Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat.

ABSTRACT:

Background

Wheat (Triticum aestivum L.) is an important cereal crop. Increasing grain yield for wheat is always a priority. Due to the complex genome of hexaploid wheat with 21 chromosomes, it is difficult to identify underlying genes by traditional genetic approach. The combination of genetics and omics analysis has displayed the powerful capability to identify candidate genes for major quantitative trait loci (QTLs), but such studies have rarely been carried out in wheat. In this study, candidate genes related to yield were predicted by a combined use of linkage mapping and weighted gene co-expression network analysis (WGCNA) in a recombinant inbred line population.

Results

QTL mapping was performed for plant height (PH), spike length (SL) and seed traits. A total of 68 QT

SUBMITTER: Wei J 

PROVIDER: S-EPMC9190149 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature