Person:

Handsaker, Robert

Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.

Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analysing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother–father–child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately (10^{−8}) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research.

Schizophrenia is a heritable brain illness with unknown pathogenic mechanisms. Schizophrenia’s strongest genetic association at a population level involves variation in the Major Histocompatibility Complex (MHC) locus, but the genes and molecular mechanisms accounting for this have been challenging to recognize. We show here that schizophrenia’s association with the MHC locus arises in substantial part from many structurally diverse alleles of the complement component 4 (C4) genes. We found that these alleles promoted widely varying levels of C4A and C4B expression and associated with schizophrenia in proportion to their tendency to promote greater expression of C4A in the brain. Human C4 protein localized at neuronal synapses, dendrites, axons, and cell bodies. In mice, C4 mediated synapse elimination during postnatal development. These results implicate excessive complement activity in the development of schizophrenia and may help explain the reduced numbers of synapses in the brains of individuals affected with schizophrenia.

Tens of millions of base pairs of euchromatic human genome sequence, including many protein-coding genes, have no known location in the human genome. We describe an approach for localizing the human genome's missing pieces by utilizing the patterns of genome sequence variation created by population admixture. We mapped the locations of 70 scaffolds spanning four million base pairs of the human genome's unplaced euchromatic sequence, including more than a dozen protein-coding genes, and identified eight large novel inter-chromosomal segmental duplications. We find that most of these sequences are hidden in the genome's heterochromatin, particularly its pericentromeric regions. Many cryptic, pericentromeric genes are expressed in RNA and have been maintained intact for millions of years while their expression patterns diverged from those of paralogous genes elsewhere in the genome. We describe how knowledge of the locations of these sequences can inform disease association and genome biology studies.

While genetic lesions responsible for some Mendelian disorders can be rapidly discovered through massively parallel sequencing (MPS) of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple Mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing, and de novo assembly, we found that each of six MCKD1 families harbors an equivalent, but apparently independently arising, mutation in sequence dramatically underrepresented in MPS data: the insertion of a single C in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (~1.5-5 kb), GC-rich (>80%), coding VNTR in the mucin 1 gene. The results provide a cautionary tale about the challenges in identifying genes responsible for Mendelian, let alone more complex, disorders through MPS.

Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.

Accurate and complete analysis of genome variation in large populations will be required to understand the role of genome variation in complex disease. We present an analytical framework for characterizing genome deletion polymorphism in populations, using sequence data that are distributed across hundreds or thousands of genomes. Our approach uses population-level relationships to re-interpret the technical features of sequence data that often reflect structural variation. In the 1000 Genomes Project pilot, this approach identified deletion polymorphism across 168 genomes (sequenced at 4x average coverage) with sensitivity and specificity unmatched by other algorithms. We also describe a way to determine the allelic state or genotype of each deletion polymorphism in each genome; the 1000 Genomes Project used this approach to type 13,826 deletion polymorphisms (48 bp – 960 kbp) at high accuracy in populations. These methods offer a way to relate genome structural polymorphism to complex disease in populations.

Background: Depressive disorders are the second-leading cause of global disability, and an area of increasing focus in international health efforts. We describe a community health worker (CHW) program rolled out in a stepped-wedge design during the course of routine patient care to 74 patients with depression in 4 communities in rural Mexico. Methods: We used random effects models to calculate the change in Patient Health Questionnaire-9 (PHQ-9) scores, an internationally validated measure of depression, before and after the CHW program was introduced. As a secondary outcome, we also examined the change pre- and post-intervention in the proportion of patients who had a mean of at least one visit per month for depression follow-up, in accordance with clinic visit guidelines. Results: In multivariate mixed-effects regression, the introduction of the CHW program was associated with a 2.1-point decrease in PHQ-9 score (95% CI: -3.7 to -0.50) followed by a decrease in PHQ-9 score of 0.19 points per month (95% CI: -0.41 to 0.02), beyond standard care. There was strong evidence that patients were far more likely to attend a mean of at least one visit per month (adjusted OR = 8.5, 95% CI: 7.2 to 9.7) after the intervention was introduced in a community. Conclusions: Our results suggest an association between the introduction of a CHW program and improved depression outcomes and appointment adherence. Our findings are limited by missing data. Future research is necessary to develop evidence-based mental health interventions implementable in low-resource settings.

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10−4), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.