A cattle graph genome incorporating global breed diversity

Despite only 8% of cattle being found in Europe, European breeds dominate current genetic resources. This adversely impacts cattle research in other important global cattle breeds, especially those from Africa for which genomic resources are particularly limited, despite their disproportionate impor...

Full description

Saved in:

Bibliographic Details
Published in:	Nature communications 2022-02, Vol.13 (1), p.910-910, Article 910
Main Authors:	Talenti, A, Powell, J, Hemmink, J D, Cook, E A J, Wragg, D, Jayaraman, S, Paxton, E, Ezeasor, C, Obishakin, E T, Agusi, E R, Tijjani, A, Amanyire, W, Muhanguzi, D, Marshall, K, Fisch, A, Ferreira, B R, Qasim, A, Chaudhry, U, Wiener, P, Toye, P, Morrison, L J, Connelley, T, Prendergast, J G D
Format:	Article
Language:	eng
Subjects:	Africa Alleles Animals Assemblies Assembly Cattle Cattle - genetics Chromosome Mapping Europe Gene mapping Genetic resources Genetic Variation Genome Genomes Genomics Male Mapping
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Despite only 8% of cattle being found in Europe, European breeds dominate current genetic resources. This adversely impacts cattle research in other important global cattle breeds, especially those from Africa for which genomic resources are particularly limited, despite their disproportionate importance to the continent's economies. To mitigate this issue, we have generated assemblies of African breeds, which have been integrated with genomic data for 294 diverse cattle into a graph genome that incorporates global cattle diversity. We illustrate how this more representative reference assembly contains an extra 116.1 Mb (4.2%) of sequence absent from the current Hereford sequence and consequently inaccessible to current studies. We further demonstrate how using this graph genome increases read mapping rates, reduces allelic biases and improves the agreement of structural variant calling with independent optical mapping data. Consequently, we present an improved, more representative, reference assembly that will improve global cattle research.
ISSN:	2041-1723 2041-1723