Development of a comprehensive cardiovascular disease genetic risk assessment test.

Background: Despite monogenic and polygenic contributions to cardiovascular disease (CVD), genetic testing is not widely adopted, and current tests are limited by the breadth of surveyed conditions and interpretation burden. Methods: We developed a comprehensive clinical genome CVD test with semi-automated interpretation. Monogenic conditions and risk alleles were selected based on the strength of disease association and evidence for increased disease risk, respectively. Non-CVD secondary findings genes, pharmacogenomic (PGx) variants and CVD polygenic risk scores (PRS) were assessed for inclusion. Test performance was modeled using 2,594 genomes from the 1000 Genomes Project, and further investigated in 20 previously tested individuals. Results: The CVD genome test is composed of a panel of 215 CVD gene-disease pairs, 35 non-CVD secondary findings genes, 4 risk alleles or genotypes, 10 PGx genes and a PRS for coronary artery disease. Modeling of test performance using samples from the 1000 Genomes Project revealed ~6% of individuals with a monogenic finding in a CVD-associated gene, 6% with a risk allele finding, ~1% with a non-CVD secondary finding, and 93% with CVD-associated PGx variants. Assessment of blinded clinical samples showed complete concordance with prior testing. An average of 4 variants were reviewed per case, with interpretation and reporting time ranging from 9-96 min. Conclusions: A genome sequencing based CVD genetic risk assessment can provide comprehensive genetic disease and genetic risk information to patients with CVD. The semi-automated and limited interpretation burden suggest that this testing approach could be scaled to support population-level initiatives.

A reference data set of 5.4 million phased human variants validated by genetic inheritance from sequencing a three-generation 17-member pedigree.

Improvement of variant calling in next-generation sequence data requires a comprehensive, genome-wide catalog of high-confidence variants called in a set of genomes for use as a benchmark. We generated deep, whole-genome sequence data of 17 individuals in a three-generation pedigree and called variants in each genome using a range of currently available algorithms. We used haplotype transmission information to create a phased "Platinum" variant catalog of 4.7 million single-nucleotide variants (SNVs) plus 0.7 million small (1-50 bp) insertions and deletions (indels) that are consistent with the pattern of inheritance in the parents and 11 children of this pedigree. Platinum genotypes are highly concordant with the current catalog of the National Institute of Standards and Technology for both SNVs (>99.99%) and indels (99.92%) and add a validated truth catalog that has 26% more SNVs and 45% more indels. Analysis of 334,652 SNVs that were consistent between informatics pipelines yet inconsistent with haplotype transmission ("nonplatinum") revealed that the majority of these variants are de novo and cell-line mutations or reside within previously unidentified duplications and deletions. The reference materials from this study are a resource for objective assessment of the accuracy of variant calls throughout genomes.

Somatic mutations in MAP3K5 attenuate its proapoptotic function in melanoma through increased binding to thioredoxin.

Patients with advanced metastatic melanoma have poor prognosis and the genetics underlying its pathogenesis are poorly understood. High-throughput sequencing has allowed comprehensive discovery of somatic mutations in cancer samples. Here, on analysis of our whole-genome and whole-exome sequencing data of 29 melanoma samples, we identified several genes that harbor recurrent nonsynonymous mutations. These included MAP3K5 (mitogen-activated protein kinase kinase kinase-5), which in a prevalence screen of 288 melanomas was found to harbor a R256C substitution in 5 cases. All MAP3K5-mutated samples were wild type for BRAF, suggesting a mutual exclusivity for these mutations. Functional analysis of the MAP3K5 R256C mutation revealed attenuation of MKK4 (mitogen-activated protein kinase kinase 4) activation through increased binding of the inhibitory protein thioredoxin (TXN/TRX-1/Trx), resulting in increased proliferation and anchorage-independent growth of melanoma cells. This mutation represents a potential target for the design of new therapies to treat melanoma.

