Dataset Information

Hybrid sequencing reveals insight into heat sensing and signaling of bread wheat.

ABSTRACT: Wheat (Triticum aestivum L.), a globally important crop, is challenged by increasing temperatures (heat stress, HS). However its polyploid nature, the incompleteness of its genome sequences and annotation, the lack of comprehensive HS-responsive transcriptomes and the unexplored heat sensing and signaling of wheat hinder our full understanding of its adaptations to HS. The recently released genome sequences of wheat, as well as emerging single-molecular sequencing technologies, provide an opportunity to thoroughly investigate the molecular mechanisms of the wheat response to HS. We generated a high-resolution spatio-temporal transcriptome map of wheat flag leaves and filling grain under HS at 0 min, 5 min, 10 min, 30 min, 1 h and 4 h by combining full-length single-molecular sequencing and Illumina short reads sequencing. This hybrid sequencing newly discovered 4947 loci and 70 285 transcripts, generating the comprehensive and dynamic list of HS-responsive full-length transcripts and complementing the recently released wheat reference genome. Large-scale analysis revealed a global landscape of heat adaptations, uncovering unexpected rapid heat sensing and signaling, significant changes of more than half of HS-responsive genes within 30 min, heat shock factor-dependent and -independent heat signaling, and metabolic alterations in early HS-responses. Integrated analysis also demonstrated the differential responses and partitioned functions between organs and subgenomes, and suggested a differential pattern of transcriptional and alternative splicing regulation in the HS response. This study provided comprehensive data for dissecting molecular mechanisms of early HS responses in wheat and highlighted the genomic plasticity and evolutionary divergence of polyploidy wheat.

SUBMITTER: Wang X

PROVIDER: S-EPMC6850178 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Hybrid performance during wheat breeding can be improved by analyzing genetic distance (GD) among wheat genotypes and determining its correlation with heterosis. This study evaluated the GD between 16 wheat genotypes by using 60 simple sequence repeat (SSR) markers to classify them according to their relationships and select those with greater genetic diversity, evaluate the correlation of the SSR marker distance with heterotic performance and specific combining ability (SCA) for heat stress tolerance, and identify traits that most influence grain yield (GY). Eight parental genotypes with greater genetic diversity and their 28 F1 hybrids generated using diallel crossing were evaluated for 12 measured traits in two seasons. The GD varied from 0.235 to 0.911 across the 16 genotypes. Cluster analysis based on the GD estimated using SSRs classified the genotypes into three major groups and six sub-groups, almost consistent with the results of principal coordinate analysis. The combined data indicated that five hybrids showed 20% greater yield than mid-parent or better-parent. Two hybrids (P2 × P4) and (P2 × P5), which showed the highest performance of days to heading (DH), grain filling duration (GFD), and GY, and had large genetic diversity among themselves (0.883 and 0.911, respectively), were deemed as promising heat-tolerant hybrids. They showed the best mid-parent heterosis and better-parent heterosis (BPH) for DH (-11.57 and -7.65%; -13.39 and -8.36%, respectively), GFD (12.74 and 12.17%; 12.09 and 10.59%, respectively), and GY (36.04 and 20.04%; 44.06 and 37.73%, respectively). Correlation between GD and each of BPH and SCA effects based on SSR markers was significantly positive for GFD, hundred kernel weight, number of kernels per spike, harvest index, GY, and grain filling rate and was significantly negative for DH. These correlations indicate that the performance of wheat hybrids with high GY and earliness could be predicted by determining the GD of the parents by using SSR markers. Multivariate analysis (stepwise regression and path coefficient) suggested that GFD, hundred kernel weight, days to maturity, and number of kernels per spike had the highest influence on GY.

Dataset Information

Hybrid sequencing reveals insight into heat sensing and signaling of bread wheat.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets