effects. "Good" programs reduce total fatalities among young drivers by 19.4% (c.i. -33.0%, -5.9%). "Fair" programs reduce night-time young driver fatalities by 12.6% (c.i. -23.9%, -1.2%), but have no effect on day-time fatalities. "Marginal" programs had no statistically meaningful effect on driver fatalities. All three types of programs reduced teen passenger fatalities, but the effects of limitations on the number of passengers appear to have had only minimal effects in reducing fatalities among young drivers themselves. Stronger GDL programs are more effective than weaker programs in reducing teenage motor vehicle fatalities.

Determination of characteristics of fatally injured drivers

DOT National Transportation Integrated Search

2001-12-01

The objective of this study was to identify driver characteristics that can be used to predict driver risk of fatal crashes. The study had 3 components: (1) Comparisons were made among drivers who were killed in single-vehicle crashes or were at faul...

A gene-trap strategy identifies quiescence-induced genes in synchronized myoblasts.

PubMed

Sambasivan, Ramkumar; Pavlath, Grace K; Dhawan, Jyotsna

2008-03-01

Cellular quiescence is characterized not only by reduced mitotic and metabolic activity but also by altered gene expression. Growing evidence suggests that quiescence is not merely a basal state but is regulated by active mechanisms. To understand the molecular programme that governs reversible cell cycle exit, we focused on quiescence-related gene expression in a culture model of myogenic cell arrest and activation. Here we report the identification of quiescence-induced genes using a gene-trap strategy. Using a retroviral vector, we generated a library of gene traps in C2C12 myoblasts that were screened for arrest-induced insertions by live cell sorting (FACS-gal). Several independent gene- trap lines revealed arrest-dependent induction of betagal activity, confirming the efficacy of the FACS screen. The locus of integration was identified in 15 lines. In three lines,insertion occurred in genes previously implicated in the control of quiescence, i.e. EMSY - a BRCA2--interacting protein, p8/com1 - a p300HAT -- binding protein and MLL5 - a SET domain protein. Our results demonstrate that expression of chromatin modulatory genes is induced in G0, providing support to the notion that this reversibly arrested state is actively regulated.

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

PubMed Central

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

PubMed

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

Comprehensive analysis of transcriptome variation uncovers known and novel driver events in T-cell acute lymphoblastic leukemia.

PubMed

Atak, Zeynep Kalender; Gianfelici, Valentina; Hulselmans, Gert; De Keersmaecker, Kim; Devasia, Arun George; Geerdens, Ellen; Mentens, Nicole; Chiaretti, Sabina; Durinck, Kaat; Uyttebroeck, Anne; Vandenberghe, Peter; Wlodarska, Iwona; Cloos, Jacqueline; Foà, Robin; Speleman, Frank; Cools, Jan; Aerts, Stein

2013-01-01

RNA-seq is a promising technology to re-sequence protein coding genes for the identification of single nucleotide variants (SNV), while simultaneously obtaining information on structural variations and gene expression perturbations. We asked whether RNA-seq is suitable for the detection of driver mutations in T-cell acute lymphoblastic leukemia (T-ALL). These leukemias are caused by a combination of gene fusions, over-expression of transcription factors and cooperative point mutations in oncogenes and tumor suppressor genes. We analyzed 31 T-ALL patient samples and 18 T-ALL cell lines by high-coverage paired-end RNA-seq. First, we optimized the detection of SNVs in RNA-seq data by comparing the results with exome re-sequencing data. We identified known driver genes with recurrent protein altering variations, as well as several new candidates including H3F3A, PTK2B, and STAT5B. Next, we determined accurate gene expression levels from the RNA-seq data through normalizations and batch effect removal, and used these to classify patients into T-ALL subtypes. Finally, we detected gene fusions, of which several can explain the over-expression of key driver genes such as TLX1, PLAG1, LMO1, or NKX2-1; and others result in novel fusion transcripts encoding activated kinases (SSBP2-FER and TPM3-JAK2) or involving MLLT10. In conclusion, we present novel analysis pipelines for variant calling, variant filtering, and expression normalization on RNA-seq data, and successfully applied these for the detection of translocations, point mutations, INDELs, exon-skipping events, and expression perturbations in T-ALL.

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.

Born to roam? Surveying cat owners in Tasmania, Australia, to identify the drivers and barriers to cat containment.

PubMed

McLeod, Lynette J; Hine, Donald W; Bengsen, Andrew J

2015-12-01

Free-roaming domestic cats, Felis catus, are a major public nuisance in neighbourhoods across the world, and have been linked to biodiversity loss and a host of community health problems. Owners who let their cats roam, also place their cats at risk of serious injury. One management strategy that is gaining considerable support involves encouraging cat owners to contain their pets within their property. Contemporary behaviour change models highlight the importance of identifying drivers and barriers that encourage and discourage target behaviours such as cat containment. Results from a random dial phone survey of 356 cat owners in northern Tasmania identified four distinct cat containment profiles: owners who contained their cat all the time, owners who only contained their cat at night, owners who sporadically contained their cat with no set routine, and owners who made no attempt to contain their pet. Our results indicated that cat-owners' decisions to contain or not contain their cats were guided by a range of factors including owners' beliefs about their ability to implement an effective containment strategy and their views about the physical and psychological needs of their cats. The results are discussed in terms of improving the behavioural effectiveness of cat containment interventions by selecting appropriate behavioural change tools for the identified drivers and barriers, and developing targeted engagement strategies and messaging. Copyright © 2015 Elsevier B.V. All rights reserved.

Identifying multiple coral reef regimes and their drivers across the Hawaiian archipelago

PubMed Central

Jouffray, Jean-Baptiste; Nyström, Magnus; Norström, Albert V.; Williams, Ivor D.; Wedding, Lisa M.; Kittinger, John N.; Williams, Gareth J.

2015-01-01

Loss of coral reef resilience can lead to dramatic changes in benthic structure, often called regime shifts, which significantly alter ecosystem processes and functioning. In the face of global change and increasing direct human impacts, there is an urgent need to anticipate and prevent undesirable regime shifts and, conversely, to reverse shifts in already degraded reef systems. Such challenges require a better understanding of the human and natural drivers that support or undermine different reef regimes. The Hawaiian archipelago extends across a wide gradient of natural and anthropogenic conditions and provides us a unique opportunity to investigate the relationships between multiple reef regimes, their dynamics and potential drivers. We applied a combination of exploratory ordination methods and inferential statistics to one of the most comprehensive coral reef datasets available in order to detect, visualize and define potential multiple ecosystem regimes. This study demonstrates the existence of three distinct reef regimes dominated by hard corals, turf algae or macroalgae. Results from boosted regression trees show nonlinear patterns among predictors that help to explain the occurrence of these regimes, and highlight herbivore biomass as the key driver in addition to effluent, latitude and depth.

Identifying Effective Drivers for Knowledge Exchange in the United Kingdom

ERIC Educational Resources Information Center

Upton, Stevie

2012-01-01

This paper examines the drivers for knowledge exchange in British research-intensive universities, at a time when research impact is coming to be seen as an increasingly important outcome of research in all disciplines. It provides evidence of an over-emphasis of the economic benefits of knowledge exchange in the policy sphere and of a quite…

Gene-Trap Mutagenesis Identifies Mammalian Genes Contributing to Intoxication by Clostridium perfringens ε-Toxin

PubMed Central

Ivie, Susan E.; Fennessey, Christine M.; Sheng, Jinsong; Rubin, Donald H.; McClain, Mark S.

2011-01-01

The Clostridium perfringens ε-toxin is an extremely potent toxin associated with lethal toxemias in domesticated ruminants and may be toxic to humans. Intoxication results in fluid accumulation in various tissues, most notably in the brain and kidneys. Previous studies suggest that the toxin is a pore-forming toxin, leading to dysregulated ion homeostasis and ultimately cell death. However, mammalian host factors that likely contribute to ε-toxin-induced cytotoxicity are poorly understood. A library of insertional mutant Madin Darby canine kidney (MDCK) cells, which are highly susceptible to the lethal affects of ε-toxin, was used to select clones of cells resistant to ε-toxin-induced cytotoxicity. The genes mutated in 9 surviving resistant cell clones were identified. We focused additional experiments on one of the identified genes as a means of validating the experimental approach. Gene expression microarray analysis revealed that one of the identified genes, hepatitis A virus cellular receptor 1 (HAVCR1, KIM-1, TIM1), is more abundantly expressed in human kidney cell lines than it is expressed in human cells known to be resistant to ε-toxin. One human kidney cell line, ACHN, was found to be sensitive to the toxin and expresses a larger isoform of the HAVCR1 protein than the HAVCR1 protein expressed by other, toxin-resistant human kidney cell lines. RNA interference studies in MDCK and in ACHN cells confirmed that HAVCR1 contributes to ε-toxin-induced cytotoxicity. Additionally, ε-toxin was shown to bind to HAVCR1 in vitro. The results of this study indicate that HAVCR1 and the other genes identified through the use of gene-trap mutagenesis and RNA interference strategies represent important targets for investigation of the process by which ε-toxin induces cell death and new targets for potential therapeutic intervention. PMID:21412435

Gene-trap mutagenesis identifies mammalian genes contributing to intoxication by Clostridium perfringens ε-toxin.

PubMed

Ivie, Susan E; Fennessey, Christine M; Sheng, Jinsong; Rubin, Donald H; McClain, Mark S

2011-03-11

The Clostridium perfringens ε-toxin is an extremely potent toxin associated with lethal toxemias in domesticated ruminants and may be toxic to humans. Intoxication results in fluid accumulation in various tissues, most notably in the brain and kidneys. Previous studies suggest that the toxin is a pore-forming toxin, leading to dysregulated ion homeostasis and ultimately cell death. However, mammalian host factors that likely contribute to ε-toxin-induced cytotoxicity are poorly understood. A library of insertional mutant Madin Darby canine kidney (MDCK) cells, which are highly susceptible to the lethal affects of ε-toxin, was used to select clones of cells resistant to ε-toxin-induced cytotoxicity. The genes mutated in 9 surviving resistant cell clones were identified. We focused additional experiments on one of the identified genes as a means of validating the experimental approach. Gene expression microarray analysis revealed that one of the identified genes, hepatitis A virus cellular receptor 1 (HAVCR1, KIM-1, TIM1), is more abundantly expressed in human kidney cell lines than it is expressed in human cells known to be resistant to ε-toxin. One human kidney cell line, ACHN, was found to be sensitive to the toxin and expresses a larger isoform of the HAVCR1 protein than the HAVCR1 protein expressed by other, toxin-resistant human kidney cell lines. RNA interference studies in MDCK and in ACHN cells confirmed that HAVCR1 contributes to ε-toxin-induced cytotoxicity. Additionally, ε-toxin was shown to bind to HAVCR1 in vitro. The results of this study indicate that HAVCR1 and the other genes identified through the use of gene-trap mutagenesis and RNA interference strategies represent important targets for investigation of the process by which ε-toxin induces cell death and new targets for potential therapeutic intervention.

A Penalized Robust Method for Identifying Gene-Environment Interactions

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

2015-01-01

In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063

Advanced driver assistance systems for teen drivers: Teen and parent impressions, perceived need, and intervention preferences.

PubMed

Weiss, Eve; Fisher Thiel, Megan; Sultana, Nahida; Hannan, Chloe; Seacrist, Thomas

2018-02-28

From the advent of airbags to electronic stability control, technological advances introduced into automobile design have significantly reduced injury and death from motor vehicle crashes. These advances are especially pertinent among teen drivers, a population whose leading cause of death is motor vehicle crashes. Recently developed advanced driver assistance systems (ADAS) have the potential to compensate for skill deficits and reduce overall crash risk. Yet, ADAS is only effective if drivers are willing to use it. Limited research has been conducted on the suitability of ADAS for teen drivers. The goal of this study is to identify teen drivers' perceived need for ADAS, receptiveness to in-vehicle technology, and intervention preferences. The long-term goal is to understand public perceptions and barriers to ADAS use and to help determine how these systems must evolve to meet the needs of the riskiest driving populations. Three focus groups (N = 24) were conducted with licensed teen drivers aged 16-19 years and 2 focus groups with parents of teen drivers (N = 12). Discussion topics included views on how ADAS might influence driving skills and behaviors; trust in technology; and data privacy. Discussions were transcribed; the team used conventional content analysis and open coding methods to identify 12 coding domains and code transcripts with NVivo 10. Interrater reliability testing showed moderate to high kappa scores. Overall, participants recognized potential benefits of ADAS, including improved safety and crash reduction. Teens suggested that ADAS is still developing and therefore has potential to malfunction. Many teens reported a greater trust in their own driving ability over vehicle technology. They expressed that novice drivers should learn to drive on non-ADAS-equipped cars and that ADAS should be considered a supplemental aid. Many teens felt that overreliance on ADAS may increase distracted driving or risky behaviors among teens. Parents also

Identifying at-risk drivers : a survey of state programs : final report.

DOT National Transportation Integrated Search

1990-01-01

Motor vehicle administrators have long realized that certain drivers present more of safety problem than others. Tests of static visual acuity, knowledge of the rules of the road, and on-the-road driving performance are used to ensure that each drive...

Pan-cancer transcriptomic analysis associates long non-coding RNAs with key mutational driver events

PubMed Central

Ashouri, Arghavan; Sayin, Volkan I.; Van den Eynden, Jimmy; Singh, Simranjit X.; Papagiannakopoulos, Thales; Larsson, Erik

2016-01-01

Thousands of long non-coding RNAs (lncRNAs) lie interspersed with coding genes across the genome, and a small subset has been implicated as downstream effectors in oncogenic pathways. Here we make use of transcriptome and exome sequencing data from thousands of tumours across 19 cancer types, to identify lncRNAs that are induced or repressed in relation to somatic mutations in key oncogenic driver genes. Our screen confirms known coding and non-coding effectors and also associates many new lncRNAs to relevant pathways. The associations are often highly reproducible across cancer types, and while many lncRNAs are co-expressed with their protein-coding hosts or neighbours, some are intergenic and independent. We highlight lncRNAs with possible functions downstream of the tumour suppressor TP53 and the master antioxidant transcription factor NFE2L2. Our study provides a comprehensive overview of lncRNA transcriptional alterations in relation to key driver mutational events in human cancers. PMID:28959951

Predicting hepatocellular carcinoma through cross-talk genes identified by risk pathways

PubMed Central

Shao, Zhuo; Huo, Diwei; Zhang, Denan; Xie, Hongbo; Yang, Jingbo; Liu, Qiuqi; Chen, Xiujie

2018-01-01

Hepatocellular carcinoma (HCC) is the most frequent type of liver cancer with poor survival rate and high mortality. Despite efforts on the mechanism of HCC, new molecular markers are needed for exact diagnosis, evaluation and treatment. Here, we combined transcriptome of HCC with networks and pathways to identify reliable molecular markers. Through integrating 249 differentially expressed genes with syncretic protein interaction networks, we constructed a HCC-specific network, from which we further extracted 480 pivotal genes. Based on the cross-talk between the enriched pathways of the pivotal genes, we finally identified a HCC signature of 45 genes, which could accurately distinguish HCC patients with normal individuals and reveal the prognosis of HCC patients. Among these 45 genes, 15 showed dysregulated expression patterns and a part have been reported to be associated with HCC and/or other cancers. These findings suggested that our identified 45 gene signature could be potential and valuable molecular markers for diagnosis and evaluation of HCC. PMID:29765536

Inferring Gene Family Histories in Yeast Identifies Lineage Specific Expansions

PubMed Central

Ames, Ryan M.; Money, Daniel; Lovell, Simon C.

2014-01-01

The complement of genes found in the genome is a balance between gene gain and gene loss. Knowledge of the specific genes that are gained and lost over evolutionary time allows an understanding of the evolution of biological functions. Here we use new evolutionary models to infer gene family histories across complete yeast genomes; these models allow us to estimate the relative genome-wide rates of gene birth, death, innovation and extinction (loss of an entire family) for the first time. We show that the rates of gene family evolution vary both between gene families and between species. We are also able to identify those families that have experienced rapid lineage specific expansion/contraction and show that these families are enriched for specific functions. Moreover, we find that families with specific functions are repeatedly expanded in multiple species, suggesting the presence of common adaptations and that these family expansions/contractions are not random. Additionally, we identify potential specialisations, unique to specific species, in the functions of lineage specific expanded families. These results suggest that an important mechanism in the evolution of genome content is the presence of lineage-specific gene family changes. PMID:24921666

Older drivers' foot movements : traffic tech.

DOT National Transportation Integrated Search

2017-07-01

This study explored how older drivers use their accelerator and : brake pedals, to identify characteristics that could pose an increased : risk of a pedal application error. The study also explored whether : driver-vehicle fit was related to these ch...

Assessing drivers' response during automated driver support system failures with non-driving tasks.

PubMed

Shen, Sijun; Neyens, David M

2017-06-01

With the increase in automated driver support systems, drivers are shifting from operating their vehicles to supervising their automation. As a result, it is important to understand how drivers interact with these automated systems and evaluate their effect on driver responses to safety critical events. This study aimed to identify how drivers responded when experiencing a safety critical event in automated vehicles while also engaged in non-driving tasks. In total 48 participants were included in this driving simulator study with two levels of automated driving: (a) driving with no automation and (b) driving with adaptive cruise control (ACC) and lane keeping (LK) systems engaged; and also two levels of a non-driving task (a) watching a movie or (b) no non-driving task. In addition to driving performance measures, non-driving task performance and the mean glance duration for the non-driving task were compared between the two levels of automated driving. Drivers using the automated systems responded worse than those manually driving in terms of reaction time, lane departure duration, and maximum steering wheel angle to an induced lane departure event. These results also found that non-driving tasks further impaired driver responses to a safety critical event in the automated system condition. In the automated driving condition, driver responses to the safety critical events were slower, especially when engaged in a non-driving task. Traditional driver performance variables may not necessarily effectively and accurately evaluate driver responses to events when supervising autonomous vehicle systems. Thus, it is important to develop and use appropriate variables to quantify drivers' performance under these conditions. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

Mandatory Physician Reporting of At-Risk Drivers: The Older Driver Example.

PubMed

Agimi, Yll; Albert, Steven M; Youk, Ada O; Documet, Patricia I; Steiner, Claudia A

2018-05-08

In a number of states, physicians are mandated by state law to report at-risk drivers to licensing authorities. Often these patients are older adult drivers who may exhibit unsafe driving behaviors, have functional/cognitive impairments, or are diagnosed with conditions such as Alzheimer's disease and/or seizure disorders. The hypothesis that mandatory physician reporting laws reduce the rate of crash-related hospitalizations among older adult drivers was tested. Using retrospective data (2004-2009), this study identified 176,066 older driver crash-related hospitalizations, from the State Inpatient Databases. Three age-specific negative binomial generalized estimating equation models were used to estimate the effect of physician reporting laws on state's incidence rate of crash-related hospitalizations among older drivers. No evidence was found for an independent association between mandatory physician reporting laws and a lower crash hospitalization rate among any of the age groups examined. The main predictor of interest, mandatory physician reporting, failed to explain any significant variation in crash hospitalization rates, when adjusting for other state-specific laws and characteristics. Vision testing at in-person license renewal was a significant predictor of lower crash hospitalization rate, ranging from incidence rate ratio of 0.77 (95% confidence interval 0.62-0.94) among 60- to 64-year olds to 0.83 (95% confidence interval 0.67-0.97) among 80- to 84-year olds. Physician reporting laws and age-based licensing requirements are often at odds with older driver's need to maintain independence. This study examines this balance and finds no evidence of the benefits of mandatory physician reporting requirements on driver crash hospitalizations, suggesting that physician mandates do not yet yield significant older driver safety benefits, possibly to the detriment of older driver's well-being and independence.

Psychological reactions of drivers to railway suicide.

PubMed

Tranah, T; Farmer, R D

1994-02-01

Around 90 London Underground train drivers experience a person jumping or falling in front of their train each year. The majority of these incidents are suicides or attempted suicides. 76 drivers were interviewed in order to assess the range of responses to these incidents. The following psychometric instruments were used: Present State Examination (PSE9); Post-Traumatic Stress Disorder (PTSD) Interview; General Health Questionnaire (GHQ-28); Impact of Events Scale (IES); Post-Traumatic Symptom Scale; Recent Difficulties/Events scale; Perceived Stress Scale and Eysenck Personality Questionnaire (EPQ). When interviewed 1 month after the incident 13 (17.11%) drivers presented with PTSD. Diagnoses other than PTSD e.g. neurotic depression and phobic state were present in 24 (31.58%) drivers (including 12 of the 13 PTSD cases who had one additional diagnosis). On the basis of diagnoses three groups were identified: Group 1 drivers had PTSD and in most cases an additional PSE9 diagnosis; Group 2 drivers had a PSE9 diagnosis only; Group 3 drivers were not cases. 56 drivers were again interviewed 6 months after the incident to assess duration of caseness and/or symptoms and to identify any cases of delayed onset. Two drivers were still cases at 6 months (neurotic depression and phobic state), no driver presented with PTSD at 6 months. At 6 months there was a significant drop in symptom scores compared with measures taken at 1 month. These results suggest that although approximately one-third of drivers suffered a severe psychological reaction following a railway suicide, when interviewed again 6 months after the incident most drivers reported a marked reduction in symptoms.

The genetics of alcoholism: identifying specific genes through family studies.

PubMed

Edenberg, Howard J; Foroud, Tatiana

2006-09-01

Alcoholism is a complex disorder with both genetic and environmental risk factors. Studies in humans have begun to elucidate the genetic underpinnings of the risk for alcoholism. Here we briefly review strategies for identifying individual genes in which variations affect the risk for alcoholism and related phenotypes, in the context of one large study that has successfully identified such genes. The Collaborative Study on the Genetics of Alcoholism (COGA) is a family-based study that has collected detailed phenotypic data on individuals in families with multiple alcoholic members. A genome-wide linkage approach led to the identification of chromosomal regions containing genes that influenced alcoholism risk and related phenotypes. Subsequently, single nucleotide polymorphisms (SNPs) were genotyped in positional candidate genes located within the linked chromosomal regions, and analyzed for association with these phenotypes. Using this sequential approach, COGA has detected association with GABRA2, CHRM2 and ADH4; these associations have all been replicated by other researchers. COGA has detected association to additional genes including GABRG3, TAS2R16, SNCA, OPRK1 and PDYN, results that are awaiting confirmation. These successes demonstrate that genes contributing to the risk for alcoholism can be reliably identified using human subjects.

A Landscape of Driver Mutations in Melanoma

PubMed Central

Hodis, Eran; Watson, Ian R.; Kryukov, Gregory V.; Arold, Stefan T.; Imielinski, Marcin; Theurillat, Jean-Philippe; Nickerson, Elizabeth; Auclair, Daniel; Li, Liren; Place, Chelsea; DiCara, Daniel; Ramos, Alex H.; Lawrence, Michael S.; Cibulskis, Kristian; Sivachenko, Andrey; Voet, Douglas; Saksena, Gordon; Stransky, Nicolas; Onofrio, Robert C.; Winckler, Wendy; Ardlie, Kristin; Wagle, Nikhil; Wargo, Jennifer; Chong, Kelly; Morton, Donald L.; Stemke-Hale, Katherine; Chen, Guo; Noble, Michael; Meyerson, Matthew; Ladbury, John E.; Davies, Michael A.; Gershenwald, Jeffrey E.; Wagner, Stephan N.; Hoon, Dave S.B.; Schadendorf, Dirk; Lander, Eric S.; Gabriel, Stacey B.; Getz, Gad; Garraway, Levi A.; Chin, Lynda

2012-01-01

SUMMARY Despite recent insights into melanoma genetics, systematic surveys for driver mutations are challenged by an abundance of passenger mutations caused by carcinogenic ultraviolet (UV) light exposure. We developed a permutation-based framework to address this challenge, employing mutation data from intronic sequences to control for passenger mutational load on a per gene basis. Analysis of large-scale melanoma exome data by this approach discovered six novel melanoma genes (PPP6C, RAC1, SNX31, TACC1, STK19 and ARID2), three of which - RAC1, PPP6C and STK19 - harbored recurrent and potentially targetable mutations. Integration with chromosomal copy number data contextualized the landscape of driver mutations, providing oncogenic insights in BRAF- and NRAS-driven melanoma as well as those without known NRAS/BRAF mutations. The landscape also clarified a mutational basis for RB and p53 pathway deregulation in this malignancy. Finally, the spectrum of driver mutations provided unequivocal genomic evidence for a direct mutagenic role of UV light in melanoma pathogenesis. PMID:22817889

Kinase Gene Fusions in Defined Subsets of Melanoma

PubMed Central

Turner, Jacqueline; Couts, Kasey; Sheren, Jamie; Saichaemchan, Siriwimon; Ariyawutyakorn, Witthawat; Avolio, Izabela; Cabral, Ethan; Glogowska, Magdelena; Amato, Carol; Robinson, Steven; Hintzsche, Jennifer; Applegate, Allison; Seelenfreund, Eric; Gonzalez, Rita; Wells, Keith; Bagby, Stacey; Tentler, John; Tan, Aik-Choon; Wisell, Joshua; Varella-Garcia, Marileila; Robinson, William

2017-01-01

Summary Genomic rearrangements resulting in activating kinase fusions have been increasingly described in a number of cancers including malignant melanoma, but their frequency in specific melanoma subtypes has not been reported. We used break-apart fluorescence in-situ hybridization (FISH) to identify genomic rearrangements in tissues from 59 patients with various types of malignant melanoma including acral lentiginous, mucosal, superficial spreading, and nodular. We identified four genomic rearrangements involving the genes BRAF, RET, and ROS1. Of these, three were confirmed by IHC or sequencing and one was found to be an ARMC10-BRAF fusion that has not been previously reported in melanoma. These fusions occurred in different subtypes of melanoma but all in tumors lacking known driver mutations. Our data suggest gene fusions are more common than previously thought-and should be further explored particularly in melanomas lacking known driver mutations. PMID:27864876

Gene expression patterns combined with bioinformatics analysis identify genes associated with cholangiocarcinoma.

PubMed

Li, Chen; Shen, Weixing; Shen, Sheng; Ai, Zhilong

2013-12-01

To explore the molecular mechanisms of cholangiocarcinoma (CC), microarray technology was used to find biomarkers for early detection and diagnosis. The gene expression profiles from 6 patients with CC and 5 normal controls were downloaded from Gene Expression Omnibus and compared. As a result, 204 differentially co-expressed genes (DCGs) in CC patients compared to normal controls were identified using a computational bioinformatics analysis. These genes were mainly involved in coenzyme metabolic process, peptidase activity and oxidation reduction. A regulatory network was constructed by mapping the DCGs to known regulation data. Four transcription factors, FOXC1, ZIC2, NKX2-2 and GCGR, were hub nodes in the network. In conclusion, this study provides a set of targets useful for future investigations into molecular biomarker studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

VarWalker: Personalized Mutation Network Analysis of Putative Cancer Genes from Next-Generation Sequencing Data

PubMed Central

Jia, Peilin; Zhao, Zhongming

2014-01-01

A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data. PMID:24516372

VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.

PubMed

Jia, Peilin; Zhao, Zhongming

2014-02-01

A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data.

Transportation needs of the older driver : final report.

DOT National Transportation Integrated Search

1993-01-01

A growing percentage of all drivers are aged 55 and older. The findings of a number of safety studies have also fostered national interest in older driver issues. The needs and problems of Virginia drivers age 55 and older were identified in 10 focus...

A Systems Biology Approach Identifies FUT8 as a Driver of Melanoma Metastasis.

PubMed

Agrawal, Praveen; Fontanals-Cirera, Barbara; Sokolova, Elena; Jacob, Samson; Vaiana, Christopher A; Argibay, Diana; Davalos, Veronica; McDermott, Meagan; Nayak, Shruti; Darvishian, Farbod; Castillo, Mireia; Ueberheide, Beatrix; Osman, Iman; Fenyö, David; Mahal, Lara K; Hernando, Eva

2017-06-12

Association of aberrant glycosylation with melanoma progression is based mainly on analyses of cell lines. Here we present a systems-based study of glycomic changes and corresponding enzymes associated with melanoma metastasis in patient samples. Upregulation of core fucosylation (FUT8) and downregulation of α-1,2 fucosylation (FUT1, FUT2) were identified as features of metastatic melanoma. Using both in vitro and in vivo studies, we demonstrate FUT8 is a driver of melanoma metastasis which, when silenced, suppresses invasion and tumor dissemination. Glycoprotein targets of FUT8 were enriched in cell migration proteins including the adhesion molecule L1CAM. Core fucosylation impacted L1CAM cleavage and the ability of L1CAM to support melanoma invasion. FUT8 and its targets represent therapeutic targets in melanoma metastasis. Copyright © 2017 Elsevier Inc. All rights reserved.

An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

PubMed Central

Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

2009-01-01

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

PubMed Central

Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

2013-01-01

Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213

Identifying conserved gene clusters in the presence of homology families.

PubMed

He, Xin; Goldwasser, Michael H

2005-01-01

The study of conserved gene clusters is important for understanding the forces behind genome organization and evolution, as well as the function of individual genes or gene groups. In this paper, we present a new model and algorithm for identifying conserved gene clusters from pairwise genome comparison. This generalizes a recent model called "gene teams." A gene team is a set of genes that appear homologously in two or more species, possibly in a different order yet with the distance of adjacent genes in the team for each chromosome always no more than a certain threshold. We remove the constraint in the original model that each gene must have a unique occurrence in each chromosome and thus allow the analysis on complex prokaryotic or eukaryotic genomes with extensive paralogs. Our algorithm analyzes a pair of chromosomes in O(mn) time and uses O(m+n) space, where m and n are the number of genes in the respective chromosomes. We demonstrate the utility of our methods by studying two bacterial genomes, E. coli K-12 and B. subtilis. Many of the teams identified by our algorithm correlate with documented E. coli operons, while several others match predicted operons, previously suggested by computational techniques. Our implementation and data are publicly available at euler.slu.edu/ approximately goldwasser/homologyteams/.

Determinants and Drivers of Infectious Disease Threat Events in Europe.

PubMed

Semenza, Jan C; Lindgren, Elisabet; Balkanyi, Laszlo; Espinosa, Laura; Almqvist, My S; Penttinen, Pasi; Rocklöv, Joacim

2016-04-01

Infectious disease threat events (IDTEs) are increasing in frequency worldwide. We analyzed underlying drivers of 116 IDTEs detected in Europe during 2008-2013 by epidemic intelligence at the European Centre of Disease Prevention and Control. Seventeen drivers were identified and categorized into 3 groups: globalization and environment, sociodemographic, and public health systems. A combination of >2 drivers was responsible for most IDTEs. The driver category globalization and environment contributed to 61% of individual IDTEs, and the top 5 individual drivers of all IDTEs were travel and tourism, food and water quality, natural environment, global trade, and climate. Hierarchical cluster analysis of all drivers identified travel and tourism as a distinctly separate driver. Monitoring and modeling such disease drivers can help anticipate future IDTEs and strengthen control measures. More important, intervening directly on these underlying drivers can diminish the likelihood of the occurrence of an IDTE and reduce the associated human and economic costs.

Determinants and Drivers of Infectious Disease Threat Events in Europe

PubMed Central

Lindgren, Elisabet; Balkanyi, Laszlo; Espinosa, Laura; Almqvist, My S.; Penttinen, Pasi; Rocklöv, Joacim

2016-01-01

Infectious disease threat events (IDTEs) are increasing in frequency worldwide. We analyzed underlying drivers of 116 IDTEs detected in Europe during 2008–2013 by epidemic intelligence at the European Centre of Disease Prevention and Control. Seventeen drivers were identified and categorized into 3 groups: globalization and environment, sociodemographic, and public health systems. A combination of >2 drivers was responsible for most IDTEs. The driver category globalization and environment contributed to 61% of individual IDTEs, and the top 5 individual drivers of all IDTEs were travel and tourism, food and water quality, natural environment, global trade, and climate. Hierarchical cluster analysis of all drivers identified travel and tourism as a distinctly separate driver. Monitoring and modeling such disease drivers can help anticipate future IDTEs and strengthen control measures. More important, intervening directly on these underlying drivers can diminish the likelihood of the occurrence of an IDTE and reduce the associated human and economic costs. PMID:26982104

Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype

PubMed Central

Kanth, Priyanka; Bronner, Mary P.; Boucher, Kenneth M.; Burt, Randall W.; Neklason, Deborah W.; Hagedorn, Curt H.; Delker, Don A.

2016-01-01

Sessile serrated colon adenoma/polyps (SSA/Ps) are found during routine screening colonoscopy and may account for 20–30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. Additionally, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon and 20 control colon specimens. Differential expression and leave-one-out cross validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n=12) and sporadic SSA/Ps (n=9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability (MSI-H). A smaller seven-gene panel showed high sensitivity and specificity in identifying BRAF mutant, CpG island methylator phenotype high (CIMP-H) and MLH1 silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. PMID:27026680

Kinase gene fusions in defined subsets of melanoma.

PubMed

Turner, Jacqueline; Couts, Kasey; Sheren, Jamie; Saichaemchan, Siriwimon; Ariyawutyakorn, Witthawat; Avolio, Izabela; Cabral, Ethan; Glogowska, Magdelena; Amato, Carol; Robinson, Steven; Hintzsche, Jennifer; Applegate, Allison; Seelenfreund, Eric; Gonzalez, Rita; Wells, Keith; Bagby, Stacey; Tentler, John; Tan, Aik-Choon; Wisell, Joshua; Varella-Garcia, Marileila; Robinson, William

2017-01-01

Genomic rearrangements resulting in activating kinase fusions have been increasingly described in a number of cancers including malignant melanoma, but their frequency in specific melanoma subtypes has not been reported. We used break-apart fluorescence in situ hybridization (FISH) to identify genomic rearrangements in tissues from 59 patients with various types of malignant melanoma including acral lentiginous, mucosal, superficial spreading, and nodular. We identified four genomic rearrangements involving the genes BRAF, RET, and ROS1. Of these, three were confirmed by Immunohistochemistry (IHC) or sequencing and one was found to be an ARMC10-BRAF fusion that has not been previously reported in melanoma. These fusions occurred in different subtypes of melanoma but all in tumors lacking known driver mutations. Our data suggest gene fusions are more common than previously thought and should be further explored particularly in melanomas lacking known driver mutations. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Targeted sequencing-based analyses of candidate gene variants in ulcerative colitis-associated colorectal neoplasia.

PubMed

Chakrabarty, Sanjiban; Varghese, Vinay Koshy; Sahu, Pranoy; Jayaram, Pradyumna; Shivakumar, Bhadravathi M; Pai, Cannanore Ganesh; Satyamoorthy, Kapaettu

2017-06-27

Long-standing ulcerative colitis (UC) leading to colorectal cancer (CRC) is one of the most serious and life-threatening consequences acknowledged globally. Ulcerative colitis-associated colorectal carcinogenesis showed distinct molecular alterations when compared with sporadic colorectal carcinoma. Targeted sequencing of 409 genes in tissue samples of 18 long-standing UC subjects at high risk of colorectal carcinoma (UCHR) was performed to identify somatic driver mutations, which may be involved in the molecular changes during the transformation of non-dysplastic mucosa to high-grade dysplasia. Findings from the study are also compared with previously published genome wide and exome sequencing data in inflammatory bowel disease-associated and sporadic colorectal carcinoma. Next-generation sequencing analysis identified 1107 mutations in 275 genes in UCHR subjects. In addition to TP53 (17%) and KRAS (22%) mutations, recurrent mutations in APC (33%), ACVR2A (61%), ARID1A (44%), RAF1 (39%) and MTOR (61%) were observed in UCHR subjects. In addition, APC, FGFR3, FGFR2 and PIK3CA driver mutations were identified in UCHR subjects. Recurrent mutations in ARID1A (44%), SMARCA4 (17%), MLL2 (44%), MLL3 (67%), SETD2 (17%) and TET2 (50%) genes involved in histone modification and chromatin remodelling were identified in UCHR subjects. Our study identifies new oncogenic driver mutations which may be involved in the transition of non-dysplastic cells to dysplastic phenotype in the subjects with long-standing UC with high risk of progression into colorectal neoplasia.

Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

PubMed Central

Edmunds, Richard C.; Su, Baofeng; Balhoff, James P.; Eames, B. Frank; Dahdul, Wasila M.; Lapp, Hilmar; Lundberg, John G.; Vision, Todd J.; Dunham, Rex A.; Mabee, Paula M.; Westerfield, Monte

2016-01-01

Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

Common Marker Genes Identified from Various Sample Types for Systemic Lupus Erythematosus.

PubMed

Bing, Peng-Fei; Xia, Wei; Wang, Lan; Zhang, Yong-Hong; Lei, Shu-Feng; Deng, Fei-Yan

2016-01-01

Systemic lupus erythematosus (SLE) is a complex auto-immune disease. Gene expression studies have been conducted to identify SLE-related genes in various types of samples. It is unknown whether there are common marker genes significant for SLE but independent of sample types, which may have potentials for follow-up translational research. The aim of this study is to identify common marker genes across various sample types for SLE. Based on four public microarray gene expression datasets for SLE covering three representative types of blood-born samples (monocyte; peripheral blood mononuclear cell, PBMC; whole blood), we utilized three statistics (fold-change, FC; t-test p value; false discovery rate adjusted p value) to scrutinize genes simultaneously regulated with SLE across various sample types. For common marker genes, we conducted the Gene Ontology enrichment analysis and Protein-Protein Interaction analysis to gain insights into their functions. We identified 10 common marker genes associated with SLE (IFI6, IFI27, IFI44L, OAS1, OAS2, EIF2AK2, PLSCR1, STAT1, RNASE2, and GSTO1). Significant up-regulation of IFI6, IFI27, and IFI44L with SLE was observed in all the studied sample types, though the FC was most striking in monocyte, compared with PBMC and whole blood (8.82-251.66 vs. 3.73-74.05 vs. 1.19-1.87). Eight of the above 10 genes, except RNASE2 and GSTO1, interact with each other and with known SLE susceptibility genes, participate in immune response, RNA and protein catabolism, and cell death. Our data suggest that there exist common marker genes across various sample types for SLE. The 10 common marker genes, identified herein, deserve follow-up studies to dissert their potentials as diagnostic or therapeutic markers to predict SLE or treatment response.

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

PubMed Central

He, Hao; Zhang, Lei; Li, Jian; Wang, Yu-Ping; Zhang, Ji-Gang; Shen, Jie; Guo, Yan-Fang

2014-01-01

Context: To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk. Methods: First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa. Results: In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value <.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation. Conclusion: We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis. PMID:25119315

Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma.

PubMed

Reddy, Anupama; Zhang, Jenny; Davis, Nicholas S; Moffitt, Andrea B; Love, Cassandra L; Waldrop, Alexander; Leppa, Sirpa; Pasanen, Annika; Meriranta, Leo; Karjalainen-Lindsberg, Marja-Liisa; Nørgaard, Peter; Pedersen, Mette; Gang, Anne O; Høgdall, Estrid; Heavican, Tayla B; Lone, Waseem; Iqbal, Javeed; Qin, Qiu; Li, Guojie; Kim, So Young; Healy, Jane; Richards, Kristy L; Fedoriw, Yuri; Bernal-Mizrachi, Leon; Koff, Jean L; Staton, Ashley D; Flowers, Christopher R; Paltiel, Ora; Goldschmidt, Neta; Calaminici, Maria; Clear, Andrew; Gribben, John; Nguyen, Evelyn; Czader, Magdalena B; Ondrejka, Sarah L; Collie, Angela; Hsi, Eric D; Tse, Eric; Au-Yeung, Rex K H; Kwong, Yok-Lam; Srivastava, Gopesh; Choi, William W L; Evens, Andrew M; Pilichowska, Monika; Sengar, Manju; Reddy, Nishitha; Li, Shaoying; Chadburn, Amy; Gordon, Leo I; Jaffe, Elaine S; Levy, Shawn; Rempel, Rachel; Tzeng, Tiffany; Happ, Lanie E; Dave, Tushar; Rajagopalan, Deepthi; Datta, Jyotishka; Dunson, David B; Dave, Sandeep S

2017-10-05

Diffuse large B cell lymphoma (DLBCL) is the most common form of blood cancer and is characterized by a striking degree of genetic and clinical heterogeneity. This heterogeneity poses a major barrier to understanding the genetic basis of the disease and its response to therapy. Here, we performed an integrative analysis of whole-exome sequencing and transcriptome sequencing in a cohort of 1,001 DLBCL patients to comprehensively define the landscape of 150 genetic drivers of the disease. We characterized the functional impact of these genes using an unbiased CRISPR screen of DLBCL cell lines to define oncogenes that promote cell growth. A prognostic model comprising these genetic alterations outperformed current established methods: cell of origin, the International Prognostic Index comprising clinical variables, and dual MYC and BCL2 expression. These results comprehensively define the genetic drivers and their functional roles in DLBCL to identify new therapeutic opportunities in the disease. Copyright © 2017 Elsevier Inc. All rights reserved.

A Novel mRNA Level Subtraction Method for Quick Identification of Target-Orientated Uniquely Expressed Genes Between Peanut Immature Pod and Leaf

PubMed Central

2010-01-01

Subtraction technique has been broadly applied for target gene discovery. However, most current protocols apply relative differential subtraction and result in great amount clone mixtures of unique and differentially expressed genes. This makes it more difficult to identify unique or target-orientated expressed genes. In this study, we developed a novel method for subtraction at mRNA level by integrating magnetic particle technology into driver preparation and tester–driver hybridization to facilitate uniquely expressed gene discovery between peanut immature pod and leaf through a single round subtraction. The resulting target clones were further validated through polymerase chain reaction screening using peanut immature pod and leaf cDNA libraries as templates. This study has resulted in identifying several genes expressed uniquely in immature peanut pod. These target genes can be used for future peanut functional genome and genetic engineering research. PMID:21406066

Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health.

PubMed

Stern, Hal S; Blower, Daniel; Cohen, Michael L; Czeisler, Charles A; Dinges, David F; Greenhouse, Joel B; Guo, Feng; Hanowski, Richard J; Hartenbaum, Natalie P; Krueger, Gerald P; Mallis, Melissa M; Pain, Richard F; Rizzo, Matthew; Sinha, Esha; Small, Dylan S; Stuart, Elizabeth A; Wegman, David H

2018-03-09

This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

PubMed

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

A cross-species bi-clustering approach to identifying conserved co-regulated genes.

PubMed

Sun, Jiangwen; Jiang, Zongliang; Tian, Xiuchun; Bi, Jinbo

2016-06-15

A growing number of studies have explored the process of pre-implantation embryonic development of multiple mammalian species. However, the conservation and variation among different species in their developmental programming are poorly defined due to the lack of effective computational methods for detecting co-regularized genes that are conserved across species. The most sophisticated method to date for identifying conserved co-regulated genes is a two-step approach. This approach first identifies gene clusters for each species by a cluster analysis of gene expression data, and subsequently computes the overlaps of clusters identified from different species to reveal common subgroups. This approach is ineffective to deal with the noise in the expression data introduced by the complicated procedures in quantifying gene expression. Furthermore, due to the sequential nature of the approach, the gene clusters identified in the first step may have little overlap among different species in the second step, thus difficult to detect conserved co-regulated genes. We propose a cross-species bi-clustering approach which first denoises the gene expression data of each species into a data matrix. The rows of the data matrices of different species represent the same set of genes that are characterized by their expression patterns over the developmental stages of each species as columns. A novel bi-clustering method is then developed to cluster genes into subgroups by a joint sparse rank-one factorization of all the data matrices. This method decomposes a data matrix into a product of a column vector and a row vector where the column vector is a consistent indicator across the matrices (species) to identify the same gene cluster and the row vector specifies for each species the developmental stages that the clustered genes co-regulate. Efficient optimization algorithm has been developed with convergence analysis. This approach was first validated on synthetic data and compared

A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification.

PubMed

Guo, Wei-Feng; Zhang, Shao-Wu; Shi, Qian-Qian; Zhang, Cheng-Ming; Zeng, Tao; Chen, Luonan

2018-01-19

The advances in target control of complex networks not only can offer new insights into the general control dynamics of complex systems, but also be useful for the practical application in systems biology, such as discovering new therapeutic targets for disease intervention. In many cases, e.g. drug target identification in biological networks, we usually require a target control on a subset of nodes (i.e., disease-associated genes) with minimum cost, and we further expect that more driver nodes consistent with a certain well-selected network nodes (i.e., prior-known drug-target genes). Therefore, motivated by this fact, we pose and address a new and practical problem called as target control problem with objectives-guided optimization (TCO): how could we control the interested variables (or targets) of a system with the optional driver nodes by minimizing the total quantity of drivers and meantime maximizing the quantity of constrained nodes among those drivers. Here, we design an efficient algorithm (TCOA) to find the optional driver nodes for controlling targets in complex networks. We apply our TCOA to several real-world networks, and the results support that our TCOA can identify more precise driver nodes than the existing control-fucus approaches. Furthermore, we have applied TCOA to two bimolecular expert-curate networks. Source code for our TCOA is freely available from http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm or https://github.com/WilfongGuo/guoweifeng . In the previous theoretical research for the full control, there exists an observation and conclusion that the driver nodes tend to be low-degree nodes. However, for target control the biological networks, we find interestingly that the driver nodes tend to be high-degree nodes, which is more consistent with the biological experimental observations. Furthermore, our results supply the novel insights into how we can efficiently target control a complex system, and especially many evidences on the

CCR researchers identify pathway critical for preventing premature aging | Center for Cancer Research

Cancer.gov

Hutchinson-Gilford progeria syndrome (HGPS) is a rare, fatal disease in which patients age prematurely. To identify primary HGPS driver mechanisms, Nard Kubben, Ph.D., a Research Fellow in the laboratory of Tom Misteli, Ph.D., in CCR’s Laboratory of Receptor Biology and Gene Expression, and colleagues in the NCI High-throughput Imaging Facility developed an imaging-based

An application of the driver behavior questionnaire to Chinese carless young drivers.

PubMed

Zhang, Qian; Jiang, Zuhua; Zheng, Dongpeng; Wang, Yifan; Man, Dong

2013-01-01

Carless young drivers refers to those drivers aged between 18 and 25 years who have a driver's license but seldom have opportunities to practice their driving skills because they do not have their own cars. Due to China's lower private car ownership, many young drivers turn into carless young drivers after licensure, and the safety issue associated with them has become a matter of great concern in China. Because few studies have examined the driving behaviors of these drivers, this study aims to utilize the Driver Behavior Questionnaire (DBQ) to investigate the self-reported driving behaviors of Chinese carless young drivers. A total of 523 Chinese carless young drivers (214 females, 309 males) with an average age of 21.91 years completed a questionnaire including the 27-item DBQ and demographics. The data were first randomized into 2 subsamples for factor analysis and then combined together for the following analyses. Both an exploratory factor analysis (EFA, n = 174) and a confirmatory factor analysis (CFA, n = 349) were performed to investigate the factor structure of the DBQ. Correlation analysis was conducted to examine the relationships between the demographics and the DBQ scales' variables. Multivariate linear regression and logistic regression were performed to investigate the prediction of the DBQ scales and crash involvement in the previous year. The EFA produced a 4-factor structure identified as errors, violations, attention lapses, and memory lapses, and the CFA revealed a good model fit after the removal of one item with a low factor loading and the permission of the error covariance between some items. The Chinese carless young drivers reported a comparatively low level of aberrant driving behaviors. The 3 most frequently reported behaviors were all lapses and the 3 least were all violations. Gender was the only significant predictor of the 2 lapses scales and lifetime mileage was the only significant predictor of the violations scale. Only the

Identifying beliefs underlying pre-drivers' intentions to take risks: An application of the Theory of Planned Behaviour.

PubMed

Rowe, Richard; Andrews, Elizabeth; Harris, Peter R; Armitage, Christopher J; McKenna, Frank P; Norman, Paul

2016-04-01

Novice motorists are at high crash risk during the first few months of driving. Risky behaviours such as speeding and driving while distracted are well-documented contributors to crash risk during this period. To reduce this public health burden, effective road safety interventions need to target the pre-driving period. We use the Theory of Planned Behaviour (TPB) to identify the pre-driver beliefs underlying intentions to drive over the speed limit (N=77), and while over the legal alcohol limit (N=72), talking on a hand-held mobile phone (N=77) and feeling very tired (N=68). The TPB explained between 41% and 69% of the variance in intentions to perform these behaviours. Attitudes were strong predictors of intentions for all behaviours. Subjective norms and perceived behavioural control were significant, though weaker, independent predictors of speeding and mobile phone use. Behavioural beliefs underlying these attitudes could be separated into those reflecting perceived disadvantages (e.g., speeding increases my risk of crash) and advantages (e.g., speeding gives me a thrill). Interventions that can make these beliefs safer in pre-drivers may reduce crash risk once independent driving has begun. Copyright © 2015 Elsevier Ltd. All rights reserved.

ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

PubMed

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

PubMed

Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

2011-10-01

Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Key drivers of airline loyalty.

PubMed

Dolnicar, Sara; Grabler, Klaus; Grün, Bettina; Kulnig, Anna

2011-10-01

This study investigates drivers of airline loyalty. It contributes to the body of knowledge in the area by investigating loyalty for a number of a priori market segments identified by airline management and by using a method which accounts for the multi-step nature of the airline choice process. The study is based on responses from 687 passengers. Results indicate that, at aggregate level, frequent flyer membership, price, the status of being a national carrier and the reputation of the airline as perceived by friends are the variables which best discriminate between travellers loyal to the airline and those who are not. Differences in drivers of airline loyalty for a number of segments were identified. For example, loyalty programs play a key role for business travellers whereas airline loyalty of leisure travellers is difficult to trace back to single factors. For none of the calculated models satisfaction emerged as a key driver of airline loyalty.

Key drivers of airline loyalty

PubMed Central

Dolnicar, Sara; Grabler, Klaus; Grün, Bettina; Kulnig, Anna

2011-01-01

This study investigates drivers of airline loyalty. It contributes to the body of knowledge in the area by investigating loyalty for a number of a priori market segments identified by airline management and by using a method which accounts for the multi-step nature of the airline choice process. The study is based on responses from 687 passengers. Results indicate that, at aggregate level, frequent flyer membership, price, the status of being a national carrier and the reputation of the airline as perceived by friends are the variables which best discriminate between travellers loyal to the airline and those who are not. Differences in drivers of airline loyalty for a number of segments were identified. For example, loyalty programs play a key role for business travellers whereas airline loyalty of leisure travellers is difficult to trace back to single factors. For none of the calculated models satisfaction emerged as a key driver of airline loyalty. PMID:27064618

Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers

USGS Publications Warehouse

Lottig, Noah R.; Tan, Pang-Ning; Wagner, Tyler; Cheruvelil, Kendra Spence; Soranno, Patricia A.; Stanley, Emily H.; Scott, Caren E.; Stow, Craig A.; Yuan, Shuai

2017-01-01

Ecology has a rich history of studying ecosystem dynamics across time and space that has been motivated by both practical management needs and the need to develop basic ideas about pattern and process in nature. In situations in which both spatial and temporal observations are available, similarities in temporal behavior among sites (i.e., synchrony) provide a means of understanding underlying processes that create patterns over space and time. We used pattern analysis algorithms and data spanning 22–25 yr from 601 lakes to ask three questions: What are the temporal patterns of lake water clarity at sub‐continental scales? What are the spatial patterns (i.e., geography) of synchrony for lake water clarity? And, what are the drivers of spatial and temporal patterns in lake water clarity? We found that the synchrony of water clarity among lakes is not spatially structured at sub‐continental scales. Our results also provide strong evidence that the drivers related to spatial patterns in water clarity are not related to the temporal patterns of water clarity. This analysis of long‐term patterns of water clarity and possible drivers contributes to understanding of broad‐scale spatial patterns in the geography of synchrony and complex relationships between spatial and temporal patterns across ecosystems.

Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

PubMed

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.

Gene Expression Profiling Combined with Bioinformatics Analysis Identify Biomarkers for Parkinson Disease

PubMed Central

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

Axon Regeneration Genes Identified by RNAi Screening in C. elegans

PubMed Central

Nix, Paola; Hammarlund, Marc; Hauth, Linda; Lachnit, Martina; Jorgensen, Erik M.

2014-01-01

Axons of the mammalian CNS lose the ability to regenerate soon after development due to both an inhibitory CNS environment and the loss of cell-intrinsic factors necessary for regeneration. The complex molecular events required for robust regeneration of mature neurons are not fully understood, particularly in vivo. To identify genes affecting axon regeneration in Caenorhabditis elegans, we performed both an RNAi-based screen for defective motor axon regeneration in unc-70/β-spectrin mutants and a candidate gene screen. From these screens, we identified at least 50 conserved genes with growth-promoting or growth-inhibiting functions. Through our analysis of mutants, we shed new light on certain aspects of regeneration, including the role of β-spectrin and membrane dynamics, the antagonistic activity of MAP kinase signaling pathways, and the role of stress in promoting axon regeneration. Many gene candidates had not previously been associated with axon regeneration and implicate new pathways of interest for therapeutic intervention. PMID:24403161

Exploratory multinomial logit model-based driver injury severity analyses for teenage and adult drivers in intersection-related crashes.

PubMed

Wu, Qiong; Zhang, Guohui; Ci, Yusheng; Wu, Lina; Tarefder, Rafiqul A; Alcántara, Adélamar Dely

2016-05-18

Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle-infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities. Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality. The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups. The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.

Identification of critical regulatory genes in cancer signaling network using controllability analysis

NASA Astrophysics Data System (ADS)

Ravindran, Vandana; Sunitha, V.; Bagler, Ganesh

2017-05-01

Cancer is characterized by a complex web of regulatory mechanisms which makes it difficult to identify features that are central to its control. Molecular integrative models of cancer, generated with the help of data from experimental assays, facilitate use of control theory to probe for ways of controlling the state of such a complex dynamic network. We modeled the human cancer signaling network as a directed graph and analyzed it for its controllability, identification of driver nodes and their characterization. We identified the driver nodes using the maximum matching algorithm and classified them as backbone, peripheral and ordinary based on their role in regulatory interactions and control of the network. We found that the backbone driver nodes were key to driving the regulatory network into cancer phenotype (via mutations) as well as for steering into healthy phenotype (as drug targets). This implies that while backbone genes could lead to cancer by virtue of mutations, they are also therapeutic targets of cancer. Further, based on their impact on the size of the set of driver nodes, genes were characterized as indispensable, dispensable and neutral. Indispensable nodes within backbone of the network emerged as central to regulatory mechanisms of control of cancer. In addition to probing the cancer signaling network from the perspective of control, our findings suggest that indispensable backbone driver nodes could be potentially leveraged as therapeutic targets. This study also illustrates the application of structural controllability for studying the mechanisms underlying the regulation of complex diseases.

Gene expression profiles analysis identifies key genes for acute lung injury in patients with sepsis.

