{"title":"Barbel chub Squaliobarbus课程的染色体水平基因组组装与注释。","authors":"Qingmei Zheng, Feng Huang, Haiyan Zheng, Hui Zhang, Rushu Wen, Chao Li","doi":"10.1038/s41597-024-04354-1","DOIUrl":null,"url":null,"abstract":"<p><p>The barbel chub Squaliobarbus curriculus, is an economically important freshwater fish in China. The fishery production of the wild populations has declined dramatically, making the development of aquaculture urgently needed. However, the lack of high-quality genome has impeded its artificial breeding and genetic breeding. Herein, we present a chromosome-level genome assembly for S. curriculus by combining HiFi sequencing, Hi-C sequencing, Iso-seq and short-reads RNA-seq data. This assembly was 910.27 Mb in size, with a contig N50 length of 34.70 Mb. 99.50% of the assembled sequences were placed onto 24 chromosomes supported by Hi-C contact map. Using Iso-seq and short-reads RNA-seq data, we identified 28,329 protein-coding genes based on three prediction methods. Of these genes, 27,207 genes (96.04%) were functionally annotated to at least one of the six commonly used databases. Additionally, we annotated 2,041 miRNAs, 16,426 tRNAs, 5,488 rRNAs and 1,536 snRNAs in the S. curriculus genome. Overall, the chromosome-level genome of S. curriculus will provide valuable genomic resources for genetic breeding, population genomics, sex-related marker identifications, and other future studies.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"11 1","pages":"1453"},"PeriodicalIF":6.9000,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11688417/pdf/","citationCount":"0","resultStr":"{\"title\":\"Chromosome-level genome assembly and annotation of Barbel chub Squaliobarbus curriculus.\",\"authors\":\"Qingmei Zheng, Feng Huang, Haiyan Zheng, Hui Zhang, Rushu Wen, Chao Li\",\"doi\":\"10.1038/s41597-024-04354-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The barbel chub Squaliobarbus curriculus, is an economically important freshwater fish in China. The fishery production of the wild populations has declined dramatically, making the development of aquaculture urgently needed. However, the lack of high-quality genome has impeded its artificial breeding and genetic breeding. Herein, we present a chromosome-level genome assembly for S. curriculus by combining HiFi sequencing, Hi-C sequencing, Iso-seq and short-reads RNA-seq data. This assembly was 910.27 Mb in size, with a contig N50 length of 34.70 Mb. 99.50% of the assembled sequences were placed onto 24 chromosomes supported by Hi-C contact map. Using Iso-seq and short-reads RNA-seq data, we identified 28,329 protein-coding genes based on three prediction methods. Of these genes, 27,207 genes (96.04%) were functionally annotated to at least one of the six commonly used databases. Additionally, we annotated 2,041 miRNAs, 16,426 tRNAs, 5,488 rRNAs and 1,536 snRNAs in the S. curriculus genome. Overall, the chromosome-level genome of S. curriculus will provide valuable genomic resources for genetic breeding, population genomics, sex-related marker identifications, and other future studies.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"11 1\",\"pages\":\"1453\"},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2024-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11688417/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-024-04354-1\",\"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/s41597-024-04354-1","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}
Chromosome-level genome assembly and annotation of Barbel chub Squaliobarbus curriculus.
The barbel chub Squaliobarbus curriculus, is an economically important freshwater fish in China. The fishery production of the wild populations has declined dramatically, making the development of aquaculture urgently needed. However, the lack of high-quality genome has impeded its artificial breeding and genetic breeding. Herein, we present a chromosome-level genome assembly for S. curriculus by combining HiFi sequencing, Hi-C sequencing, Iso-seq and short-reads RNA-seq data. This assembly was 910.27 Mb in size, with a contig N50 length of 34.70 Mb. 99.50% of the assembled sequences were placed onto 24 chromosomes supported by Hi-C contact map. Using Iso-seq and short-reads RNA-seq data, we identified 28,329 protein-coding genes based on three prediction methods. Of these genes, 27,207 genes (96.04%) were functionally annotated to at least one of the six commonly used databases. Additionally, we annotated 2,041 miRNAs, 16,426 tRNAs, 5,488 rRNAs and 1,536 snRNAs in the S. curriculus genome. Overall, the chromosome-level genome of S. curriculus will provide valuable genomic resources for genetic breeding, population genomics, sex-related marker identifications, and other future studies.
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.