Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India.
BMC Genet. 2013 Dec 9;14:118. doi: 10.1186/1471-2156-14-118.
Identification of true to breed type animal for conservation purpose is imperative. Breed dilution is one of the major problems in sustainability except cases of commercial crossbreeding under controlled condition. Breed descriptor has been developed to identify breed but such descriptors cover only "pure breed" or true to the breed type animals excluding undefined or admixture population. Moreover, in case of semen, ova, embryo and breed product, the breed cannot be identified due to lack of visible phenotypic descriptors. Advent of molecular markers like microsatellite and SNP have revolutionized breed identification from even small biological tissue or germplasm. Microsatellite DNA marker based breed assignments has been reported in various domestic animals. Such methods have limitations viz. non availability of allele data in public domain, thus each time all reference breed has to be genotyped which is neither logical nor economical. Even if such data is available but computational methods needs expertise of data analysis and interpretation.
We found Bayesian Networks as best classifier with highest accuracy of 98.7% using 51850 reference allele data generated by 25 microsatellite loci on 22 goat breed population of India. The FST values in the study were seen to be low ranging from 0.051 to 0.297 and overall genetic differentiation of 13.8%, suggesting more number of loci needed for higher accuracy. We report here world's first model webserver for breed identification using microsatellite DNA markers freely accessible at http://cabin.iasri.res.in/gomi/.
Higher number of loci is required due to less differentiable population and large number of breeds taken in this study. This server will reduce the cost with computational ease. This methodology can be a model for various other domestic animal species as a valuable tool for conservation and breed improvement programmes.
为了保护目的而识别真正的品种动物是至关重要的。除了商业杂交种在受控条件下的情况外，品种稀释是可持续性的主要问题之一。品种描述符已被开发用于识别品种，但这些描述符仅涵盖“纯种”或真正的品种类型动物，不包括未定义或混合种群。此外，在精液、卵子、胚胎和品种产品的情况下，由于缺乏可见的表型描述符，无法识别品种。像微卫星和 SNP 这样的分子标记的出现彻底改变了品种识别，即使是从最小的生物组织或种质中进行识别。已经在各种家畜中报道了基于微卫星 DNA 标记的品种分配。这些方法存在局限性，例如公共领域缺乏等位基因数据，因此每次都必须对所有参考品种进行基因分型，这既不合逻辑也不经济。即使有这样的数据，但计算方法需要数据分析和解释的专业知识。
我们发现贝叶斯网络是最好的分类器，使用在 22 个印度山羊品种群体的 25 个微卫星基因座上生成的 51850 个参考等位基因数据，其准确性最高可达 98.7%。研究中的 FST 值较低，范围从 0.051 到 0.297，整体遗传分化为 13.8%，表明需要更多的基因座来提高准确性。我们在这里报告了世界上第一个使用微卫星 DNA 标记进行品种识别的模型网络服务器，该服务器可免费访问 http://cabin.iasri.res.in/gomi/。
由于研究中采用的群体分化程度较低，品种数量较多，因此需要更多的基因座。该服务器将降低成本并简化计算。这种方法可以作为各种其他家畜物种的模型，作为保护和品种改良计划的宝贵工具。