PubMed

Guo, Zhiqiang; Zhao, Chuncheng; Wang, Zheng

2014-09-26

To identify critical genes and biological pathways in acute lung injury (ALI), a comparative analysis of gene expression profiles of patients with ALI + sepsis compared with patients with sepsis alone were performed with bioinformatic tools. GSE10474 was downloaded from Gene Expression Omnibus, including a collective of 13 whole blood samples with ALI + sepsis and 21 whole blood samples with sepsis alone. After pre-treatment with robust multichip averaging (RMA) method, differential analysis was conducted using simpleaffy package based upon t-test and fold change. Hierarchical clustering was also performed using function hclust from package stats. Beisides, functional enrichment analysis was conducted using iGepros. Moreover, the gene regulatory network was constructed with information from Kyoto Encyclopedia of Genes and Genomes (KEGG) and then visualized by Cytoscape. A total of 128 differentially expressed genes (DEGs) were identified, including 47 up- and 81 down-regulated genes. The significantly enriched functions included negative regulation of cell proliferation, regulation of response to stimulus and cellular component morphogenesis. A total of 27 DEGs were significantly enriched in 16 KEGG pathways, such as protein digestion and absorption, fatty acid metabolism, amoebiasis, etc. Furthermore, the regulatory network of these 27 DEGs was constructed, which involved several key genes, including protein tyrosine kinase 2 (PTK2), v-src avian sarcoma (SRC) and Caveolin 2 (CAV2). PTK2, SRC and CAV2 may be potential markers for diagnosis and treatment of ALI. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5865162912987143.

Portable Diagnostic Devices for Identifying Obstructive Sleep Apnea among Commercial Motor Vehicle Drivers: Considerations and Unanswered Questions

PubMed Central

Zhang, Chunbai; Berger, Mark; Malhotra, Atul; Kales, Stefanos N.

2012-01-01

Obstructive sleep apnea (OSA), a syndrome defined by breathing abnormalities during sleep, can lead to fatigue and excessive daytime sleepiness (EDS) with an increased risk of motor vehicle crashes. Identifying commercial motor vehicle operators with unrecognized OSA is a major public health priority. Portable monitors (PMs) are being actively marketed to trucking firms as potentially lower-cost and more accessible alternatives to the reference standard of in-laboratory polysomnography (PSG) in the diagnosis of OSA among commercial motor vehicle operators. Several factors regarding PMs remain uncertain in this unique patient population: their sensitivity and specificity; the cost-benefit ratio of the PMs versus PSG; potential barriers from human factors; and evolving technologic advancement. Human factors that alter test accuracy are a major concern among commercial drivers motivated to gain/maintain employment. Current available data using PMs as a diagnostic tool among CMV operators indicate relatively high data loss and high loss to follow-up. Loss to follow-up has also been an issue using PSG in commercial motor vehicle operators. Furthermore, PM testing and PM results interpretation protocols may have no sleep specialist oversight, and sometimes minimal physician oversight and involvement. Additional studies comparing unattended and unmonitored PMs directly against full in-laboratory PSG are needed to provide evidence for their efficacy among commercial motor vehicle operators. Citation: Zhang C; Berger M; Malhotra A; Kales SN. Portable diagnostic devices for identifying obstructive sleep apnea among commercial motor vehicle drivers: considerations and unanswered questions. SLEEP 2012;35(11):1481-1489. PMID:23115397

Combining Genome-Scale Experimental and Computational Methods To Identify Essential Genes in Rhodobacter sphaeroides

DOE PAGES

Burger, Brian T.; Imam, Saheed; Scarborough, Matthew J.; ...

2017-06-06

Rhodobacter sphaeroides is one of the best-studied alphaproteobacteria from biochemical, genetic, and genomic perspectives. To gain a better systems-level understanding of this organism, we generated a large transposon mutant library and used transposon sequencing (Tn-seq) to identify genes that are essential under several growth conditions. Using newly developed Tn-seq analysis software (TSAS), we identified 493 genes as essential for aerobic growth on a rich medium. We then used the mutant library to identify conditionally essential genes under two laboratory growth conditions, identifying 85 additional genes required for aerobic growth in a minimal medium and 31 additional genes required for photosyntheticmore » growth. In all instances, our analyses confirmed essentiality for many known genes and identified genes not previously considered to be essential. We used the resulting Tn-seq data to refine and improve a genome-scale metabolic network model (GEM) for R. sphaeroides. Together, we demonstrate how genetic, genomic, and computational approaches can be combined to obtain a systems-level understanding of the genetic framework underlying metabolic diversity in bacterial species.« less

A Functional Genomics Approach to Identify Novel Breast Cancer Gene Targets in Yeast

DTIC Science & Technology

2004-05-01

AD Award Number: DAMD17-03-1-0232 TITLE: A Functional Genomics Approach to Identify Novel Breast Cancer Gene Targets in Yeast PRINCIPAL INVESTIGATOR...Approach to Identify Novel Breast DAMD17-03-1-0232 Cancer Gene Targets in Yeast 6. A UTHOR(S) Craig Bennett, Ph.D. 7. PERFORMING ORGANIZA TION NAME(S...Unlimited 13. ABSTRACT (Maximum 200 Words) We are using the yeast Saccharomyces cerevisiae to identify new cancer gene targets that interact with the

Driver behaviour profiles for road safety analysis.

PubMed

Ellison, Adrian B; Greaves, Stephen P; Bliemer, Michiel C J

2015-03-01

Driver behaviour is a contributing factor in over 90 percent of road crashes. As a consequence, there is significant benefit in identifying drivers who engage in unsafe driving practices. Driver behaviour profiles (DBPs) are introduced here as an approach for evaluating driver behaviour as a function of the risk of a casualty crash. They employ data collected using global positioning system (GPS) devices, supplemented with spatiotemporal information. These profiles are comprised of common risk scores that can be used to compare drivers between each other and across time and space. The paper details the development of these DBPs and demonstrates their use as an input into modelling the factors that influence driver behaviour. The results show that even having controlled for the influence of the road environment, these factors remain the strongest predictors of driver behaviour suggesting different spatiotemporal environments elicit a variety of psychological responses in drivers. The approach and outcomes will be of interest to insurance companies in enhancing the risk-profiling of drivers with on-road driving and government through assessing the impacts of behaviour-change interventions. Copyright © 2015 Elsevier Ltd. All rights reserved.

ICan: An Integrated Co-Alteration Network to Identify Ovarian Cancer-Related Genes

PubMed Central

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Background Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. Results We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). Conclusion In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data. PMID:25803614

MMTV insertional mutagenesis identifies genes, gene families and pathways involved in mammary cancer.

PubMed

Theodorou, Vassiliki; Kimm, Melanie A; Boer, Mandy; Wessels, Lodewyk; Theelen, Wendy; Jonkers, Jos; Hilkens, John

2007-06-01

We performed a high-throughput retroviral insertional mutagenesis screen in mouse mammary tumor virus (MMTV)-induced mammary tumors and identified 33 common insertion sites, of which 17 genes were previously not known to be associated with mammary cancer and 13 had not previously been linked to cancer in general. Although members of the Wnt and fibroblast growth factors (Fgf) families were frequently tagged, our exhaustive screening for MMTV insertion sites uncovered a new repertoire of candidate breast cancer oncogenes. We validated one of these genes, Rspo3, as an oncogene by overexpression in a p53-deficient mammary epithelial cell line. The human orthologs of the candidate oncogenes were frequently deregulated in human breast cancers and associated with several tumor parameters. Computational analysis of all MMTV-tagged genes uncovered specific gene families not previously associated with cancer and showed a significant overrepresentation of protein domains and signaling pathways mainly associated with development and growth factor signaling. Comparison of all tagged genes in MMTV and Moloney murine leukemia virus-induced malignancies showed that both viruses target mostly different genes that act predominantly in distinct pathways.

Identifying Mendelian disease genes with the Variant Effect Scoring Tool

PubMed Central

2013-01-01

Background Whole exome sequencing studies identify hundreds to thousands of rare protein coding variants of ambiguous significance for human health. Computational tools are needed to accelerate the identification of specific variants and genes that contribute to human disease. Results We have developed the Variant Effect Scoring Tool (VEST), a supervised machine learning-based classifier, to prioritize rare missense variants with likely involvement in human disease. The VEST classifier training set comprised ~ 45,000 disease mutations from the latest Human Gene Mutation Database release and another ~45,000 high frequency (allele frequency >1%) putatively neutral missense variants from the Exome Sequencing Project. VEST outperforms some of the most popular methods for prioritizing missense variants in carefully designed holdout benchmarking experiments (VEST ROC AUC = 0.91, PolyPhen2 ROC AUC = 0.86, SIFT4.0 ROC AUC = 0.84). VEST estimates variant score p-values against a null distribution of VEST scores for neutral variants not included in the VEST training set. These p-values can be aggregated at the gene level across multiple disease exomes to rank genes for probable disease involvement. We tested the ability of an aggregate VEST gene score to identify candidate Mendelian disease genes, based on whole-exome sequencing of a small number of disease cases. We used whole-exome data for two Mendelian disorders for which the causal gene is known. Considering only genes that contained variants in all cases, the VEST gene score ranked dihydroorotate dehydrogenase (DHODH) number 2 of 2253 genes in four cases of Miller syndrome, and myosin-3 (MYH3) number 2 of 2313 genes in three cases of Freeman Sheldon syndrome. Conclusions Our results demonstrate the potential power gain of aggregating bioinformatics variant scores into gene-level scores and the general utility of bioinformatics in assisting the search for disease genes in large-scale exome sequencing studies. VEST is

Gene-Based Genome-Wide Association Analysis in European and Asian Populations Identified Novel Genes for Rheumatoid Arthritis.

PubMed

Zhu, Hong; Xia, Wei; Mo, Xing-Bo; Lin, Xiang; Qiu, Ying-Hua; Yi, Neng-Jun; Zhang, Yong-Hong; Deng, Fei-Yan; Lei, Shu-Feng

2016-01-01

Rheumatoid arthritis (RA) is a complex autoimmune disease. Using a gene-based association research strategy, the present study aims to detect unknown susceptibility to RA and to address the ethnic differences in genetic susceptibility to RA between European and Asian populations. Gene-based association analyses were performed with KGG 2.5 by using publicly available large RA datasets (14,361 RA cases and 43,923 controls of European subjects, 4,873 RA cases and 17,642 controls of Asian Subjects). For the newly identified RA-associated genes, gene set enrichment analyses and protein-protein interactions analyses were carried out with DAVID and STRING version 10.0, respectively. Differential expression verification was conducted using 4 GEO datasets. The expression levels of three selected 'highly verified' genes were measured by ELISA among our in-house RA cases and controls. A total of 221 RA-associated genes were newly identified by gene-based association study, including 71'overlapped', 76 'European-specific' and 74 'Asian-specific' genes. Among them, 105 genes had significant differential expressions between RA patients and health controls at least in one dataset, especially for 20 genes including 11 'overlapped' (ABCF1, FLOT1, HLA-F, IER3, TUBB, ZKSCAN4, BTN3A3, HSP90AB1, CUTA, BRD2, HLA-DMA), 5 'European-specific' (PHTF1, RPS18, BAK1, TNFRSF14, SUOX) and 4 'Asian-specific' (RNASET2, HFE, BTN2A2, MAPK13) genes whose differential expressions were significant at least in three datasets. The protein expressions of two selected genes FLOT1 (P value = 1.70E-02) and HLA-DMA (P value = 4.70E-02) in plasma were significantly different in our in-house samples. Our study identified 221 novel RA-associated genes and especially highlighted the importance of 20 candidate genes on RA. The results addressed ethnic genetic background differences for RA susceptibility between European and Asian populations and detected a long list of overlapped or ethnic specific RA genes. The

Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

PubMed

Feng, Yinling; Wang, Xuefeng

2017-03-01

In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

Driver behavior analysis for right-turn drivers at signalized intersections using SHRP 2 naturalistic driving study data.

PubMed

Wu, Jianqing; Xu, Hao

2017-12-01

Understanding driver behavior is important for traffic safety and operation, especially at intersections where different traffic movements conflict. While most driver-behavior studies are based on simulation, this paper documents the analysis of driver-behavior at signalized intersections with the SHRP 2 Naturalistic Driving Study (NDS) data. This study analyzes the different influencing factors on the operation (speed control) and observation of right-turn drivers. A total of 300 NDS trips at six signalized intersections were used, including the NDS time-series sensor data, the forward videos and driver face videos. Different factors of drivers, vehicles, roads and environments were studied for their influence on driver behavior. An influencing index function was developed and the index was calculated for each influencing factor to quantitatively describe its influencing level. The influencing index was applied to prioritize the factors, which facilitates development and selection of safety countermeasures to improve intersection safety. Drivers' speed control was analyzed under different conditions with consideration of the prioritized influencing factors. Vehicle type, traffic signal status, conflicting traffic, conflicting pedestrian and driver age group were identified as the five major influencing factors on driver observation. This research revealed that drivers have high acceleration and low observation frequency under Right-Turn-On-Red (RTOR), which constituted potential danger for other roadway users, especially for pedestrians. As speed has a direct influence on crash rates and severities, the revealed speed patterns of the different situations also benefit selection of safety countermeasures at signalized intersections. Published by Elsevier Ltd.

Identifying Candidate Reprogramming Genes in Mouse Induced Pluripotent Stem Cells.

PubMed

Gao, Fang; Li, Jingyu; Zhang, Heng; Yang, Xu; An, Tiezhu

2017-08-01

Factor-based induced reprogramming approaches have tremendous potential for human regenerative medicine, but the efficiencies of these approaches are still low. In this study, we analyzed the global transcriptional profiles of mouse induced pluripotent stem cells (miPSCs) and mouse embryonic stem cells (mESCs) from seven different labs and present here the first successful clustering according to cell type, not by lab of origin. We identified 2131 different expression genes (DEs) as candidate pluripotency-associated genes by comparing mESCs/miPSCs with somatic cells and 720 DEs between miPSCs and mESCs. Interestingly, there was a significant overlap between the two DE sets. Therefore, we defined the overlap DEs as "consensus DEs" including 313 miPSC-specific genes expressed at a higher level in miPSCs versus mESCs and 184 mESC-specific genes in total and reasoned that these may contribute to the differences in pluripotency between mESCs and miPSCs. A classification of "consensus DEs" according to their different expression levels between somatic cells and mESCs/miPSCs shows that 86% of the miPSC-specific genes are more highly expressed in somatic cells, while 73% of mESC-specific genes are highly expressed in mESCs/miPSCs, indicating that the miPSCs have not efficiently silenced the expression pattern of the somatic cells from which they are derived and failed to completely induce the genes with high expression levels in mESCs. We further revealed a strong correlation between oocyte-enriched factors and insufficiently induced mESC-specific genes and identified 11 hub genes via network analysis. In light of these findings, we postulated that these key hub genes might not only drive somatic cell nuclear transfer (SCNT) reprogramming but also augment the efficiency and quality of miPSC reprogramming.

Graduated driver license compliant teens involved in fatal motor vehicle crashes.

PubMed

Pressley, Joyce C; Addison, Diane; Dawson, Patrick; Nelson, Sharifa S

2015-09-01

Significant reductions in motor vehicle injury mortality have been reported for teen drivers after passage of graduated driver licensing (GDL), seat belt, and no tolerance alcohol and drug laws. Despite this, teen drivers remain a vulnerable population with elevated fatal crash involvement. This study examines driver, vehicle, and crash characteristics of GDL-compliant, belted, and unimpaired teen drivers with the goal of identifying areas where further improvements might be realized. The Fatality Analysis Reporting System (FARS) for 2007 to 2009 was used to examine and classify driver violations/errors in compliant teen drivers (n = 1,571) of passenger vehicles involved in a fatal collision. Teens driving unbelted, non-GDL compliant, or impaired by alcohol or drugs were excluded. Statistical analysis used χ, Fisher's exact and multivariable logistic regression. Odds ratios are reported with 95% confidence intervals. Significance was defined as p < 0.05. Nearly one third (n = 1,571) of teen drivers involved in a fatal motor vehicle crash were GDL compliant, unimpaired, and belted. The majority held an intermediate GDL license (90.6%). Crash-related factors were identified for 63.1% of fatal crashes. Age- and sex-adjusted odds identified overcorrecting, speeding, lane errors, school morning crashes, distractions, and driving on slippery surfaces as having increased odds of fatality for the teen driver as well as newer vehicle models and heavier vehicle weight as protective. Among compliant drivers, weekday crashes before and after school and committing a driving violation at the time of crash were associated with increased risk of driver death and higher incidence of incapacitating injury in surviving drivers. Therapeutic study, level V.

Acceptability and validity of older driver screening with the DrivingHealth Inventory.

PubMed

Edwards, Jerri D; Leonard, Kathleen M; Lunsman, Melissa; Dodson, Joan; Bradley, Stacy; Myers, Charlsie A; Hubble, Bridgette

2008-05-01

Research has indicated that technology can be effectively used to identify high-risk older drivers. However, adaptation of such technology has been limited. Researchers debate whether older drivers represent a safety problem as well as whether they should be screened for driving fitness. The present study examined how drivers feel regarding technological screening and mandatory state testing. The validity and acceptability of a new technological screening battery for identifying high-risk drivers, the DrivingHealth Inventory (DHI), was also evaluated. In a sample of 258 Alabama drivers aged 18-87, older drivers performed significantly worse than younger drivers on sensory, cognitive, and physical subtests of the DHI, and older drivers with a crash history performed worse than older drivers without crashes. Regardless of age, 90% of participants supported states requiring screening for older drivers' license renewal. The majority of the participants (72%) supported use of technological screening batteries such as the DHI as a driver screening tool. Considering the acceptability and potential efficacy of the DHI, it may be a useful tool in evaluating driving fitness among older adults.

Exome Sequencing Identifies Three Novel Candidate Genes Implicated in Intellectual Disability

PubMed Central

Azam, Maleeha; Ayub, Humaira; Vissers, Lisenka E. L. M.; Gilissen, Christian; Ali, Syeda Hafiza Benish; Riaz, Moeen; Veltman, Joris A.; Pfundt, Rolph; van Bokhoven, Hans; Qamar, Raheel

2014-01-01

Intellectual disability (ID) is a major health problem mostly with an unknown etiology. Recently exome sequencing of individuals with ID identified novel genes implicated in the disease. Therefore the purpose of the present study was to identify the genetic cause of ID in one syndromic and two non-syndromic Pakistani families. Whole exome of three ID probands was sequenced. Missense variations in two plausible novel genes implicated in autosomal recessive ID were identified: lysine (K)-specific methyltransferase 2B (KMT2B), zinc finger protein 589 (ZNF589), as well as hedgehog acyltransferase (HHAT) with a de novo mutation with autosomal dominant mode of inheritance. The KMT2B recessive variant is the first report of recessive Kleefstra syndrome-like phenotype. Identification of plausible causative mutations for two recessive and a dominant type of ID, in genes not previously implicated in disease, underscores the large genetic heterogeneity of ID. These results also support the viewpoint that large number of ID genes converge on limited number of common networks i.e. ZNF589 belongs to KRAB-domain zinc-finger proteins previously implicated in ID, HHAT is predicted to affect sonic hedgehog, which is involved in several disorders with ID, KMT2B associated with syndromic ID fits the epigenetic module underlying the Kleefstra syndromic spectrum. The association of these novel genes in three different Pakistani ID families highlights the importance of screening these genes in more families with similar phenotypes from different populations to confirm the involvement of these genes in pathogenesis of ID. PMID:25405613

Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits.

PubMed

Mancuso, Nicholas; Shi, Huwenbo; Goddard, Pagé; Kichaev, Gleb; Gusev, Alexander; Pasaniuc, Bogdan

2017-03-02

Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genomic characterization of pediatric T-cell acute lymphoblastic leukemia reveals novel recurrent driver mutations

PubMed Central

Spinella, Jean-François; Cassart, Pauline; Richer, Chantal; Saillour, Virginie; Ouimet, Manon; Langlois, Sylvie; St-Onge, Pascal; Sontag, Thomas; Healy, Jasmine; Minden, Mark D.; Sinnett, Daniel

2016-01-01

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy with variable prognosis. It represents 15% of diagnosed pediatric ALL cases and has a threefold higher incidence among males. Many recurrent alterations have been identified and help define molecular subgroups of T-ALL, however the full range of events involved in driving transformation remain to be defined. Using an integrative approach combining genomic and transcriptomic data, we molecularly characterized 30 pediatric T-ALLs and identified common recurrent T-ALL targets such as FBXW7, JAK1, JAK3, PHF6, KDM6A and NOTCH1 as well as novel candidate T-ALL driver mutations including the p.R35L missense mutation in splicesome factor U2AF1 found in 3 patients and loss of function mutations in the X-linked tumor suppressor genes MED12 (frameshit mutation p.V167fs, splice site mutation g.chrX:70339329T>C, missense mutation p.R1989H) and USP9X (nonsense mutation p.Q117*). In vitro functional studies further supported the putative role of these novel T-ALL genes in driving transformation. U2AF1 p.R35L was shown to induce aberrant splicing of downstream target genes, and shRNA knockdown of MED12 and USP9X was shown to confer resistance to apoptosis following T-ALL relevant chemotherapy drug treatment in Jurkat leukemia cells. Interestingly, nearly 60% of novel candidate driver events were identified among immature T-ALL cases, highlighting the underlying genomic complexity of pediatric T-ALL, and the need for larger integrative studies to decipher the mechanisms that contribute to its various subtypes and provide opportunities to refine patient stratification and treatment. PMID:27602765

Adjusting for background mutation frequency biases improves the identification of cancer driver genes.

PubMed

Evans, Perry; Avey, Stefan; Kong, Yong; Krauthammer, Michael

2013-09-01

A common goal of tumor sequencing projects is finding genes whose mutations are selected for during tumor development. This is accomplished by choosing genes that have more non-synonymous mutations than expected from an estimated background mutation frequency. While this background frequency is unknown, it can be estimated using both the observed synonymous mutation frequency and the non-synonymous to synonymous mutation ratio. The synonymous mutation frequency can be determined across all genes or in a gene-specific manner. This choice introduces an interesting trade-off. A gene-specific frequency adjusts for an underlying mutation bias, but is difficult to estimate given missing synonymous mutation counts. Using a genome-wide synonymous frequency is more robust, but is less suited for adjusting biases. Studying four evaluation criteria for identifying genes with high non-synonymous mutation burden (reflecting preferential selection of expressed genes, genes with mutations in conserved bases, genes with many protein interactions, and genes that show loss of heterozygosity), we find that the gene-specific synonymous frequency is superior in the gene expression and protein interaction tests. In conclusion, the use of the gene-specific synonymous mutation frequency is well suited for assessing a gene's non-synonymous mutation burden.

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

PubMed

Gao, Qingsong; Liang, Wen-Wei; Foltz, Steven M; Mutharasu, Gnanavel; Jayasinghe, Reyka G; Cao, Song; Liao, Wen-Wei; Reynolds, Sheila M; Wyczalkowski, Matthew A; Yao, Lijun; Yu, Lihua; Sun, Sam Q; Chen, Ken; Lazar, Alexander J; Fields, Ryan C; Wendl, Michael C; Van Tine, Brian A; Vij, Ravi; Chen, Feng; Nykter, Matti; Shmulevich, Ilya; Ding, Li

2018-04-03

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Association of Graduated Driver Licensing With Driver, Non-Driver, and Total Fatalities Among Adolescents.

PubMed

Zhu, Motao; Zhao, Songzhu; Long, D Leann; Curry, Allison E

2016-07-01

Graduated driver licensing systems typically require an extended learner permit phase, and create night-time driving or passenger restrictions for adolescent drivers. Restricted driving might increase the use of alternative transportation to replace driving and consequently increase crashes and injuries for passengers, bus riders, pedestrians, and bicyclists. This study examined whether graduated driver licensing increases non-driver fatalities among adolescents, and whether it reduces total traffic fatalities combining drivers and non-drivers. Longitudinal analyses were conducted using data from the 1995-2012 U.S. Fatality Analysis Reporting System. Adjusted rate ratios were estimated for being fatally injured in a crash according to: (1) presence/absence of a graduated driver licensing system; and (2) four levels of graduated driver licensing systems (absent, weak, medium, strong). Analyses were conducted in 2015. Among adolescents aged 16 years, graduated driver licensing was not associated with increased passenger fatalities (adjusted rate ratio, 0.96; 95% CI=0.90, 1.03) or pedestrian and bicyclist fatalities (adjusted rate ratio, 1.09; 95% CI=0.85, 1.39), but was associated with an 11% reduction in total traffic fatalities. Among those aged 17 years, graduated driver licensing was not associated with increased fatalities as passengers, pedestrians, or bicyclists, and was not associated with reduced total traffic fatalities. In general, graduated driver licensing systems were not associated with increased fatalities as passengers, pedestrians, bicyclists, and bus riders. Graduated driver licensing systems were associated with reduced total fatalities of adolescents aged 16 years. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Using SCOPE to identify potential regulatory motifs in coregulated genes.

PubMed

Martyanov, Viktor; Gross, Robert H

2011-05-31

SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data. In this article, we utilize a web version of SCOPE to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs and has been used in other studies. The three algorithms that comprise SCOPE are BEAM, which finds non-degenerate motifs (ACCGGT), PRISM, which finds degenerate motifs (ASCGWT), and SPACER, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from

[Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

PubMed

Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

2012-07-01

In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

Novel Myopia Genes and Pathways Identified From Syndromic Forms of Myopia

PubMed Central

Loughman, James; Wildsoet, Christine F.; Williams, Cathy; Guggenheim, Jeremy A.

2018-01-01

Purpose To test the hypothesis that genes known to cause clinical syndromes featuring myopia also harbor polymorphisms contributing to nonsyndromic refractive errors. Methods Clinical phenotypes and syndromes that have refractive errors as a recognized feature were identified using the Online Mendelian Inheritance in Man (OMIM) database. One hundred fifty-four unique causative genes were identified, of which 119 were specifically linked with myopia and 114 represented syndromic myopia (i.e., myopia and at least one other clinical feature). Myopia was the only refractive error listed for 98 genes and hyperopia and the only refractive error noted for 28 genes, with the remaining 28 genes linked to phenotypes with multiple forms of refractive error. Pathway analysis was carried out to find biological processes overrepresented within these sets of genes. Genetic variants located within 50 kb of the 119 myopia-related genes were evaluated for involvement in refractive error by analysis of summary statistics from genome-wide association studies (GWAS) conducted by the CREAM Consortium and 23andMe, using both single-marker and gene-based tests. Results Pathway analysis identified several biological processes already implicated in refractive error development through prior GWAS analyses and animal studies, including extracellular matrix remodeling, focal adhesion, and axon guidance, supporting the research hypothesis. Novel pathways also implicated in myopia development included mannosylation, glycosylation, lens development, gliogenesis, and Schwann cell differentiation. Hyperopia was found to be linked to a different pattern of biological processes, mostly related to organogenesis. Comparison with GWAS findings further confirmed that syndromic myopia genes were enriched for genetic variants that influence refractive errors in the general population. Gene-based analyses implicated 21 novel candidate myopia genes (ADAMTS18, ADAMTS2, ADAMTSL4, AGK, ALDH18A1, ASXL1, COL4A1

Expression profiling identifies novel Hh/Gli regulated genes in developing zebrafish embryos.

PubMed Central

Bergeron, Sadie A.; Milla, Luis A.; Villegas, Rosario; Shen, Meng-Chieh; Burgess, Shawn M.; Allende, Miguel L.; Karlstrom, Rolf O.; Palma, Verónica

2008-01-01

The Hedgehog (Hh) signaling pathway plays critical instructional roles during embryonic development. Mis-regulation of Hh/Gli signaling is a major causative factor in human congenital disorders and in a variety of cancers. The zebrafish is a powerful genetic model for the study of Hh signaling during embryogenesis, as a large number of mutants have been identified affecting different components of the Hh/Gli signaling system. By performing global profiling of gene expression in different Hh/Gli gain- and loss-of-function scenarios we identified several known (e.g. ptc1 and nkx2.2a) as well as a large number of novel Hh regulated genes that are differentially expressed in embryos with altered Hh/Gli signaling function. By uncovering changes in tissue specific gene expression, we revealed new embryological processes that are influenced by Hh signaling. We thus provide a comprehensive survey of Hh/Gli regulated genes during embryogenesis and we identify new Hh-regulated genes that may be targets of mis-regulation during tumorogenesis. PMID:18055165

Identifying Stress Transcription Factors Using Gene Expression and TF-Gene Association Data

PubMed Central

Wu, Wei-Sheng; Chen, Bor-Sen

2007-01-01

Unicellular organisms such as yeasts have evolved to survive environmental stresses by rapidly reorganizing the genomic expression program to meet the challenges of harsh environments. The complex adaptation mechanisms to stress remain to be elucidated. In this study, we developed Stress Transcription Factor Identification Algorithm (STFIA), which integrates gene expression and TF-gene association data to identify the stress transcription factors (TFs) of six kinds of stresses. We identified some general stress TFs that are in response to various stresses, and some specific stress TFs that are in response to one specific stress. The biological significance of our findings is validated by the literature. We found that a small number of TFs may be sufficient to control a wide variety of expression patterns in yeast under different stresses. Two implications can be inferred from this observation. First, the adaptation mechanisms to different stresses may have a bow-tie structure. Second, there may exist extensive regulatory cross-talk among different stress responses. In conclusion, this study proposes a network of the regulators of stress responses and their mechanism of action. PMID:20066130

Older Driver and Passenger Collaboration for Wayfinding in Unfamiliar Areas

ERIC Educational Resources Information Center

Bryden, Kelly Jane; Charlton, Judith; Oxley, Jennifer; Lowndes, Georgia

2014-01-01

Passenger collaboration offers a potential compensatory strategy to assist older drivers who have difficulty driving in unfamiliar areas (wayfinding). This article describes a survey of 194 healthy, community-dwelling older drivers and their regular passengers to investigate how passengers assist drivers, and to identify the characteristics of…

GeneCOST: a novel scoring-based prioritization framework for identifying disease causing genes.

PubMed

Ozer, Bugra; Sağıroğlu, Mahmut; Demirci, Hüseyin

2015-11-15

Due to the big data produced by next-generation sequencing studies, there is an evident need for methods to extract the valuable information gathered from these experiments. In this work, we propose GeneCOST, a novel scoring-based method to evaluate every gene for their disease association. Without any prior filtering and any prior knowledge, we assign a disease likelihood score to each gene in correspondence with their variations. Then, we rank all genes based on frequency, conservation, pedigree and detailed variation information to find out the causative reason of the disease state. We demonstrate the usage of GeneCOST with public and real life Mendelian disease cases including recessive, dominant, compound heterozygous and sporadic models. As a result, we were able to identify causative reason behind the disease state in top rankings of our list, proving that this novel prioritization framework provides a powerful environment for the analysis in genetic disease studies alternative to filtering-based approaches. GeneCOST software is freely available at www.igbam.bilgem.tubitak.gov.tr/en/softwares/genecost-en/index.html. buozer@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Pathway-driven gene stability selection of two rheumatoid arthritis GWAS identifies and validates new susceptibility genes in receptor mediated signalling pathways.

PubMed

Eleftherohorinou, Hariklia; Hoggart, Clive J; Wright, Victoria J; Levin, Michael; Coin, Lachlan J M

2011-09-01

Rheumatoid arthritis (RA) is the commonest chronic, systemic, inflammatory disorder affecting ∼1% of the world population. It has a strong genetic component and a growing number of associated genes have been discovered in genome-wide association studies (GWAS), which nevertheless only account for 23% of the total genetic risk. We aimed to identify additional susceptibility loci through the analysis of GWAS in the context of biological function. We bridge the gap between pathway and gene-oriented analyses of GWAS, by introducing a pathway-driven gene stability-selection methodology that identifies potential causal genes in the top-associated disease pathways that may be driving the pathway association signals. We analysed the WTCCC and the NARAC studies of ∼5000 and ∼2000 subjects, respectively. We examined 700 pathways comprising ∼8000 genes. Ranking pathways by significance revealed that the NARAC top-ranked ∼6% laid within the top 10% of WTCCC. Gene selection on those pathways identified 58 genes in WTCCC and 61 in NARAC; 21 of those were common (P(overlap)< 10(-21)), of which 16 were novel discoveries. Among the identified genes, we validated 10 known RA associations in WTCCC and 13 in NARAC, not discovered using single-SNP approaches on the same data. Gene ontology functional enrichment analysis on the identified genes showed significant over-representation of signalling activity (P< 10(-29)) in both studies. Our findings suggest a novel model of RA genetic predisposition, which involves cell-membrane receptors and genes in second messenger signalling systems, in addition to genes that regulate immune responses, which have been the focus of interest previously.

Use of RNA-seq to identify cardiac genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy

PubMed Central

Friedenberg, Steven G.; Chdid, Lhoucine; Keene, Bruce; Sherry, Barbara; Motsinger-Reif, Alison; Meurs, Kathryn M.

2017-01-01

OBJECTIVE To identify cardiac tissue genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy (DCM). ANIMALS 8 dogs with and 5 dogs without DCM. PROCEDURES Following euthanasia, samples of left ventricular myocardium were collected from each dog. Total RNA was extracted from tissue samples, and RNA sequencing was performed on each sample. Samples from dogs with and without DCM were grouped to identify genes that were differentially regulated between the 2 populations. Overrepresentation analysis was performed on upregulated and downregulated gene sets to identify altered molecular pathways in dogs with DCM. RESULTS Genes involved in cellular energy metabolism, especially metabolism of carbohydrates and fats, were significantly downregulated in dogs with DCM. Expression of cardiac structural proteins was also altered in affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that RNA sequencing may provide important insights into the pathogenesis of DCM in dogs and highlight pathways that should be explored to identify causative mutations and develop novel therapeutic interventions. PMID:27347821

Use of RNA-seq to identify cardiac genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy.

PubMed

Friedenberg, Steven G; Chdid, Lhoucine; Keene, Bruce; Sherry, Barbara; Motsinger-Reif, Alison; Meurs, Kathryn M

2016-07-01

OBJECTIVE To identify cardiac tissue genes and gene pathways differentially expressed between dogs with and without dilated cardiomyopathy (DCM). ANIMALS 8 dogs with and 5 dogs without DCM. PROCEDURES Following euthanasia, samples of left ventricular myocardium were collected from each dog. Total RNA was extracted from tissue samples, and RNA sequencing was performed on each sample. Samples from dogs with and without DCM were grouped to identify genes that were differentially regulated between the 2 populations. Overrepresentation analysis was performed on upregulated and downregulated gene sets to identify altered molecular pathways in dogs with DCM. RESULTS Genes involved in cellular energy metabolism, especially metabolism of carbohydrates and fats, were significantly downregulated in dogs with DCM. Expression of cardiac structural proteins was also altered in affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that RNA sequencing may provide important insights into the pathogenesis of DCM in dogs and highlight pathways that should be explored to identify causative mutations and develop novel therapeutic interventions.

Obstructive sleep apnea in North American commercial drivers.

PubMed

Kales, Stefanos N; Straubel, Madeleine G

2014-01-01

The most common medical cause of excessive daytime sleepiness (EDS) is obstructive sleep apnea (OSA). Specifically, among an estimated 14 million US commercial drivers, 17-28% or 2.4 to 3.9 million are expected to have OSA. Based on existing epidemiologic evidence, most of these drivers are undiagnosed and not adequately treated. Untreated OSA increases the risk of vehicular crashes as documented in multiple independent studies and by meta-analysis. Therefore, identifying commercial drivers with OSA and having them effectively treated should decrease crash-related fatalities and injuries. Several strategies are available for screening and identifying drivers with OSA. The simplest and most effective objective strategies use body mass index (BMI) cutoffs for obesity. Functional screens are promising adjuncts to other objective tests. The most effective approach will likely be a combination of a good questionnaire; BMI measures; and a careful physician-obtained history complemented by a functional screen.

Whole-Genome Sequencing of Sordaria macrospora Mutants Identifies Developmental Genes.

PubMed

Nowrousian, Minou; Teichert, Ines; Masloff, Sandra; Kück, Ulrich

2012-02-01

The study of mutants to elucidate gene functions has a long and successful history; however, to discover causative mutations in mutants that were generated by random mutagenesis often takes years of laboratory work and requires previously generated genetic and/or physical markers, or resources like DNA libraries for complementation. Here, we present an alternative method to identify defective genes in developmental mutants of the filamentous fungus Sordaria macrospora through Illumina/Solexa whole-genome sequencing. We sequenced pooled DNA from progeny of crosses of three mutants and the wild type and were able to pinpoint the causative mutations in the mutant strains through bioinformatics analysis. One mutant is a spore color mutant, and the mutated gene encodes a melanin biosynthesis enzyme. The causative mutation is a G to A change in the first base of an intron, leading to a splice defect. The second mutant carries an allelic mutation in the pro41 gene encoding a protein essential for sexual development. In the mutant, we detected a complex pattern of deletion/rearrangements at the pro41 locus. In the third mutant, a point mutation in the stop codon of a transcription factor-encoding gene leads to the production of immature fruiting bodies. For all mutants, transformation with a wild type-copy of the affected gene restored the wild-type phenotype. Our data demonstrate that whole-genome sequencing of mutant strains is a rapid method to identify developmental genes in an organism that can be genetically crossed and where a reference genome sequence is available, even without prior mapping information.

Whole-Genome Sequencing of Sordaria macrospora Mutants Identifies Developmental Genes

PubMed Central

Nowrousian, Minou; Teichert, Ines; Masloff, Sandra; Kück, Ulrich

2012-01-01

The study of mutants to elucidate gene functions has a long and successful history; however, to discover causative mutations in mutants that were generated by random mutagenesis often takes years of laboratory work and requires previously generated genetic and/or physical markers, or resources like DNA libraries for complementation. Here, we present an alternative method to identify defective genes in developmental mutants of the filamentous fungus Sordaria macrospora through Illumina/Solexa whole-genome sequencing. We sequenced pooled DNA from progeny of crosses of three mutants and the wild type and were able to pinpoint the causative mutations in the mutant strains through bioinformatics analysis. One mutant is a spore color mutant, and the mutated gene encodes a melanin biosynthesis enzyme. The causative mutation is a G to A change in the first base of an intron, leading to a splice defect. The second mutant carries an allelic mutation in the pro41 gene encoding a protein essential for sexual development. In the mutant, we detected a complex pattern of deletion/rearrangements at the pro41 locus. In the third mutant, a point mutation in the stop codon of a transcription factor-encoding gene leads to the production of immature fruiting bodies. For all mutants, transformation with a wild type-copy of the affected gene restored the wild-type phenotype. Our data demonstrate that whole-genome sequencing of mutant strains is a rapid method to identify developmental genes in an organism that can be genetically crossed and where a reference genome sequence is available, even without prior mapping information. PMID:22384404

A general method for identifying major hybrid male sterility genes in Drosophila.

PubMed

Zeng, L W; Singh, R S

1995-10-01

The genes responsible for hybrid male sterility in species crosses are usually identified by introgressing chromosome segments, monitored by visible markers, between closely related species by continuous backcrosses. This commonly used method, however, suffers from two problems. First, it relies on the availability of markers to monitor the introgressed regions and so the portion of the genome examined is limited to the marked regions. Secondly, the introgressed regions are usually large and it is impossible to tell if the effects of the introgressed regions are the result of single (or few) major genes or many minor genes (polygenes). Here we introduce a simple and general method for identifying putative major hybrid male sterility genes which is free of these problems. In this method, the actual hybrid male sterility genes (rather than markers), or tightly linked gene complexes with large effects, are selectively introgressed from one species into the background of another species by repeated backcrosses. This is performed by selectively backcrossing heterozygous (for hybrid male sterility gene or genes) females producing fertile and sterile sons in roughly equal proportions to males of either parental species. As no marker gene is required for this procedure, this method can be used with any species pairs that produce unisexual sterility. With the application of this method, a small X chromosome region of Drosophila mauritiana which produces complete hybrid male sterility (aspermic testes) in the background of D. simulans was identified. Recombination analysis reveals that this region contains a second major hybrid male sterility gene linked to the forked locus located at either 62.7 +/- 0.66 map units or at the centromere region of the X chromosome of D. mauritiana.

Epidermal growth factor gene is a newly identified candidate gene for gout.

PubMed

Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

2016-08-10

Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67-0.88, Padjusted = 6.42 × 10(-3)). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations.

Using fixed-parameter and random-parameter ordered regression models to identify significant factors that affect the severity of drivers' injuries in vehicle-train collisions.

PubMed

Dabbour, Essam; Easa, Said; Haider, Murtaza

2017-10-01

This study attempts to identify significant factors that affect the severity of drivers' injuries when colliding with trains at railroad-grade crossings by analyzing the individual-specific heterogeneity related to those factors over a period of 15 years. Both fixed-parameter and random-parameter ordered regression models were used to analyze records of all vehicle-train collisions that occurred in the United States from January 1, 2001 to December 31, 2015. For fixed-parameter ordered models, both probit and negative log-log link functions were used. The latter function accounts for the fact that lower injury severity levels are more probable than higher ones. Separate models were developed for heavy and light-duty vehicles. Higher train and vehicle speeds, female, and young drivers (below the age of 21 years) were found to be consistently associated with higher severity of drivers' injuries for both heavy and light-duty vehicles. Furthermore, favorable weather, light-duty trucks (including pickup trucks, panel trucks, mini-vans, vans, and sports-utility vehicles), and senior drivers (above the age of 65 years) were found be consistently associated with higher severity of drivers' injuries for light-duty vehicles only. All other factors (e.g. air temperature, the type of warning devices, darkness conditions, and highway pavement type) were found to be temporally unstable, which may explain the conflicting findings of previous studies related to those factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Driving, navigation, and vehicular technology: experiences of older drivers and their co-pilots.

PubMed

Vrkljan, Brenda H; Polgar, Janice Miller

2007-12-01

The objective of this article is to explore relationship between older drivers and their passengers (co-pilots) and potential implications of in-vehicle navigation technology on their driving safety. Semi-structured interviews were conducted with 44 healthy, community-dwelling older adults (aged 60-83) or 22 married couples. Males identified themselves as drivers and females identified themselves as passengers (i.e., co-pilot). Findings indicate that operating a motor vehicle in older adulthood is a shared activity between drivers and passengers. Older drivers and co-pilots reported their level of interaction depended on their familiarity with their route. Navigating unfamiliar areas, particularly large urban centers, was identified as the most challenging driving situation. Participants identified their level of collaboration would increase with the advent of in-vehicle navigation technology. Safety concerns related to the use of this technology, included distraction of both drivers and passengers. Differences amongst couples in their perceptions of using this technology were linked to their level of experience with using other forms of technology. Older drivers and passengers identified working closely together when operating a motor vehicle. Further investigation into the effects of in-vehicle navigation technology on the driving safety of older drivers and their co-pilots is warranted.

RNase H As Gene Modifier, Driver of Evolution and Antiviral Defense.

PubMed

Moelling, Karin; Broecker, Felix; Russo, Giancarlo; Sunagawa, Shinichi

2017-01-01

Retroviral infections are 'mini-symbiotic' events supplying recipient cells with sequences for viral replication, including the reverse transcriptase (RT) and ribonuclease H (RNase H). These proteins and other viral or cellular sequences can provide novel cellular functions including immune defense mechanisms. Their high error rate renders RT-RNases H drivers of evolutionary innovation. Integrated retroviruses and the related transposable elements (TEs) have existed for at least 150 million years, constitute up to 80% of eukaryotic genomes and are also present in prokaryotes. Endogenous retroviruses regulate host genes, have provided novel genes including the syncytins that mediate maternal-fetal immune tolerance and can be experimentally rendered infectious again. The RT and the RNase H are among the most ancient and abundant protein folds. RNases H may have evolved from ribozymes, related to viroids, early in the RNA world, forming ribosomes, RNA replicases and polymerases. Basic RNA-binding peptides enhance ribozyme catalysis. RT and ribozymes or RNases H are present today in bacterial group II introns, the precedents of TEs. Thousands of unique RTs and RNases H are present in eukaryotes, bacteria, and viruses. These enzymes mediate viral and cellular replication and antiviral defense in eukaryotes and prokaryotes, splicing, R-loop resolvation, DNA repair. RNase H-like activities are also required for the activity of small regulatory RNAs. The retroviral replication components share striking similarities with the RNA-induced silencing complex (RISC), the prokaryotic CRISPR-Cas machinery, eukaryotic V(D)J recombination and interferon systems. Viruses supply antiviral defense tools to cellular organisms. TEs are the evolutionary origin of siRNA and miRNA genes that, through RISC, counteract detrimental activities of TEs and chromosomal instability. Moreover, piRNAs, implicated in transgenerational inheritance, suppress TEs in germ cells. Thus, virtually all known

RNase H As Gene Modifier, Driver of Evolution and Antiviral Defense

PubMed Central

Moelling, Karin; Broecker, Felix; Russo, Giancarlo; Sunagawa, Shinichi

2017-01-01

Retroviral infections are ‘mini-symbiotic’ events supplying recipient cells with sequences for viral replication, including the reverse transcriptase (RT) and ribonuclease H (RNase H). These proteins and other viral or cellular sequences can provide novel cellular functions including immune defense mechanisms. Their high error rate renders RT-RNases H drivers of evolutionary innovation. Integrated retroviruses and the related transposable elements (TEs) have existed for at least 150 million years, constitute up to 80% of eukaryotic genomes and are also present in prokaryotes. Endogenous retroviruses regulate host genes, have provided novel genes including the syncytins that mediate maternal-fetal immune tolerance and can be experimentally rendered infectious again. The RT and the RNase H are among the most ancient and abundant protein folds. RNases H may have evolved from ribozymes, related to viroids, early in the RNA world, forming ribosomes, RNA replicases and polymerases. Basic RNA-binding peptides enhance ribozyme catalysis. RT and ribozymes or RNases H are present today in bacterial group II introns, the precedents of TEs. Thousands of unique RTs and RNases H are present in eukaryotes, bacteria, and viruses. These enzymes mediate viral and cellular replication and antiviral defense in eukaryotes and prokaryotes, splicing, R-loop resolvation, DNA repair. RNase H-like activities are also required for the activity of small regulatory RNAs. The retroviral replication components share striking similarities with the RNA-induced silencing complex (RISC), the prokaryotic CRISPR-Cas machinery, eukaryotic V(D)J recombination and interferon systems. Viruses supply antiviral defense tools to cellular organisms. TEs are the evolutionary origin of siRNA and miRNA genes that, through RISC, counteract detrimental activities of TEs and chromosomal instability. Moreover, piRNAs, implicated in transgenerational inheritance, suppress TEs in germ cells. Thus, virtually all

Whole exome sequencing identifies novel candidate genes that modify chronic obstructive pulmonary disease susceptibility.

PubMed

Bruse, Shannon; Moreau, Michael; Bromberg, Yana; Jang, Jun-Ho; Wang, Nan; Ha, Hongseok; Picchi, Maria; Lin, Yong; Langley, Raymond J; Qualls, Clifford; Klensney-Tait, Julia; Zabner, Joseph; Leng, Shuguang; Mao, Jenny; Belinsky, Steven A; Xing, Jinchuan; Nyunoya, Toru

2016-01-07

Chronic obstructive pulmonary disease (COPD) is characterized by an irreversible airflow limitation in response to inhalation of noxious stimuli, such as cigarette smoke. However, only 15-20 % smokers manifest COPD, suggesting a role for genetic predisposition. Although genome-wide association studies have identified common genetic variants that are associated with susceptibility to COPD, effect sizes of the identified variants are modest, as is the total heritability accounted for by these variants. In this study, an extreme phenotype exome sequencing study was combined with in vitro modeling to identify COPD candidate genes. We performed whole exome sequencing of 62 highly susceptible smokers and 30 exceptionally resistant smokers to identify rare variants that may contribute to disease risk or resistance to COPD. This was a cross-sectional case-control study without therapeutic intervention or longitudinal follow-up information. We identified candidate genes based on rare variant analyses and evaluated exonic variants to pinpoint individual genes whose function was computationally established to be significantly different between susceptible and resistant smokers. Top scoring candidate genes from these analyses were further filtered by requiring that each gene be expressed in human bronchial epithelial cells (HBECs). A total of 81 candidate genes were thus selected for in vitro functional testing in cigarette smoke extract (CSE)-exposed HBECs. Using small interfering RNA (siRNA)-mediated gene silencing experiments, we showed that silencing of several candidate genes augmented CSE-induced cytotoxicity in vitro. Our integrative analysis through both genetic and functional approaches identified two candidate genes (TACC2 and MYO1E) that augment cigarette smoke (CS)-induced cytotoxicity and, potentially, COPD susceptibility.

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Genes Important for Schizosaccharomyces pombe Meiosis Identified Through a Functional Genomics Screen

PubMed Central

Blyth, Julie; Makrantoni, Vasso; Barton, Rachael E.; Spanos, Christos; Rappsilber, Juri; Marston, Adele L.

2018-01-01

Meiosis is a specialized cell division that generates gametes, such as eggs and sperm. Errors in meiosis result in miscarriages and are the leading cause of birth defects; however, the molecular origins of these defects remain unknown. Studies in model organisms are beginning to identify the genes and pathways important for meiosis, but the parts list is still poorly defined. Here we present a comprehensive catalog of genes important for meiosis in the fission yeast, Schizosaccharomyces pombe. Our genome-wide functional screen surveyed all nonessential genes for roles in chromosome segregation and spore formation. Novel genes important at distinct stages of the meiotic chromosome segregation and differentiation program were identified. Preliminary characterization implicated three of these genes in centrosome/spindle pole body, centromere, and cohesion function. Our findings represent a near-complete parts list of genes important for meiosis in fission yeast, providing a valuable resource to advance our molecular understanding of meiosis. PMID:29259000

Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes.

PubMed

Sveen, A; Kilpinen, S; Ruusulehto, A; Lothe, R A; Skotheim, R I

2016-05-12

Alternative splicing is a widespread process contributing to structural transcript variation and proteome diversity. In cancer, the splicing process is commonly disrupted, resulting in both functional and non-functional end-products. Cancer-specific splicing events are known to contribute to disease progression; however, the dysregulated splicing patterns found on a genome-wide scale have until recently been less well-studied. In this review, we provide an overview of aberrant RNA splicing and its regulation in cancer. We then focus on the executors of the splicing process. Based on a comprehensive catalog of splicing factor encoding genes and analyses of available gene expression and somatic mutation data, we identify cancer-associated patterns of dysregulation. Splicing factor genes are shown to be significantly differentially expressed between cancer and corresponding normal samples, and to have reduced inter-individual expression variation in cancer. Furthermore, we identify enrichment of predicted cancer-critical genes among the splicing factors. In addition to previously described oncogenic splicing factor genes, we propose 24 novel cancer-critical splicing factors predicted from somatic mutations.

Targeted next generation sequencing of mucosal melanomas identifies frequent NF1 and RAS mutations.

PubMed

Cosgarea, Ioana; Ugurel, Selma; Sucker, Antje; Livingstone, Elisabeth; Zimmer, Lisa; Ziemer, Mirjana; Utikal, Jochen; Mohr, Peter; Pfeiffer, Christiane; Pföhler, Claudia; Hillen, Uwe; Horn, Susanne; Schadendorf, Dirk; Griewank, Klaus G; Roesch, Alexander

2017-06-20

Mucosal melanoma represents ~1% of all melanomas, frequently having a poor prognosis due to diagnosis at a late stage of disease. Mucosal melanoma differs from cutaneous melanoma not only in terms of poorer clinical outcome but also on the molecular level having e.g. less BRAF and more frequent KIT mutations than cutaneous melanomas. For the majority of mucosal melanomas oncogenic driver mutations remain unknown. In our study, 75 tumor tissues from patients diagnosed with mucosal melanoma were analyzed, applying a targeted next generation sequencing panel covering 29 known recurrently mutated genes in melanoma. NF1 and RAS mutations were identified as the most frequently mutated genes occurring in 18.3% and 16.9% of samples, respectively. Mutations in BRAF were identified in 8.4% and KIT in 7.0% of tumor samples. Our study identifies NF1 as the most frequently occurring driver mutation in mucosal melanoma. RAS alterations, consisting of NRAS and KRAS mutations, were the second most frequent mutation type. BRAF and KIT mutations were rare with frequencies below 10% each. Our data indicate that in mucosal melanomas RAS/NF1 alterations are frequent, implying a significant pathogenetic role for MAPK and potentially PI3K pathway activation in these tumors.

Targeted next generation sequencing of mucosal melanomas identifies frequent NF1 and RAS mutations

PubMed Central

Cosgarea, Ioana; Ugurel, Selma; Sucker, Antje; Livingstone, Elisabeth; Zimmer, Lisa; Ziemer, Mirjana; Utikal, Jochen; Mohr, Peter; Pfeiffer, Christiane; Pföhler, Claudia; Hillen, Uwe; Horn, Susanne; Schadendorf, Dirk

2017-01-01

Purpose Mucosal melanoma represents ~1% of all melanomas, frequently having a poor prognosis due to diagnosis at a late stage of disease. Mucosal melanoma differs from cutaneous melanoma not only in terms of poorer clinical outcome but also on the molecular level having e.g. less BRAF and more frequent KIT mutations than cutaneous melanomas. For the majority of mucosal melanomas oncogenic driver mutations remain unknown. Experimental Design and Results In our study, 75 tumor tissues from patients diagnosed with mucosal melanoma were analyzed, applying a targeted next generation sequencing panel covering 29 known recurrently mutated genes in melanoma. NF1 and RAS mutations were identified as the most frequently mutated genes occurring in 18.3% and 16.9% of samples, respectively. Mutations in BRAF were identified in 8.4% and KIT in 7.0% of tumor samples. Conclusions Our study identifies NF1 as the most frequently occurring driver mutation in mucosal melanoma. RAS alterations, consisting of NRAS and KRAS mutations, were the second most frequent mutation type. BRAF and KIT mutations were rare with frequencies below 10% each. Our data indicate that in mucosal melanomas RAS/NF1 alterations are frequent, implying a significant pathogenetic role for MAPK and potentially PI3K pathway activation in these tumors. PMID:28380455

Microarray and differential display identify genes involved in jasmonate-dependent anther development.