Whole-genome sequencing identifies a recurrent functional synonymous mutation in melanoma.

Synonymous mutations, which do not alter the protein sequence, have been shown to affect protein function [Sauna ZE, Kimchi-Sarfaty C (2011) Nat Rev Genet 12(10):683-691]. However, synonymous mutations are rarely investigated in the cancer genomics field. We used whole-genome and -exome sequencing to identify somatic mutations in 29 melanoma samples. Validation of one synonymous somatic mutation in BCL2L12 in 285 samples identified 12 cases that harbored the recurrent F17F mutation. This mutation led to increased BCL2L12 mRNA and protein levels because of differential targeting of WT and mutant BCL2L12 by hsa-miR-671-5p. Protein made from mutant BCL2L12 transcript bound p53, inhibited UV-induced apoptosis more efficiently than WT BCL2L12, and reduced endogenous p53 target gene transcription. This report shows selection of a recurrent somatic synonymous mutation in cancer. Our data indicate that silent alterations have a role to play in human cancer, emphasizing the importance of their investigation in future cancer genome studies.

Adult pallium transcriptomes surprise in not reflecting predicted homologies across diverse chicken and mouse pallial sectors.

The thorniest problem in comparative neurobiology is the identification of the particular brain region of birds and reptiles that corresponds to the mammalian neocortex [Butler AB, Reiner A, Karten HJ (2011) Ann N Y Acad Sci 1225:14-27; Wang Y, Brzozowska-Prechtl A, Karten HJ (2010) Proc Natl Acad Sci USA 107(28):12676-12681]. We explored which genes are actively transcribed in the regions of controversial ancestry in a representative bird (chicken) and mammal (mouse) at adult stages. We conducted four analyses comparing the expression patterns of their 5,130 most highly expressed one-to-one orthologous genes that considered global patterns of expression specificity, strong gene markers, and coexpression networks. Our study demonstrates transcriptomic divergence, plausible convergence, and, in two exceptional cases, conservation between specialized avian and mammalian telencephalic regions. This large-scale study potentially resolves the complex relationship between developmental homology and functional characteristics on the molecular level and settles long-standing evolutionary debates.

Sequencing studies in human genetics: design and interpretation.

Next-generation sequencing is becoming the primary discovery tool in human genetics. There have been many clear successes in identifying genes that are responsible for Mendelian diseases, and sequencing approaches are now poised to identify the mutations that cause undiagnosed childhood genetic diseases and those that predispose individuals to more common complex diseases. There are, however, growing concerns that the complexity and magnitude of complete sequence data could lead to an explosion of weakly justified claims of association between genetic variants and disease. Here, we provide an overview of the basic workflow in next-generation sequencing studies and emphasize, where possible, measures and considerations that facilitate accurate inferences from human sequencing studies.

Isaac: ultra-fast whole-genome secondary analysis on Illumina sequencing platforms.

SUMMARY: An ultrafast DNA sequence aligner (Isaac Genome Alignment Software) that takes advantage of high-memory hardware (>48 GB) and variant caller (Isaac Variant Caller) have been developed. We demonstrate that our combined pipeline (Isaac) is four to five times faster than BWA + GATK on equivalent hardware, with comparable accuracy as measured by trio conflict rates and sensitivity. We further show that Isaac is effective in the detection of disease-causing variants and can easily/economically be run on commodity hardware. AVAILABILITY: Isaac has an open source license and can be obtained at https://github.com/sequencing.

Rapid whole-genome sequencing for genetic disease diagnosis in neonatal intensive care units.

Monogenic diseases are frequent causes of neonatal morbidity and mortality, and disease presentations are often undifferentiated at birth. More than 3500 monogenic diseases have been characterized, but clinical testing is available for only some of them and many feature clinical and genetic heterogeneity. Hence, an immense unmet need exists for improved molecular diagnosis in infants. Because disease progression is extremely rapid, albeit heterogeneous, in newborns, molecular diagnoses must occur quickly to be relevant for clinical decision-making. We describe 50-hour differential diagnosis of genetic disorders by whole-genome sequencing (WGS) that features automated bioinformatic analysis and is intended to be a prototype for use in neonatal intensive care units. Retrospective 50-hour WGS identified known molecular diagnoses in two children. Prospective WGS disclosed potential molecular diagnosis of a severe GJB2-related skin disease in one neonate; BRAT1-related lethal neonatal rigidity and multifocal seizure syndrome in another infant; identified BCL9L as a novel, recessive visceral heterotaxy gene (HTX6) in a pedigree; and ruled out known candidate genes in one infant. Sequencing of parents or affected siblings expedited the identification of disease genes in prospective cases. Thus, rapid WGS can potentially broaden and foreshorten differential diagnosis, resulting in fewer empirical treatments and faster progression to genetic and prognostic counseling.

Mutational signatures of de-differentiation in functional non-coding regions of melanoma genomes.

Much emphasis has been placed on the identification, functional characterization, and therapeutic potential of somatic variants in tumor genomes. However, the majority of somatic variants lie outside coding regions and their role in cancer progression remains to be determined. In order to establish a system to test the functional importance of non-coding somatic variants in cancer, we created a low-passage cell culture of a metastatic melanoma tumor sample. As a foundation for interpreting functional assays, we performed whole-genome sequencing and analysis of this cell culture, the metastatic tumor from which it was derived, and the patient-matched normal genomes. When comparing somatic mutations identified in the cell culture and tissue genomes, we observe concordance at the majority of single nucleotide variants, whereas copy number changes are more variable. To understand the functional impact of non-coding somatic variation, we leveraged functional data generated by the ENCODE Project Consortium. We analyzed regulatory regions derived from multiple different cell types and found that melanocyte-specific regions are among the most depleted for somatic mutation accumulation. Significant depletion in other cell types suggests the metastatic melanoma cells de-differentiated to a more basal regulatory state. Experimental identification of genome-wide regulatory sites in two different melanoma samples supports this observation. Together, these results show that mutation accumulation in metastatic melanoma is nonrandom across the genome and that a de-differentiated regulatory architecture is common among different samples. Our findings enable identification of the underlying genetic components of melanoma and define the differences between a tissue-derived tumor sample and the cell culture created from it. Such information helps establish a broader mechanistic understanding of the linkage between non-coding genomic variations and the cellular evolution of cancer.

Extensive evolutionary changes in regulatory element activity during human origins are associated with altered gene expression and positive selection.

Understanding the molecular basis for phenotypic differences between humans and other primates remains an outstanding challenge. Mutations in non-coding regulatory DNA that alter gene expression have been hypothesized as a key driver of these phenotypic differences. This has been supported by differential gene expression analyses in general, but not by the identification of specific regulatory elements responsible for changes in transcription and phenotype. To identify the genetic source of regulatory differences, we mapped DNaseI hypersensitive (DHS) sites, which mark all types of active gene regulatory elements, genome-wide in the same cell type isolated from human, chimpanzee, and macaque. Most DHS sites were conserved among all three species, as expected based on their central role in regulating transcription. However, we found evidence that several hundred DHS sites were gained or lost on the lineages leading to modern human and chimpanzee. Species-specific DHS site gains are enriched near differentially expressed genes, are positively correlated with increased transcription, show evidence of branch-specific positive selection, and overlap with active chromatin marks. Species-specific sequence differences in transcription factor motifs found within these DHS sites are linked with species-specific changes in chromatin accessibility. Together, these indicate that the regulatory elements identified here are genetic contributors to transcriptional and phenotypic differences among primate species.

Genome-wide DNA methylation profiles in hematopoietic stem and progenitor cells reveal overrepresentation of ETS transcription factor binding sites.

