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Authors: Kuderna, Lukas F K and Tomlinson, Chad and Hillier, LaDeana W and Tran, Annabel and Fiddes, Ian T and Armstrong, Joel and Laayouni, Hafid and Gordon, David and Huddleston, John and Garcia Perez, Raquel and Povolotskaya, Inna and Serres Armero, Aitor and Gómez Garrido, Jèssica and Ho, Daniel and Ribeca, Paolo and Alioto, Tyler and Green, Richard E and Paten, Benedict and Navarro, Arcadi and Betranpetit, Jaume and Herrero, Javier and Eichler, Evan E and Sharp, Andrew J and Feuk, Lars and Warren, Wesley C and Marques-Bonet, Tomas

The chimpanzee is arguably the most important species for the study of human origins. A key resource for these studies is a high-quality reference genome assembly; however, as with most mammalian genomes, the current iteration of the chimpanzee reference genome assembly is highly fragmented. In the current iteration of the chimpanzee reference genome assembly (Pan_tro_2.1.4), the sequence is scattered across more then 183 000 contigs, incorporating more than 159 000 gaps, with a genome-wide contig N50 of 51 Kbp. In this work, we produce an extensive and diverse array of sequencing datasets to rapidly assemble a new chimpanzee reference that surpasses previous iterations in bases represented and organized in large scaffolds. To this end, we show substantial improvements over the current release of the chimpanzee genome (Pan_tro_2.1.4) by several metrics, such as increased contiguity by >750% and 300% on contigs and scaffolds, respectively, and closure of 77% of gaps in the Pan_tro_2.1.4 assembly gaps spanning >850 Kbp of the novel coding sequence based on RNASeq data. We further report more than 2700 genes that had putatively erroneous frame-shift predictions to human in Pan_tro_2.1.4 and show a substantial increase in the annotation of repetitive elements. We apply a simple 3-way hybrid approach to considerably improve the reference genome assembly for the chimpanzee, providing a valuable resource for the study of human origins. Furthermore, we produce extensive sequencing datasets that are all derived from the same cell line, generating a broad non-human benchmark dataset.© The Author 2017. Published by Oxford University Press.

Journal: GigaScience
DOI: 10.1093/gigascience/gix098
Year: 2017

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