浙江豇豆地方品种的遗传多样性
Genetic diversity of cowpea landraces in Zhejiang Province,China
汪宝根 1陈小央 2吴健 3李潇 3汪颖 1王尖 1吴晓花 1鲁忠富 1孙玉燕 1董文其 1李国景 1吴新义4
作者信息
- 1. 浙江省农业科学院 蔬菜研究所,浙江 杭州 310021;浙江省农业科学院 农业农村部南方豆类蔬菜种质创新与分子育种重点实验室(部省共建),浙江 杭州 310021
- 2. 浙江省种子管理总站,浙江杭州 310020
- 3. 浙江省农业科学院 蔬菜研究所,浙江 杭州 310021;浙江农林大学园艺科学学院,浙江杭州 311300
- 4. 浙江省农业科学院 蔬菜研究所,浙江 杭州 310021;浙江省农业科学院 农业农村部南方豆类蔬菜种质创新与分子育种重点实验室(部省共建),浙江 杭州 310021;浙江省农业科学院 省部共建农产品质量安全危害因子与风险防控国家重点实验室,浙江 杭州 310021
- 折叠
摘要
浙江省是我国豇豆的主要产区之一,为全面梳理、鉴定浙江省地方豇豆种质资源,对浙江省历年来收集到的220 份豇豆地方品种进行21 个重要性状的田间鉴定.结果表明,浙江省豇豆地方种质具有丰富的表型变异,基于表型数据的聚类分析可以将它们分为4 个类群,其中类群Ⅲ的综合表现接近目前生产上的育成品种,具有较高的育种使用价值.本研究还利用豇豆物种特异的核心单核苷酸多态性(SNP)标记对其进行基因型鉴定,构建了各种质DNA指纹图谱,基于基因型数据将之分为4 个亚群,其中亚群Ⅲ的荚长较长.本研究从多角度评价了浙江省豇豆地方种质的遗传多样性,研究结果可以为豇豆种质创新和新品种选育提供科学依据.
Abstract
Zhejiang is one of the main cowpea producing areas in China.To systematically sort out and identify the cowpea landraces in Zhejiang Province,220 cowpea accessions collected in Zhejiang Province in multi-years were e-valuated on 21 important traits in the field.The results showed that these landraces had large phenotypic variation,and they could be divided into four clusters according to their phenotype data,of which,Cluster Ⅲ displayed the similar phenotypes with the current released cultivars,indicating that these accessions had high values for cowpea breeding.Using the cowpea specific core single nucleotide polymorphisms(SNPs),the genotypes of 220 landraces were also identified and their DNA fingerprinting was constructed.Based on their genotype data,these accessions were also divided into four subpopulations,and subpopulationⅢ showed the longest pods.In summary,the genetic diversity of Zhejiang cowpea landraces was evaluated from different perspectives,and the results would provide a sci-entific basis for cowpea germplasm enhancement and new cultivars development.
关键词
豇豆/种质资源/遗传多样性/基因型Key words
cowpea/germplasm/genetic diversity/genotype引用本文复制引用
基金项目
2022-2024年农作物种质资源精准鉴定评价任务(豇豆)(2023R23T60D01)
2022-2024年农作物种质资源精准鉴定评价任务(豇豆)(2022R23T60D04)
浙江省农业新品种选育重大专项(2021C02065-6-3)
浙江省重点研发计划(2022C02016)
出版年
2024
国家科技期刊平台
NSTL
万方数据