Brito Luiz F, Jafarikia Mohsen, Grossi Daniela A, Kijas James W, Porto-Neto Laercio R, Ventura Ricardo V, Salgorzaei Mehdi, Schenkel Flavio S
Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, ON, Canada.
Canadian Centre for Swine Improvement Inc, Ottawa, ON, Canada.
BMC Genet. 2015 Jun 25;16:67. doi: 10.1186/s12863-015-0220-1.
Basic understanding of linkage disequilibrium (LD) and population structure, as well as the consistency of gametic phase across breeds is crucial for genome-wide association studies and successful implementation of genomic selection. However, it is still limited in goats. Therefore, the objectives of this research were: (i) to estimate genome-wide levels of LD in goat breeds using data generated with the Illumina Goat SNP50 BeadChip; (ii) to study the consistency of gametic phase across breeds in order to evaluate the possible use of a multi-breed training population for genomic selection and (iii) develop insights concerning the population history of goat breeds.
Average r(2) between adjacent SNP pairs ranged from 0.28 to 0.11 for Boer and Rangeland populations. At the average distance between adjacent SNPs in the current 50 k SNP panel (~0.06 Mb), the breeds LaMancha, Nubian, Toggenburg and Boer exceeded or approached the level of linkage disequilibrium that is useful (r(2) > 0.2) for genomic predictions. In all breeds LD decayed rapidly with increasing inter-marker distance. The estimated correlations for all the breed pairs, except Canadian and Australian Boer populations, were lower than 0.70 for all marker distances greater than 0.02 Mb. These results are not high enough to encourage the pooling of breeds in a single training population for genomic selection. The admixture analysis shows that some breeds have distinct genotypes based on SNP50 genotypes, such as the Boer, Cashmere and Nubian populations. The other groups share higher genome proportions with each other, indicating higher admixture and a more diverse genetic composition.
This work presents results of a diverse collection of breeds, which are of great interest for the implementation of genomic selection in goats. The LD results indicate that, with a large enough training population, genomic selection could potentially be implemented within breed with the current 50 k panel, but some breeds might benefit from a denser panel. For multi-breed genomic evaluation, a denser SNP panel also seems to be required.
对连锁不平衡(LD)和群体结构的基本理解,以及不同品种间配子相位的一致性,对于全基因组关联研究和基因组选择的成功实施至关重要。然而,在山羊方面这方面的研究仍然有限。因此,本研究的目的是:(i)使用Illumina山羊SNP50芯片生成的数据估计山羊品种全基因组水平的连锁不平衡;(ii)研究不同品种间配子相位的一致性,以评估多品种训练群体用于基因组选择的可能性;(iii)深入了解山羊品种的群体历史。
布尔山羊和草原山羊群体中相邻SNP对之间的平均r²范围为0.28至0.11。在当前50k SNP芯片中相邻SNP的平均距离(约0.06 Mb)下,拉曼查山羊、努比亚山羊、吐根堡山羊和布尔山羊品种的连锁不平衡水平超过或接近对基因组预测有用的水平(r²>0.2)。在所有品种中,连锁不平衡随标记间距离增加而迅速衰减。对于所有大于0.02 Mb的标记距离,除加拿大布尔山羊和澳大利亚布尔山羊群体外,所有品种对之间的估计相关性均低于0.70。这些结果不足以鼓励将不同品种合并到一个单一的基因组选择训练群体中。混合分析表明,一些品种基于SNP50基因型具有独特的基因型,如布尔山羊、绒山羊和努比亚山羊群体。其他群体彼此之间共享更高的基因组比例,表明混合程度更高且遗传组成更加多样。
本研究展示了多个不同品种的研究结果,这些结果对于山羊基因组选择的实施具有重要意义。连锁不平衡结果表明,有足够大的训练群体时,使用当前的50k芯片有可能在品种内实施基因组选择,但一些品种可能会从密度更高的芯片中受益。对于多品种基因组评估,似乎也需要密度更高的SNP芯片。