PubMed

Mandaokar, Ajin; Kumar, V Dinesh; Amway, Matt; Browse, John

2003-07-01

Jasmonate (JA) is a signaling compound essential for anther development and pollen fertility in Arabidopsis. Mutations that block the pathway of JA synthesis result into male sterility. To understand the processes of anther and pollen maturation, we used microarray and differential display approaches to compare gene expression pattern in anthers of wild-type Arabidopsis and the male-sterile mutant, opr3. Microarray experiment revealed 25 genes that were up-regulated more than 1.8-fold in wild-type anthers as compared to mutant anthers. Experiments based on differential display identified 13 additional genes up-regulated in wild-type anthers compared to opr3 for a total of 38 differentially expressed genes. Searches of the Arabidopsis and non-redundant databases disclosed known or likely functions for 28 of the 38 genes identified, while 10 genes encode proteins of unknown function. Northern blot analysis of eight representative clones as probes confirmed low expression in opr3 anthers compared with wild-type anthers. JA responsiveness of these same genes was also investigated by northern blot analysis of anther RNA isolated from wild-type and opr3 plants, In these experiments, four genes were induced in opr3 anthers within 0.5-1 h of JA treatment while the remaining genes were up-regulated only 1-8 h after JA application. None of these genes was induced by JA in anthers of the coil mutant that is deficient in JA responsiveness. The four early-induced genes in opr3 encode lipoxygenase, a putative bHLH transcription factor, epithiospecifier protein and an unknown protein. We propose that these and other early components may be involved in JA signaling and in the initiation of developmental processes. The four late genes encode an extensin-like protein, a peptide transporter and two unknown proteins, which may represent components required later in anther and pollen maturation. Transcript profiling has provided a successful approach to identify genes involved in

Lentiviral vector-based insertional mutagenesis identifies genes associated with liver cancer

PubMed Central

Ranzani, Marco; Cesana, Daniela; Bartholomae, Cynthia C.; Sanvito, Francesca; Pala, Mauro; Benedicenti, Fabrizio; Gallina, Pierangela; Sergi, Lucia Sergi; Merella, Stefania; Bulfone, Alessandro; Doglioni, Claudio; von Kalle, Christof; Kim, Yoon Jun; Schmidt, Manfred; Tonon, Giovanni; Naldini, Luigi; Montini, Eugenio

2013-01-01

Transposons and γ-retroviruses have been efficiently used as insertional mutagens in different tissues to identify molecular culprits of cancer. However, these systems are characterized by recurring integrations that accumulate in tumor cells, hampering the identification of early cancer-driving events amongst bystander and progression-related events. We developed an insertional mutagenesis platform based on lentiviral vectors (LVV) by which we could efficiently induce hepatocellular carcinoma (HCC) in 3 different mouse models. By virtue of LVV’s replication-deficient nature and broad genome-wide integration pattern, LVV-based insertional mutagenesis allowed identification of 4 new liver cancer genes from a limited number of integrations. We validated the oncogenic potential of all the identified genes in vivo, with different levels of penetrance. Our newly identified cancer genes are likely to play a role in human disease, since they are upregulated and/or amplified/deleted in human HCCs and can predict clinical outcome of patients. PMID:23314173

Integrated data analysis reveals potential drivers and pathways disrupted by DNA methylation in papillary thyroid carcinomas.

PubMed

Beltrami, Caroline Moraes; Dos Reis, Mariana Bisarro; Barros-Filho, Mateus Camargo; Marchi, Fabio Albuquerque; Kuasne, Hellen; Pinto, Clóvis Antônio Lopes; Ambatipudi, Srikant; Herceg, Zdenko; Kowalski, Luiz Paulo; Rogatto, Silvia Regina

2017-01-01

Papillary thyroid carcinoma (PTC) is a common endocrine neoplasm with a recent increase in incidence in many countries. Although PTC has been explored by gene expression and DNA methylation studies, the regulatory mechanisms of the methylation on the gene expression was poorly clarified. In this study, DNA methylation profile (Illumina HumanMethylation 450K) of 41 PTC paired with non-neoplastic adjacent tissues (NT) was carried out to identify and contribute to the elucidation of the role of novel genic and intergenic regions beyond those described in the promoter and CpG islands (CGI). An integrative and cross-validation analysis were performed aiming to identify molecular drivers and pathways that are PTC-related. The comparisons between PTC and NT revealed 4995 methylated probes (88% hypomethylated in PTC) and 1446 differentially expressed transcripts cross-validated by the The Cancer Genome Atlas data. The majority of these probes was found in non-promoters regions, distant from CGI and enriched by enhancers. The integrative analysis between gene expression and DNA methylation revealed 185 and 38 genes (mainly in the promoter and body regions, respectively) with negative and positive correlation, respectively. Genes showing negative correlation underlined FGF and retinoic acid signaling as critical canonical pathways disrupted by DNA methylation in PTC. BRAF mutation was detected in 68% (28 of 41) of the tumors, which presented a higher level of demethylation (95% hypomethylated probes) compared with BRAF wild-type tumors. A similar integrative analysis uncovered 40 of 254 differentially expressed genes, which are potentially regulated by DNA methylation in BRAF V600E-positive tumors. The methylation and expression pattern of six selected genes ( ERBB3 , FGF1 , FGFR2 , GABRB2 , HMGA2 , and RDH5 ) were confirmed as altered by pyrosequencing and RT-qPCR. DNA methylation loss in non-promoter, poor CGI and enhancer-enriched regions was a significant event in PTC

Physics at an upgraded Fermilab proton driver

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

Geer, S.; /Fermilab

2005-07-01

In 2004 the Fermilab Long Range Planning Committee identified a new high intensity Proton Driver as an attractive option for the future, primarily motivated by the recent exciting developments in neutrino physics. Over the last few months a physics study has developed the physics case for the Fermilab Proton Driver. The potential physics opportunities are discussed.

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

PubMed

Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

2015-01-01

The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

Identifying candidate genes for Type 2 Diabetes Mellitus and obesity through gene expression profiling in multiple tissues or cells.

PubMed

Chen, Junhui; Meng, Yuhuan; Zhou, Jinghui; Zhuo, Min; Ling, Fei; Zhang, Yu; Du, Hongli; Wang, Xiaoning

2013-01-01

Type 2 Diabetes Mellitus (T2DM) and obesity have become increasingly prevalent in recent years. Recent studies have focused on identifying causal variations or candidate genes for obesity and T2DM via analysis of expression quantitative trait loci (eQTL) within a single tissue. T2DM and obesity are affected by comprehensive sets of genes in multiple tissues. In the current study, gene expression levels in multiple human tissues from GEO datasets were analyzed, and 21 candidate genes displaying high percentages of differential expression were filtered out. Specifically, DENND1B, LYN, MRPL30, POC1B, PRKCB, RP4-655J12.3, HIBADH, and TMBIM4 were identified from the T2DM-control study, and BCAT1, BMP2K, CSRNP2, MYNN, NCKAP5L, SAP30BP, SLC35B4, SP1, BAP1, GRB14, HSP90AB1, ITGA5, and TOMM5 were identified from the obesity-control study. The majority of these genes are known to be involved in T2DM and obesity. Therefore, analysis of gene expression in various tissues using GEO datasets may be an effective and feasible method to determine novel or causal genes associated with T2DM and obesity.

Applying Multivariate Adaptive Splines to Identify Genes With Expressions Varying After Diagnosis in Microarray Experiments.

PubMed

Duan, Fenghai; Xu, Ye

2017-01-01

To analyze a microarray experiment to identify the genes with expressions varying after the diagnosis of breast cancer. A total of 44 928 probe sets in an Affymetrix microarray data publicly available on Gene Expression Omnibus from 249 patients with breast cancer were analyzed by the nonparametric multivariate adaptive splines. Then, the identified genes with turning points were grouped by K-means clustering, and their network relationship was subsequently analyzed by the Ingenuity Pathway Analysis. In total, 1640 probe sets (genes) were reliably identified to have turning points along with the age at diagnosis in their expression profiling, of which 927 expressed lower after turning points and 713 expressed higher after the turning points. K-means clustered them into 3 groups with turning points centering at 54, 62.5, and 72, respectively. The pathway analysis showed that the identified genes were actively involved in various cancer-related functions or networks. In this article, we applied the nonparametric multivariate adaptive splines method to a publicly available gene expression data and successfully identified genes with expressions varying before and after breast cancer diagnosis.

TGMI: an efficient algorithm for identifying pathway regulators through evaluation of triple-gene mutual interaction

PubMed Central

Gunasekara, Chathura; Zhang, Kui; Deng, Wenping; Brown, Laura

2018-01-01

Abstract Despite their important roles, the regulators for most metabolic pathways and biological processes remain elusive. Presently, the methods for identifying metabolic pathway and biological process regulators are intensively sought after. We developed a novel algorithm called triple-gene mutual interaction (TGMI) for identifying these regulators using high-throughput gene expression data. It first calculated the regulatory interactions among triple gene blocks (two pathway genes and one transcription factor (TF)), using conditional mutual information, and then identifies significantly interacted triple genes using a newly identified novel mutual interaction measure (MIM), which was substantiated to reflect strengths of regulatory interactions within each triple gene block. The TGMI calculated the MIM for each triple gene block and then examined its statistical significance using bootstrap. Finally, the frequencies of all TFs present in all significantly interacted triple gene blocks were calculated and ranked. We showed that the TFs with higher frequencies were usually genuine pathway regulators upon evaluating multiple pathways in plants, animals and yeast. Comparison of TGMI with several other algorithms demonstrated its higher accuracy. Therefore, TGMI will be a valuable tool that can help biologists to identify regulators of metabolic pathways and biological processes from the exploded high-throughput gene expression data in public repositories. PMID:29579312

The effect of the learner license Graduated Driver Licensing components on teen drivers' crashes.

PubMed

Ehsani, Johnathon Pouya; Bingham, C Raymond; Shope, Jean T

2013-10-01

Most studies evaluating the effectiveness of Graduated Driver Licensing (GDL) have focused on the overall system. Studies examining individual components have rarely accounted for the confounding of multiple, simultaneously implemented components. The purpose of this paper is to quantify the effects of a required learner license duration and required hours of supervised driving on teen driver fatal crashes. States that introduced a single GDL component independent of any other during the period 1990-2009 were identified. Monthly and quarterly fatal crash rates per 100,000 population of 16- and 17-year-old drivers were analyzed using single-state time series analysis, adjusting for adult crash rates and gasoline prices. Using the parameter estimates from each state's time series model, the pooled effect of each GDL component on 16- and 17-year-old drivers' fatal crashes was estimated using a random effects meta-analytic model to combine findings across states. In three states, a six-month minimum learner license duration was associated with a significant decline in combined 16- and 17-year-old drivers' fatal crash rates. The pooled effect of the minimum learner license duration across all states in the sample was associated with a significant change in combined 16- and 17-year-old driver fatal crash rates of -.07 (95% Confidence Interval [CI] -.11, -.03). Following the introduction of 30 h of required supervised driving in one state, novice drivers' fatal crash rates increased 35%. The pooled effect across all states in the study sample of having a supervised driving hour requirement was not significantly different from zero (.04, 95% CI -.15, .22). These findings suggest that a learner license duration of at least six-months may be necessary to achieve a significant decline in teen drivers' fatal crash rates. Evidence of the effect of required hours of supervised driving on teen drivers' fatal crash rates was mixed. Copyright © 2013 Elsevier Ltd. All rights

Epidermal growth factor gene is a newly identified candidate gene for gout

PubMed Central

Han, Lin; Cao, Chunwei; Jia, Zhaotong; Liu, Shiguo; Liu, Zhen; Xin, Ruosai; Wang, Can; Li, Xinde; Ren, Wei; Wang, Xuefeng; Li, Changgui

2016-01-01

Chromosome 4q25 has been identified as a genomic region associated with gout. However, the associations of gout with the genes in this region have not yet been confirmed. Here, we performed two-stage analysis to determine whether variations in candidate genes in the 4q25 region are associated with gout in a male Chinese Han population. We first evaluated 96 tag single nucleotide polymorphisms (SNPs) in eight inflammatory/immune pathway- or glucose/lipid metabolism-related genes in the 4q25 region in 480 male gout patients and 480 controls. The SNP rs12504538, located in the elongation of very-long-chain-fatty-acid-like family member 6 gene (Elovl6), was found to be associated with gout susceptibility (Padjusted = 0.00595). In the second stage of analysis, we performed fine mapping analysis of 93 tag SNPs in Elovl6 and in the epidermal growth factor gene (EGF) and its flanking regions in 1017 male patients gout and 1897 healthy male controls. We observed a significant association between the T allele of EGF rs2298999 and gout (odds ratio = 0.77, 95% confidence interval = 0.67–0.88, Padjusted = 6.42 × 10−3). These results provide the first evidence for an association between the EGF rs2298999 C/T polymorphism and gout. Our findings should be validated in additional populations. PMID:27506295

Novel recurrently mutated genes in African American colon cancers.

PubMed

Guda, Kishore; Veigl, Martina L; Varadan, Vinay; Nosrati, Arman; Ravi, Lakshmeswari; Lutterbaugh, James; Beard, Lydia; Willson, James K V; Sedwick, W David; Wang, Zhenghe John; Molyneaux, Neil; Miron, Alexander; Adams, Mark D; Elston, Robert C; Markowitz, Sanford D; Willis, Joseph E

2015-01-27

We used whole-exome and targeted sequencing to characterize somatic mutations in 103 colorectal cancers (CRC) from African Americans, identifying 20 new genes as significantly mutated in CRC. Resequencing 129 Caucasian derived CRCs confirmed a 15-gene set as a preferential target for mutations in African American CRCs. Two predominant genes, ephrin type A receptor 6 (EPHA6) and folliculin (FLCN), with mutations exclusive to African American CRCs, are by genetic and biological criteria highly likely African American CRC driver genes. These previously unsuspected differences in the mutational landscapes of CRCs arising among individuals of different ethnicities have potential to impact on broader disparities in cancer behaviors.

Driver distraction and driver inattention: definition, relationship and taxonomy.

PubMed

Regan, Michael A; Hallett, Charlene; Gordon, Craig P

2011-09-01

There is accumulating evidence that driver distraction and driver inattention are leading causes of vehicle crashes and incidents. However, as applied psychological constructs, they have been inconsistently defined and the relationship between them remains unclear. In this paper, driver distraction and driver inattention are defined and a taxonomy is presented in which driver distraction is distinguished from other forms of driver inattention. The taxonomy and the definitions provided are intended (a) to provide a common framework for coding different forms of driver inattention as contributing factors in crashes and incidents, so that comparable estimates of their role as contributing factors can be made across different studies, and (b) to make it possible to more accurately interpret and compare, across studies, the research findings for a given form of driver inattention. Copyright © 2011 Elsevier Ltd. All rights reserved.

Identifying the genes of unconventional high temperature superconductors.

PubMed

Hu, Jiangping

We elucidate a recently emergent framework in unifying the two families of high temperature (high [Formula: see text]) superconductors, cuprates and iron-based superconductors. The unification suggests that the latter is simply the counterpart of the former to realize robust extended s-wave pairing symmetries in a square lattice. The unification identifies that the key ingredients (gene) of high [Formula: see text] superconductors is a quasi two dimensional electronic environment in which the d -orbitals of cations that participate in strong in-plane couplings to the p -orbitals of anions are isolated near Fermi energy. With this gene, the superexchange magnetic interactions mediated by anions could maximize their contributions to superconductivity. Creating the gene requires special arrangements between local electronic structures and crystal lattice structures. The speciality explains why high [Formula: see text] superconductors are so rare. An explicit prediction is made to realize high [Formula: see text] superconductivity in Co/Ni-based materials with a quasi two dimensional hexagonal lattice structure formed by trigonal bipyramidal complexes.

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

PubMed Central

Mäkinen, Ville-Petteri; Civelek, Mete; Meng, Qingying; Zhang, Bin; Zhu, Jun; Levian, Candace; Huan, Tianxiao; Segrè, Ayellet V.; Ghosh, Sujoy; Vivar, Juan; Nikpay, Majid; Stewart, Alexandre F. R.; Nelson, Christopher P.; Willenborg, Christina; Erdmann, Jeanette; Blakenberg, Stefan; O'Donnell, Christopher J.; März, Winfried; Laaksonen, Reijo; Epstein, Stephen E.; Kathiresan, Sekar; Shah, Svati H.; Hazen, Stanley L.; Reilly, Muredach P.; Lusis, Aldons J.; Samani, Nilesh J.; Schunkert, Heribert; Quertermous, Thomas; McPherson, Ruth; Yang, Xia; Assimes, Themistocles L.

2014-01-01

The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions. PMID:25033284

Combining gene expression and genetic analyses to identify candidate genes involved in cold responses in pea.

PubMed

Legrand, Sylvain; Marque, Gilles; Blassiau, Christelle; Bluteau, Aurélie; Canoy, Anne-Sophie; Fontaine, Véronique; Jaminon, Odile; Bahrman, Nasser; Mautord, Julie; Morin, Julie; Petit, Aurélie; Baranger, Alain; Rivière, Nathalie; Wilmer, Jeroen; Delbreil, Bruno; Lejeune-Hénaut, Isabelle

2013-09-01

Cold stress affects plant growth and development. In order to better understand the responses to cold (chilling or freezing tolerance), we used two contrasted pea lines. Following a chilling period, the Champagne line becomes tolerant to frost whereas the Terese line remains sensitive. Four suppression subtractive hybridisation libraries were obtained using mRNAs isolated from pea genotypes Champagne and Terese. Using quantitative polymerase chain reaction (qPCR) performed on 159 genes, 43 and 54 genes were identified as differentially expressed at the initial time point and during the time course study, respectively. Molecular markers were developed from the differentially expressed genes and were genotyped on a population of 164 RILs derived from a cross between Champagne and Terese. We identified 5 candidate genes colocalizing with 3 different frost damage quantitative trait loci (QTL) intervals and a protein quantity locus (PQL) rich region previously reported. This investigation revealed the role of constitutive differences between both genotypes in the cold responses, in particular with genes related to glycine degradation pathway that could confer to Champagne a better frost tolerance. We showed that freezing tolerance involves a decrease of expression of genes related to photosynthesis and the expression of a gene involved in the production of cysteine and methionine that could act as cryoprotectant molecules. Although it remains to be confirmed, this study could also reveal the involvement of the jasmonate pathway in the cold responses, since we observed that two genes related to this pathway were mapped in a frost damage QTL interval and in a PQL rich region interval, respectively. Copyright © 2013 Elsevier GmbH. All rights reserved.

Functional genomic Landscape of Human Breast Cancer drivers, vulnerabilities, and resistance

PubMed Central

Marcotte, Richard; Sayad, Azin; Brown, Kevin R.; Sanchez-Garcia, Felix; Reimand, Jüri; Haider, Maliha; Virtanen, Carl; Bradner, James E.; Bader, Gary D.; Mills, Gordon B.; Pe’er, Dana; Moffat, Jason; Neel, Benjamin G.

2016-01-01

Summary Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations, and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole genome shRNA “dropout screens” on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate “drivers,” and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer, and PIK3CA mutations as a resistance determinant for BET-inhibitors. PMID:26771497

Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance.

PubMed

Marcotte, Richard; Sayad, Azin; Brown, Kevin R; Sanchez-Garcia, Felix; Reimand, Jüri; Haider, Maliha; Virtanen, Carl; Bradner, James E; Bader, Gary D; Mills, Gordon B; Pe'er, Dana; Moffat, Jason; Neel, Benjamin G

2016-01-14

Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole-genome small hairpin RNA (shRNA) "dropout screens" on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate "drivers," and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer and PIK3CA mutations as a resistance determinant for BET-inhibitors. Copyright © 2016 Elsevier Inc. All rights reserved.

Graduated driver licensing for reducing motor vehicle crashes among young drivers.

PubMed

Russell, Kelly F; Vandermeer, Ben; Hartling, Lisa

2011-10-05

Graduated driver licensing (GDL) has been proposed as a means of reducing crash rates among novice drivers by gradually introducing them to higher risk driving situations. To examine the effectiveness of GDL in reducing crash rates among young drivers. Studies were identified through searching MEDLINE, EMBASE, CINAHL, Healthstar, Web of Science, NTIS Bibliographic Database, TRIS Online, SIGLE, the World Wide Web, conference proceedings, consultation with experts and reference lists in relevant published literature. The searches were conducted from the time of inception to May 2009, and the Cochrane Injuries Group conducted an updated search of the TRANSPORT database in September 2009. Studies were included if: 1) they compared outcomes pre- and post-implementation of a GDL program within the same jurisdiction, 2) comparisons were made between jurisdictions with and without GDL, or 3) both. Studies had to report at least one objective, quantified outcome. Results were not pooled due to substantial heterogeneity. Percentage change was calculated for each year after the intervention, using one year prior to the intervention as baseline. Results were adjusted by internal controls. Analyses were stratified by denominators (population, licensed drivers). Results were calculated for the different crash types and presented for 16 year-olds alone as well as all teenage drivers. We included 34 studies evaluating 21 GDL programs and 2 analyses of >40 US states. GDL programs were implemented in the US (n=16), Canada (n=3), New Zealand (n=1), and Australia (n=1) and varied in their restrictions during the intermediate stage. Based on the Insurance Institute for Highway Safety (IIHS) classification, eleven programs were good, four were fair, five were marginal, one was poor and two could not be assessed. Reductions in crash rates were seen in all jurisdictions and for all crash types. Among 16 year-old drivers, the median decrease in per population adjusted overall crash rates

Deep targeted sequencing in pediatric acute lymphoblastic leukemia unveils distinct mutational patterns between genetic subtypes and novel relapse-associated genes.

PubMed

Lindqvist, C Mårten; Lundmark, Anders; Nordlund, Jessica; Freyhult, Eva; Ekman, Diana; Carlsson Almlöf, Jonas; Raine, Amanda; Övernäs, Elin; Abrahamsson, Jonas; Frost, Britt-Marie; Grandér, Dan; Heyman, Mats; Palle, Josefine; Forestier, Erik; Lönnerholm, Gudmar; Berglund, Eva C; Syvänen, Ann-Christine

2016-09-27

To characterize the mutational patterns of acute lymphoblastic leukemia (ALL) we performed deep next generation sequencing of 872 cancer genes in 172 diagnostic and 24 relapse samples from 172 pediatric ALL patients. We found an overall greater mutational burden and more driver mutations in T-cell ALL (T-ALL) patients compared to B-cell precursor ALL (BCP-ALL) patients. In addition, the majority of the mutations in T-ALL had occurred in the original leukemic clone, while most of the mutations in BCP-ALL were subclonal. BCP-ALL patients carrying any of the recurrent translocations ETV6-RUNX1, BCR-ABL or TCF3-PBX1 harbored few mutations in driver genes compared to other BCP-ALL patients. Specifically in BCP-ALL, we identified ATRX as a novel putative driver gene and uncovered an association between somatic mutations in the Notch signaling pathway at ALL diagnosis and increased risk of relapse. Furthermore, we identified EP300, ARID1A and SH2B3 as relapse-associated genes. The genes highlighted in our study were frequently involved in epigenetic regulation, associated with germline susceptibility to ALL, and present in minor subclones at diagnosis that became dominant at relapse. We observed a high degree of clonal heterogeneity and evolution between diagnosis and relapse in both BCP-ALL and T-ALL, which could have implications for the treatment efficiency.

Microarray expression profiling identifies genes with altered expression in HDL-deficient mice

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

Callow, Matthew J.; Dudoit, Sandrine; Gong, Elaine L.

2000-05-05

Based on the assumption that severe alterations in the expression of genes known to be involved in HDL metabolism may affect the expression of other genes we screened an array of over 5000 mouse expressed sequence tags (ESTs) for altered gene expression in the livers of two lines of mice with dramatic decreases in HDL plasma concentrations. Labeled cDNA from livers of apolipoprotein AI (apo AI) knockout mice, Scavenger Receptor BI (SR-BI) transgenic mice and control mice were co-hybridized to microarrays. Two-sample t-statistics were used to identify genes with altered expression levels in the knockout or transgenic mice compared withmore » the control mice. In the SR-BI group we found 9 array elements representing at least 5 genes to be significantly altered on the basis of an adjusted p value of less than 0.05. In the apo AI knockout group 8 array elements representing 4 genes were altered compared with the control group (p < 0.05). Several of the genes identified in the SR-BI transgenic suggest altered sterol metabolism and oxidative processes. These studies illustrate the use of multiple-testing methods for the identification of genes with altered expression in replicated microarray experiments of apo AI knockout and SR-BI transgenic mice.« less

Drivers of atmospheric evaporative demand during African droughts

NASA Astrophysics Data System (ADS)

Blakeley, S. L.; Harrison, L.; Hobbins, M.; Dewes, C.; Funk, C. C.; Shukla, S.; Husak, G. J.

2017-12-01

Seeking to advance the practice of famine early warning across sub-Saharan Africa we illuminate past drivers of high-impact droughts to gain a better understanding of the evaporative processes involved in drought dynamics. Atmospheric evaporative demand (ETo) is often used to estimate plant water balance and drought impacts to vegetation, and previously demonstrated linkages between precipitation, temperature, and ETo need to be better understood. This work is timely as new data streams will enable near-real-time monitoring of ETo and incorporation of ETo forecasts into seasonal outlooks for African growing seasons. For historical droughts during major growing seasons in sub-Saharan Africa, we evaluate ETo and identify main drivers for drought cases-identified based on below-normal precipitation during the wettest three months of the growing season-and contrast these with the ETo drivers that dominate in wetter years (we also consider droughts triggered by above normal ETo). Our focus is on regions of Africa where adequate precipitation is important for productive agriculture and pastoral activities and where evaporative demand might exacerbate moisture limitations. It is expected that important ETo drivers are partly connected with precipitation-related processes but that there are variations between regions and events. The goal here is to provide a generalized understanding of what aspects of evaporative demand historically have posed an additional hazard to plant stress and how precipitation outcomes are responsible for the ETo drivers. In addition, we explore whether there have been discernible changes through time in regard to ETo drivers during below-normal precipitation seasons. Upper and lower terciles of CHIRPS precipitation are used to identify anomalous dry and wet cases. The ETo dataset spans the 1980-near present period and is calculated following ASCE's formulation of Penman-Monteith method driven by daily temperature, humidity, wind speed, and solar

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility.

PubMed

Bagot, Rosemary C; Cates, Hannah M; Purushothaman, Immanuel; Lorsch, Zachary S; Walker, Deena M; Wang, Junshi; Huang, Xiaojie; Schlüter, Oliver M; Maze, Ian; Peña, Catherine J; Heller, Elizabeth A; Issler, Orna; Wang, Minghui; Song, Won-Min; Stein, Jason L; Liu, Xiaochuan; Doyle, Marie A; Scobie, Kimberly N; Sun, Hao Sheng; Neve, Rachael L; Geschwind, Daniel; Dong, Yan; Shen, Li; Zhang, Bin; Nestler, Eric J

2016-06-01

Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here, we performed RNA sequencing on four brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying the rooted species tree from the distribution of unrooted gene trees under the coalescent.

PubMed

Allman, Elizabeth S; Degnan, James H; Rhodes, John A

2011-06-01

Gene trees are evolutionary trees representing the ancestry of genes sampled from multiple populations. Species trees represent populations of individuals-each with many genes-splitting into new populations or species. The coalescent process, which models ancestry of gene copies within populations, is often used to model the probability distribution of gene trees given a fixed species tree. This multispecies coalescent model provides a framework for phylogeneticists to infer species trees from gene trees using maximum likelihood or Bayesian approaches. Because the coalescent models a branching process over time, all trees are typically assumed to be rooted in this setting. Often, however, gene trees inferred by traditional phylogenetic methods are unrooted. We investigate probabilities of unrooted gene trees under the multispecies coalescent model. We show that when there are four species with one gene sampled per species, the distribution of unrooted gene tree topologies identifies the unrooted species tree topology and some, but not all, information in the species tree edges (branch lengths). The location of the root on the species tree is not identifiable in this situation. However, for 5 or more species with one gene sampled per species, we show that the distribution of unrooted gene tree topologies identifies the rooted species tree topology and all its internal branch lengths. The length of any pendant branch leading to a leaf of the species tree is also identifiable for any species from which more than one gene is sampled.

Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines

PubMed Central

Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J

2016-01-01

Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours’ biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription–quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes. PMID:29263807

Genome-wide methylation analysis identifies genes silenced in non-seminoma cell lines.

PubMed

Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J

2016-01-01

Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours' biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription-quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes.

Effects of driver cell-phone use on driver aggression.

PubMed

McGarva, Andrew R; Ramsey, Matthew; Shear, Suzannah A

2006-04-01

Using 2 field procedures, the authors assessed impacts of cell-phone use on mild forms of driver aggression. Participants were 135 drivers traveling within a city of approximately 17,000 people in an otherwise little-populated region of western North Dakota. The authors videotaped the participants while a confederate driver in a low-status vehicle frustrated them. In Experiment 1, the confederate was traveling well under the posted speed limit. In Experiment 2, the confederate remained motionless at a stoplight that had turned green. When the confederate visibly talked on a hand-held cell phone (n = 67), male drivers exhibited their frustration by honking their horn more quickly and frequently than did drivers in no-cell-phone trials, and female drivers were more angry according to blind judgments of videotaped facial expressions that were compared with those of drivers in no-cell-phone trials (n = 68). The present results suggested that driver cell-phone use contributes to the growing crisis of roadway aggression.

