Literature DB >> 35150300

Selection signatures for heat tolerance in Brazilian horse breeds.

Danielle Assis de Faria1, Tiago do Prado Paim2, Camila Alves Dos Santos2, Samuel Rezende Paiva3, Marcelo Bchara Nogueira1, Concepta McManus4.   

Abstract

Since domestication, horse breeds have adapted to their environments and differentiated from one another. This paper uses two methods to detect selection signatures in 23 horse breeds, eight of which are Brazilian (610 animals), both cold-blooded and warm-blooded, from temperate and tropical regions. These animals were genotyped using the GGP Equine BeadChip and we analysed the data by Principal Component Analysis (PCA). The samples were separated into groups based on their geographical area of origin and PCA results studied. The genomic regions under selection were detected by hapFLK and PCAdapt methodologies, identifying six regions under selection with at least one Brazilian horse breed. These regions contain genes associated with heat tolerance, skin colour, body size, energy production/metabolism, genes involved in protein degradation/turnover/DNA repair, genes reducing the impact of oxidative stress/cellular repair, and transcriptional regulation. This work confirmed LCORL and NCAPG gene regions in previous studies associated with body size on Equine Chromosome Autosome 3 (ECA3). On the same ECA3, a region implicating genes linked to coat colour was identified, also previously related to heat stress. Regions with genes coding heat shock proteins were found on ECA1 and 2, and many candidate genes for oxidation-reduction which are a natural response to heat stress. However, a larger sample size and whole-genome SNPs are needed to understand better and identify new candidate regions as well as their functional relation with heat tolerance.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Heat shock proteins; PCAdapt; Principal components; Redox; Temperate and tropical climates; hapFLK

Mesh:

Year:  2022        PMID: 35150300     DOI: 10.1007/s00438-022-01862-w

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


  44 in total

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