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Background: Mucinous neoplasms of the appendix (MNA) are rare tumors which may progress from benign to malignant disease with an aggressive biological behavior. MNA is often diagnosed after metastasis to the peritoneal surfaces resulting in mucinous carcinomatosis peritonei (MCP). Genetic alterations in MNA are poorly characterized due to its low incidence, the hypo-cellularity of MCPs, and a lack of relevant pre-clinical models. As such, application of targeted therapies to this disease is limited to those developed for colorectal cancer and not based on molecular rationale., Methods: We sequenced the whole exomes of 10 MCPs of appendiceal origin to identify genome-wide somatic mutations and copy number aberrations and validated significant findings in 19 additional cases., Results: Our study demonstrates that MNA has a different molecular makeup than colorectal cancer. Most tumors have co-existing oncogenic mutations in KRAS (26/29) and GNAS (20/29) and are characterized by downstream PKA activation. High-grade tumors are GNAS wild-type (5/6), suggesting they do not progress from low-grade tumors. MNAs do share some genetic alterations with colorectal cancer including gain of 1q (5/10), Wnt, and TGFβ pathway alterations. In contrast, mutations in TP53 (1/10) and APC (0/10), common in colorectal cancer, are rare in MNA. Concurrent activation of the KRAS and GNAS mediated signaling pathways appears to be shared with pancreatic intraductal papillary mucinous neoplasm., Conclusions: MNA genome-wide mutational analysis reveals genetic alterations distinct from colorectal cancer, in support of its unique pathophysiology and suggests new targeted therapeutic opportunities.

Cellular membranes act as signaling platforms and control solute transport. Membrane receptors, transporters, and enzymes communicate with intracellular processes through protein-protein interactions. Using a split-ubiquitin yeast two-hybrid screen that covers a test-space of 6.4 × 10(6) pairs, we identified 12,102 membrane/signaling protein interactions from Arabidopsis. Besides confirmation of expected interactions such as heterotrimeric G protein subunit interactions and aquaporin oligomerization, >99% of the interactions were previously unknown. Interactions were confirmed at a rate of 32% in orthogonal in planta split-green flourescent protein interaction assays, which was statistically indistinguishable from the confirmation rate for known interactions collected from literature (38%). Regulatory associations in membrane protein trafficking, turnover, and phosphorylation include regulation of potassium channel activity through abscisic acid signaling, transporter activity by a WNK kinase, and a brassinolide receptor kinase by trafficking-related proteins. These examples underscore the utility of the membrane/signaling protein interaction network for gene discovery and hypothesis generation in plants and other organisms., (Copyright © 2014, American Association for the Advancement of Science.)

Background: Genotypes generated in next generation sequencing studies contain errors which can significantly impact the power to detect signals in common and rare variant association tests. These genotyping errors are not explicitly filtered by the standard GATK Variant Quality Score Recalibration (VQSR) tool and thus remain a source of errors in whole exome sequencing (WES) projects that follow GATK's recommended best practices. Therefore, additional data filtering methods are required to effectively remove these errors before performing association analyses with complex phenotypes. Here we empirically derive thresholds for genotype and variant filters that, when used in conjunction with the VQSR tool, achieve higher data quality than when using VQSR alone., Results: The detailed filtering strategies improve the concordance of sequenced genotypes with array genotypes from 99.33% to 99.77%; improve the percent of discordant genotypes removed from 10.5% to 69.5%; and improve the Ti/Tv ratio from 2.63 to 2.75. We also demonstrate that managing batch effects by separating samples based on different target capture and sequencing chemistry protocols results in a final data set containing 40.9% more high-quality variants. In addition, imputation is an important component of WES studies and is used to estimate common variant genotypes to generate additional markers for association analyses. As such, we demonstrate filtering methods for imputed data that improve genotype concordance from 79.3% to 99.8% while removing 99.5% of discordant genotypes., Conclusions: The described filtering methods are advantageous for large population-based WES studies designed to identify common and rare variation associated with complex diseases. Compared to data processed through standard practices, these strategies result in substantially higher quality data for common and rare association analyses.

Background: Although it has long been proposed that genetic factors contribute to adaptation to high altitude, such factors remain largely unverified. Recent advances in high-throughput sequencing have made it feasible to analyze genome-wide patterns of genetic variation in human populations. Since traditionally such studies surveyed only a small fraction of the genome, interpretation of the results was limited., Results: We report here the results of the first whole genome resequencing-based analysis identifying genes that likely modulate high altitude adaptation in native Ethiopians residing at 3,500 m above sea level on Bale Plateau or Chennek field in Ethiopia. Using cross-population tests of selection, we identify regions with a significant loss of diversity, indicative of a selective sweep. We focus on a 208 kbp gene-rich region on chromosome 19, which is significant in both of the Ethiopian subpopulations sampled. This region contains eight protein-coding genes and spans 135 SNPs. To elucidate its potential role in hypoxia tolerance, we experimentally tested whether individual genes from the region affect hypoxia tolerance in Drosophila. Three genes significantly impact survival rates in low oxygen: cic, an ortholog of human CIC, Hsl, an ortholog of human LIPE, and Paf-AHα, an ortholog of human PAFAH1B3., Conclusions: Our study reveals evolutionarily conserved genes that modulate hypoxia tolerance. In addition, we show that many of our results would likely be unattainable using data from exome sequencing or microarray studies. This highlights the importance of whole genome sequencing for investigating adaptation by natural selection.

