A haplotype-aware de novo assembly of related individuals using pedigree graph
Shilpa GargiD, John AachiD, Heng LiiD, Richard Michael DurbiniD, George McDonald ChurchiD
Abstract
MotivationReconstructing high-quality haplotype-resolved assemblies for related individuals of various species has important applications in understanding Mendelian diseases along with evolutionary and comparative genomics. Through major genomics sequencing efforts such as the Personal Genome Project, the Vertebrate Genome Project (VGP), the Earth Biogenome Project (EBP) and the Genome in a Bottle project (GIAB), a variety of sequencing datasets from mother-father-child trios of various diploid species are becoming available.\n\nCurrent trio assembly approaches are not designed to incorporate long-read sequencing data from parents in a trio, and therefore require relatively high coverages of costly long-read data to produce high-quality assemblies. Thus, building a trio-aware assembler capable of producing accurate and chromosomal-scale diploid genomes in a pedigree, while being cost-effective in terms of sequencing costs, is a pressing need of the genomics community.\n\nResultsWe present a novel pedigree-graph-based approach to diploid assembly using accurate Illumina data and long-read Pacific Biosciences (PacBio) data from all related individuals, thereby generalizing our previous work on single individuals. We demonstrate the effectiveness of our pedigree approach on a simulated trio of pseudo-diploid yeast genomes with different heterozygosity rates, and real data from Arabidopsis Thaliana. We show that we require as little as 30x coverage Illumina data and 15x PacBio data from each individual in a trio to generate chromosomal-scale phased assemblies. Additionally, we show that we can detect and phase variants from generated phased assemblies.\n\nAvailabilityhttps://github.com/shilpagarg/WHdenovo\n\nContactshilpa_garg@hms.harvard.edu, gchurch@genetics.med.harvard.edu
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