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

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 QTLs were identified for them, among which, 12 QTLs were stably identified across different environments. Using RNA sequencing, we scanned the 99,168 genes expression patterns of the whole spike for the recombinant inbred line population. By the combined use of QTL mapping and WGCNA, 29, 47, 20, 26, 54, 46 and 22 candidate genes were predicted for PH, SL, kernel length (KL), kernel width, thousand kernel weight, seed dormancy, and seed vigor, respectively. Candidate genes for different traits had distinct preferences. The known PH regulation genes Rht-B and Rht-D, and the known seed dormancy regulation genes TaMFT can be selected as candidate gene. Moreover, further experiment revealed that there was a SL regulatory QTL located in an interval of about 7 Mbp on chromosome 7A, named TaSL1, which also involved in the regulation of KL. CONCLUSIONS: A combination of QTL mapping and WGCNA was applied to predicted wheat candidate genes for PH, SL and seed traits. This strategy will facilitate the identification of candidate genes for related QTLs in wheat. In addition, the QTL TaSL1 that had multi-effect regulation of KL and SL was identified, which can be used for wheat improvement. These results provided valuable molecular marker and gene information for fine mapping and cloning of the yield-related trait loci in the future.

Insights into transcriptional characteristics and homoeolog expression bias of embryo and de-embryonated kernels in developing grain through RNA-Seq and Iso-Seq.

Bread wheat (Triticum aestivum L.) is an allohexaploid, and the transcriptional characteristics of the wheat embryo and endosperm during grain development remain unclear. To analyze the transcriptome, we performed isoform sequencing (Iso-Seq) for wheat grain and RNA sequencing (RNA-Seq) for the embryo and de-embryonated kernels. The differential regulation between the embryo and de-embryonated kernels was found to be greater than the difference between the two time points for each tissue. Exactly 2264 and 4790 tissue-specific genes were found at 14 days post-anthesis (DPA), while 5166 and 3784 genes were found at 25 DPA in the embryo and de-embryonated kernels, respectively. Genes expressed in the embryo were more likely to be related to nucleic acid and enzyme regulation. In de-embryonated kernels, genes were rich in substance metabolism and enzyme activity functions. Moreover, 4351, 4641, 4516, and 4453 genes with the A, B, and D homoeoloci were detected for each of the four tissues. Expression characteristics suggested that the D genome may be the largest contributor to the transcriptome in developing grain. Among these, 48, 66, and 38 silenced genes emerged in the A, B, and D genomes, respectively. Gene ontology analysis showed that silenced genes could be inclined to different functions in different genomes. Our study provided specific gene pools of the embryo and de-embryonated kernels and a homoeolog expression bias model on a large scale. This is helpful for providing new insights into the molecular physiology of wheat.