Background: The National Children's Study (NCS) is a prospective epidemiological study in the USA tasked with identifying a nationally representative sample of 100,000 children, and following them from their gestation until they are 21 years of age. The objective of the study is to measure environmental and genetic influences on growth, development, and health. Determination of the ancestry of these NCS participants is important for assessing the diversity of study participants and for examining the effect of ancestry on various health outcomes., Results: We estimated the genetic ancestry of a convenience sample of 641 parents enrolled at the 7 original NCS Vanguard sites, by analyzing 30,000 markers on exome arrays, using the 1000 Genomes Project superpopulations as reference populations, and compared this with the measures of self-reported ethnicity and race. For 99% of the individuals, self-reported ethnicity and race agreed with the predicted superpopulation. NCS individuals self-reporting as Asian had genetic ancestry of either South Asian or East Asian groups, while those reporting as either Hispanic White or Hispanic Other had similar genetic ancestry. Of the 33 individuals who self-reported as Multiracial or Non-Hispanic Other, 33% matched the South Asian or East Asian groups, while these groups represented only 4.4% of the other reported categories., Conclusions: Our data suggest that self-reported ethnicity and race have some limitations in accurately capturing Hispanic and South Asian populations. Overall, however, our data indicate that despite the complexity of the US population, individuals know their ancestral origins, and that self-reported ethnicity and race is a reliable indicator of genetic ancestry.

Hepatocellular carcinoma (HCC) is a slowly developing malignancy postulated to evolve from premalignant lesions in chronically damaged livers. However, it was never established that premalignant lesions actually contain tumor progenitors that give rise to cancer. Here, we describe isolation and characterization of HCC progenitor cells (HcPCs) from different mouse HCC models. Unlike fully malignant HCC, HcPCs give rise to cancer only when introduced into a liver undergoing chronic damage and compensatory proliferation. Although HcPCs exhibit a similar transcriptomic profile to bipotential hepatobiliary progenitors, the latter do not give rise to tumors. Cells resembling HcPCs reside within dysplastic lesions that appear several months before HCC nodules. Unlike early hepatocarcinogenesis, which depends on paracrine IL-6 production by inflammatory cells, due to upregulation of LIN28 expression, HcPCs had acquired autocrine IL-6 signaling that stimulates their in vivo growth and malignant progression. This may be a general mechanism that drives other IL-6-producing malignancies., (Copyright © 2013 Elsevier Inc. All rights reserved.)

The hypoxic conditions at high altitudes present a challenge for survival, causing pressure for adaptation. Interestingly, many high-altitude denizens (particularly in the Andes) are maladapted, with a condition known as chronic mountain sickness (CMS) or Monge disease. To decode the genetic basis of this disease, we sequenced and compared the whole genomes of 20 Andean subjects (10 with CMS and 10 without). We discovered 11 regions genome-wide with significant differences in haplotype frequencies consistent with selective sweeps. In these regions, two genes (an erythropoiesis regulator, SENP1, and an oncogene, ANP32D) had a higher transcriptional response to hypoxia in individuals with CMS relative to those without. We further found that downregulating the orthologs of these genes in flies dramatically enhanced survival rates under hypoxia, demonstrating that suppression of SENP1 and ANP32D plays an essential role in hypoxia tolerance. Our study provides an unbiased framework to identify and validate the genetic basis of adaptation to high altitudes and identifies potentially targetable mechanisms for CMS treatment., (Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Primary central nervous system lymphomas (PCNSL) have a dramatically increased prevalence among persons living with AIDS and are known to be associated with human Epstein Barr virus (EBV) infection. Previous work suggests that in some cases, co-infection with other viruses may be important for PCNSL pathogenesis. Viral transcription in tumor samples can be measured using next generation transcriptome sequencing. We demonstrate the ability of transcriptome sequencing to identify viruses, characterize viral expression, and identify viral variants by sequencing four archived AIDS-related PCNSL tissue samples and analyzing raw sequencing reads. EBV was detected in all four PCNSL samples and cytomegalovirus (CMV), JC polyomavirus (JCV), and HIV were also discovered, consistent with clinical diagnoses. CMV was found to express three long non-coding RNAs recently reported as expressed during active infection. Single nucleotide variants were observed in each of the viruses observed and three indels were found in CMV. No viruses were found in several control tumor types including 32 diffuse large B-cell lymphoma samples. This study demonstrates the ability of next generation transcriptome sequencing to accurately identify viruses, including DNA viruses, in solid human cancer tissue samples.

Summary: We present Mutascope, a sequencing analysis pipeline specifically developed for the identification of somatic variants present at low-allelic fraction from high-throughput sequencing of amplicons from matched tumor-normal specimen. Using datasets reproducing tumor genetic heterogeneity, we demonstrate that Mutascope has a higher sensitivity and generates fewer false-positive calls than tools designed for shotgun sequencing or diploid genomes., Availability: Freely available on the web at http://sourceforge.net/projects/mutascope/., Contact: oharismendy@ucsd.edu, Supplementary Information: Supplementary data are available at Bioinformatics online.

Although the potential for genomics to contribute to clinical care has long been anticipated, the pace of defining the risks and benefits of incorporating genomic findings into medical practice has been relatively slow. Several institutions have recently begun genomic medicine programs, encountering many of the same obstacles and developing the same solutions, often independently. Recognizing that successful early experiences can inform subsequent efforts, the National Human Genome Research Institute brought together a number of these groups to describe their ongoing projects and challenges, identify common infrastructure and research needs, and outline an implementation framework for investigating and introducing similar programs elsewhere. Chief among the challenges were limited evidence and consensus on which genomic variants were medically relevant; lack of reimbursement for genomically driven interventions; and burden to patients and clinicians of assaying, reporting, intervening, and following up genomic findings. Key infrastructure needs included an openly accessible knowledge base capturing sequence variants and their phenotypic associations and a framework for defining and cataloging clinically actionable variants. Multiple institutions are actively engaged in using genomic information in clinical care. Much of this work is being done in isolation and would benefit from more structured collaboration and sharing of best practices.Genet Med 2013:15(4):258-267.

