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The Human Genome Structural Variation Consortium,

Publications and source records attributed to The Human Genome Structural Variation Consortium,.

4 recordsLinked to original sources

Large complex structural rearrangements in human genomes harbor cryptic structures

Structural variation is a major contributor to human diversity, adaptation, and disease. Simple structural variant (SV) types include deletions, insertions, duplications, inversions, and translocations, and SVs account for most of the variable bases between genomes. Complex structural variants (CSVs) that consist of one or more simple events in cis appear more frequently in diseases and cancers where DNA repair, apoptosis, and cell cycle checkpoints are compromised, although CSVs can also appear in germline genome sequences of healthy individuals. CSVs are often characterized by short tracts of homology or no homology, and while CSVs are more prevalent in complex regions that contain large repeats, smaller stretches of homology can also enable their formation across more unique loci. Long-read assemblies have increased the size of detectable SVs and expanded variant detection into more complex regions of the genome, and while they reconstruct CSVs, methods for identifying CSVs from assemblies is limited. Here, we have developed a new assembly-based approach to trace through complex loci rather than relying upon reference representations of alignments. We can now access CSVs in large complex segmental duplications, reveal structures that were previously unknown, and identify SV breakpoints with greater accuracy. We find 72 large CSVs per genome and 128 unique complex structures and CSVs in highly repetitive regions can now be detected including several distinct complex events in repetitive NBPF genes that was not previously callable with short-read or long-read CSV methods. This approach is implemented within a key assembly-based variant calling tool, PAV, and represents a substantial improvement identifying complex variants now ascertainable from contiguous genome assemblies.

genomics↗

Mako: a graph-based pattern growth approach to detect complex structural variants

Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. We systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections and pattern growth enables CSV detection without predefined models. Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms. Notably, validation rates of CSV on real data based on experimental and computational validations as well as manual inspections are around 70%, where the medians of experimental and computational breakpoint shift are 13bp and 26bp, respectively. Moreover, Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types, including two novel types of adjacent segments swap and tandem dispersed duplication. Further analysis of these CSVs also revealed impact of sequence homology in the formation of CSVs. Mako is publicly available at https://github.com/jiadong324/Mako.

bioinformatics↗

High coverage whole genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios

The 1000 Genomes Project (1kGP) is the largest fully open resource of whole genome sequencing (WGS) data consented for public distribution of raw sequence data without access or use restrictions. The final release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low coverage WGS. Here, we present a new, high coverage 3,202-sample WGS 1kGP resource, sequenced to a targeted depth of 30X using the Illumina NovaSeq 6000 system, which now includes 602 complete trios. We performed SNV/INDEL calling against the GRCh38 reference using GATKs HaplotypeCaller, and generated a comprehensive set of SVs by integrating multiple analytic methods through a sophisticated machine learning model. We make all the data generated as part of this project publicly available and we envision it to become the new de facto public resource for the worldwide genomics and genetics community.

genomics↗

Profiling variable-number tandem repeat variation across populations using repeat-pangenome graphs

Variable number tandem repeat sequences (VNTR) are composed of consecutive repeats of short segments of DNA with hypervariable repeat count and composition. They include protein coding sequences and associations with clinical disorders. It has been difficult to incorporate VNTR analysis in disease studies that use short-read sequencing because the traditional approach of mapping to the human reference is less effective for repetitive and divergent sequences. We solve VNTR mapping for short reads with a repeat-pangenome graph (RPGG), a data structure that encodes both the population diversity and repeat structure of VNTR loci from multiple haplotype-resolved assemblies. We developed software to build a RPGG, and use the RPGG to estimate VNTR composition with short reads. We used this to discover VNTRs with length stratified by continental population, and novel expression quantitative trait loci, indicating that RPGG analysis of VNTRs will be critical for future studies of diversity and disease.

bioinformatics↗