Dataset Information

Combination of short-read, long-read, and optical mapping assemblies reveals large-scale tandem repeat arrays with population genetic implications.

ABSTRACT: Accurate and contiguous genome assembly is key to a comprehensive understanding of the processes shaping genomic diversity and evolution. Yet, it is frequently constrained by constitutive heterochromatin, usually characterized by highly repetitive DNA. As a key feature of genome architecture associated with centromeric and subtelomeric regions, it locally influences meiotic recombination. In this study, we assess the impact of large tandem repeat arrays on the recombination rate landscape in an avian speciation model, the Eurasian crow. We assembled two high-quality genome references using single-molecule real-time sequencing (long-read assembly [LR]) and single-molecule optical maps (optical map assembly [OM]). A three-way comparison including the published short-read assembly (SR) constructed for the same individual allowed assessing assembly properties and pinpointing misassemblies. By combining information from all three assemblies, we characterized 36 previously unidentified large repetitive regions in the proximity of sequence assembly breakpoints, the majority of which contained complex arrays of a 14-kb satellite repeat or its 1.2-kb subunit. Using whole-genome population resequencing data, we estimated the population-scaled recombination rate (?) and found it to be significantly reduced in these regions. These findings are consistent with an effect of low recombination in regions adjacent to centromeric or subtelomeric heterochromatin and add to our understanding of the processes generating widespread heterogeneity in genetic diversity and differentiation along the genome. By combining three different technologies, our results highlight the importance of adding a layer of information on genome structure that is inaccessible to each approach independently.

SUBMITTER: Weissensteiner MH

PROVIDER: S-EPMC5411765 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Combination of short-read, long-read, and optical mapping assemblies reveals large-scale tandem repeat arrays with population genetic implications.

Weissensteiner Matthias H MH Pang Andy W C AWC Bunikis Ignas I Höijer Ida I Vinnere-Petterson Olga O Suh Alexander A Wolf Jochen B W JBW

Genome research 20170330 5

Accurate and contiguous genome assembly is key to a comprehensive understanding of the processes shaping genomic diversity and evolution. Yet, it is frequently constrained by constitutive heterochromatin, usually characterized by highly repetitive DNA. As a key feature of genome architecture associated with centromeric and subtelomeric regions, it locally influences meiotic recombination. In this study, we assess the impact of large tandem repeat arrays on the recombination rate landscape in an ...[more]

PMID: 28360231

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Project description:BackgroundDe novo genome assembly is essential to modern genomics studies. As it is not biased by a reference, it is also a useful method for studying genomes with high variation, such as cancer genomes. De novo short-read assemblers commonly use de Bruijn graphs, where nodes are sequences of equal length k, also known as k-mers. Edges in this graph are established between nodes that overlap by [Formula: see text] bases, and nodes along unambiguous walks in the graph are subsequently merged. The selection of k is influenced by multiple factors, and optimizing this value results in a trade-off between graph connectivity and sequence contiguity. Ideally, multiple k sizes should be used, so lower values can provide good connectivity in lesser covered regions and higher values can increase contiguity in well-covered regions. However, current approaches that use multiple k values do not address the scalability issues inherent to the assembly of large genomes.ResultsHere we present RResolver, a scalable algorithm that takes a short-read de Bruijn graph assembly with a starting k as input and uses a k value closer to that of the read length to resolve repeats. RResolver builds a Bloom filter of sequencing reads which is used to evaluate the assembly graph path support at branching points and removes paths with insufficient support. RResolver runs efficiently, taking only 26 min on average for an ABySS human assembly with 48 threads and 60 GiB memory. Across all experiments, compared to a baseline assembly, RResolver improves scaffold contiguity (NGA50) by up to 15% and reduces misassemblies by up to 12%.ConclusionsRResolver adds a missing component to scalable de Bruijn graph genome assembly. By improving the initial and fundamental graph traversal outcome, all downstream ABySS algorithms greatly benefit by working with a more accurate and less complex representation of the genome. The RResolver code is integrated into ABySS and is available at https://github.com/bcgsc/abyss/tree/master/RResolver .

Project description:BACKGROUND: High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. Error detection and correction are crucial to many short read sequencing applications including de novo genome sequencing, genome resequencing, and digital gene expression analysis. Short read error detection is typically carried out by counting the observed frequencies of kmers in reads and validating those with frequencies exceeding a threshold. In case of genomes with high repeat content, an erroneous kmer may be frequently observed if it has few nucleotide differences with valid kmers with multiple occurrences in the genome. Error detection and correction were mostly applied to genomes with low repeat content and this remains a challenging problem for genomes with high repeat content. RESULTS: We develop a statistical model and a computational method for error detection and correction in the presence of genomic repeats. We propose a method to infer genomic frequencies of kmers from their observed frequencies by analyzing the misread relationships among observed kmers. We also propose a method to estimate the threshold useful for validating kmers whose estimated genomic frequency exceeds the threshold. We demonstrate that superior error detection is achieved using these methods. Furthermore, we break away from the common assumption of uniformly distributed errors within a read, and provide a framework to model position-dependent error occurrence frequencies common to many short read platforms. Lastly, we achieve better error correction in genomes with high repeat content. AVAILABILITY: The software is implemented in C++ and is freely available under GNU GPL3 license and Boost Software V1.0 license at "http://aluru-sun.ece.iastate.edu/doku.php?id = redeem". CONCLUSIONS: We introduce a statistical framework to model sequencing errors in next-generation reads, which led to promising results in detecting and correcting errors for genomes with high repeat content.

Dataset Information

Combination of short-read, long-read, and optical mapping assemblies reveals large-scale tandem repeat arrays with population genetic implications.

Publications

Combination of short-read, long-read, and optical mapping assemblies reveals large-scale tandem repeat arrays with population genetic implications.

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