Leukemia stem cells (LSCs) play a pivotal role in the resistance of chronic myeloid leukemia (CML) to tyrosine kinase inhibitors (TKIs) and its progression to blast crisis (BC), in part, through the alternative splicing of self-renewal and survival genes. To elucidate splice-isoform regulators of human BC LSC maintenance, we performed whole-transcriptome RNA sequencing, splice-isoform-specific quantitative RT-PCR (qRT-PCR), nanoproteomics, stromal coculture, and BC LSC xenotransplantation analyses. Cumulatively, these studies show that the alternative splicing of multiple prosurvival BCL2 family genes promotes malignant transformation of myeloid progenitors into BC LSCS that are quiescent in the marrow niche and that contribute to therapeutic resistance. Notably, sabutoclax, a pan-BCL2 inhibitor, renders marrow-niche-resident BC LSCs sensitive to TKIs at doses that spare normal progenitors. These findings underscore the importance of alternative BCL2 family splice-isoform expression in BC LSC maintenance and suggest that the combinatorial inhibition of prosurvival BCL2 family proteins and BCR-ABL may eliminate dormant LSCs and obviate resistance., (Copyright © 2013 Elsevier Inc. All rights reserved.)

The molecular etiology of human progenitor reprogramming into self-renewing leukemia stem cells (LSC) has remained elusive. Although DNA sequencing has uncovered spliceosome gene mutations that promote alternative splicing and portend leukemic transformation, isoform diversity also may be generated by RNA editing mediated by adenosine deaminase acting on RNA (ADAR) enzymes that regulate stem cell maintenance. In this study, whole-transcriptome sequencing of normal, chronic phase, and serially transplantable blast crisis chronic myeloid leukemia (CML) progenitors revealed increased IFN-γ pathway gene expression in concert with BCR-ABL amplification, enhanced expression of the IFN-responsive ADAR1 p150 isoform, and a propensity for increased adenosine-to-inosine RNA editing during CML progression. Lentiviral overexpression experiments demonstrate that ADAR1 p150 promotes expression of the myeloid transcription factor PU.1 and induces malignant reprogramming of myeloid progenitors. Moreover, enforced ADAR1 p150 expression was associated with production of a misspliced form of GSK3β implicated in LSC self-renewal. Finally, functional serial transplantation and shRNA studies demonstrate that ADAR1 knockdown impaired in vivo self-renewal capacity of blast crisis CML progenitors. Together these data provide a compelling rationale for developing ADAR1-based LSC detection and eradication strategies.

Recent advances in the ability to efficiently characterize tumor genomes is enabling targeted drug development, which requires rigorous biomarker-based patient selection to increase effectiveness. Consequently, representative DNA biomarkers become equally important in pre-clinical studies. However, it is still unclear how well these markers are maintained between the primary tumor and the patient-derived tumor models. Here, we report the comprehensive identification of somatic coding mutations and copy number aberrations in four glioblastoma (GBM) primary tumors and their matched pre-clinical models: serum-free neurospheres, adherent cell cultures, and mouse xenografts. We developed innovative methods to improve the data quality and allow a strict comparison of matched tumor samples. Our analysis identifies known GBM mutations altering PTEN and TP53 genes, and new actionable mutations such as the loss of PIK3R1, and reveals clear patient-to-patient differences. In contrast, for each patient, we do not observe any significant remodeling of the mutational profile between primary to model tumors and the few discrepancies can be attributed to stochastic errors or differences in sample purity. Similarly, we observe ∼96% primary-to-model concordance in copy number calls in the high-cellularity samples. In contrast to previous reports based on gene expression profiles, we do not observe significant differences at the DNA level between in vitro compared to in vivo models. This study suggests, at a remarkable resolution, the genome-wide conservation of a patient's tumor genetics in various pre-clinical models, and therefore supports their use for the development and testing of personalized targeted therapies.

Background: The only therapeutic options that exist for squamous cell lung carcinoma (SCC) are standard radiation and cytotoxic chemotherapy. Cancer stem cells (CSCs) are hypothesized to account for therapeutic resistance, suggesting that CSCs must be specifically targeted. Here, we analyze the transcriptome of CSC and non-CSC subpopulations by RNA-seq to identify new potential therapeutic strategies for SCC., Methods: We sorted a SCC into CD133- and CD133+ subpopulations and then examined both by copy number analysis (CNA) and whole genome and transcriptome sequencing. We analyzed The Cancer Genome Atlas (TCGA) transcriptome data of 221 SCCs to determine the generality of our observations., Results: Both subpopulations highly expressed numerous mRNA isoforms whose protein products are active drug targets for other cancers; 31 (25%) correspond to 18 genes under active investigation as mAb targets and an additional 4 (3%) are of therapeutic interest. Moreover, we found evidence that both subpopulations were proliferatively driven by very high levels of c-Myc and the TRAIL long isoform (TRAILL) and that normal apoptotic responses to high expression of these genes was prevented through high levels of Mcl-1L and Bcl-xL and c-FlipL-isoforms for which drugs are now in clinical development. SCC RNA-seq data (n = 221) from TCGA supported our findings. Our analysis is inconsistent with the CSC concept that most cells in a cancer have lost their proliferative potential. Furthermore, our study suggests how to target both the CSC and non-CSC subpopulations with one treatment strategy., Conclusions: Our study is relevant to SCC in particular for it presents numerous potential options to standard therapy that target the entire tumor. In so doing, it demonstrates how transcriptome sequencing provides insights into the molecular underpinnings of cancer propagating cells that, importantly, can be leveraged to identify new potential therapeutic options for cancers beyond what is possible with DNA sequencing.

The utilization of archived, formalin-fixed paraffin-embedded (FFPE) tumor samples for massive parallel sequencing has been challenging due to DNA damage and contamination with normal stroma. Here, we perform whole genome sequencing of DNA isolated from two triple-negative breast cancer tumors archived for >11 years as 5 µm FFPE sections and matched germline DNA. The tumor samples show differing amounts of FFPE damaged DNA sequencing reads revealed as relatively high alignment mismatch rates enriched for C · G > T · A substitutions compared to germline samples. This increase in mismatch rate is observable with as few as one million reads, allowing for an upfront evaluation of the sample integrity before whole genome sequencing. By applying innovative quality filters incorporating global nucleotide mismatch rates and local mismatch rates, we present a method to identify high-confidence somatic mutations even in the presence of FFPE induced DNA damage. This results in a breast cancer mutational profile consistent with previous studies and revealing potentially important functional mutations. Our study demonstrates the feasibility of performing genome-wide deep sequencing analysis of FFPE archived tumors of limited sample size such as residual cancer after treatment or metastatic biopsies.

