Un-zipping diploid genomes – revealing all kinds of heterozygous variants from comprehensive hapltotig assemblies

Author(s): Chin, Jason and Peluso, Paul and Rank, David, and Nattestad, Maria, and Sedlazeck, Fritz J. and Schatz, Michael and Clum, Alicia and Barry, Kerrie and Copeland, Alex and OMalley, Ronan and Luo, Chongyuan Luo and Ecker, Joseph

Outside of the simplest cases (haploid, bacteria, or inbreds), genomic information is not carried in a single reference per individual, but rather has higher ploidy (n=>2) for almost all organisms. The existence of two or more highly related sequences within an individual makes it extremely difficult to build high quality, highly contiguous genome assemblies from short DNA fragments. Based on the earlier work on a polyploidy aware assembler, FALCON (, we developed new algorithms and software (FALCON-unzip) for de novo haplotype reconstructions from SMRT Sequencing data. We apply the algorithms and the prototype software for (1) a highly repetitive diploid fungal genome (Clavicorona pyxidata) and (2) an F1 hybrid from two inbred Arabidopsis strains: CVI-0 and COL-0. For the fungal genome, we achieved an N50 of 1.53 Mb (of the 1n assembly contigs) of the ~42 Mb 1n genome and an N50 of the haplotigs of 872 kb from a 95X read length N50 ~16 kb dataset. We found that ~ 45% of the genome was highly heterozygous and ~55% of the genome was highly homozygous. We developed methods to assess the base-level accuracy and local haplotype phasing accuracy of the assembly with short-read data from the Illumina platform. For the Arabidopsis F1 hybrid genome, we found that 80% of the genome could be separated into haplotigs. The long range accuracy of phasing haplotigs was evaluated by comparing them to the assemblies from the two inbred parental lines. We show that a more complete view of all haplotypes could provide useful biological insights through improved annotation, characterization of heterozygous variants of all sizes, and resolution of differential allele expression. Finally, we applied this method to WGS human data sets to demonstrate the potential for resolving complicated, medically-relevant genomic regions.

Organization: PacBio
Year: 2016

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