Literature DB >> 31152338

Identification of quantitative trait loci associated with flowering time in perilla using genotyping-by-sequencing.

Yun-Joo Kang1, Bo-Mi Lee1, Moon Nam1, Ki-Won Oh2, Myoung-Hee Lee2, Tae-Ho Kim3, Sung-Hwan Jo4, Jeong-Hee Lee5.   

Abstract

Understanding the transition to the reproductive period is important for crop breeding. This information can facilitate the production of novel varieties that are better adapted to local environments or changing climatic conditions. Here, we report the development of a high-density linkage map based on genotyping-by-sequencing (GBS) for the genus perilla. Through GBS library construction and Illumina sequencing of an F2 population, a total of 9607 single-nucleotide polymorphism (SNP) markers were developed. The ten-group linkage map of 1309.39 cM contained 2518 markers, with an average marker density of 0.56 cM per linkage group (LG). Using this map, a total of six QTLs were identified. These quantitative trait loci (QTLs) are associated with three traits related to flowering time: days to visible flower bud, days to flowering, and days to maturity. Ortholog analysis conducted with known genes involved in the regulation of flowering time among different crop species identified GI, CO and ELF4 as putative perilla orthologs that are closely linked to the QTL regions associated with flowering time. These results provide a foundation that will be useful for future studies of flowering time in perilla using fine mapping, and marker-assisted selection for the development of new varieties of perilla.

Entities:  

Keywords:  Crop breeding; Flowering; Genotyping-by-sequencing; Linkage map; Orthologs

Mesh:

Year:  2019        PMID: 31152338     DOI: 10.1007/s11033-019-04894-5

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


  1 in total

1.  Bulk segregant analysis identifies SSR markers associated with leaf- and seed-related traits in Perilla crop (Perilla frutescens L.).

Authors:  Su Eun Lim; Kyu Jin Sa; Ju Kyong Lee
Journal:  Genes Genomics       Date:  2021-02-04       Impact factor: 1.839

  1 in total

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