Ultra-deep targeted sequencing (UDT-Seq) can identify subclonal somatic mutations in tumor samples. Early assays' limited breadth and depth restrict their clinical utility. Here, we target 71 kb of mutational hotspots in 42 cancer genes. We present novel methods enhancing both laboratory workflow and mutation detection. We evaluate UDT-Seq true sensitivity and specificity (> 94% and > 99%, respectively) for low prevalence mutations in a mixing experiment and demonstrate its utility using six tumor samples. With an improved performance when run on the Illumina Miseq, the UDT-Seq assay is well suited for clinical applications to guide therapy and study clonal selection in heterogeneous samples.

Motivation: Paired-end whole transcriptome sequencing provides evidence for fusion transcripts. However, due to the repetitiveness of the transcriptome, many reads have multiple high-quality mappings. Previous methods to find gene fusions either ignored these reads or required additional longer single reads. This can obscure up to 30% of fusions and unnecessarily discards much of the data., Results: We present a method for using paired-end reads to find fusion transcripts without requiring unique mappings or additional single read sequencing. Using simulated data and data from tumors and cell lines, we show that our method can find fusions with ambiguously mapping read pairs without generating numerous spurious fusions from the many mapping locations., Availability: A C++ and Python implementation of the method demonstrated in this article is available at http://exon.ucsd.edu/ShortFuse., Contact: mckinsel@ucsd.edu, Supplementary Information: Supplementary data are available at Bioinformatics online.

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) in the 9p21 gene desert associated with coronary artery disease (CAD) and type 2 diabetes. Despite evidence for a role of the associated interval in neighbouring gene regulation, the biological underpinnings of these genetic associations with CAD or type 2 diabetes have not yet been explained. Here we identify 33 enhancers in 9p21; the interval is the second densest gene desert for predicted enhancers and six times denser than the whole genome (P < 6.55 × 10(-33)). The CAD risk alleles of SNPs rs10811656 and rs10757278 are located in one of these enhancers and disrupt a binding site for STAT1. Lymphoblastoid cell lines homozygous for the CAD risk haplotype show no binding of STAT1, and in lymphoblastoid cell lines homozygous for the CAD non-risk haplotype, binding of STAT1 inhibits CDKN2BAS (also known as CDKN2B-AS1) expression, which is reversed by short interfering RNA knockdown of STAT1. Using a new, open-ended approach to detect long-distance interactions, we find that in human vascular endothelial cells the enhancer interval containing the CAD locus physically interacts with the CDKN2A/B locus, the MTAP gene and an interval downstream of IFNA21. In human vascular endothelial cells, interferon-γ activation strongly affects the structure of the chromatin and the transcriptional regulation in the 9p21 locus, including STAT1-binding, long-range enhancer interactions and altered expression of neighbouring genes. Our findings establish a link between CAD genetic susceptibility and the response to inflammatory signalling in a vascular cell type and thus demonstrate the utility of genome-wide association study findings in directing studies to novel genomic loci and biological processes important for disease aetiology.

Through long-term laboratory selection (over 200 generations), we have generated Drosophila melanogaster populations that tolerate severe, normally lethal, levels of hypoxia. Because of initial experiments suspecting genetic mechanisms underlying this adaptation, we compared the genomes of the hypoxia-selected flies with those of controls using deep resequencing. By applying unique computing and analytical methods we identified a number of DNA regions under selection, mostly on the X chromosome. Several of the hypoxia-selected regions contained genes encoding or regulating the Notch pathway. In addition, previous expression profiling revealed an activation of the Notch pathway in the hypoxia-selected flies. We confirmed the contribution of Notch activation to hypoxia tolerance using a specific γ-secretase inhibitor, N-[N-(3,5-Difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester (DAPT), which significantly reduced adult survival and life span in the hypoxia-selected flies. We also demonstrated that flies with loss-of-function Notch mutations or RNAi-mediated Notch knockdown had a significant reduction in hypoxia tolerance, but those with a gain-of-function had a dramatic opposite effect. Using the UAS-Gal4 system, we also showed that specific overexpression of the Notch intracellular domain in glial cells was critical for conferring hypoxia tolerance. Unique analytical tools and genetic and bioinformatic strategies allowed us to discover that Notch activation plays a major role in this hypoxia tolerance in Drosophila melanogaster.

The genetics of phenotypic variation in inbred mice has for nearly a century provided a primary weapon in the medical research arsenal. A catalog of the genetic variation among inbred mouse strains, however, is required to enable powerful positional cloning and association techniques. A recent whole-genome resequencing study of 15 inbred mouse strains captured a significant fraction of the genetic variation among a limited number of strains, yet the common use of hundreds of inbred strains in medical research motivates the need for a high-density variation map of a larger set of strains. Here we report a dense set of genotypes from 94 inbred mouse strains containing 10.77 million genotypes over 121,433 single nucleotide polymorphisms (SNPs), dispersed at 20-kb intervals on average across the genome, with an average concordance of 99.94% with previous SNP sets. Through pairwise comparisons of the strains, we identified an average of 4.70 distinct segments over 73 classical inbred strains in each region of the genome, suggesting limited genetic diversity between the strains. Combining these data with genotypes of 7570 gap-filling SNPs, we further imputed the untyped or missing genotypes of 94 strains over 8.27 million Perlegen SNPs. The imputation accuracy among classical inbred strains is estimated at 99.7% for the genotypes imputed with high confidence. We demonstrated the utility of these data in high-resolution linkage mapping through power simulations and statistical power analysis and provide guidelines for developing such studies. We also provide a resource of in silico association mapping between the complex traits deposited in the Mouse Phenome Database with our genotypes. We expect that these resources will facilitate effective designs of both human and mouse studies for dissecting the genetic basis of complex traits.

Next-generation sequencing technologies have made it possible to sequence targeted regions of the human genome in hundreds of individuals. Deep sequencing represents a powerful approach for the discovery of the complete spectrum of DNA sequence variants in functionally important genomic intervals. Current methods for single nucleotide polymorphism (SNP) detection are designed to detect SNPs from single individual sequence data sets. Here, we describe a novel method SNIP-Seq (single nucleotide polymorphism identification from population sequence data) that leverages sequence data from a population of individuals to detect SNPs and assign genotypes to individuals. To evaluate our method, we utilized sequence data from a 200-kilobase (kb) region on chromosome 9p21 of the human genome. This region was sequenced in 48 individuals (five sequenced in duplicate) using the Illumina GA platform. Using this data set, we demonstrate that our method is highly accurate for detecting variants and can filter out false SNPs that are attributable to sequencing errors. The concordance of sequencing-based genotype assignments between duplicate samples was 98.8%. The 200-kb region was independently sequenced to a high depth of coverage using two sequence pools containing the 48 individuals. Many of the novel SNPs identified by SNIP-Seq from the individual sequencing were validated by the pooled sequencing data and were subsequently confirmed by Sanger sequencing. We estimate that SNIP-Seq achieves a low false-positive rate of approximately 2%, improving upon the higher false-positive rate for existing methods that do not utilize population sequence data. Collectively, these results suggest that analysis of population sequencing data is a powerful approach for the accurate detection of SNPs and the assignment of genotypes to individual samples.

Background: Targeted re-sequencing of candidate genes in individuals at the extremes of a quantitative phenotype distribution is a method of choice to gain information on the contribution of rare variants to disease susceptibility. The endocannabinoid system mediates signaling in the brain and peripheral tissues involved in the regulation of energy balance, is highly active in obese patients, and represents a strong candidate pathway to examine for genetic association with body mass index (BMI)., Results: We sequenced two intervals (covering 188 kb) encoding the endocannabinoid metabolic enzymes fatty-acid amide hydrolase (FAAH) and monoglyceride lipase (MGLL) in 147 normal controls and 142 extremely obese cases. After applying quality filters, we called 1,393 high quality single nucleotide variants, 55% of which are rare, and 143 indels. Using single marker tests and collapsed marker tests, we identified four intervals associated with BMI: the FAAH promoter, the MGLL promoter, MGLL intron 2, and MGLL intron 3. Two of these intervals are composed of rare variants and the majority of the associated variants are located in promoter sequences or in predicted transcriptional enhancers, suggesting a regulatory role. The set of rare variants in the FAAH promoter associated with BMI is also associated with increased level of FAAH substrate anandamide, further implicating a functional role in obesity., Conclusions: Our study, which is one of the first reports of a sequence-based association study using next-generation sequencing of candidate genes, provides insights into study design and analysis approaches and demonstrates the importance of examining regulatory elements rather than exclusively focusing on exon sequences., (© 2010 Harismendy et al.; licensee BioMed Central Ltd.)

Targeted enrichment of specific loci of the human genome is a promising approach to enable sequencing-based studies of genetic variation in large populations. Here we describe an enrichment approach based on microdroplet PCR, which enables 1.5 million amplifications in parallel. We sequenced six samples enriched by microdroplet or traditional singleplex PCR using primers targeting 435 exons of 47 genes. Both methods generated similarly high-quality data: 84% of the uniquely mapping reads fell within the targeted sequences; coverage was uniform across approximately 90% of targeted bases; sequence variants were called with >99% accuracy; and reproducibility between samples was high (r(2) = 0.9). We scaled the microdroplet PCR to 3,976 amplicons totaling 1.49 Mb of sequence, sequenced the resulting sample with both Illumina GAII and Roche 454, and obtained data with equally high specificity and sensitivity. Our results demonstrate that microdroplet technology is well suited for processing DNA for massively parallel enrichment of specific subsets of the human genome for targeted sequencing.

Rice, the primary source of dietary calories for half of humanity, is the first crop plant for which a high-quality reference genome sequence from a single variety was produced. We used resequencing microarrays to interrogate 100 Mb of the unique fraction of the reference genome for 20 diverse varieties and landraces that capture the impressive genotypic and phenotypic diversity of domesticated rice. Here, we report the distribution of 160,000 nonredundant SNPs. Introgression patterns of shared SNPs revealed the breeding history and relationships among the 20 varieties; some introgressed regions are associated with agronomic traits that mark major milestones in rice improvement. These comprehensive SNP data provide a foundation for deep exploration of rice diversity and gene-trait relationships and their use for future rice improvement.

There has been growing debate over the nature of the genetic contribution to individual susceptibility to common complex diseases such as diabetes, osteoporosis, and cancer. The 'Common Disease, Common Variant (CDCV)' hypothesis argues that genetic variations with appreciable frequency in the population at large, but relatively low 'penetrance' (or the probability that a carrier of the relevant variants will express the disease), are the major contributors to genetic susceptibility to common diseases. The 'Common Disease, Rare Variant (CDRV)' hypothesis, on the contrary, argues that multiple rare DNA sequence variations, each with relatively high penetrance, are the major contributors to genetic susceptibility to common diseases. Both hypotheses have their place in current research efforts.

The last few years have seen extensive efforts to catalogue human genetic variation and correlate it with phenotypic differences. Most common SNPs have now been assessed in genome-wide studies for statistical associations with many complex traits, including many important common diseases. Although these studies have provided new biological insights, only a limited amount of the heritable component of any complex trait has been identified and it remains a challenge to elucidate the functional link between associated variants and phenotypic traits. Technological advances, such as the ability to detect rare and structural variants, and a clear understanding of the challenges in linking different types of variation with phenotype, will be essential for future progress.