DNA methylation is an essential epigenetic mark that is required for normal development. Knockout of the DNA methyltransferase enzymes in the mouse hematopoietic compartment reveals that methylation is critical for hematopoietic differentiation. To better understand the role of DNA methylation in hematopoiesis, we characterized genome-wide DNA methylation in primary mouse hematopoietic stem cells (HSCs), common myeloid progenitors (CMPs), and erythroblasts (ERYs). Methyl binding domain protein 2 (MBD) enrichment of DNA followed by massively parallel sequencing (MBD-seq) was used to map genome-wide DNA methylation. Globally, DNA methylation was most abundant in HSCs, with a 40% reduction in CMPs, and a 67% reduction in ERYs. Only 3% of peaks arise during differentiation, demonstrating a genome-wide decline in DNA methylation during erythroid development. Analysis of genomic features revealed that 98% of promoter CpG islands are hypomethylated, while 20%-25% of non-promoter CpG islands are methylated. Proximal promoter sequences of expressed genes are hypomethylated in all cell types, while gene body methylation positively correlates with gene expression in HSCs and CMPs. Elevated genome-wide DNA methylation in HSCs and the positive association between methylation and gene expression demonstrates that DNA methylation is a mark of cellular plasticity in HSCs. Using de novo motif discovery, we identified overrepresented transcription factor consensus binding motifs in methylated sequences. Motifs for several ETS transcription factors, including GABPA and ELF1, are overrepresented in methylated regions. Our genome-wide survey demonstrates that DNA methylation is markedly altered during myeloid differentiation and identifies critical regions of the genome and transcription factor programs that contribute to hematopoiesis.

Exon capture analysis of G protein-coupled receptors identifies activating mutations in GRM3 in melanoma.

G protein-coupled receptors (GPCRs), the largest human gene family, are important regulators of signaling pathways. However, knowledge of their genetic alterations is limited. In this study, we used exon capture and massively parallel sequencing methods to analyze the mutational status of 734 GPCRs in melanoma. This investigation revealed that one family member, GRM3, was frequently mutated and that one of its mutations clustered within one position. Biochemical analysis of GRM3 alterations revealed that mutant GRM3 selectively regulated the phosphorylation of MEK, leading to increased anchorage-independent growth and migration. Melanoma cells expressing mutant GRM3 had reduced cell growth and cellular migration after short hairpin RNA-mediated knockdown of GRM3 or treatment with a selective MEK inhibitor, AZD-6244, which is currently being used in phase 2 clinical trials. Our study yields the most comprehensive map of genetic alterations in the GPCR gene family.

Genome-wide ChIP-Seq reveals a dramatic shift in the binding of the transcription factor erythroid Kruppel-like factor during erythrocyte differentiation.

Erythropoiesis is dependent on the activity of transcription factors, including the erythroid-specific erythroid Kruppel-like factor (EKLF). ChIP followed by massively parallel sequencing (ChIP-Seq) is a powerful, unbiased method to map trans-factor occupancy. We used ChIP-Seq to study the interactome of EKLF in mouse erythroid progenitor cells and more differentiated erythroblasts. We correlated these results with the nuclear distribution of EKLF, RNA-Seq analysis of the transcriptome, and the occupancy of other erythroid transcription factors. In progenitor cells, EKLF is found predominantly at the periphery of the nucleus, where EKLF primarily occupies the promoter regions of genes and acts as a transcriptional activator. In erythroblasts, EKLF is distributed throughout the nucleus, and erythroblast-specific EKLF occupancy is predominantly in intragenic regions. In progenitor cells, EKLF modulates general cell growth and cell cycle regulatory pathways, whereas in erythroblasts EKLF is associated with repression of these pathways. The EKLF interactome shows very little overlap with the interactomes of GATA1, GATA2, or TAL1, leading to a model in which EKLF directs programs that are independent of those regulated by the GATA factors or TAL1.

A transcriptomic atlas of mouse neocortical layers.

In the mammalian cortex, neurons and glia form a patterned structure across six layers whose complex cytoarchitectonic arrangement is likely to contribute to cognition. We sequenced transcriptomes from layers 1-6b of different areas (primary and secondary) of the adult (postnatal day 56) mouse somatosensory cortex to understand the transcriptional levels and functional repertoires of coding and noncoding loci for cells constituting these layers. A total of 5,835 protein-coding genes and 66 noncoding RNA loci are differentially expressed ("patterned") across the layers, on the basis of a machine-learning model (naive Bayes) approach. Layers 2-6b are each associated with specific functional and disease annotations that provide insights into their biological roles. This new resource (http://genserv.anat.ox.ac.uk/layers) greatly extends currently available resources, such as the Allen Mouse Brain Atlas and microarray data sets, by providing quantitative expression levels, by being genome-wide, by including novel loci, and by identifying candidate alternatively spliced transcripts that are differentially expressed across layers.

A bioinformatics approach for determining sample identity from different lanes of high-throughput sequencing data.

The ability to generate whole genome data is rapidly becoming commoditized. For example, a mammalian sized genome (∼3Gb) can now be sequenced using approximately ten lanes on an Illumina HiSeq 2000. Since lanes from different runs are often combined, verifying that each lane in a genome's build is from the same sample is an important quality control. We sought to address this issue in a post hoc bioinformatic manner, instead of using upstream sample or "barcode" modifications. We rely on the inherent small differences between any two individuals to show that genotype concordance rates can be effectively used to test if any two lanes of HiSeq 2000 data are from the same sample. As proof of principle, we use recent data from three different human samples generated on this platform. We show that the distributions of concordance rates are non-overlapping when comparing lanes from the same sample versus lanes from different samples. Our method proves to be robust even when different numbers of reads are analyzed. Finally, we provide a straightforward method for determining the gender of any given sample. Our results suggest that examining the concordance of detected genotypes from lanes purported to be from the same sample is a relatively simple approach for confirming that combined lanes of data are of the same identity and quality.

Accurate and comprehensive sequencing of personal genomes.

As whole-genome sequencing becomes commoditized and we begin to sequence and analyze personal genomes for clinical and diagnostic purposes, it is necessary to understand what constitutes a complete sequencing experiment for determining genotypes and detecting single-nucleotide variants. Here, we show that the current recommendation of ∼30× coverage is not adequate to produce genotype calls across a large fraction of the genome with acceptably low error rates. Our results are based on analyses of a clinical sample sequenced on two related Illumina platforms, GAII(x) and HiSeq 2000, to a very high depth (126×). We used these data to establish genotype-calling filters that dramatically increase accuracy. We also empirically determined how the callable portion of the genome varies as a function of the amount of sequence data used. These results help provide a "sequencing guide" for future whole-genome sequencing decisions and metrics by which coverage statistics should be reported.

National Cancer Institute Prostate Cancer Genetics Workshop.

Compelling evidence supports a genetic component to prostate cancer susceptibility and aggressiveness. Recent genome-wide association studies have identified more than 30 single-nucleotide polymorphisms associated with prostate cancer susceptibility. It remains unclear, however, whether such genetic variants are associated with disease aggressiveness--one of the most important questions in prostate cancer research today. To help clarify this and substantially expand research in the genetic determinants of prostate cancer aggressiveness, the first National Cancer Institute Prostate Cancer Genetics Workshop assembled researchers to develop plans for a large new research consortium and patient cohort. The workshop reviewed the prior work in this area and addressed the practical issues in planning future studies. With new DNA sequencing technology, the potential application of sequencing information to patient care is emerging. The workshop, therefore, included state-of-the-art presentations by experts on new genotyping technologies, including sequencing and associated bioinformatics issues, which are just beginning to be applied to cancer genetics.

Global epigenomic analysis of primary human pancreatic islets provides insights into type 2 diabetes susceptibility loci.

