Boitard Simon, Paris Cyriel, Sevane Natalia, Servin Bertrand, Bazi-Kabbaj Kenza, Dunner Susana
GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, Castanet-Tolosan, France.
Dpto. Animal Production, Facultad de Veterinaria, Universidad Complutense de Madrid, Madrid, Spain.
Front Genet. 2021 Feb 2;12:575405. doi: 10.3389/fgene.2021.575405. eCollection 2021.
Gene banks, framed within the efforts for conserving animal genetic resources to ensure the adaptability of livestock production systems to population growth, income, and climate change challenges, have emerged as invaluable resources for biodiversity and scientific research. Allele frequency trajectories over the few last generations contain rich information about the selection history of populations, which cannot be obtained from classical selection scan approaches based on present time data only. Here we apply a new statistical approach taking advantage of genomic time series and a state of the art statistic (nSL) based on present time data to disentangle both old and recent signatures of selection in the Asturiana de los Valles cattle breed. This local Spanish originally multipurpose breed native to Asturias has been selected for beef production over the last few generations. With the use of SNP chip and whole-genome sequencing (WGS) data, we detect candidate regions under selection reflecting the effort of breeders to produce economically valuable beef individuals, e.g., by improving carcass and meat traits with genes such as , , , , , , or , while maintaining the ability to thrive under a semi-intensive production system, with the selection of immune (, , , and ) or olfactory receptor (, , , and ) genes. This kind of information will allow us to take advantage of the invaluable resources provided by gene bank collections from local less competitive breeds, enabling the livestock industry to exploit the different mechanisms fine-tuned by natural and human-driven selection on different populations to improve productivity.
基因库作为生物多样性和科学研究的宝贵资源,已在保护动物遗传资源以确保畜牧生产系统适应人口增长、收入和气候变化挑战的努力中崭露头角。过去几代的等位基因频率轨迹包含了有关种群选择历史的丰富信息,而这些信息无法仅从基于当前数据的经典选择扫描方法中获得。在这里,我们应用一种新的统计方法,利用基因组时间序列和基于当前数据的先进统计量(nSL),来解析阿斯图里亚斯山谷牛品种中古老和近期的选择特征。这种原产于西班牙阿斯图里亚斯的当地多用途品种,在过去几代中已被选育用于牛肉生产。通过使用SNP芯片和全基因组测序(WGS)数据,我们检测到了受选择的候选区域,这些区域反映了育种者培育具有经济价值的肉牛个体的努力,例如,通过利用如、、、、、、或等基因改善胴体和肉质性状,同时通过选择免疫(、、、和)或嗅觉受体(、、、和)基因,保持在半集约化生产系统下茁壮成长的能力。这类信息将使我们能够利用当地竞争力较弱品种的基因库所提供的宝贵资源,使畜牧业能够利用自然和人为驱动的选择在不同种群上微调的不同机制来提高生产力。