Background: Next generation sequencing (NGS) platforms are currently being utilized for targeted sequencing of candidate genes or genomic intervals to perform sequence-based association studies. To evaluate these platforms for this application, we analyzed human sequence generated by the Roche 454, Illumina GA, and the ABI SOLiD technologies for the same 260 kb in four individuals., Results: Local sequence characteristics contribute to systematic variability in sequence coverage (>100-fold difference in per-base coverage), resulting in patterns for each NGS technology that are highly correlated between samples. A comparison of the base calls to 88 kb of overlapping ABI 3730xL Sanger sequence generated for the same samples showed that the NGS platforms all have high sensitivity, identifying >95% of variant sites. At high coverage, depth base calling errors are systematic, resulting from local sequence contexts; as the coverage is lowered additional 'random sampling' errors in base calling occur., Conclusions: Our study provides important insights into systematic biases and data variability that need to be considered when utilizing NGS platforms for population targeted sequencing studies.

To exploit fully the potential of current sequencing technologies for population-based studies, one must enrich for loci from the human genome. Here we evaluate the hybridization-based approach by using oligonucleotide capture probes in solution to enrich for approximately 3.9 Mb of sequence target. We demonstrate that the tiling probe frequency is important for generating sequence data with high uniform coverage of targets. We obtained 93% sensitivity to detect SNPs, with a calling accuracy greater than 99%.

New technologies for rapidly assaying DNA sequences have revealed that the degree and nature of human genetic variation is far more complex then previously realized. These same technologies have also resulted in the identification of common genetic variants associated with more than 30 human diseases and traits.

We tested over 267,000 SNPs in 1,005 Northern Europeans and 248,000 in 1,006 Indian Asians for association with triglycerides and HDL cholesterol, with replication in 10,536 subjects. We found association of a nonsynonymous SNP (rs3812316, G771C, Gln241His) in MLXIPL with plasma triglyceride levels (combined P = 1.4 x 10(-10)). MLXIPL coordinates transcriptional regulation of enzymes that channel glycolytic end-products into lipogenesis and energy storage, making MLXIPL a plausible 'thrifty gene'.

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.

With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia.

Significant efforts have been made to determine the correlation structure of common SNPs in the human genome. One method has been to identify the sets of tagSNPs that capture most of the genetic variation. Here, we evaluate the transferability of tagSNPs between populations using a population sample of Sami, the indigenous people of Scandinavia. Array-based SNP discovery in a 4.4 Mb region of 28 phased copies of chromosome 21 uncovered 5,132 segregating sites, 3,188 of which had a minimum minor allele frequency (mMAF) of 0.1. Due to the population structure and consequently high LD, the number of tagSNPs needed to capture all SNP variation in Sami is much lower than that for the HapMap populations. TagSNPs identified from the HapMap data perform only slightly better in the Sami than choosing tagSNPs at random from the same set of common SNPs. Surprisingly, tagSNPs defined from the HapMap data did not perform better than selecting the same number of SNPs at random from all SNPs discovered in Sami. Nearly half (46%) of the Sami SNPs with a mMAF of 0.1 are not present in the HapMap dataset. Among sites overlapping between Sami and HapMap populations, 18% are not tagged by the European American (CEU) HapMap tagSNPs, while 43% of the SNPs that are unique to Sami are not tagged by the CEU tagSNPs. These results point to serious limitations in the transferability of common tagSNPs to capture random sequence variation, even between closely related populations, such as CEU and Sami.

A dense map of genetic variation in the laboratory mouse genome will provide insights into the evolutionary history of the species and lead to an improved understanding of the relationship between inter-strain genotypic and phenotypic differences. Here we resequence the genomes of four wild-derived and eleven classical strains. We identify 8.27 million high-quality single nucleotide polymorphisms (SNPs) densely distributed across the genome, and determine the locations of the high (divergent subspecies ancestry) and low (common subspecies ancestry) SNP-rate intervals for every pairwise combination of classical strains. Using these data, we generate a genome-wide haplotype map containing 40,898 segments, each with an average of three distinct ancestral haplotypes. For the haplotypes in the classical strains that are unequivocally assigned ancestry, the genetic contributions of the Mus musculus subspecies--M. m. domesticus, M. m. musculus, M. m. castaneus and the hybrid M. m. molossinus--are 68%, 6%, 3% and 10%, respectively; the remaining 13% of haplotypes are of unknown ancestral origin. The considerable regional redundancy of the SNP data will facilitate imputation of the majority of these genotypes in less-densely typed classical inbred strains to provide a complete view of variation in additional strains.

Efforts to develop effective therapeutic treatments for promoting fast wound healing after injury to the epidermis are hindered by a lack of understanding of the factors involved. Re-epithelialization is an essential step of wound healing involving the migration of epidermal keratinocytes over the wound site. Here, we examine genetic variants in the keratin-1 (KRT1) locus for association with migration rates of human epidermal keratinocytes (HEK) isolated from different individuals. Although the role of intermediate filament genes, including KRT1, in wound activated keratinocytes is well established, this is the first study to examine if genetic variants in humans contribute to differences in the migration rates of these cells. Using an in vitro scratch wound assay we observe quantifiable variation in HEK migration rates in two independent sets of samples; 24 samples in the first set and 17 samples in the second set. We analyze genetic variants in the KRT1 interval and identify SNPs significantly associated with HEK migration rates in both samples sets. Additionally, we show in the first set of samples that the average migration rate of HEK cells homozygous for one common haplotype pattern in the KRT1 interval is significantly faster than that of HEK cells homozygous for a second common haplotype pattern. Our study demonstrates that genetic variants in the KRT1 interval contribute to quantifiable differences in the migration rates of keratinocytes isolated from different individuals. Furthermore we show that in vitro cell assays can successfully be used to deconstruct complex traits into simple biological model systems for genetic association studies.

The genomes of individuals from the same species vary in sequence as a result of different evolutionary processes. To examine the patterns of, and the forces shaping, sequence variation in Arabidopsis thaliana, we performed high-density array resequencing of 20 diverse strains (accessions). More than 1 million nonredundant single-nucleotide polymorphisms (SNPs) were identified at moderate false discovery rates (FDRs), and approximately 4% of the genome was identified as being highly dissimilar or deleted relative to the reference genome sequence. Patterns of polymorphism are highly nonrandom among gene families, with genes mediating interaction with the biotic environment having exceptional polymorphism levels. At the chromosomal scale, regional variation in polymorphism was readily apparent. A scan for recent selective sweeps revealed several candidate regions, including a notable example in which almost all variation was removed in a 500-kilobase window. Analyzing the polymorphisms we describe in larger sets of accessions will enable a detailed understanding of forces shaping population-wide sequence variation in A. thaliana.

