Dataset Information

Sixteen diverse laboratory mouse reference genomes define strain-specific haplotypes and novel functional loci.

ABSTRACT: We report full-length draft de novo genome assemblies for 16 widely used inbred mouse strains and find extensive strain-specific haplotype variation. We identify and characterize 2,567 regions on the current mouse reference genome exhibiting the greatest sequence diversity. These regions are enriched for genes involved in pathogen defence and immunity and exhibit enrichment of transposable elements and signatures of recent retrotransposition events. Combinations of alleles and genes unique to an individual strain are commonly observed at these loci, reflecting distinct strain phenotypes. We used these genomes to improve the mouse reference genome, resulting in the completion of 10 new gene structures. Also, 62 new coding loci were added to the reference genome annotation. These genomes identified a large, previously unannotated, gene (Efcab3-like) encoding 5,874 amino acids. Mutant Efcab3-like mice display anomalies in multiple brain regions, suggesting a possible role for this gene in the regulation of brain development.

SUBMITTER: Lilue J

PROVIDER: S-EPMC6205630 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sixteen diverse laboratory mouse reference genomes define strain-specific haplotypes and novel functional loci.

Lilue Jingtao J Doran Anthony G AG Fiddes Ian T IT Abrudan Monica M Armstrong Joel J Bennett Ruth R Chow William W Collins Joanna J Collins Stephan S Czechanski Anne A Danecek Petr P Diekhans Mark M Dolle Dirk-Dominik DD Dunn Matt M Durbin Richard R Earl Dent D Ferguson-Smith Anne A Flicek Paul P Flint Jonathan J Frankish Adam A Fu Beiyuan B Gerstein Mark M Gilbert James J Goodstadt Leo L Harrow Jennifer J Howe Kerstin K Ibarra-Soria Ximena X Kolmogorov Mikhail M Lelliott Chris J CJ Logan Darren W DW Loveland Jane J Mathews Clayton E CE Mott Richard R Muir Paul P Nachtweide Stefanie S Navarro Fabio C P FCP Odom Duncan T DT Park Naomi N Pelan Sarah S Pham Son K SK Quail Mike M Reinholdt Laura L Romoth Lars L Shirley Lesley L Sisu Cristina C Sjoberg-Herrera Marcela M Stanke Mario M Steward Charles C Thomas Mark M Threadgold Glen G Thybert David D Torrance James J Wong Kim K Wood Jonathan J Yalcin Binnaz B Yang Fengtang F Adams David J DJ Paten Benedict B Keane Thomas M TM

Nature genetics 20181001 11

We report full-length draft de novo genome assemblies for 16 widely used inbred mouse strains and find extensive strain-specific haplotype variation. We identify and characterize 2,567 regions on the current mouse reference genome exhibiting the greatest sequence diversity. These regions are enriched for genes involved in pathogen defence and immunity and exhibit enrichment of transposable elements and signatures of recent retrotransposition events. Combinations of alleles and genes unique to an ...[more]

PMID: 30275530

Similar Datasets

Project description:MotivationHuman ancient DNA (aDNA) studies have surged in recent years, revolutionizing the study of the human past. Typically, aDNA is preserved poorly, making such data prone to contamination from other human DNA. Therefore, it is important to rule out substantial contamination before proceeding to downstream analysis. As most aDNA samples can only be sequenced to low coverages (<1× average depth), computational methods that can robustly estimate contamination in the low coverage regime are needed. However, the ultra low-coverage regime (0.1× and below) remains a challenging task for existing approaches.ResultsWe present a new method to estimate contamination in aDNA for male modern humans. It utilizes a Li&Stephens haplotype copying model for haploid X chromosomes, with mismatches modeled as errors or contamination. We assessed this new approach, hapCon, on simulated and down-sampled empirical aDNA data. Our experiments demonstrate that hapCon outperforms a commonly used tool for estimating male X contamination (ANGSD), with substantially lower variance and narrower confidence intervals, especially in the low coverage regime. We found that hapCon provides useful contamination estimates for coverages as low as 0.1× for SNP capture data (1240k) and 0.02× for whole genome sequencing data, substantially extending the coverage limit of previous male X chromosome-based contamination estimation methods. Our experiments demonstrate that hapCon has little bias for contamination up to 25-30% as long as the contaminating source is specified within continental genetic variation, and that its application range extends to human aDNA as old as ∼45 000 and various global ancestries.Availability and implementationWe make hapCon available as part of a python package (hapROH), which is available at the Python Package Index (https://pypi.org/project/hapROH) and can be installed via pip. The documentation provides example use cases as blueprints for custom applications (https://haproh.readthedocs.io/en/latest/hapCon.html). The program can analyze either BAM files or pileup files produced with samtools. An implementation of our software (hapCon) using Python and C is deposited at https://github.com/hyl317/hapROH.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

Sixteen diverse laboratory mouse reference genomes define strain-specific haplotypes and novel functional loci.

Publications

Sixteen diverse laboratory mouse reference genomes define strain-specific haplotypes and novel functional loci.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets