Kai Zhang, Jianqing Zhao, Shirong Mi, Jiqiang Liu, Jun Luo, Jianxin Liu, Hengbo Shi
{"title":"298只萨宁奶山羊全基因组变异资源。","authors":"Kai Zhang, Jianqing Zhao, Shirong Mi, Jiqiang Liu, Jun Luo, Jianxin Liu, Hengbo Shi","doi":"10.1038/s41597-025-04880-6","DOIUrl":null,"url":null,"abstract":"<p><p>The Saanen breeds are often used as terminal sires for hybridization and play an important role in the global dairy food industry. However, there is still a lack of genomics information on the Saanen dairy goats. Whole-genome sequencing offers a promising approach to identify genetic markers associated with economic traits and discover new candidate genes. This can effectively utilize genetic resources to accelerate breeding processes and improve lactation performance in Saanen dairy goats. In this study, we present the genomes of 298 Saanen dairy goats. Through rigorous sequencing and quality control, we achieved an average sequencing depth of 14.6X, with 92.3% of high-quality (Q30 > 90%) data and an average mapping ratio of 99.9%, indicating reliable results. By comparing our data to a reference genome of Saanen dairy goats, we identified14.59 million single nucleotide polymorphisms (SNPs) and 1.34 million insertions-deletions (InDels). This dataset significantly contributes to enriching public databases in dairy goats and provides valuable resources for studying genetic diversity, improving breeds, and developing new varieties.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"528"},"PeriodicalIF":6.9000,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954942/pdf/","citationCount":"0","resultStr":"{\"title\":\"Whole-genome variants resource of 298 Saanen dairy goats.\",\"authors\":\"Kai Zhang, Jianqing Zhao, Shirong Mi, Jiqiang Liu, Jun Luo, Jianxin Liu, Hengbo Shi\",\"doi\":\"10.1038/s41597-025-04880-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The Saanen breeds are often used as terminal sires for hybridization and play an important role in the global dairy food industry. However, there is still a lack of genomics information on the Saanen dairy goats. Whole-genome sequencing offers a promising approach to identify genetic markers associated with economic traits and discover new candidate genes. This can effectively utilize genetic resources to accelerate breeding processes and improve lactation performance in Saanen dairy goats. In this study, we present the genomes of 298 Saanen dairy goats. Through rigorous sequencing and quality control, we achieved an average sequencing depth of 14.6X, with 92.3% of high-quality (Q30 > 90%) data and an average mapping ratio of 99.9%, indicating reliable results. By comparing our data to a reference genome of Saanen dairy goats, we identified14.59 million single nucleotide polymorphisms (SNPs) and 1.34 million insertions-deletions (InDels). This dataset significantly contributes to enriching public databases in dairy goats and provides valuable resources for studying genetic diversity, improving breeds, and developing new varieties.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"12 1\",\"pages\":\"528\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2025-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954942/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-025-04880-6\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-04880-6","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Whole-genome variants resource of 298 Saanen dairy goats.
The Saanen breeds are often used as terminal sires for hybridization and play an important role in the global dairy food industry. However, there is still a lack of genomics information on the Saanen dairy goats. Whole-genome sequencing offers a promising approach to identify genetic markers associated with economic traits and discover new candidate genes. This can effectively utilize genetic resources to accelerate breeding processes and improve lactation performance in Saanen dairy goats. In this study, we present the genomes of 298 Saanen dairy goats. Through rigorous sequencing and quality control, we achieved an average sequencing depth of 14.6X, with 92.3% of high-quality (Q30 > 90%) data and an average mapping ratio of 99.9%, indicating reliable results. By comparing our data to a reference genome of Saanen dairy goats, we identified14.59 million single nucleotide polymorphisms (SNPs) and 1.34 million insertions-deletions (InDels). This dataset significantly contributes to enriching public databases in dairy goats and provides valuable resources for studying genetic diversity, improving breeds, and developing new varieties.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.