Variant calling on the GRCh38 assembly with the data from phase three of the 1000 Genomes Project

We present biallelic SNVs called from 2,548 samples across 26 populationsfrom the 1000 Genomes Project, called directly on GRCh38. We believethis will be a useful reference resource for those using GRCh38,representing an improvement over the “lift-overs” of the 1000 GenomesProject data that have been available to date and providing a resourcenecessary for the full adoption of GRCh38 by the community. Here, wedescribe how the call set was created and provide benchmarking datadescribing how our call set compares to that produced by the final phase ofthe 1000 Genomes Project on GRCh37

Analysis of variable retroduplications in human populations suggests coupling of retrotransposition to cell division

In primates and other animals, reverse transcription of mRNA followed by genomic integration creates retroduplications. Expressed retroduplications are either “retrogenes” coding for functioning proteins, or expressed “processed pseudogenes,” which can function as noncoding RNAs. To date, little is known about the variation in retroduplications in terms of their presence or absence across individuals in the human population. We have developed new methodologies that allow us to identify “novel” retroduplications (i.e., those not present in the reference genome), to find their insertion points, and to genotype them. Using these methods, we catalogued and analyzed 174 retroduplication variants in almost one thousand humans, which were sequenced as part of Phase 1 of The 1000 Genomes Project Consortium. The accuracy of our data set was corroborated by (1) multiple lines of sequencing evidence for retroduplication (e.g., depth of coverage in exons vs. introns), (2) experimental validation, and (3) the fact that we can reconstruct a correct phylogenetic tree of human subpopulations based solely on retroduplications. We also show that parent genes of retroduplication variants tend to be expressed at the M-to-G1 transition in the cell cycle and that M-to-G1 expressed genes have more copies of fixed retroduplications than genes expressed at other times. These findings suggest that cell division is coupled to retrotransposition and, perhaps, is even a requirement for it

Mining data from 1000 genomes to identify the causal variant in regions under positive selection

The human genome contains hundreds of regions in which the patterns of genetic variation indicate recent positive natural selection, yet for most of these the underlying gene and the advantageous mutation remain unknown. We recently reported the development of a method, Composite of Multiple Signals (CMS), that combines tests for multiple signals of natural selection and increases resolution by up to 100-fold

Enriching rare variants using family-specific linkage information

Genome-wide association studies have been successful in identifying common variants for common complex traits in recent years. However, common variants have generally failed to explain substantial proportions of the trait heritabilities. Rare variants, structural variations, and gene-gene and gene-environment interactions, among others, have been suggested as potential sources of the so-called missing heritability. With the advent of exome-wide and whole-genome next-generation sequencing technologies, finding rare variants in functionally important sites (e.g., protein-coding regions) becomes feasible. We investigate the role of linkage information to select families enriched for rare variants using the simulated Genetic Analysis Workshop 17 data. In each replicate of simulated phenotypes Q1 and Q2 on 697 subjects in 8 extended pedigrees, we select one pedigree with the largest family-specific LOD score. Across all 200 replications, we compare the probability that rare causal alleles will be carried in the selected pedigree versus a randomly chosen pedigree. One example of successful enrichment was exhibited for gene VEGFC. The causal variant had minor allele frequency of 0.0717% in the simulated unrelated individuals and explained about 0.1% of the phenotypic variance. However, it explained 7.9% of the phenotypic variance in the eight simulated pedigrees and 23.8% in the family that carried the minor allele. The carrier’s family was selected in all 200 replications. Thus our results show that family-specific linkage information is useful for selecting families for sequencing, thus ensuring that rare functional variants are segregating in the sequencing samples

Deleterious- and Disease-Allele Prevalence in Healthy Individuals: Insights from Current Predictions, Mutation Databases, and Population-Scale Resequencing

We have assessed the numbers of potentially deleterious variants in the genomes of apparently healthy humans by using (1) low-coverage whole-genome sequence data from 179 individuals in the 1000 Genomes Pilot Project and (2) current predictions and databases of deleterious variants. Each individual carried 281–515 missense substitutions, 40–85 of which were homozygous, predicted to be highly damaging. They also carried 40–110 variants classified by the Human Gene Mutation Database (HGMD) as disease-causing mutations (DMs), 3–24 variants in the homozygous state, and many polymorphisms putatively associated with disease. Whereas many of these DMs are likely to represent disease-allele-annotation errors, between 0 and 8 DMs (0–1 homozygous) per individual are predicted to be highly damaging, and some of them provide information of medical relevance. These analyses emphasize the need for improved annotation of disease alleles both in mutation databases and in the primary literature; some HGMD mutation data have been recategorized on the basis of the present findings, an iterative process that is both necessary and ongoing. Our estimates of deleterious-allele numbers are likely to be subject to both overcounting and undercounting. However, our current best mean estimates of ∼400 damaging variants and ∼2 bona fide disease mutations per individual are likely to increase rather than decrease as sequencing studies ascertain rare variants more effectively and as additional disease alleles are discovered

Regional variation in health is predominantly driven by lifestyle rather than genetics

Health-related traits are known to vary geographically. Here, Amador and colleagues show that regional variation of obesity-related traits in a Scottish population is influenced more by lifestyle differences than it is by genetic differences

SEQanswers: an open access community for collaboratively decoding genomes

Summary: The affordability of high-throughput sequencing has created an unprecedented surge in the use of genomic data in basic, translational and clinical research. The rapid evolution of sequencing technology, coupled with its broad adoption across biology and medicine, necessitates fast, collaborative interdisciplinary discussion. SEQanswers provides a real-time knowledge-sharing resource to address this need, covering experimental and computational aspects of sequencing and sequence analysis. Developers of popular analysis tools are among the >4000 active members, and ~40 peer-reviewed publications have referenced SEQanswers

Implementing a genomic data management system using iRODS in the Wellcome Trust Sanger Institute

<p>Abstract</p> <p>Background</p> <p>Increasingly large amounts of DNA sequencing data are being generated within the Wellcome Trust Sanger Institute (WTSI). The traditional file system struggles to handle these increasing amounts of sequence data. A good data management system therefore needs to be implemented and integrated into the current WTSI infrastructure. Such a system enables good management of the IT infrastructure of the sequencing pipeline and allows biologists to track their data.</p> <p>Results</p> <p>We have chosen a data grid system, iRODS (Rule-Oriented Data management systems), to act as the data management system for the WTSI. iRODS provides a rule-based system management approach which makes data replication much easier and provides extra data protection. Unlike the metadata provided by traditional file systems, the metadata system of iRODS is comprehensive and allows users to customize their own application level metadata. Users and IT experts in the WTSI can then query the metadata to find and track data.</p> <p>The aim of this paper is to describe how we designed and used (from both system and user viewpoints) iRODS as a data management system. Details are given about the problems faced and the solutions found when iRODS was implemented. A simple use case describing how users within the WTSI use iRODS is also introduced.</p> <p>Conclusions</p> <p>iRODS has been implemented and works as the production system for the sequencing pipeline of the WTSI. Both biologists and IT experts can now track and manage data, which could not previously be achieved. This novel approach allows biologists to define their own metadata and query the genomic data using those metadata.</p