ABSTRACT
The 1000 Genomes Project (1kGP) is the largest fully open resource of whole-genome sequencing (WGS) data consented for public distribution without access or use restrictions. The final, phase 3 release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low-coverage WGS. Here, we present a high-coverage 3,202-sample WGS 1kGP resource, which now includes 602 complete trios, sequenced to a depth of 30X using Illumina. We performed single-nucleotide variant (SNV) and short insertion and deletion (INDEL) discovery and generated a comprehensive set of structural variants (SVs) by integrating multiple analytic methods through a machine learning model. We show gains in sensitivity and precision of variant calls compared to phase 3, especially among rare SNVs as well as INDELs and SVs spanning frequency spectrum. We also generated an improved reference imputation panel, making variants discovered here accessible for association studies.
Subject(s)
Genome, Human , Whole Genome Sequencing , Female , High-Throughput Nucleotide Sequencing/methods , Humans , INDEL Mutation , Male , Polymorphism, Single NucleotideABSTRACT
A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline1 to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.
Subject(s)
Genetic Variation , Genome, Human/genetics , Whole Genome Sequencing , Alleles , Case-Control Studies , Epigenesis, Genetic , Female , Gene Dosage/genetics , Genetics, Population , High-Throughput Nucleotide Sequencing , Humans , Male , Molecular Sequence Annotation , Quantitative Trait Loci , Racial Groups/genetics , SoftwareABSTRACT
The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10-54) and is also associated with increased levels of total cholesterol (p = 1.22 × 10-28) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10-21) and alanine (p = 6.14 × 10-12) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10-10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10-35). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.
Subject(s)
Cardiovascular Diseases/genetics , Genomic Structural Variation/genetics , Alleles , Cholesterol/blood , DNA Copy Number Variations/genetics , Female , Finland , Genome, Human/genetics , Genotype , High-Throughput Nucleotide Sequencing , Humans , Male , Mitochondrial Proteins/genetics , Promoter Regions, Genetic/genetics , Pyruvate Dehydrogenase (Lipoamide)-Phosphatase/genetics , Pyruvic Acid/metabolism , Serum Albumin, Human/geneticsABSTRACT
In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.
Subject(s)
Chromosome Mapping/methods , Genome, Human/genetics , Knowledge Bases , Models, Genetic , Sequence Analysis, DNA/methods , User-Computer Interface , Algorithms , Computer Simulation , Database Management Systems , Databases, Genetic , Humans , Sequence Alignment/methodsABSTRACT
Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.
Subject(s)
Genetic Variation , Genome, Human , Haplotypes , Female , Genotype , High-Throughput Nucleotide Sequencing , Humans , INDEL Mutation , Interspersed Repetitive Sequences , Male , Population Groups/genetics , Quantitative Trait Loci , Retroelements , Sequence Analysis, DNA , Sequence Inversion , Whole Genome SequencingABSTRACT
BACKGROUND: Alternative arrangements of chromosome 2 inversions in Anopheles gambiae are important sources of population structure, and are associated with adaptation to environmental heterogeneity. The forces responsible for their origin and maintenance are incompletely understood. Molecular characterization of inversion breakpoints provides insight into how they arose, and provides the basis for development of molecular karyotyping methods useful in future studies. METHODS: Sequence comparison of regions near the cytological breakpoints of 2Rb allowed the molecular delineation of breakpoint boundaries. Comparisons were made between the standard 2R+b arrangement in the An. gambiae PEST reference genome and the inverted 2Rb arrangements in the An. gambiae M and S genome assemblies. Sequence differences between alternative 2Rb arrangements were exploited in the design of a PCR diagnostic assay, which was evaluated against the known chromosomal banding pattern of laboratory colonies and field-collected samples from Mali and Cameroon. RESULTS: The breakpoints of the 7.55 Mb 2Rb inversion are flanked by extensive runs of the same short (72 bp) tandemly organized sequence, which was likely responsible for chromosomal breakage and rearrangement. Application of the molecular diagnostic assay suggested that 2Rb has a single common origin in An. gambiae and its sibling species, Anopheles arabiensis, and also that the standard arrangement (2R+b) may have arisen twice through breakpoint reuse. The molecular diagnostic was reliable when applied to laboratory colonies, but its accuracy was lower in natural populations. CONCLUSIONS: The complex repetitive sequence flanking the 2Rb breakpoint region may be prone to structural and sequence-level instability. The 2Rb molecular diagnostic has immediate application in studies based on laboratory colonies, but its usefulness in natural populations awaits development of complementary molecular tools.
Subject(s)
Anopheles/genetics , Chromosome Inversion , Chromosomes, Insect , Animals , Anopheles/cytology , Cameroon , Chromosome Banding/methods , Entomology/methods , Humans , Karyotyping/methods , Mali , Polymerase Chain Reaction/methods , Sequence Analysis, DNAABSTRACT
Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power. A central challenge for joint analysis is that different WGS data processing pipelines cause substantial differences in variant calling in combined datasets, necessitating computationally expensive reprocessing. This approach is no longer tenable given the scale of current studies and data volumes. Here, we define WGS data processing standards that allow different groups to produce functionally equivalent (FE) results, yet still innovate on data processing pipelines. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results and produce significantly less variability than sequencing replicates. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for community-wide human genetics studies.