Н. Кипень, В. Снытков, В. Иванова, V. Kipen, M. Mikhailova, E. V. Snytkov, E. Romanishko, Ekaterina V. Ivanova
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For the first time, using bioinformatics methods, an analysis of genome-wide projects was carried out for 264 individuals of the species Sus scrofa located in the Sequence Read Archive (NCBI-SRA). The in silico genotype was determined for 692 SNPs, of which 59 SNPs showed a significant potential for differentiation of four commercial breeds: large white (the most significant SNPs are Chr. 6: g.85845403T> G and Chr.16: g.74053569T> C), duroc (Chr. 4: g.55661608A> G, Chr. 14: g.107689091T> C and Chr. 14: g.107939105T> C), landrace (Chr. 5: g.99925204A> G, Chr. 18: g .40100481A> G and Chr. 18: g.7664624A> G) and pietrain (Chr. 13: g.136017764T> C and Chr.17: g.47595840A> G). For breeds of duroc and pietrain pigs, the accuracy of differentiation was at least 99%, for breeds of large white and landrace pigs - over 80%, however, the sensitivity indicator characterizing the percentage of false positive results of classification was slightly over 65%. Creation of models for molecularand-genetic studies of these breeds will allow for a genetic examination of their purebredity, which will contribute to an increase in their breeding value and preservation of the national gene pool.","PeriodicalId":41146,"journal":{"name":"Proceedings of the National Academy of Sciences of Belarus-Agrarian Series","volume":"1 1","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Bioinformatic analysis of genomes of commercial breeds of domestic pigs for identification of breed-specific SNPs\",\"authors\":\"Н. Кипень, В. Снытков, В. Иванова, V. Kipen, M. Mikhailova, E. V. Snytkov, E. Romanishko, Ekaterina V. 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引用次数: 3
摘要
在育种系统中确定农场动物的纯种性对整个畜牧业至关重要。植物品种的纯种育种旨在确保生产高价值的改良育种材料,用于商业性牲畜育种。用单核苷酸多态性(SNP)测定猪的纯种性。今天的多路复用技术已经达到了一个水平,可以在一次运行的设备中同时表征数百只动物的数万和数十万个多态性变体。利用生物信息学方法,首次对序列读取档案(Sequence Read Archive, NCBI-SRA)中264个苏氏scrofa个体的全基因组项目进行了分析。其中59个snp对4个商品品种具有显著的分化潜力:大白(最显著的snp为Chr. 6: G . 85845403t > G和Chr.16: G . 74053569t > C)、杜洛克(Chr. 4: G . 55661608a > G、Chr. 14: G . 107689091t > C和Chr. 14: G . 107939105t > C)、长白(Chr. 5: G . 99925204a > G、Chr. 18: G . 40100481a > G和Chr. 18: G . 7664624a > G)和pietrain (Chr. 13: G . 136017764t > C和Chr.17)。G . 47595840a > G)。杜洛克猪和彼得列猪品种的分类准确率至少为99%,大白猪和长白猪品种的分类准确率超过80%,但分类误报率的敏感性指标略高于65%。为这些品种的分子遗传学研究建立模型将允许对其纯种性进行遗传检查,这将有助于提高其育种价值和保存国家基因库。
Bioinformatic analysis of genomes of commercial breeds of domestic pigs for identification of breed-specific SNPs
Determining the purebredity of farm animals in a breeding system is of key importance for the entire livestock industry. Purebred breeding of plant breeds is designed to ensure the production of high-value improving breeding material for commercial livestock breeding. Determination of purebredity of pigs can be carried out using single nucleotide polymorphisms (SNP). The multiplexing technology today has reached a level that makes it possible to characterize tens and hundreds of thousands of polymorphic variants simultaneously for hundreds of animals in one run of the device. For the first time, using bioinformatics methods, an analysis of genome-wide projects was carried out for 264 individuals of the species Sus scrofa located in the Sequence Read Archive (NCBI-SRA). The in silico genotype was determined for 692 SNPs, of which 59 SNPs showed a significant potential for differentiation of four commercial breeds: large white (the most significant SNPs are Chr. 6: g.85845403T> G and Chr.16: g.74053569T> C), duroc (Chr. 4: g.55661608A> G, Chr. 14: g.107689091T> C and Chr. 14: g.107939105T> C), landrace (Chr. 5: g.99925204A> G, Chr. 18: g .40100481A> G and Chr. 18: g.7664624A> G) and pietrain (Chr. 13: g.136017764T> C and Chr.17: g.47595840A> G). For breeds of duroc and pietrain pigs, the accuracy of differentiation was at least 99%, for breeds of large white and landrace pigs - over 80%, however, the sensitivity indicator characterizing the percentage of false positive results of classification was slightly over 65%. Creation of models for molecularand-genetic studies of these breeds will allow for a genetic examination of their purebredity, which will contribute to an increase in their breeding value and preservation of the national gene pool.