The driver landscape of sporadic chordoma

DOE PAGES

Tarpey, Patrick S.; Behjati, Sam; Young, Matthew D.; ...

2017-10-12

Chordoma is a malignant, often incurable bone tumour showing notochordal differentiation. Here, we defined the somatic driver landscape of 104 cases of sporadic chordoma. We reveal somatic duplications of the notochordal transcription factor brachyury (T) in up to 27% of cases. These variants recapitulate the rearrangement architecture of the pathogenic germline duplications of T that underlie familial chordoma. In addition, we find potentially clinically actionable PI3K signalling mutations in 16% of cases. Intriguingly, one of the most frequently altered genes, mutated exclusively by inactivating mutation, was LYST (10%), which may represent a novel cancer gene in chordoma.

The driver landscape of sporadic chordoma

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

Tarpey, Patrick S.; Behjati, Sam; Young, Matthew D.

Chordoma is a malignant, often incurable bone tumour showing notochordal differentiation. Here, we defined the somatic driver landscape of 104 cases of sporadic chordoma. We reveal somatic duplications of the notochordal transcription factor brachyury (T) in up to 27% of cases. These variants recapitulate the rearrangement architecture of the pathogenic germline duplications of T that underlie familial chordoma. In addition, we find potentially clinically actionable PI3K signalling mutations in 16% of cases. Intriguingly, one of the most frequently altered genes, mutated exclusively by inactivating mutation, was LYST (10%), which may represent a novel cancer gene in chordoma.

Haplotype Analysis in Multiple Crosses to Identify a QTL Gene

PubMed Central

Wang, Xiaosong; Korstanje, Ron; Higgins, David; Paigen, Beverly

2004-01-01

Identifying quantitative trait locus (QTL) genes is a challenging task. Herein, we report using a two-step process to identify Apoa2 as the gene underlying Hdlq5, a QTL for plasma high-density lipoprotein cholesterol (HDL) levels on mouse chromosome 1. First, we performed a sequence analysis of the Apoa2 coding region in 46 genetically diverse mouse strains and found five different APOA2 protein variants, which we named APOA2a to APOA2e. Second, we conducted a haplotype analysis of the strains in 21 crosses that have so far detected HDL QTLs; we found that Hdlq5 was detected only in the nine crosses where one parent had the APOA2b protein variant characterized by an Ala61-to-Val61 substitution. We then found that strains with the APOA2b variant had significantly higher (P ≤ 0.002) plasma HDL levels than those with either the APOA2a or the APOA2c variant. These findings support Apoa2 as the underlying Hdlq5 gene and suggest the Apoa2 polymorphisms responsible for the Hdlq5 phenotype. Therefore, haplotype analysis in multiple crosses can be used to support a candidate QTL gene. PMID:15310659

Haplotype analysis in multiple crosses to identify a QTL gene.

PubMed

Wang, Xiaosong; Korstanje, Ron; Higgins, David; Paigen, Beverly

2004-09-01

Identifying quantitative trait locus (QTL) genes is a challenging task. Herein, we report using a two-step process to identify Apoa2 as the gene underlying Hdlq5, a QTL for plasma high-density lipoprotein cholesterol (HDL) levels on mouse chromosome 1. First, we performed a sequence analysis of the Apoa2 coding region in 46 genetically diverse mouse strains and found five different APOA2 protein variants, which we named APOA2a to APOA2e. Second, we conducted a haplotype analysis of the strains in 21 crosses that have so far detected HDL QTLs; we found that Hdlq5 was detected only in the nine crosses where one parent had the APOA2b protein variant characterized by an Ala61-to-Val61 substitution. We then found that strains with the APOA2b variant had significantly higher (P < or = 0.002) plasma HDL levels than those with either the APOA2a or the APOA2c variant. These findings support Apoa2 as the underlying Hdlq5 gene and suggest the Apoa2 polymorphisms responsible for the Hdlq5 phenotype. Therefore, haplotype analysis in multiple crosses can be used to support a candidate QTL gene.

Teaching Driver Education Technology to Novice Drivers.

ERIC Educational Resources Information Center

Young, Anthony

A cybernetic unit in driver education was developed to help grade 10 students develop the skills needed to acquire and process driver education information and prepare for the driving phase of driver education in grade 11. Students used a simulator to engage in a series of scenarios designed to promote development of social, behavioral, and mental…

Aging baby boomers--a blessing or challenge for driver licensing authorities.

PubMed

Dobbs, Bonnie M

2008-08-01

In less than 5 years, the first wave of baby boomers will begin turning 65, with the last wave of boomers entering their senior years in January 2029. Currently, boomers make up a significant percentage of the population in Canada, the United States, and other developed countries. The baby boom generation has had a profound impact on our society over the last six decades, and this large cohort will continue to exert its influence for several decades to come. Central to this article is the rapid growth in the number of persons 65 years of age and older, beginning in 2011, with a corresponding increase in the number of older drivers. The demographic shift has important implications for licensing authorities, the regulatory bodies charged with licensing and 'fitness to drive' decisions. The objectives of this paper are to summarize the published scientific literature on licensing policies and procedures currently in use for older drivers, discuss their limitations, and provide recommendations for meeting the upcoming challenges of an aging baby boomer population of drivers. Online searches were conducted using the following databases: PsycINFO, MEDLINE, Scopus, and TRIS. Google and Google Scholar also were searched for scientific articles. References identified from database and online searches were examined for relevant articles. A number of studies have investigated the utility of different licensing policies and procedures for identifying older drivers who may be at risk for impaired driving performance. Overall, results suggest that current policies and procedures are ineffective in identifying high-risk older drivers. The results also emphasize the need for a different approach for the identification of high risk older drivers by licensing agencies. Recommendations to assist with that goal are provided. The aging of the baby boomer population, combined with the projected high crash rates for this cohort of drivers as it moves through the senior years, underscores

New genes as drivers of phenotypic evolution

PubMed Central

Chen, Sidi; Krinsky, Benjamin H.; Long, Manyuan

2014-01-01

During the course of evolution, genomes acquire novel genetic elements as sources of functional and phenotypic diversity, including new genes that originated in recent evolution. In the past few years, substantial progress has been made in understanding the evolution and phenotypic effects of new genes. In particular, an emerging picture is that new genes, despite being present in the genomes of only a subset of species, can rapidly evolve indispensable roles in fundamental biological processes, including development, reproduction, brain function and behaviour. The molecular underpinnings of how new genes can develop these roles are starting to be characterized. These recent discoveries yield fresh insights into our broad understanding of biological diversity at refined resolution. PMID:23949544

New genes as drivers of phenotypic evolution.

PubMed

Chen, Sidi; Krinsky, Benjamin H; Long, Manyuan

2013-09-01

During the course of evolution, genomes acquire novel genetic elements as sources of functional and phenotypic diversity, including new genes that originated in recent evolution. In the past few years, substantial progress has been made in understanding the evolution and phenotypic effects of new genes. In particular, an emerging picture is that new genes, despite being present in the genomes of only a subset of species, can rapidly evolve indispensable roles in fundamental biological processes, including development, reproduction, brain function and behaviour. The molecular underpinnings of how new genes can develop these roles are starting to be characterized. These recent discoveries yield fresh insights into our broad understanding of biological diversity at refined resolution.

Factors associated with hit-and-run pedestrian fatalities and driver identification.

PubMed

MacLeod, Kara E; Griswold, Julia B; Arnold, Lindsay S; Ragland, David R

2012-03-01

As hit-and-run crashes account for a significant proportion of pedestrian fatalities, a better understanding of these crash types will assist efforts to reduce these fatalities. Of the more than 48,000 pedestrian deaths that were recorded in the United States between 1998 and 2007, 18.1% of them were caused by hit-and-run drivers. Using national data on single pedestrian-motor vehicle fatal crashes (1998-2007), logistic regression analyses were conducted to identify factors related to hit-and-run and to identify factors related to the identification of the hit-and-run driver. Results indicate an increased risk of hit-and-run in the early morning, poor light conditions, and on the weekend. There may also be an association between the type of victim and the likelihood of the driver leaving and being identified. Results also indicate that certain driver characteristics, behavior, and driving history are associated with hit-and-run. Alcohol use and invalid license were among the leading driver factor associated with an increased risk of hit-and-run. Prevention efforts that address such issues could substantially reduce pedestrian fatalities as a result of hit-and-run. However, more information about this driver population may be necessary. Copyright © 2011. Published by Elsevier Ltd.

Comparison of gene expression in segregating families identifies genes and genomic regions involved in a novel adaptation, zinc hyperaccumulation.

PubMed

Filatov, Victor; Dowdle, John; Smirnoff, Nicholas; Ford-Lloyd, Brian; Newbury, H John; Macnair, Mark R

2006-09-01

One of the challenges of comparative genomics is to identify specific genetic changes associated with the evolution of a novel adaptation or trait. We need to be able to disassociate the genes involved with a particular character from all the other genetic changes that take place as lineages diverge. Here we show that by comparing the transcriptional profile of segregating families with that of parent species differing in a novel trait, it is possible to narrow down substantially the list of potential target genes. In addition, by assuming synteny with a related model organism for which the complete genome sequence is available, it is possible to use the cosegregation of markers differing in transcription level to identify regions of the genome which probably contain quantitative trait loci (QTLs) for the character. This novel combination of genomics and classical genetics provides a very powerful tool to identify candidate genes. We use this methodology to investigate zinc hyperaccumulation in Arabidopsis halleri, the sister species to the model plant, Arabidopsis thaliana. We compare the transcriptional profile of A. halleri with that of its sister nonaccumulator species, Arabidopsis petraea, and between accumulator and nonaccumulator F(3)s derived from the cross between the two species. We identify eight genes which consistently show greater expression in accumulator phenotypes in both roots and shoots, including two metal transporter genes (NRAMP3 and ZIP6), and cytoplasmic aconitase, a gene involved in iron homeostasis in mammals. We also show that there appear to be two QTLs for zinc accumulation, on chromosomes 3 and 7.

The driver, the road, the rules … and the rest? A systems-based approach to young driver road safety.

PubMed

Scott-Parker, B; Goode, N; Salmon, P

2015-01-01

The persistent overrepresentation of young drivers in road crashes is universally recognised. A multitude of factors influencing their behaviour and safety have been identified through methods including crash analyses, simulated and naturalistic driving studies, and self-report measures. Across the globe numerous, diverse, countermeasures have been implemented; the design of the vast majority of these has been informed by a driver-centric approach. An alternative approach gaining popularity in transport safety is the systems approach which considers not only the characteristics of the individual, but also the decisions and actions of other actors within the road transport system, along with the interactions amongst them. This paper argues that for substantial improvements to be made in young driver road safety, what has been learnt from driver-centric research needs to be integrated into a systems approach, thus providing a holistic appraisal of the young driver road safety problem. Only then will more effective opportunities and avenues for intervention be realised. Copyright © 2014 Elsevier Ltd. All rights reserved.

Naturalistic distraction and driving safety in older drivers

PubMed Central

Aksan, Nazan; Dawson, Jeffrey D.; Emerson, Jamie L.; Yu, Lixi; Uc, Ergun Y.; Anderson, Steven W.; Rizzo, Matthew

2013-01-01

Objective This study aimed to quantify and compare performance of middle-aged and older drivers during a naturalistic distraction paradigm (visual search for roadside targets) and predict older driver performance given functioning in visual, motor, and cognitive domains. Background Distracted driving can imperil healthy adults and may disproportionally affect the safety of older drivers with visual, motor, and cognitive decline. Methods Two hundred and three drivers, 120 healthy older (61 men and 59 women, ages 65 years or greater) and 83 middle-aged drivers (38 men and 45 women, ages 40–64 years), participated in an on-road test in an instrumented vehicle. Outcome measures included performance in roadside target identification (traffic signs and restaurants) and concurrent driver safety. Differences in visual, motor, and cognitive functioning served as predictors. Results Older drivers identified fewer landmarks and drove slower but committed more safety errors than middle-aged drivers. Greater familiarity with local roads benefited performance of middle-aged but not older drivers. Visual cognition predicted both traffic sign identification and safety errors while executive function predicted traffic sign identification over and above vision. Conclusion Older adults are susceptible to driving safety errors while distracted by common secondary visual search tasks that are inherent to driving. The findings underscore that age-related cognitive decline affects older driver management of driving tasks at multiple levels, and can help inform the design of on-road tests and interventions for older drivers. PMID:23964422

Naturalistic distraction and driving safety in older drivers.

PubMed

Aksan, Nazan; Dawson, Jeffrey D; Emerson, Jamie L; Yu, Lixi; Uc, Ergun Y; Anderson, Steven W; Rizzo, Matthew

2013-08-01

In this study, we aimed to quantify and compare performance of middle-aged and older drivers during a naturalistic distraction paradigm (visual search for roadside targets) and to predict older drivers performance given functioning in visual, motor, and cognitive domains. Distracted driving can imperil healthy adults and may disproportionally affect the safety of older drivers with visual, motor, and cognitive decline. A total of 203 drivers, 120 healthy older (61 men and 59 women, ages 65 years and older) and 83 middle-aged drivers (38 men and 45 women, ages 40 to 64 years), participated in an on-road test in an instrumented vehicle. Outcome measures included performance in roadside target identification (traffic signs and restaurants) and concurrent driver safety. Differences in visual, motor, and cognitive functioning served as predictors. Older drivers identified fewer landmarks and drove slower but committed more safety errors than did middle-aged drivers. Greater familiarity with local roads benefited performance of middle-aged but not older drivers.Visual cognition predicted both traffic sign identification and safety errors, and executive function predicted traffic sign identification over and above vision. Older adults are susceptible to driving safety errors while distracted by common secondary visual search tasks that are inherent to driving. The findings underscore that age-related cognitive decline affects older drivers' management of driving tasks at multiple levels and can help inform the design of on-road tests and interventions for older drivers.

Driver anger on the information superhighway: A content analysis of online complaints of offensive driver behaviour.

PubMed

Wickens, Christine M; Wiesenthal, David L; Hall, Ashley; Roseborough, James E W

2013-03-01

In recent years, several websites have been developed allowing drivers to post their complaints about other motorists online. These websites allow drivers to describe the nature of the offensive behaviour and to identify the offending motorist by vehicle type, colour, and license plate number. Some websites also ask drivers to list the location where the event took place and the exact date and time of the offence. The current study was a content analysis of complaints posted to RoadRagers.com between 1999 and 2007 (N=5624). The purpose of the study was to: (1) assess the research value of this novel data source; (2) demonstrate the value of content analysis to the study of driver behaviour; (3) further validate an existing coding scheme; (4) determine whether this new data source would replicate previous research findings regarding the most frequent types of driver complaints and temporal distribution of these reports; (5) provide recommendations for improved driver training and public safety initiatives based on these data. A coding scheme that was originally developed for an assessment of complaints submitted to the Ontario Provincial Police (OPP) (Wickens et al., 2005) was revised to accommodate the new dataset. The inter-rater reliability of the revised coding scheme as applied to the website complaints was very good (kappa=.85). The most frequently reported improper driver behaviours were cutting/weaving, speeding, perceived displays of hostility, and tailgating. Reports were most frequent on weekdays and during the morning and afternoon rush hour. The current study replicated several findings from the analysis of reports to the OPP, but possible differences in the sample and data collection method also produced some differences in findings. The value of content analysis to driver behaviour research and of driver complaint websites as a data source was demonstrated. Implications for driver safety initiatives and future research will be discussed. Copyright �

Horizontal gene transfer is a significant driver of gene innovation in dinoflagellates.

PubMed

Wisecaver, Jennifer H; Brosnahan, Michael L; Hackett, Jeremiah D

2013-01-01

The dinoflagellates are an evolutionarily and ecologically important group of microbial eukaryotes. Previous work suggests that horizontal gene transfer (HGT) is an important source of gene innovation in these organisms. However, dinoflagellate genomes are notoriously large and complex, making genomic investigation of this phenomenon impractical with currently available sequencing technology. Fortunately, de novo transcriptome sequencing and assembly provides an alternative approach for investigating HGT. We sequenced the transcriptome of the dinoflagellate Alexandrium tamarense Group IV to investigate how HGT has contributed to gene innovation in this group. Our comprehensive A. tamarense Group IV gene set was compared with those of 16 other eukaryotic genomes. Ancestral gene content reconstruction of ortholog groups shows that A. tamarense Group IV has the largest number of gene families gained (314-1,563 depending on inference method) relative to all other organisms in the analysis (0-782). Phylogenomic analysis indicates that genes horizontally acquired from bacteria are a significant proportion of this gene influx, as are genes transferred from other eukaryotes either through HGT or endosymbiosis. The dinoflagellates also display curious cases of gene loss associated with mitochondrial metabolism including the entire Complex I of oxidative phosphorylation. Some of these missing genes have been functionally replaced by bacterial and eukaryotic xenologs. The transcriptome of A. tamarense Group IV lends strong support to a growing body of evidence that dinoflagellate genomes are extraordinarily impacted by HGT.

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

PubMed

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

Spider Transcriptomes Identify Ancient Large-Scale Gene Duplication Event Potentially Important in Silk Gland Evolution

PubMed Central

Clarke, Thomas H.; Garb, Jessica E.; Hayashi, Cheryl Y.; Arensburger, Peter; Ayoub, Nadia A.

2015-01-01

The evolution of specialized tissues with novel functions, such as the silk synthesizing glands in spiders, is likely an influential driver of adaptive success. Large-scale gene duplication events and subsequent paralog divergence are thought to be required for generating evolutionary novelty. Such an event has been proposed for spiders, but not tested. We de novo assembled transcriptomes from three cobweb weaving spider species. Based on phylogenetic analyses of gene families with representatives from each of the three species, we found numerous duplication events indicative of a whole genome or segmental duplication. We estimated the age of the gene duplications relative to several speciation events within spiders and arachnids and found that the duplications likely occurred after the divergence of scorpions (order Scorpionida) and spiders (order Araneae), but before the divergence of the spider suborders Mygalomorphae and Araneomorphae, near the evolutionary origin of spider silk glands. Transcripts that are expressed exclusively or primarily within black widow silk glands are more likely to have a paralog descended from the ancient duplication event and have elevated amino acid replacement rates compared with other transcripts. Thus, an ancient large-scale gene duplication event within the spider lineage was likely an important source of molecular novelty during the evolution of silk gland-specific expression. This duplication event may have provided genetic material for subsequent silk gland diversification in the true spiders (Araneomorphae). PMID:26058392

A Multiomics Approach to Identify Genes Associated with Childhood Asthma Risk and Morbidity.

PubMed

Forno, Erick; Wang, Ting; Yan, Qi; Brehm, John; Acosta-Perez, Edna; Colon-Semidey, Angel; Alvarez, Maria; Boutaoui, Nadia; Cloutier, Michelle M; Alcorn, John F; Canino, Glorisa; Chen, Wei; Celedón, Juan C

2017-10-01

Childhood asthma is a complex disease. In this study, we aim to identify genes associated with childhood asthma through a multiomics "vertical" approach that integrates multiple analytical steps using linear and logistic regression models. In a case-control study of childhood asthma in Puerto Ricans (n = 1,127), we used adjusted linear or logistic regression models to evaluate associations between several analytical steps of omics data, including genome-wide (GW) genotype data, GW methylation, GW expression profiling, cytokine levels, asthma-intermediate phenotypes, and asthma status. At each point, only the top genes/single-nucleotide polymorphisms/probes/cytokines were carried forward for subsequent analysis. In step 1, asthma modified the gene expression-protein level association for 1,645 genes; pathway analysis showed an enrichment of these genes in the cytokine signaling system (n = 269 genes). In steps 2-3, expression levels of 40 genes were associated with intermediate phenotypes (asthma onset age, forced expiratory volume in 1 second, exacerbations, eosinophil counts, and skin test reactivity); of those, methylation of seven genes was also associated with asthma. Of these seven candidate genes, IL5RA was also significant in analytical steps 4-8. We then measured plasma IL-5 receptor α levels, which were associated with asthma age of onset and moderate-severe exacerbations. In addition, in silico database analysis showed that several of our identified IL5RA single-nucleotide polymorphisms are associated with transcription factors related to asthma and atopy. This approach integrates several analytical steps and is able to identify biologically relevant asthma-related genes, such as IL5RA. It differs from other methods that rely on complex statistical models with various assumptions.

Examination of Supplemental Driver Training and Online Basic Driver Education

DOT National Transportation Integrated Search

2012-06-01

This report describes supplemental driver training programs and online basic driver education. It coves supplemental driver training that : focused on knowledge and skills beyond those normally found in traditional driver education delivered in the U...

A large-scale RNA interference screen identifies genes that regulate autophagy at different stages.

PubMed

Guo, Sujuan; Pridham, Kevin J; Virbasius, Ching-Man; He, Bin; Zhang, Liqing; Varmark, Hanne; Green, Michael R; Sheng, Zhi

2018-02-12

Dysregulated autophagy is central to the pathogenesis and therapeutic development of cancer. However, how autophagy is regulated in cancer is not well understood and genes that modulate cancer autophagy are not fully defined. To gain more insights into autophagy regulation in cancer, we performed a large-scale RNA interference screen in K562 human chronic myeloid leukemia cells using monodansylcadaverine staining, an autophagy-detecting approach equivalent to immunoblotting of the autophagy marker LC3B or fluorescence microscopy of GFP-LC3B. By coupling monodansylcadaverine staining with fluorescence-activated cell sorting, we successfully isolated autophagic K562 cells where we identified 336 short hairpin RNAs. After candidate validation using Cyto-ID fluorescence spectrophotometry, LC3B immunoblotting, and quantitative RT-PCR, 82 genes were identified as autophagy-regulating genes. 20 genes have been reported previously and the remaining 62 candidates are novel autophagy mediators. Bioinformatic analyses revealed that most candidate genes were involved in molecular pathways regulating autophagy, rather than directly participating in the autophagy process. Further autophagy flux assays revealed that 57 autophagy-regulating genes suppressed autophagy initiation, whereas 21 candidates promoted autophagy maturation. Our RNA interference screen identifies identified genes that regulate autophagy at different stages, which helps decode autophagy regulation in cancer and offers novel avenues to develop autophagy-related therapies for cancer.

Overexpression screens identify conserved dosage chromosome instability genes in yeast and human cancer

PubMed Central

Duffy, Supipi; Fam, Hok Khim; Wang, Yi Kan; Styles, Erin B.; Kim, Jung-Hyun; Ang, J. Sidney; Singh, Tejomayee; Larionov, Vladimir; Shah, Sohrab P.; Andrews, Brenda; Boerkoel, Cornelius F.; Hieter, Philip

2016-01-01

Somatic copy number amplification and gene overexpression are common features of many cancers. To determine the role of gene overexpression on chromosome instability (CIN), we performed genome-wide screens in the budding yeast for yeast genes that cause CIN when overexpressed, a phenotype we refer to as dosage CIN (dCIN), and identified 245 dCIN genes. This catalog of genes reveals human orthologs known to be recurrently overexpressed and/or amplified in tumors. We show that two genes, TDP1, a tyrosyl-DNA-phosphdiesterase, and TAF12, an RNA polymerase II TATA-box binding factor, cause CIN when overexpressed in human cells. Rhabdomyosarcoma lines with elevated human Tdp1 levels also exhibit CIN that can be partially rescued by siRNA-mediated knockdown of TDP1. Overexpression of dCIN genes represents a genetic vulnerability that could be leveraged for selective killing of cancer cells through targeting of an unlinked synthetic dosage lethal (SDL) partner. Using SDL screens in yeast, we identified a set of genes that when deleted specifically kill cells with high levels of Tdp1. One gene was the histone deacetylase RPD3, for which there are known inhibitors. Both HT1080 cells overexpressing hTDP1 and rhabdomyosarcoma cells with elevated levels of hTdp1 were more sensitive to histone deacetylase inhibitors valproic acid (VPA) and trichostatin A (TSA), recapitulating the SDL interaction in human cells and suggesting VPA and TSA as potential therapeutic agents for tumors with elevated levels of hTdp1. The catalog of dCIN genes presented here provides a candidate list to identify genes that cause CIN when overexpressed in cancer, which can then be leveraged through SDL to selectively target tumors. PMID:27551064

Driver behaviour with adaptive cruise control.

PubMed

Stanton, Neville A; Young, Mark S

2005-08-15

This paper reports on the evaluation of adaptive cruise control (ACC) from a psychological perspective. It was anticipated that ACC would have an effect upon the psychology of driving, i.e. make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but workload might be reduced and driving might be less stressful. Drivers were asked to drive in a driving simulator under manual and ACC conditions. Analysis of variance techniques were used to determine the effects of workload (i.e. amount of traffic) and feedback (i.e. degree of information from the ACC system) on the psychological variables measured (i.e. locus of control, trust, workload, stress, mental models and situation awareness). The results showed that: locus of control and trust were unaffected by ACC, whereas situation awareness, workload and stress were reduced by ACC. Ways of improving situation awareness could include cues to help the driver predict vehicle trajectory and identify conflicts.

Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

DOE PAGES

Schulze, Kornelius; Imbeaud, Sandrine; Letouzé, Eric; ...

2015-03-30

Our genomic analyses promise to improve tumor characterization to optimize personalized treatment for patients with hepatocellular carcinoma (HCC). Exome sequencing analysis of 243 liver tumors identified mutational signatures associated with specific risk factors, mainly combined alcohol and tobacco consumption and exposure to aflatoxin B1. We identified 161 putative driver genes associated with 11 recurrently altered pathways. Associations of mutations defined 3 groups of genes related to risk factors and centered on CTNNB1 (alcohol), TP53 (hepatitis B virus, HBV) and AXIN1. These analyses according to tumor stage progression identified TERT promoter mutation as an early event, whereasFGF3, FGF4, FGF19 or CCND1more » amplification and TP53 and CDKN2A alterations appeared at more advanced stages in aggressive tumors. In 28% of the tumors, we identified genetic alterations potentially targetable by US Food and Drug Administration (FDA)–approved drugs. Finally, we identified risk factor–specific mutational signatures and defined the extensive landscape of altered genes and pathways in HCC, which will be useful to design clinical trials for targeted therapy.« less

Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

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

Schulze, Kornelius; Imbeaud, Sandrine; Letouzé, Eric

Our genomic analyses promise to improve tumor characterization to optimize personalized treatment for patients with hepatocellular carcinoma (HCC). Exome sequencing analysis of 243 liver tumors identified mutational signatures associated with specific risk factors, mainly combined alcohol and tobacco consumption and exposure to aflatoxin B1. We identified 161 putative driver genes associated with 11 recurrently altered pathways. Associations of mutations defined 3 groups of genes related to risk factors and centered on CTNNB1 (alcohol), TP53 (hepatitis B virus, HBV) and AXIN1. These analyses according to tumor stage progression identified TERT promoter mutation as an early event, whereasFGF3, FGF4, FGF19 or CCND1more » amplification and TP53 and CDKN2A alterations appeared at more advanced stages in aggressive tumors. In 28% of the tumors, we identified genetic alterations potentially targetable by US Food and Drug Administration (FDA)–approved drugs. Finally, we identified risk factor–specific mutational signatures and defined the extensive landscape of altered genes and pathways in HCC, which will be useful to design clinical trials for targeted therapy.« less

Horizontal Gene Transfer is a Significant Driver of Gene Innovation in Dinoflagellates

PubMed Central

Wisecaver, Jennifer H.; Brosnahan, Michael L.; Hackett, Jeremiah D.

2013-01-01

The dinoflagellates are an evolutionarily and ecologically important group of microbial eukaryotes. Previous work suggests that horizontal gene transfer (HGT) is an important source of gene innovation in these organisms. However, dinoflagellate genomes are notoriously large and complex, making genomic investigation of this phenomenon impractical with currently available sequencing technology. Fortunately, de novo transcriptome sequencing and assembly provides an alternative approach for investigating HGT. We sequenced the transcriptome of the dinoflagellate Alexandrium tamarense Group IV to investigate how HGT has contributed to gene innovation in this group. Our comprehensive A. tamarense Group IV gene set was compared with those of 16 other eukaryotic genomes. Ancestral gene content reconstruction of ortholog groups shows that A. tamarense Group IV has the largest number of gene families gained (314–1,563 depending on inference method) relative to all other organisms in the analysis (0–782). Phylogenomic analysis indicates that genes horizontally acquired from bacteria are a significant proportion of this gene influx, as are genes transferred from other eukaryotes either through HGT or endosymbiosis. The dinoflagellates also display curious cases of gene loss associated with mitochondrial metabolism including the entire Complex I of oxidative phosphorylation. Some of these missing genes have been functionally replaced by bacterial and eukaryotic xenologs. The transcriptome of A. tamarense Group IV lends strong support to a growing body of evidence that dinoflagellate genomes are extraordinarily impacted by HGT. PMID:24259313

Integrating mean and variance heterogeneities to identify differentially expressed genes.

PubMed

Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

2016-12-06

In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

Characteristics of fatigued commercial motor vehicle drivers : a preliminary investigation.

DOT National Transportation Integrated Search

2012-12-01

The goal of this research was to identify and correlate easily observable characteristics of drivers to different levels of : fatigue, thus enabling state patrol officers to make more judicious decisions related to driver fatigue. A literature review...

Traffic Operations Control For Older Drivers And Pedestrians: Summary Report

DOT National Transportation Integrated Search

1996-07-01

The purpose of this investigation was to determine which intersection operational characteristics could be altered to accommodate age-related changes. Two key drivers issues were examined in order to identify the specific older driver problems and th...

G20210A prothrombin gene mutation identified in patients with venous leg ulcers.

PubMed

Jebeleanu, G; Procopciuc, L

2001-01-01

The G20210A mutation variant of prothrombin gene is the second most frequent mutation identified in patients with deep venous thrombosis, after factor V Leiden. The risk for developing deep venous thrombosis is high in patients identified as heterozygous for G20210A mutation. In order to identify this polymorphism in the gene coding prothrombin, the 345bp fragment in the 3'- untranslated region of the prothrombin gene was amplified using amplification by polymerase chain reaction and enzymatic digestion by HindIII (restriction endonuclease enzyme). The products of amplification and enzymatic's digestion were analized using agarose gel electrophoresis. We investigated 20 patients with venous leg ulcers and we found 2 heterozygous (10%) for G20210A mutation. None of the patients in the control group had G20210A mutation. Our study confirms the presence of G20210A mutation in the Romanian population. Our study also shows the link between venous leg ulcers and this polymorphism in the prothrombin gene.

A Novel Yeast Genomics Method for Identifying New Breast Cancer Susceptibility Genes

DTIC Science & Technology

2007-05-01

find new candidate genes for breast cancer susceptibility in women and identifying these human genes can further improve monitoring and treatment...breast cancer susceptibility genes in humans that are currently unknown and not deducible from current methodologies. It is a fundamental...template to faithfully repair the broken strand. In human cancer it is loss of HR, rather than NHEJ, that is more important in increasing cancer

Next-generation sequencing to identify candidate genes and develop diagnostic markers for a novel Phytophthora resistance gene, RpsHC18, in soybean.

PubMed

Zhong, Chao; Sun, Suli; Li, Yinping; Duan, Canxing; Zhu, Zhendong

2018-03-01

A novel Phytophthora sojae resistance gene RpsHC18 was identified and finely mapped on soybean chromosome 3. Two NBS-LRR candidate genes were identified and two diagnostic markers of RpsHC18 were developed. Phytophthora root rot caused by Phytophthora sojae is a destructive disease of soybean. The most effective disease-control strategy is to deploy resistant cultivars carrying Phytophthora-resistant Rps genes. The soybean cultivar Huachun 18 has a broad and distinct resistance spectrum to 12 P. sojae isolates. Quantitative trait loci sequencing (QTL-seq), based on the whole-genome resequencing (WGRS) of two extreme resistant and susceptible phenotype bulks from an F 2:3 population, was performed, and one 767-kb genomic region with ΔSNP-index ≥ 0.9 on chromosome 3 was identified as the RpsHC18 candidate region in Huachun 18. The candidate region was reduced to a 146-kb region by fine mapping. Nonsynonymous SNP and haplotype analyses were carried out in the 146-kb region among ten soybean genotypes using WGRS. Four specific nonsynonymous SNPs were identified in two nucleotide-binding sites-leucine-rich repeat (NBS-LRR) genes, RpsHC18-NBL1 and RpsHC18-NBL2, which were considered to be the candidate genes. Finally, one specific SNP marker in each candidate gene was successfully developed using a tetra-primer ARMS-PCR assay, and the two markers were verified to be specific for RpsHC18 and to effectively distinguish other known Rps genes. In this study, we applied an integrated genomic-based strategy combining WGRS with traditional genetic mapping to identify RpsHC18 candidate genes and develop diagnostic markers. These results suggest that next-generation sequencing is a precise, rapid and cost-effective way to identify candidate genes and develop diagnostic markers, and it can accelerate Rps gene cloning and marker-assisted selection for breeding of P. sojae-resistant soybean cultivars.

A 6-gene signature identifies four molecular subgroups of neuroblastoma

PubMed Central

2011-01-01

Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p < 0.05, Fisher's exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics. PMID:21492432

Exome sequencing of a large family identifies potential candidate genes contributing risk to bipolar disorder.

PubMed

Zhang, Tianxiao; Hou, Liping; Chen, David T; McMahon, Francis J; Wang, Jen-Chyong; Rice, John P

2018-03-01

Bipolar disorder is a mental illness with lifetime prevalence of about 1%. Previous genetic studies have identified multiple chromosomal linkage regions and candidate genes that might be associated with bipolar disorder. The present study aimed to identify potential susceptibility variants for bipolar disorder using 6 related case samples from a four-generation family. A combination of exome sequencing and linkage analysis was performed to identify potential susceptibility variants for bipolar disorder. Our study identified a list of five potential candidate genes for bipolar disorder. Among these five genes, GRID1(Glutamate Receptor Delta-1 Subunit), which was previously reported to be associated with several psychiatric disorders and brain related traits, is particularly interesting. Variants with functional significance in this gene were identified from two cousins in our bipolar disorder pedigree. Our findings suggest a potential role for these genes and the related rare variants in the onset and development of bipolar disorder in this one family. Additional research is needed to replicate these findings and evaluate their patho-biological significance. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving Driver Performance. A Curriculum for Licensed Drivers.

ERIC Educational Resources Information Center

Highway Users Federation for Safety and Mobility, Washington, DC.

Curriculum material presented in this manual is for use in the development of an instructional program for drivers who either want or need to improve their driving performance. Three principal units are included: man and highway transportation, driver performance, and factors influencing driver behavior. Each unit is further divided into episodes…

Systems approach identifies an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1.

PubMed

Gutiérrez, Rodrigo A; Stokes, Trevor L; Thum, Karen; Xu, Xiaodong; Obertello, Mariana; Katari, Manpreet S; Tanurdzic, Milos; Dean, Alexis; Nero, Damion C; McClung, C Robertson; Coruzzi, Gloria M

2008-03-25

Understanding how nutrients affect gene expression will help us to understand the mechanisms controlling plant growth and development as a function of nutrient availability. Nitrate has been shown to serve as a signal for the control of gene expression in Arabidopsis. There is also evidence, on a gene-by-gene basis, that downstream products of nitrogen (N) assimilation such as glutamate (Glu) or glutamine (Gln) might serve as signals of organic N status that in turn regulate gene expression. To identify genome-wide responses to such organic N signals, Arabidopsis seedlings were transiently treated with ammonium nitrate in the presence or absence of MSX, an inhibitor of glutamine synthetase, resulting in a block of Glu/Gln synthesis. Genes that responded to organic N were identified as those whose response to ammonium nitrate treatment was blocked in the presence of MSX. We showed that some genes previously identified to be regulated by nitrate are under the control of an organic N-metabolite. Using an integrated network model of molecular interactions, we uncovered a subnetwork regulated by organic N that included CCA1 and target genes involved in N-assimilation. We validated some of the predicted interactions and showed that regulation of the master clock control gene CCA1 by Glu or a Glu-derived metabolite in turn regulates the expression of key N-assimilatory genes. Phase response curve analysis shows that distinct N-metabolites can advance or delay the CCA1 phase. Regulation of CCA1 by organic N signals may represent a novel input mechanism for N-nutrients to affect plant circadian clock function.

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMI.

PubMed

Wang, Weijing; Jiang, Wenjie; Hou, Lin; Duan, Haiping; Wu, Yili; Xu, Chunsheng; Tan, Qihua; Li, Shuxia; Zhang, Dongfeng

2017-11-13

The therapeutic management of obesity is challenging, hence further elucidating the underlying mechanisms of obesity development and identifying new diagnostic biomarkers and therapeutic targets are urgent and necessary. Here, we performed differential gene expression analysis and weighted gene co-expression network analysis (WGCNA) to identify significant genes and specific modules related to BMI based on gene expression profile data of 7 discordant monozygotic twins. In the differential gene expression analysis, it appeared that 32 differentially expressed genes (DEGs) were with a trend of up-regulation in twins with higher BMI when compared to their siblings. Categories of positive regulation of nitric-oxide synthase biosynthetic process, positive regulation of NF-kappa B import into nucleus, and peroxidase activity were significantly enriched within GO database and NF-kappa B signaling pathway within KEGG database. DEGs of NAMPT, TLR9, PTGS2, HBD, and PCSK1N might be associated with obesity. In the WGCNA, among the total 20 distinct co-expression modules identified, coral1 module (68 genes) had the strongest positive correlation with BMI (r = 0.56, P = 0.04) and disease status (r = 0.56, P = 0.04). Categories of positive regulation of phospholipase activity, high-density lipoprotein particle clearance, chylomicron remnant clearance, reverse cholesterol transport, intermediate-density lipoprotein particle, chylomicron, low-density lipoprotein particle, very-low-density lipoprotein particle, voltage-gated potassium channel complex, cholesterol transporter activity, and neuropeptide hormone activity were significantly enriched within GO database for this module. And alcoholism and cell adhesion molecules pathways were significantly enriched within KEGG database. Several hub genes, such as GAL, ASB9, NPPB, TBX2, IL17C, APOE, ABCG4, and APOC2 were also identified. The module eigengene of saddlebrown module (212 genes) was also significantly

Analysis of global gene expression profiles to identify differentially expressed genes critical for embryo development in Brassica rapa.

PubMed

Zhang, Yu; Peng, Lifang; Wu, Ya; Shen, Yanyue; Wu, Xiaoming; Wang, Jianbo

2014-11-01

Embryo development represents a crucial developmental period in the life cycle of flowering plants. To gain insights into the genetic programs that control embryo development in Brassica rapa L., RNA sequencing technology was used to perform transcriptome profiling analysis of B. rapa developing embryos. The results generated 42,906,229 sequence reads aligned with 32,941 genes. In total, 27,760, 28,871, 28,384, and 25,653 genes were identified from embryos at globular, heart, early cotyledon, and mature developmental stages, respectively, and analysis between stages revealed a subset of stage-specific genes. We next investigated 9,884 differentially expressed genes with more than fivefold changes in expression and false discovery rate ≤ 0.001 from three adjacent-stage comparisons; 1,514, 3,831, and 6,633 genes were detected between globular and heart stage embryo libraries, heart stage and early cotyledon stage, and early cotyledon and mature stage, respectively. Large numbers of genes related to cellular process, metabolism process, response to stimulus, and biological process were expressed during the early and middle stages of embryo development. Fatty acid biosynthesis, biosynthesis of secondary metabolites, and photosynthesis-related genes were expressed predominantly in embryos at the middle stage. Genes for lipid metabolism and storage proteins were highly expressed in the middle and late stages of embryo development. We also identified 911 transcription factor genes that show differential expression across embryo developmental stages. These results increase our understanding of the complex molecular and cellular events during embryo development in B. rapa and provide a foundation for future studies on other oilseed crops.

Driver Behavior During Overtaking Maneuvers from the 100-Car Naturalistic Driving Study.

PubMed

Chen, Rong; Kusano, Kristofer D; Gabler, Hampton C

2015-01-01

Lane changes with the intention to overtake the vehicle in front are especially challenging scenarios for forward collision warning (FCW) designs. These overtaking maneuvers can occur at high relative vehicle speeds and often involve no brake and/or turn signal application. Therefore, overtaking presents the potential of erroneously triggering the FCW. A better understanding of driver behavior during lane change events can improve designs of this human-machine interface and increase driver acceptance of FCW. The objective of this study was to aid FCW design by characterizing driver behavior during lane change events using naturalistic driving study data. The analysis was based on data from the 100-Car Naturalistic Driving Study, collected by the Virginia Tech Transportation Institute. The 100-Car study contains approximately 1.2 million vehicle miles of driving and 43,000 h of data collected from 108 primary drivers. In order to identify overtaking maneuvers from a large sample of driving data, an algorithm to automatically identify overtaking events was developed. The lead vehicle and minimum time to collision (TTC) at the start of lane change events was identified using radar processing techniques developed in a previous study. The lane change identification algorithm was validated against video analysis, which manually identified 1,425 lane change events from approximately 126 full trips. Forty-five drivers with valid time series data were selected from the 100-Car study. From the sample of drivers, our algorithm identified 326,238 lane change events. A total of 90,639 lane change events were found to involve a closing lead vehicle. Lane change events were evenly distributed between left side and right side lane changes. The characterization of lane change frequency and minimum TTC was divided into 10 mph speed bins for vehicle travel speeds between 10 and 90 mph. For all lane change events with a closing lead vehicle, the results showed that drivers change

Automobile driver on-road performance test. Volume 1, final report

DOT National Transportation Integrated Search

1981-09-30

The Automobile Driver On-Road Performance Test (ADOPT) was developed during a three-phase project. In Phase 1, 51 candidate behaviors were identified and selected with the help of experts in the fields of traffic safety, measurement of driver perform...

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

PubMed

Johnston, Iain G; Williams, Ben P

2016-02-24

Since their endosymbiotic origin, mitochondria have lost most of their genes. Although many selective mechanisms underlying the evolution of mitochondrial genomes have been proposed, a data-driven exploration of these hypotheses is lacking, and a quantitatively supported consensus remains absent. We developed HyperTraPS, a methodology coupling stochastic modeling with Bayesian inference, to identify the ordering of evolutionary events and suggest their causes. Using 2015 complete mitochondrial genomes, we inferred evolutionary trajectories of mtDNA gene loss across the eukaryotic tree of life. We find that proteins comprising the structural cores of the electron transport chain are preferentially encoded within mitochondrial genomes across eukaryotes. A combination of high GC content and high protein hydrophobicity is required to explain patterns of mtDNA gene retention; a model that accounts for these selective pressures can also predict the success of artificial gene transfer experiments in vivo. This work provides a general method for data-driven inference of the ordering of evolutionary and progressive events, here identifying the distinct features shaping mitochondrial genomes of present-day species. Copyright © 2016 Elsevier Inc. All rights reserved.

Railway suicide: the psychological effects on drivers.

PubMed

Farmer, R; Tranah, T; O'Donnell, I; Catalan, J

1992-05-01

People have jumped (or fallen) in front of trains on the London Underground system in increasing numbers throughout the twentieth century. During the past decade there have been about 100 such incidents each year, of which around 90 would involve the train driver witnessing his train strike the person on the track. Most are suicides or attempts at suicide. They represent major unexpected and violent events in the lives of the train drivers and it might be expected that some of them would respond by developing a post-traumatic stress reaction of the type identified by Horowitz (1976) or other adverse psychological reactions or both. The research reported in this paper was designed to characterize the range of responses of drivers to the experiences of killing or injuring members of the public during the course of their daily work. It was found that 16.3% of the drivers involved in incidents did develop post-traumatic stress disorder and that other diagnoses, e.g. depression and phobic states, were present in 39.5% of drivers when interviewed one month after the incident.

Identifying tectonic and climatic drivers for deep-marine siliciclastic systems: Middle Eocene, Spanish Pyrenees

NASA Astrophysics Data System (ADS)

Pickering, K. T.; Scotchman, J. I.; Robinson, S. A.

2009-12-01

Analysis of the sedimentary record in deep time requires the deconvolution of tectonic and climatic drivers. The deep-marine siliciclastic systems in the Middle Eocene Ainsa-Jaca basin, Spanish Pyrenees, with their excellent outcrops and good temporal resolution, provide an opportunity to identify the relative importance of tectonic and climatic drivers on deposition over ~10 Myr at a time when the Earth’s climate was shifting from a greenhouse to icehouse conditions. The cumulative ~4 km of stratigraphy contains 8 sandy systems with a total of ~25 discrete channelized sandbodies that accumulated in water depths of ~400-800 m, and that were controlled by the ~400-kyr Milkankovitch frequency with modes, at ~100 kyr and ~41 kyr (possibly stacked ~23-kyr) influencing bottom-water conditions, causing periodic stratification in the water column across a submarine sill within the eastern, more proximal depositional systems in the Ainsa basin. We also identify a range of sub-Milankovitch millennial-scale cycles (Scotchman et al. 2009). In the Ainsa basin, the interplay of basin-bounding growth anticlines defined and controlled the position and stacking patterns of the sandy systems and their constituent channelized sandbodies, in a process of seesaw tectonics by: (i) Westward lateral offset-stacking of channelized sandbodies due to growth of the eastern anticline (Mediano), and (ii) Eastward (orogenwards) back-stepping of the depositional axis of each sandy system, due to phases of relative uplift of the opposing Boltaña growth anticline. The first-order control on accommodation, and the flow paths, for deep-marine sedimentation were tectonic, with the pacing of the supply of coarse siliciclastics being driven by global climatic processes, particularly Milankovitch-type frequencies. The dominance of eccentricity and obliquity is similar to results from the continental lacustrine Eocene Green River Formation, and the observations from ODP Site 1258 that the early to

Factors associated with obstructive sleep apnea among commercial motor vehicle drivers.

PubMed

Xie, Wen; Chakrabarty, Sangita; Levine, Robert; Johnson, Roy; Talmage, James B

2011-02-01

Identify factors associated with obstructive sleep apnea (OSA) risk during commercial driver medical examinations. A case-control study was conducted at an occupational health clinic by reviewing the commercial driver medical examinations medical records performed from January 2007 to December 2008. The magnitude of association with OSA was estimated with logistic regression. Among 1890 commercial motor vehicle drivers, 51 were confirmed positive for OSA by polysomnography after initial screening by Joint Task Force guidelines, yielding estimated positive predictive values of 78.5% for the screening criteria. Multivariable logistic regression showed that body mass index ≥ 30 (odds ratio: 26.86), hypertension (odds ratio: 2.57), and diabetes (odds ratio: 2.03) were independently associated with OSA. Medical examiners' use of objectively measurable risk factors, such as obesity, history of hypertension, and/or diabetes, rather than symptoms, may be more effective in identifying undiagnosed OSA in commercial drivers during the commercial driver medical examinations.

Causes, consequences and countermeasures to driver fatigue in the rail industry: The train driver perspective.

PubMed

Filtness, A J; Naweed, A

2017-04-01

Fatigue is an important workplace risk management issue. Within the rail industry, the passing of a stop signal (signal passed at danger; SPAD) is considered to be one of the most major safety breaches which can occur. Train drivers are very aware of the negative consequences associated with a SPAD. Therefore, SPADs provide a practical and applied safety relevant context within which to structure a discussion on fatigue. Focus groups discussing contributing factors to SPADs were undertaken at eight passenger rail organisations across Australia and New Zealand (n = 28 drivers). Data relating to fatigue was extracted and inductively analysed identifying three themes: causes, consequences, and countermeasures (to fatigue). Drivers experienced negative consequences of fatigue, despite existing countermeasures to mitigate it. Organisational culture was a barrier to effective fatigue management. A fatigue assessment tool consistently informed rostering, however, shift swapping was commonplace and often unregulated, reducing any potential positive impact. In discussing fatigue countermeasure strategies, drivers talked interchangeably about mitigating task related fatigue (e.g. increasing cognitive load) and sleepiness (e.g. caffeine). Ensuring the concepts of fatigue and sleepiness are properly understood has the potential to maximise safety. Copyright © 2016 Elsevier Ltd. All rights reserved.

Drivers: A Biologically Contextualized, Cross-Inferential View of the Epidemiology of Neurodegenerative Disorders

PubMed Central

de Pedro-Cuesta, Jesús; Martínez-Martín, Pablo; Rábano, Alberto; Alcalde-Cabero, Enrique; José García López, Fernando; Almazán-Isla, Javier; Ruiz-Tovar, María; Medrano, Maria-José; Avellanal, Fuencisla; Calero, Olga; Calero, Miguel

2016-01-01

Background: Sutherland et al. (2011) suggested that, instead of risk factors for single neurodegenerative disorders (NDDs), there was a need to identify specific “drivers”, i.e., risk factors with impact on specific deposits, such as amyloid-β, tau, or α-synuclein, acting across entities. Objectives and Methods: Redefining drivers as “neither protein/gene- nor entity-specific features identifiable in the clinical and general epidemiology of conformational NDDs (CNDDs) as potential footprints of templating/spread/transfer mechanisms”, we conducted an analysis of the epidemiology of ten CNDDs, searching for patterns. Results: We identified seven potential drivers, each of which was shared by at least two CNDDs: 1) an age-at-exposure-related susceptibility to Creutzfeldt-Jakob disease (CJD) and several late-life CNDDs; 2) a relationship between age at onset, survival, and incidence; 3) shared genetic risk factors for CJD and late-life CNNDs; 4) partly shared personal (diagnostic, educational, behavioral, and social risk factors) predating clinical onset of late-life CNDDs; 5) two environmental risk factors, namely, surgery for sporadic CJD and amyotrophic lateral sclerosis, and Bordetella pertussis infection for Parkinson’s disease; 6) reticulo-endothelial system stressors or general drivers (andropause or premenopausal estrogen deficiency, APOEɛ4, and vascular risk factors) for late-life CNDDs such as dementia/Alzheimer’s disease, type-2 diabetes mellitus, and some sporadic cardiac and vascular degenerative diseases; and 7) a high, invariant incidence ratio of sporadic to genetic forms of mid- and late-life CNDDs, and type-2 diabetes mellitus. Conclusion: There might be a systematic epidemiologic pattern induced by specific proteins (PrP, TDP-43, SOD1, α-synuclein, amyloid-β, tau, Langerhans islet peptide, and transthyretin) or established combinations of these. PMID:26923014

Leptospirosis Outbreaks in Nicaragua: Identifying Critical Areas and Exploring Drivers for Evidence-Based Planning

PubMed Central

Schneider, Maria Cristina; Nájera, Patricia; Aldighieri, Sylvain; Bacallao, Jorge; Soto, Aida; Marquiño, Wilmer; Altamirano, Lesbia; Saenz, Carlos; Marin, Jesus; Jimenez, Eduardo; Moynihan, Matthew; Espinal, Marcos

2012-01-01

Leptospirosis is an epidemic-prone zoonotic disease that occurs worldwide. In Central America, leptospirosis outbreaks have been reported in almost all countries; Nicaragua in particular has faced several outbreaks. The objective of this study was to stratify the risk and identify “critical areas” for leptospirosis outbreaks in Nicaragua, and to perform an exploratory analysis of potential “drivers”. This ecological study includes the entire country (153 municipalities). Cases from 2004 to 2010 were obtained from the country’s health information system, demographic and socioeconomic variables from its Census, and environmental data from external sources. Criteria for risk stratification of leptospirosis were defined. Nicaragua reported 1,980 cases of leptospirosis during this period, with the highest percentage of cases (26.36%) in León, followed by Chinandega (15.35%). Among the 153 municipalities, 48 were considered critical areas, 85 were endemic and 20 silent. Using spatial and statistical analysis, the variable presenting the most evident pattern of association with critical areas defined by top quintile of incidence rate is the percentage of municipal surface occupied by the soil combination of cambisol (over pyroclastic and lava bedrock) and andosol (over a volcanic ashes foundation). Precipitation and percentage of rural population are also associated with critical areas. This methodology and findings could be used for Nicaragua’s Leptospirosis Intersectoral Plan, and to identify possible risk areas in other countries with similar drivers. PMID:23202822

Higher Education Cost Drivers, Including Two Hidden Ones with Cost Containment Possibilities.

ERIC Educational Resources Information Center

Micceri, Ted

Identifying higher education cost drivers and working to limit their effects appears to be a necessity if higher education is to retain the support historically allocated by society. Costs occur for three groups: students, institutions, and society. This paper summarizes information about cost drivers in higher education and identifies two that…

Coalitional game theory as a promising approach to identify candidate autism genes.

PubMed

Gupta, Anika; Sun, Min Woo; Paskov, Kelley Marie; Stockham, Nate Tyler; Jung, Jae-Yoon; Wall, Dennis Paul

2018-01-01

Despite mounting evidence for the strong role of genetics in the phenotypic manifestation of Autism Spectrum Disorder (ASD), the specific genes responsible for the variable forms of ASD remain undefined. ASD may be best explained by a combinatorial genetic model with varying epistatic interactions across many small effect mutations. Coalitional or cooperative game theory is a technique that studies the combined effects of groups of players, known as coalitions, seeking to identify players who tend to improve the performance--the relationship to a specific disease phenotype--of any coalition they join. This method has been previously shown to boost biologically informative signal in gene expression data but to-date has not been applied to the search for cooperative mutations among putative ASD genes. We describe our approach to highlight genes relevant to ASD using coalitional game theory on alteration data of 1,965 fully sequenced genomes from 756 multiplex families. Alterations were encoded into binary matrices for ASD (case) and unaffected (control) samples, indicating likely gene-disrupting, inherited mutations in altered genes. To determine individual gene contributions given an ASD phenotype, a "player" metric, referred to as the Shapley value, was calculated for each gene in the case and control cohorts. Sixty seven genes were found to have significantly elevated player scores and likely represent significant contributors to the genetic coordination underlying ASD. Using network and cross-study analysis, we found that these genes are involved in biological pathways known to be affected in the autism cases and that a subset directly interact with several genes known to have strong associations to autism. These findings suggest that coalitional game theory can be applied to large-scale genomic data to identify hidden yet influential players in complex polygenic disorders such as autism.

The FUN of identifying gene function in bacterial pathogens; insights from Salmonella functional genomics.

PubMed

Hammarlöf, Disa L; Canals, Rocío; Hinton, Jay C D

2013-10-01

The availability of thousands of genome sequences of bacterial pathogens poses a particular challenge because each genome contains hundreds of genes of unknown function (FUN). How can we easily discover which FUN genes encode important virulence factors? One solution is to combine two different functional genomic approaches. First, transcriptomics identifies bacterial FUN genes that show differential expression during the process of mammalian infection. Second, global mutagenesis identifies individual FUN genes that the pathogen requires to cause disease. The intersection of these datasets can reveal a small set of candidate genes most likely to encode novel virulence attributes. We demonstrate this approach with the Salmonella infection model, and propose that a similar strategy could be used for other bacterial pathogens. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identifying Novel Transcriptional and Epigenetic Features of Nuclear Lamina-associated Genes.