The differential expression of alleles occurs commonly in humans and is likely an important genetic factor underlying heritable differences in phenotypic traits. Understanding the molecular basis of allelic expression differences is thus an important challenge. Although many genes have been shown to display differential allelic expression, this is the first study to examine in detail the cumulative effects of multiple cis-regulatory polymorphisms responsible for allele-specific expression differences. We have used a variety of experimental approaches to identify and characterize cis-regulatory polymorphisms responsible for the extreme allele-specific expression differences of keratin-1 (KRT1) in human white blood cells. The combined data from our analyses provide strong evidence that the KRT1 allelic expression differences result from the haplotypic combinations and interactions of five cis-regulatory single nucleotide polymorphisms (SNPs) whose alleles differ in their affinity to bind transcription factors and modulate KRT1 promoter activity. Two of these cis-regulatory SNPs bind transcriptional activators with the alleles on the high-expressing KRT1 haplotype pattern having a higher affinity than the alleles on the low-expressing haplotype pattern. In contrast, the other three cis-regulatory SNPs bind transcriptional inhibitors with the alleles on the low-expressing haplotype pattern having a higher affinity than the alleles on the high-expressing haplotype pattern. Our study provides important new insights into the degree of complexity that the cis-regulatory sequences responsible for allele-specific transcriptional regulation have. These data suggest that allelic expression differences result from the cumulative contribution of multiple DNA sequence polymorphisms, with each having a small effect, and that allele-specific expression can thus be viewed as a complex trait., Competing Interests: Competing interests. The authors have declared that no competing interests exist.

Allelic variation of gene expression is common in humans, and is of interest because of its potential contribution to variation in heritable traits. To identify human genes with allelic expression differences, we genotype DNA and examine mRNA isolated from the white blood cells of 12 unrelated individuals using oligonucleotide arrays containing 8406 exonic SNPs. Of the exonic SNPs, 1983, located in 1389 genes, are both expressed in the white blood cells and heterozygous in at least one of the 12 individuals, and thus can be examined for differential allelic expression. Of the 1389 genes, 731 (53%) show allele expression differences in at least one individual. To gain insight into the regulatory mechanisms governing allelic expression differences, we analyze a set of 60 genes containing exonic SNPs that are heterozygous in three or more samples, and for which all heterozygotes display differential expression. We find three patterns of allelic expression, suggesting different underlying regulatory mechanisms. Exonic SNPs in three of the 60 genes are monoallelically expressed in the human white blood cells, and when examined in families show expression of only the maternal copy, consistent with regulation by imprinting. Approximately one-third of the genes have the same allele expressed more highly in all heterozygotes, suggesting that their regulation is predominantly influenced by cis-elements in strong linkage disequilibrium with the assayed exonic SNP. The remaining two-thirds of the genes have different alleles expressed more highly in different heterozygotes, suggesting that their expression differences are influenced by factors not in strong linkage disequilibrium with the assayed exonic SNP.

Humans show great variation in phenotypic traits such as height, eye color and susceptibility to disease. Genomic DNA sequence differences among individuals are responsible for the inherited components of these complex traits. Reports suggest that intermediate and large-scale DNA copy number and structural variations are prevalent enough to be an important source of genetic variation between individuals. Because association studies to identify genomic loci associated with particular phenotypic traits have focused primarily on genotyping SNPs, it is important to determine whether common structural polymorphisms are in linkage disequilibrium with common SNPs, and thus can be assessed indirectly in SNP-based studies. Here we examine 100 deletion polymorphisms ranging from 70 bp to 7 kb. We show that common deletions and SNPs ascertained with similar criteria have essentially the same distribution of linkage disequilibrium with surrounding SNPs, indicating that these polymorphisms may share evolutionary history and that most deletion polymorphisms are effectively assayed by proxy in SNP-based association studies.

Background: Evolutionarily conserved sequences likely have biological function., Methods: To determine whether variation in conserved sequences in non-coding DNA contributes to risk for human disease, we studied six conserved non-coding elements in the Th2 cytokine cluster on human chromosome 5q31 in a large Hutterite pedigree and in samples of outbred European American and African American asthma cases and controls., Results: Among six conserved non-coding elements (> 100 bp, > 70% identity; human-mouse comparison), we identified one single nucleotide polymorphism (SNP) in each of two conserved elements and six SNPs in the flanking regions of three conserved elements. We genotyped our samples for four of these SNPs and an additional three SNPs each in the IL13 and IL4 genes. While there was only modest evidence for association with single SNPs in the Hutterite and European American samples (P < 0.05), there were highly significant associations in European Americans between asthma and haplotypes comprised of SNPs in the IL4 gene (P < 0.001), including a SNP in a conserved non-coding element. Furthermore, variation in the IL13 gene was strongly associated with total IgE (P = 0.00022) and allergic sensitization to mold allergens (P = 0.00076) in the Hutterites, and more modestly associated with sensitization to molds in the European Americans and African Americans (P < 0.01)., Conclusion: These results indicate that there is overall little variation in the conserved non-coding elements on 5q31, but variation in IL4 and IL13, including possibly one SNP in a conserved element, influence asthma and atopic phenotypes in diverse populations.

