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Factors affecting heterotic grouping with cross‐pollinating crops
Agronomy Journal ( IF 2.1 ) Pub Date : 2020-10-06 , DOI: 10.1002/agj2.20485
José Marcelo Soriano Viana 1 , Leonardo Alves Risso 1 , Rodrigo Oliveira deLima 2 , Fabyano Fonseca e Silva 3
Affiliation  

Heterotic grouping based on the analyses of heterosis or combining ability and molecular diversity has not been consistent. The objectives of this study were to investigate the factors affecting heterotic grouping and the significance of the phenotypic and molecular data. We simulated grain yield and molecular data for nine populations, the nine selfed populations, the 36 interpopulation crosses, 225 doubled haploid (DH) lines (25/population), and their 25,200 single crosses. We assumed genetic control by 400 genes and genotyping for 50 and 192 simple sequence repeats (SSR)/single nucleotide polymorphisms (SNP). We assessed heterosis, combining ability, and genetic diversity using a cluster and population structure analyses. We also performed a genetic diversity analysis based on gene frequencies. This analysis revealed seven (clustering) and four (population structure) heterotic groups. Concerning the phenotypic data, there was a consistent result indicating high heterosis between populations with average frequency of the favorable genes of 0.7 and 0.9 and populations with average frequency of the favorable genes of 0.1 and 0.3, and low average intragroup heterosis. This is in agreement with the analysis based on genes. Concerning the molecular data, the correlations between genetic distance with heterosis and specific heterosis were in the range 0.15–0.35 for SSR and in the range −0.14 to 0.01 for SNP. Heterotic grouping is affected by the degree of linkage disequilibrium between genes and molecular markers, the genetic structure of the sample, molecular marker type, measure of genetic divergence, method applied, and criterion for defining the best number of clusters.

中文翻译:

影响异花授粉作物杂种分组的因素

基于杂种优势或结合能力和分子多样性分析的杂种优势分组并不一致。这项研究的目的是调查影响杂合性分组的因素以及表型和分子数据的意义。我们模拟了9个种群,9个自交种群,36个种群间杂交,225个双单倍体(DH)系(25个/种群)及其25,200个单杂交的谷物产量和分子数据。我们假设通过400个基因进行遗传控制,并对50个和192个简单序列重复(SSR)/单核苷酸多态性(SNP)进行基因分型。我们使用聚类和种群结构分析评估了杂种优势,综合能力和遗传多样性。我们还基于基因频率进行了遗传多样性分析。该分析揭示了七个(聚类)和四个(种群结构)杂合基团。关于表型数据,有一致的结果表明,平均优势基因频率为0.7和0.9的种群与平均优势基因频率为0.1和0.3的种群之间的杂种优势较高,而群体内杂种优势则较低。这与基于基因的分析一致。关于分子数据,SSR的遗传距离与杂种优势和特定杂种优势之间的相关性在0.15-0.35范围内,而SNP在-0.14至0.01的范围内。异质分组受基因和分子标记之间连锁不平衡的程度,样品的遗传结构,分子标记类型,遗传差异的度量,所采用的方法,
更新日期:2020-10-06
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