PubMed

Wu, Feinan; Yao, Jie

2017-03-07

Because a large portion of the mammalian genome is associated with the nuclear lamina (NL), it is interesting to study how native genes resided there are transcribed and regulated. In this study, we report unique transcriptional and epigenetic features of nearly 3,500 NL-associated genes (NL genes). Promoter regions of active NL genes are often excluded from NL-association, suggesting that NL-promoter interactions may repress transcription. Active NL genes with higher RNA polymerase II (Pol II) recruitment levels tend to display Pol II promoter-proximal pausing, while Pol II recruitment and Pol II pausing are not correlated among non-NL genes. At the genome-wide scale, NL-association and H3K27me3 distinguishes two large gene classes with low transcriptional activities. Notably, NL-association is anti-correlated with both transcription and active histone mark levels among genes not significantly enriched with H3K9me3 or H3K27me3, suggesting that NL-association may represent a novel gene repression pathway. Interestingly, an NL gene subgroup is not significantly enriched with H3K9me3 or H3K27me3 and is transcribed at higher levels than the rest of NL genes. Furthermore, we identified distal enhancers associated with active NL genes and reported their epigenetic features.

Using reporter gene assays to identify cis regulatory differences between humans and chimpanzees.

PubMed

Chabot, Adrien; Shrit, Ralla A; Blekhman, Ran; Gilad, Yoav

2007-08-01

Most phenotypic differences between human and chimpanzee are likely to result from differences in gene regulation, rather than changes to protein-coding regions. To date, however, only a handful of human-chimpanzee nucleotide differences leading to changes in gene regulation have been identified. To hone in on differences in regulatory elements between human and chimpanzee, we focused on 10 genes that were previously found to be differentially expressed between the two species. We then designed reporter gene assays for the putative human and chimpanzee promoters of the 10 genes. Of seven promoters that we found to be active in human liver cell lines, human and chimpanzee promoters had significantly different activity in four cases, three of which recapitulated the gene expression difference seen in the microarray experiment. For these three genes, we were therefore able to demonstrate that a change in cis influences expression differences between humans and chimpanzees. Moreover, using site-directed mutagenesis on one construct, the promoter for the DDA3 gene, we were able to identify three nucleotides that together lead to a cis regulatory difference between the species. High-throughput application of this approach can provide a map of regulatory element differences between humans and our close evolutionary relatives.

Genome-Wide Association Study Identifies Candidate Genes for Starch Content Regulation in Maize Kernels

PubMed Central

Liu, Na; Xue, Yadong; Guo, Zhanyong; Li, Weihua; Tang, Jihua

2016-01-01

Kernel starch content is an important trait in maize (Zea mays L.) as it accounts for 65–75% of the dry kernel weight and positively correlates with seed yield. A number of starch synthesis-related genes have been identified in maize in recent years. However, many loci underlying variation in starch content among maize inbred lines still remain to be identified. The current study is a genome-wide association study that used a set of 263 maize inbred lines. In this panel, the average kernel starch content was 66.99%, ranging from 60.60 to 71.58% over the three study years. These inbred lines were genotyped with the SNP50 BeadChip maize array, which is comprised of 56,110 evenly spaced, random SNPs. Population structure was controlled by a mixed linear model (MLM) as implemented in the software package TASSEL. After the statistical analyses, four SNPs were identified as significantly associated with starch content (P ≤ 0.0001), among which one each are located on chromosomes 1 and 5 and two are on chromosome 2. Furthermore, 77 candidate genes associated with starch synthesis were found within the 100-kb intervals containing these four QTLs, and four highly associated genes were within 20-kb intervals of the associated SNPs. Among the four genes, Glucose-1-phosphate adenylyltransferase (APS1; Gene ID GRMZM2G163437) is known as an important regulator of kernel starch content. The identified SNPs, QTLs, and candidate genes may not only be readily used for germplasm improvement by marker-assisted selection in breeding, but can also elucidate the genetic basis of starch content. Further studies on these identified candidate genes may help determine the molecular mechanisms regulating kernel starch content in maize and other important cereal crops. PMID:27512395

A systematic study on drug-response associated genes using baseline gene expressions of the Cancer Cell Line Encyclopedia

NASA Astrophysics Data System (ADS)

Liu, Xiaoming; Yang, Jiasheng; Zhang, Yi; Fang, Yun; Wang, Fayou; Wang, Jun; Zheng, Xiaoqi; Yang, Jialiang

2016-03-01

We have studied drug-response associated (DRA) gene expressions by applying a systems biology framework to the Cancer Cell Line Encyclopedia data. More than 4,000 genes are inferred to be DRA for at least one drug, while the number of DRA genes for each drug varies dramatically from almost 0 to 1,226. Functional enrichment analysis shows that the DRA genes are significantly enriched in genes associated with cell cycle and plasma membrane. Moreover, there might be two patterns of DRA genes between genders. There are significantly shared DRA genes between male and female for most drugs, while very little DRA genes tend to be shared between the two genders for a few drugs targeting sex-specific cancers (e.g., PD-0332991 for breast cancer and ovarian cancer). Our analyses also show substantial difference for DRA genes between young and old samples, suggesting the necessity of considering the age effects for personalized medicine in cancers. Lastly, differential module and key driver analyses confirm cell cycle related modules as top differential ones for drug sensitivity. The analyses also reveal the role of TSPO, TP53, and many other immune or cell cycle related genes as important key drivers for DRA network modules. These key drivers provide new drug targets to improve the sensitivity of cancer therapy.

GENE EXPRESSION PROFILING TO IDENTIFY MECHANISMS OF MALE REPRODUCTIVE TOXICITY

EPA Science Inventory

Gene Expression Profiling to Identify Mechanisms of Male Reproductive Toxicity
David J. Dix
National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA.
Ab...

Graduated driver licensing for reducing motor vehicle crashes among young drivers.

PubMed

Hartling, L; Wiebe, N; Russell, K; Petruk, J; Spinola, C; Klassen, T P

2004-01-01

Graduated driver licensing (GDL) has been proposed as a means of reducing crash rates among novice drivers by gradually introducing them to higher risk driving situations. To examine the effectiveness of GDL systems in reducing crash rates of young drivers. Studies were identified through searches of MEDLINE, EMBASE, CINAHL, Healthstar, Web of Science, NTIS Bibliographic Database, TRIS Online, SIGLE, the World Wide Web, relevant conference proceedings, consultation with experts and authors, and reference lists. The search was not restricted by language or publication status. Studies were included if: 1) they compared outcomes pre- and post-implementation of a GDL program within the same jurisdiction, 2) comparisons were made between jurisdictions with and without GDL, or 3) both. Studies had to report at least one objective, quantified outcome. Two reviewers independently screened searches and assessed the full text of potentially relevant studies for inclusion using a standard form. Data were extracted by one reviewer and checked by a second. Additional data were requested from authors. Results were not pooled due to substantial heterogeneity between studies. Percentage change was calculated for each year after the intervention, using one year prior to the intervention as the baseline rate. Results were adjusted by internal controls. Analyses were stratified by different denominators (population, licensed drivers). Results were calculated for the different crash types (overall, injury, fatal, night-time, alcohol, and those resulting in hospitalization). Results were presented for 16 year-olds alone and all teenage drivers combined. We included 13 studies evaluating 12 GDL programs that were implemented between 1979 and 1998 in the US (n=7), Canada (3), New Zealand (1), and Australia (1). Programs varied in their restrictions during the intermediate stage: e.g. night curfews (8); limitations of extra passengers (2); roadway restrictions (1). Based on the Insurance

An examination of the environmental, driver and vehicle factors associated with the serious and fatal crashes of older rural drivers.

PubMed

Thompson, J P; Baldock, M R J; Mathias, J L; Wundersitz, L N

2013-01-01

Motor vehicle crashes involving rural drivers aged 75 years and over are more than twice as likely to result in a serious or fatal injury as those involving their urban counterparts. The current study examined some of the reasons for this using a database of police-reported crashes (2004-2008) to identify the environmental (lighting, road and weather conditions, road layout, road surface, speed limit), driver (driver error, crash type), and vehicle (vehicle age) factors that are associated with the crashes of older rural drivers. It also determined whether these same factors are associated with an increased likelihood of serious or fatal injury in younger drivers for whom frailty does not contribute to the resulting injury severity. A number of environmental (i.e., undivided, unsealed, curved and inclined roads, and areas with a speed limit of 100km/h or greater) and driver (i.e., collision with a fixed object and rolling over) factors were more frequent in the crashes of older rural drivers and additionally associated with increased injury severity in younger drivers. Moreover, when these environmental factors were entered into a logistic regression model to predict whether older drivers who were involved in crashes did or did not sustain a serious or fatal injury, it was found that each factor independently increased the likelihood of a serious or fatal injury. Changes, such as the provision of divided and sealed roads, greater protection from fixed roadside objects, and reduced speed limits, appear to be indicated in order to improve the safety of the rural driving environment for drivers of all ages. Additionally, older rural drivers should be encouraged to reduce their exposure to these risky circumstances. Copyright © 2012 Elsevier Ltd. All rights reserved.

Medical review of fitness to drive in older drivers: the Maryland experience.

PubMed

Soderstrom, Carl A; Joyce, John J

2008-08-01

Over the next several decades, both the number and percentage of older drivers will increase dramatically. Older age is inherently associated with medical conditions, particularly those involving cognition and vision, that can affect medical fitness to drive. Over a 60-year period, the Maryland Motor Vehicle Administration (MVA) in conjunction with its medical advisory board (MAB) has matured a comprehensive system to identify at-risk older drivers and to assess their medical fitness to drive. This paper describes the medical review process in general, and in particular for older drivers, that has evolved in the state of Maryland. The resources, philosophy and research underpinnings of its MAB review process are examined. Studies of functional screening measures in older drivers indicate that older drivers at risk of being at-fault for future crashes can be identified. The feasibility of using such screening measures for drivers referred to the MVA has been confirmed by practical use for a period of seven years. It is possible to create a medical review process with a goal of "safe mobility for life" that supports preservation of the driving privilege among many older drivers.

Network perturbation by recurrent regulatory variants in cancer

PubMed Central

Cho, Ara; Lee, Insuk; Choi, Jung Kyoon

2017-01-01

Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes. PMID:28333928

The effects of mutational processes and selection on driver mutations across cancer types.

PubMed

Temko, Daniel; Tomlinson, Ian P M; Severini, Simone; Schuster-Böckler, Benjamin; Graham, Trevor A

2018-05-10

Epidemiological evidence has long associated environmental mutagens with increased cancer risk. However, links between specific mutation-causing processes and the acquisition of individual driver mutations have remained obscure. Here we have used public cancer sequencing data from 11,336 cancers of various types to infer the independent effects of mutation and selection on the set of driver mutations in a cancer type. First, we detect associations between a range of mutational processes, including those linked to smoking, ageing, APOBEC and DNA mismatch repair (MMR) and the presence of key driver mutations across cancer types. Second, we quantify differential selection between well-known alternative driver mutations, including differences in selection between distinct mutant residues in the same gene. These results show that while mutational processes have a large role in determining which driver mutations are present in a cancer, the role of selection frequently dominates.

Child passengers and driver culpability in fatal crashes by driver gender.

PubMed

Maasalo, Ida; Lehtonen, Esko; Pekkanen, Jami; Summala, Heikki

2016-07-03

Studies based on accident statistics generally suggest that the presence of a passenger reduces adult drivers' accident risk. However, passengers have been reported to be a source of distraction in a remarkable portion of distraction-related crashes. Although the effect of passengers on driving performance has been studied extensively, few studies have focused on how a child passenger affects the driver.  A child in a car is a potential distractor for parents, especially for mothers of small children, who often suffer from sleep deficit. The aim of this study was to examine how the presence of child passengers of different ages is associated with a higher driver culpability, which was expected due to child-related distraction and fatigue. The analysis was based on the comprehensive data of fatal crashes studied in-depth by multidisciplinary road accident investigation teams in Finland during 1988-2012. Teams determine the primary party who had the most crucial effect on the origin of the event. We define the primary party as culpable and the others involved as nonculpable drivers. The culpability rate was defined as the percentage of culpable drivers and rates were compared for drivers with a child/teen passenger aged 0-17 years (N = 348), with an adult passenger without children (N = 324), and when driving alone (N = 579), grouped by child age and driver gender.  Drivers with specific risk-related behavior (substantial speeding, driving when intoxicated, unbelted, or without a license) were excluded from the analyses, in order to make the drivers with and without children comparable. Only drivers 26-47 years old were included, representing parents with children 0-9 years of age. Male drivers were less often culpable with 0- to 17-year-old passengers in the car than alone or with adults. This was not the case with female drivers. The gender difference in culpability was most marked with small children age 0-4 years. Female drivers' culpability rate with a 0

A data mining paradigm for identifying key factors in biological processes using gene expression data.

PubMed

Li, Jin; Zheng, Le; Uchiyama, Akihiko; Bin, Lianghua; Mauro, Theodora M; Elias, Peter M; Pawelczyk, Tadeusz; Sakowicz-Burkiewicz, Monika; Trzeciak, Magdalena; Leung, Donald Y M; Morasso, Maria I; Yu, Peng

2018-06-13

A large volume of biological data is being generated for studying mechanisms of various biological processes. These precious data enable large-scale computational analyses to gain biological insights. However, it remains a challenge to mine the data efficiently for knowledge discovery. The heterogeneity of these data makes it difficult to consistently integrate them, slowing down the process of biological discovery. We introduce a data processing paradigm to identify key factors in biological processes via systematic collection of gene expression datasets, primary analysis of data, and evaluation of consistent signals. To demonstrate its effectiveness, our paradigm was applied to epidermal development and identified many genes that play a potential role in this process. Besides the known epidermal development genes, a substantial proportion of the identified genes are still not supported by gain- or loss-of-function studies, yielding many novel genes for future studies. Among them, we selected a top gene for loss-of-function experimental validation and confirmed its function in epidermal differentiation, proving the ability of this paradigm to identify new factors in biological processes. In addition, this paradigm revealed many key genes in cold-induced thermogenesis using data from cold-challenged tissues, demonstrating its generalizability. This paradigm can lead to fruitful results for studying molecular mechanisms in an era of explosive accumulation of publicly available biological data.

X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes.

PubMed

Hu, H; Haas, S A; Chelly, J; Van Esch, H; Raynaud, M; de Brouwer, A P M; Weinert, S; Froyen, G; Frints, S G M; Laumonnier, F; Zemojtel, T; Love, M I; Richard, H; Emde, A-K; Bienek, M; Jensen, C; Hambrock, M; Fischer, U; Langnick, C; Feldkamp, M; Wissink-Lindhout, W; Lebrun, N; Castelnau, L; Rucci, J; Montjean, R; Dorseuil, O; Billuart, P; Stuhlmann, T; Shaw, M; Corbett, M A; Gardner, A; Willis-Owen, S; Tan, C; Friend, K L; Belet, S; van Roozendaal, K E P; Jimenez-Pocquet, M; Moizard, M-P; Ronce, N; Sun, R; O'Keeffe, S; Chenna, R; van Bömmel, A; Göke, J; Hackett, A; Field, M; Christie, L; Boyle, J; Haan, E; Nelson, J; Turner, G; Baynam, G; Gillessen-Kaesbach, G; Müller, U; Steinberger, D; Budny, B; Badura-Stronka, M; Latos-Bieleńska, A; Ousager, L B; Wieacker, P; Rodríguez Criado, G; Bondeson, M-L; Annerén, G; Dufke, A; Cohen, M; Van Maldergem, L; Vincent-Delorme, C; Echenne, B; Simon-Bouy, B; Kleefstra, T; Willemsen, M; Fryns, J-P; Devriendt, K; Ullmann, R; Vingron, M; Wrogemann, K; Wienker, T F; Tzschach, A; van Bokhoven, H; Gecz, J; Jentsch, T J; Chen, W; Ropers, H-H; Kalscheuer, V M

2016-01-01

X-linked intellectual disability (XLID) is a clinically and genetically heterogeneous disorder. During the past two decades in excess of 100 X-chromosome ID genes have been identified. Yet, a large number of families mapping to the X-chromosome remained unresolved suggesting that more XLID genes or loci are yet to be identified. Here, we have investigated 405 unresolved families with XLID. We employed massively parallel sequencing of all X-chromosome exons in the index males. The majority of these males were previously tested negative for copy number variations and for mutations in a subset of known XLID genes by Sanger sequencing. In total, 745 X-chromosomal genes were screened. After stringent filtering, a total of 1297 non-recurrent exonic variants remained for prioritization. Co-segregation analysis of potential clinically relevant changes revealed that 80 families (20%) carried pathogenic variants in established XLID genes. In 19 families, we detected likely causative protein truncating and missense variants in 7 novel and validated XLID genes (CLCN4, CNKSR2, FRMPD4, KLHL15, LAS1L, RLIM and USP27X) and potentially deleterious variants in 2 novel candidate XLID genes (CDK16 and TAF1). We show that the CLCN4 and CNKSR2 variants impair protein functions as indicated by electrophysiological studies and altered differentiation of cultured primary neurons from Clcn4(-/-) mice or after mRNA knock-down. The newly identified and candidate XLID proteins belong to pathways and networks with established roles in cognitive function and intellectual disability in particular. We suggest that systematic sequencing of all X-chromosomal genes in a cohort of patients with genetic evidence for X-chromosome locus involvement may resolve up to 58% of Fragile X-negative cases.

X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes

PubMed Central

Hu, H; Haas, S A; Chelly, J; Van Esch, H; Raynaud, M; de Brouwer, A P M; Weinert, S; Froyen, G; Frints, S G M; Laumonnier, F; Zemojtel, T; Love, M I; Richard, H; Emde, A-K; Bienek, M; Jensen, C; Hambrock, M; Fischer, U; Langnick, C; Feldkamp, M; Wissink-Lindhout, W; Lebrun, N; Castelnau, L; Rucci, J; Montjean, R; Dorseuil, O; Billuart, P; Stuhlmann, T; Shaw, M; Corbett, M A; Gardner, A; Willis-Owen, S; Tan, C; Friend, K L; Belet, S; van Roozendaal, K E P; Jimenez-Pocquet, M; Moizard, M-P; Ronce, N; Sun, R; O'Keeffe, S; Chenna, R; van Bömmel, A; Göke, J; Hackett, A; Field, M; Christie, L; Boyle, J; Haan, E; Nelson, J; Turner, G; Baynam, G; Gillessen-Kaesbach, G; Müller, U; Steinberger, D; Budny, B; Badura-Stronka, M; Latos-Bieleńska, A; Ousager, L B; Wieacker, P; Rodríguez Criado, G; Bondeson, M-L; Annerén, G; Dufke, A; Cohen, M; Van Maldergem, L; Vincent-Delorme, C; Echenne, B; Simon-Bouy, B; Kleefstra, T; Willemsen, M; Fryns, J-P; Devriendt, K; Ullmann, R; Vingron, M; Wrogemann, K; Wienker, T F; Tzschach, A; van Bokhoven, H; Gecz, J; Jentsch, T J; Chen, W; Ropers, H-H; Kalscheuer, V M

2016-01-01

X-linked intellectual disability (XLID) is a clinically and genetically heterogeneous disorder. During the past two decades in excess of 100 X-chromosome ID genes have been identified. Yet, a large number of families mapping to the X-chromosome remained unresolved suggesting that more XLID genes or loci are yet to be identified. Here, we have investigated 405 unresolved families with XLID. We employed massively parallel sequencing of all X-chromosome exons in the index males. The majority of these males were previously tested negative for copy number variations and for mutations in a subset of known XLID genes by Sanger sequencing. In total, 745 X-chromosomal genes were screened. After stringent filtering, a total of 1297 non-recurrent exonic variants remained for prioritization. Co-segregation analysis of potential clinically relevant changes revealed that 80 families (20%) carried pathogenic variants in established XLID genes. In 19 families, we detected likely causative protein truncating and missense variants in 7 novel and validated XLID genes (CLCN4, CNKSR2, FRMPD4, KLHL15, LAS1L, RLIM and USP27X) and potentially deleterious variants in 2 novel candidate XLID genes (CDK16 and TAF1). We show that the CLCN4 and CNKSR2 variants impair protein functions as indicated by electrophysiological studies and altered differentiation of cultured primary neurons from Clcn4−/− mice or after mRNA knock-down. The newly identified and candidate XLID proteins belong to pathways and networks with established roles in cognitive function and intellectual disability in particular. We suggest that systematic sequencing of all X-chromosomal genes in a cohort of patients with genetic evidence for X-chromosome locus involvement may resolve up to 58% of Fragile X-negative cases. PMID:25644381

A Genome-Wide Knockout Screen to Identify Genes Involved in Acquired Carboplatin Resistance

DTIC Science & Technology

2016-07-01

library screen to identify genes that when knocked out render human ovarian cells > 2.5-fold resistant to CBDCA; 2) Validate the ability of...a GeCKOv2 library screen to identify genes that when knocked out render human ovarian cells > 2.5-fold resistant to CBDCA; 2) validate the ability of...resistance in either cell lines or clinical samples. The CRIPSR-cas9 technology now provides us with a major new tool to introduce knock out mutations

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

A Fresh Look at Driver Education in America

DOT National Transportation Integrated Search

2012-04-01

The objectives of this study were to: (1) identify and review current driver education and training programs in use nationally and : internationally; (2) identify best teaching practices for teenagers; (3) examine the optimal sequencing for the prese...

Dynamics of Driver Distraction: The process of engaging and disengaging

PubMed Central

Lee, John D.

2014-01-01

Driver distraction research has a long history, spanning nearly 50 years, but intensifying over the last decade. The dominant paradigm guiding this research defines distraction in terms of excessive workload and limited attentional resources. This approach largely ignores how drivers come to engage in these tasks and under what conditions they engage and disengage from driving—the dynamics of distraction. The dynamics of distraction identifies breakdowns of interruption management as an important contributor to distraction, leading to describe distraction in terms of failures of task timing, switching, and prioritization. The dynamics of distraction also identifies disengagement in driving (e.g., mind wandering) as a substantial challenge that secondary tasks might exacerbate or mitigate. Increasing vehicle automation accentuates the need to consider these dynamics of distraction. Automation offers drivers more opportunity to engage in distractions and disengage from driving, and can surprise drivers by unexpectedly requiring drivers to quickly re-engage in driving—placing greater importance of interruption management expertise. This review describes distraction in terms of breakdowns in interruption management and problems of engagement, and summarizes how contingency, conditioning, and consequence traps lead to problems of engaging and disengaging in driving and distractions. PMID:24776224

Identifying novel genes and chemicals related to nasopharyngeal cancer in a heterogeneous network.

PubMed

Li, Zhandong; An, Lifeng; Li, Hao; Wang, ShaoPeng; Zhou, You; Yuan, Fei; Li, Lin

2016-05-05

Nasopharyngeal cancer or nasopharyngeal carcinoma (NPC) is the most common cancer originating in the nasopharynx. The factors that induce nasopharyngeal cancer are still not clear. Additional information about the chemicals or genes related to nasopharyngeal cancer will promote a better understanding of the pathogenesis of this cancer and the factors that induce it. Thus, a computational method NPC-RGCP was proposed in this study to identify the possible relevant chemicals and genes based on the presently known chemicals and genes related to nasopharyngeal cancer. To extensively utilize the functional associations between proteins and chemicals, a heterogeneous network was constructed based on interactions of proteins and chemicals. The NPC-RGCP included two stages: the searching stage and the screening stage. The former stage is for finding new possible genes and chemicals in the heterogeneous network, while the latter stage is for screening and removing false discoveries and selecting the core genes and chemicals. As a result, five putative genes, CXCR3, IRF1, CDK1, GSTP1, and CDH2, and seven putative chemicals, iron, propionic acid, dimethyl sulfoxide, isopropanol, erythrose 4-phosphate, β-D-Fructose 6-phosphate, and flavin adenine dinucleotide, were identified by NPC-RGCP. Extensive analyses provided confirmation that the putative genes and chemicals have significant associations with nasopharyngeal cancer.

Identifying novel genes and chemicals related to nasopharyngeal cancer in a heterogeneous network

PubMed Central

Li, Zhandong; An, Lifeng; Li, Hao; Wang, ShaoPeng; Zhou, You; Yuan, Fei; Li, Lin

2016-01-01

Nasopharyngeal cancer or nasopharyngeal carcinoma (NPC) is the most common cancer originating in the nasopharynx. The factors that induce nasopharyngeal cancer are still not clear. Additional information about the chemicals or genes related to nasopharyngeal cancer will promote a better understanding of the pathogenesis of this cancer and the factors that induce it. Thus, a computational method NPC-RGCP was proposed in this study to identify the possible relevant chemicals and genes based on the presently known chemicals and genes related to nasopharyngeal cancer. To extensively utilize the functional associations between proteins and chemicals, a heterogeneous network was constructed based on interactions of proteins and chemicals. The NPC-RGCP included two stages: the searching stage and the screening stage. The former stage is for finding new possible genes and chemicals in the heterogeneous network, while the latter stage is for screening and removing false discoveries and selecting the core genes and chemicals. As a result, five putative genes, CXCR3, IRF1, CDK1, GSTP1, and CDH2, and seven putative chemicals, iron, propionic acid, dimethyl sulfoxide, isopropanol, erythrose 4-phosphate, β-D-Fructose 6-phosphate, and flavin adenine dinucleotide, were identified by NPC-RGCP. Extensive analyses provided confirmation that the putative genes and chemicals have significant associations with nasopharyngeal cancer. PMID:27149165

A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking

PubMed Central

Huan, Tianxiao; Joehanes, Roby; Schurmann, Claudia; Schramm, Katharina; Pilling, Luke C.; Peters, Marjolein J.; Mägi, Reedik; DeMeo, Dawn; O'Connor, George T.; Ferrucci, Luigi; Teumer, Alexander; Homuth, Georg; Biffar, Reiner; Völker, Uwe; Herder, Christian; Waldenberger, Melanie; Peters, Annette; Zeilinger, Sonja; Metspalu, Andres; Hofman, Albert; Uitterlinden, André G.; Hernandez, Dena G.; Singleton, Andrew B.; Bandinelli, Stefania; Munson, Peter J.; Lin, Honghuang; Benjamin, Emelia J.; Esko, Tõnu; Grabe, Hans J.; Prokisch, Holger; van Meurs, Joyce B.J.; Melzer, David; Levy, Daniel

2016-01-01

Abstract Cigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a meta-analysis of transcriptome-wide gene expression using whole blood-derived RNA from 10,233 participants of European ancestry in six cohorts (including 1421 current and 3955 former smokers) to identify associations between smoking and altered gene expression levels. At a false discovery rate (FDR) <0.1, we identified 1270 differentially expressed genes in current vs. never smokers, and 39 genes in former vs. never smokers. Expression levels of 12 genes remained elevated up to 30 years after smoking cessation, suggesting that the molecular consequence of smoking may persist for decades. Gene ontology analysis revealed enrichment of smoking-related genes for activation of platelets and lymphocytes, immune response, and apoptosis. Many of the top smoking-related differentially expressed genes, including LRRN3 and GPR15, have DNA methylation loci in promoter regions that were recently reported to be hypomethylated among smokers. By linking differential gene expression with smoking-related disease phenotypes, we demonstrated that stroke and pulmonary function show enrichment for smoking-related gene expression signatures. Mediation analysis revealed the expression of several genes (e.g. ALAS2) to be putative mediators of the associations between smoking and inflammatory biomarkers (IL6 and C-reactive protein levels). Our transcriptomic study provides potential insights into the effects of cigarette smoking on gene expression in whole blood and their relations to smoking-related diseases. The results of such analyses may highlight attractive targets for treating or preventing smoking-related health effects. PMID:28158590

Resistance gene candidates identified by PCR with degenerate oligonucleotide primers map to clusters of resistance genes in lettuce.