Joint analysis of phenotypic and molecular data for genetic diversity assessment in extra-early orange maize (Zea Mays L.)

表型和分子数据联合分析用于评估早熟橙色玉米(Zea Mays L.)的遗传多样性

阅读:2

Abstract

BACKGROUND: Maize is one of the most important cereals in the world. To maximize the potential of hybrids from heterosis, knowledge of genetic diversity is crucial. This study aimed to examine the population structure and genetic diversity of new extra-early elite orange maize inbred lines of the IITA-Maize Improvement Program using phenotypic and genome-wide SNP markers. One hundred and eighty-seven orange inbred lines sourced from four populations were phenotyped under well-watered conditions and genotyped using the high-density DArTseq platform. RESULTS: Examination of the genetic dissimilarity heatmap based on the Gower matrix derived from phenotypic data showed low variability among the inbred lines, while moderate variability existed based on the identical-by-state (IBS) matrix from SNP markers. Gower matrix (Phenotypic data) assigned the 187 inbred lines into two distinct groups, while IBS matrix (SNP marker data) assigned the inbred lines into four groups. The cophenetic correlation between the two genetics groups (Gower and IBS) was low, indicating a lack of concordance. A joint matrix derived from the Gower and IBS matrices assigned the 187 inbred lines into three groups. Mantel correlation of the combined matrix showed 0.81 and 0.68 magnitudes with the Gower and IBS matrix, respectively. CONCLUSION: The outcome of this study provided new insights into the genetic diversity and population structure of newly developed extra-early orange inbred lines. By facilitating the optimal use of heterosis in hybrid maize breeding, these findings will contribute to the development of high-yield potential and provitamin A-rich varieties, ultimately improving food security and nutrition in the region.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。