We performed a two-tiered, whole-genome association study of Parkinson disease (PD). For tier 1, we individually genotyped 198,345 uniformly spaced and informative single-nucleotide polymorphisms (SNPs) in 443 sibling pairs discordant for PD. For tier 2a, we individually genotyped 1,793 PD-associated SNPs (P<.01 in tier 1) and 300 genomic control SNPs in 332 matched case-unrelated control pairs. We identified 11 SNPs that were associated with PD (P<.01) in both tier 1 and tier 2 samples and had the same direction of effect. For these SNPs, we combined data from the case-unaffected sibling pair (tier 1) and case-unrelated control pair (tier 2) samples and employed a liberalization of the sibling transmission/disequilibrium test to calculate odds ratios, 95% confidence intervals, and P values. A SNP within the semaphorin 5A gene (SEMA5A) had the lowest combined P value (P=7.62 x 10(-6)). The protein encoded by this gene plays an important role in neurogenesis and in neuronal apoptosis, which is consistent with existing hypotheses regarding PD pathogenesis. A second SNP tagged the PARK11 late-onset PD susceptibility locus (P=1.70 x 10(-5)). In tier 2b, we also selected for genotyping additional SNPs that were borderline significant (P<.05) in tier 1 but that tested a priori biological and genetic hypotheses regarding susceptibility to PD (n=941 SNPs). In analysis of the combined tier 1 and tier 2b data, the two SNPs with the lowest P values (P=9.07 x 10(-6); P=2.96 x 10(-5)) tagged the PARK10 late-onset PD susceptibility locus. Independent replication across populations will clarify the role of the genomic loci tagged by these SNPs in conferring PD susceptibility.

Recombination rates seem to vary extensively along the human genome. Pedigree analysis suggests that rates vary by an order of magnitude when measured at the megabase scale, and at a finer scale, sperm typing studies point to the existence of recombination hotspots. These are short regions (1-2 kb) in which recombination rates are 10-1,000 times higher than the background rate. Less is known about how recombination rates change over time. Here we determined to what degree recombination rates are conserved among closely related species by estimating recombination rates from 14 Mb of linkage disequilibrium data in central chimpanzee and human populations. The results suggest that recombination hotspots are not conserved between the two species and that recombination rates in larger (50 kb) genomic regions are only weakly conserved. Therefore, the recombination landscape has changed markedly between the two species.

Individual differences in DNA sequence are the genetic basis of human variability. We have characterized whole-genome patterns of common human DNA variation by genotyping 1,586,383 single-nucleotide polymorphisms (SNPs) in 71 Americans of European, African, and Asian ancestry. Our results indicate that these SNPs capture most common genetic variation as a result of linkage disequilibrium, the correlation among common SNP alleles. We observe a strong correlation between extended regions of linkage disequilibrium and functional genomic elements. Our data provide a tool for exploring many questions that remain regarding the causal role of common human DNA variation in complex human traits and for investigating the nature of genetic variation within and between human populations.

Association studies are used to identify genetic determinants of complex human traits of medical interest. With the large number of validated single nucleotide polymorphisms (SNPs) currently available, two limiting factors in association studies are genotyping capability and costs. Pooled DNA genotyping has been proposed as an efficient means of screening SNPs for allele frequency differences in case-control studies and for prioritising them for subsequent individual genotyping analysis. Here, we apply quantitative pooled genotyping followed by individual genotyping and replication to identify associations with human serum high-density lipoprotein (HDL) cholesterol levels. The DNA from individuals with low and high HDL cholesterol levels was pooled separately, each pool was amplified by polymerase chain reaction in triplicate and each amplified product was separately hybridised to a high-density oligonucleotide array. Allele frequency differences between case and control groups with low and high HDL cholesterol levels were estimated for 7,283 SNPs distributed across 71 candidate gene regions spanning a total of 17.1 megabases. A novel method was developed to take advantage of independently derived haplotype map information to improve the pooled estimates of allele frequency differences. A subset of SNPs with the largest estimated allele frequency differences between low and high HDL cholesterol groups was chosen for individual genotyping in the study population, as well as in a separate replication population. Four SNPs in a single haplotype block within the cholesteryl ester transfer protein (CETP) gene interval were significantly associated with HDL cholesterol levels in both populations. Our study is among the first to demonstrate the application of pooled genotyping followed by confirmation with individual genotyping to identify genetic determinants of a complex trait.

High-density SNP screening of panels of inbred mouse strains has been proposed as a method to accelerate the identification of genes associated with complex biomedical phenotypes. To evaluate the potential of these studies, a more detailed understanding of the fine structure of sequence variation across inbred mouse strains is needed. Here, we use high-density oligonucleotide arrays to discover an extremely dense set of SNPs in 13 classical and two wild-derived inbred strains in five genomic intervals totaling 4.6 Mb of DNA sequence, and then analyze the segmental haplotype structure defined by these high-density SNPs. This analysis reveals segments ranging from 12 to 608 kb in length within which the inbred strains have a simple and distinct phylogenetic relationship with typically two or three clades accounting for the 13 classical strains examined. The phylogenetic relationships among strains change abruptly and unpredictably from segment to segment, and are distinct in each of the five genomic regions examined. The data suggest that at least 12 strains would need to be resequenced for exhaustive SNP discovery in every region of the mouse genome, that approximately 97% of the variation among inbred strains is ancestral (between clades) and approximately 3% private (within clades), and provides critical insights into the proposed use of panels of inbred strains to identify genes underlying quantitative trait loci., (Copyright 2004 Cold Spring Harbor Laboratory Press ISSN)

Comparison of DNA sequences from different species is a fundamental method for identifying functional elements in genomes. Here, we describe the VISTA family of tools created to assist biologists in carrying out this task. Our first VISTA server at http://www-gsd.lbl.gov/vista/ was launched in the summer of 2000 and was designed to align long genomic sequences and visualize these alignments with associated functional annotations. Currently the VISTA site includes multiple comparative genomics tools and provides users with rich capabilities to browse pre-computed whole-genome alignments of large vertebrate genomes and other groups of organisms with VISTA Browser, to submit their own sequences of interest to several VISTA servers for various types of comparative analysis and to obtain detailed comparative analysis results for a set of cardiovascular genes. We illustrate capabilities of the VISTA site by the analysis of a 180 kb interval on human chromosome 5 that encodes for the kinesin family member 3A (KIF3A) protein.