选择(遗传算法)
基因组学
生物
基因分型
生物技术
参考基因组
全基因组关联研究
分子育种
SNP基因分型
SNP公司
功能基因组学
遗传多样性
人口
遗传学
计算生物学
基因组
基因型
基因
计算机科学
人工智能
医学
单核苷酸多态性
环境卫生
作者
Jagesh Kumar Tiwari,Suresh Reddy Yerasu,Nagendra Rai,Dhananjaya P. Singh,Achuit K. Singh,Suhas G. Karkute,Prabhakar Singh,Tusar Kanti Behera
标识
DOI:10.1080/07352689.2022.2130361
摘要
AbstractTomato is an important vegetable crop for fresh and processed products. In the past decades, conventional breeding cum marker-assisted selection (MAS) has been deployed widely to develop modern tomato cultivars with desirable agronomic traits, market classes, and consumer preferences. The rapid developments in sequencing technologies with the reduced costs per sample, high-throughput single nucleotide polymorphism (SNP) genotyping platforms, and bioinformatics tools have revolutionized crop improvement programs, and deciphered the tomato genome sequence in 2012. Since then thousands of cultivated, its close relatives, and wild species have been genome resequenced to analyze structural variants population structure, genetic diversity, high-density map construction so on. Further, tomato pan-genomes have been constructed to search genomics regions associated with agronomic traits to expedite the breeding process. Importantly, genomics-assisted research has begun in tomatoes with the identification of genes, and SNP markers associated with phenotypic variation by applying genome resequencing, genome-wide association studies (GWAS) using SNP array, and genotyping-by-sequencing techniques. Further, the genomic selection (GS) method is expected to increase breeding efficiency and genetic gain rapidly. This review provides the latest information on progress in MAS to genome resequencing, pan-genomes, SNP genotyping, GWAS, and GS for genomics-assisted breeding in tomatoes.Keywords: Breedinggenome sequencinggenomics-assisted breedingmarker-assisted selectionSNPtomato AcknowledgmentsThe authors thank ICAR-IIVR, Varanasi for the necessary support. Thanks to the ICAR-Lal Bahadur Shastri Outstanding Young Scientist Award project to JKT.
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