Identifying cis-regulatory elements is important to understanding how human pancreatic islets modulate gene expression in physiologic or pathophysiologic (e.g., diabetic) conditions. We conducted genome-wide analysis of DNase I hypersensitive sites, histone H3 lysine methylation modifications (K4me1, K4me3, K79me2), and CCCTC factor (CTCF) binding in human islets. This identified ∼18,000 putative promoters (several hundred unannotated and islet-active). Surprisingly, active promoter modifications were absent at genes encoding islet-specific hormones, suggesting a distinct regulatory mechanism. Of 34,039 distal (nonpromoter) regulatory elements, 47% are islet unique and 22% are CTCF bound. In the 18 type 2 diabetes (T2D)-associated loci, we identified 118 putative regulatory elements and confirmed enhancer activity for 12 of 33 tested. Among six regulatory elements harboring T2D-associated variants, two exhibit significant allele-specific differences in activity. These findings present a global snapshot of the human islet epigenome and should provide functional context for noncoding variants emerging from genetic studies of T2D and other islet disorders.

Systematic comparison of three genomic enrichment methods for massively parallel DNA sequencing.

Massively parallel DNA sequencing technologies have greatly increased our ability to generate large amounts of sequencing data at a rapid pace. Several methods have been developed to enrich for genomic regions of interest for targeted sequencing. We have compared three of these methods: Molecular Inversion Probes (MIP), Solution Hybrid Selection (SHS), and Microarray-based Genomic Selection (MGS). Using HapMap DNA samples, we compared each of these methods with respect to their ability to capture an identical set of exons and evolutionarily conserved regions associated with 528 genes (2.61 Mb). For sequence analysis, we developed and used a novel Bayesian genotype-assigning algorithm, Most Probable Genotype (MPG). All three capture methods were effective, but sensitivities (percentage of targeted bases associated with high-quality genotypes) varied for an equivalent amount of pass-filtered sequence: for example, 70% (MIP), 84% (SHS), and 91% (MGS) for 400 Mb. In contrast, all methods yielded similar accuracies of >99.84% when compared to Infinium 1M SNP BeadChip-derived genotypes and >99.998% when compared to 30-fold coverage whole-genome shotgun sequencing data. We also observed a low false-positive rate with all three methods; of the heterozygous positions identified by each of the capture methods, >99.57% agreed with 1M SNP BeadChip, and >98.840% agreed with the whole-genome shotgun data. In addition, we successfully piloted the genomic enrichment of a set of 12 pooled samples via the MGS method using molecular bar codes. We find that these three genomic enrichment methods are highly accurate and practical, with sensitivities comparable to that of 30-fold coverage whole-genome shotgun data.

Human NPY promoter variation rs16147:T>C as a moderator of prefrontal NPY gene expression and negative affect.

Studies in humans and animals suggest a role for NPY in the mediation of behavioral stress responses. Here, we examined whether the NPY promoter variant rs16147:T>C is functional for expression of NPY in a brain region relevant for behavioral control, anxiety and depression, the anterior cingulate cortex. In silico analysis of DNA structural profile changes produced by rs16147 variation suggests allelic differences in protein binding at the rs16147 site. This was confirmed by electrophoretic mobility shift assay, demonstrating that the rs16147 C-allele has strongly reduced affinity for a yet unknown factor compared to the T-allele. Analyzing 107 human post-mortem brain samples we show that allelic variation at rs16147 contributes to regulation of NPY mRNA and peptide levels in this region. Specifically, the C-allele leads to increased gene expression. In agreement with the molecular findings, rs16147:T>C is associated with anxiety and depressive symptoms in 314 young adults via a gene x environment interaction with early childhood adversity, replicating the recent finding of rs16147-C as a risk factor for stress related psychopathology. Our results show the importance of rs16147:T>C for regulation of NPY gene expression and brain function.