@article {Chen005496, author = {Feng Chen and Zhongdong Dong and Zhang Ning and Zhang Xiangfen and Dangqun Cui}, title = {Different profile of transcriptome between wheat Yunong 201 and its high-yield mutant Yunong 3114}, elocation-id = {005496}, year = {2014}, doi = {10.1101/005496}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Wheat is one of the most important crops in the world. With the exponentially increasing population and the need for ever increased food and feed production, an increased yield of wheat grain (as well as rice, maize and other grains) will be critical. Modern technologies are utilized to assist breeding programs. Such as the transcriptome sequencing, which greatly improves our genetic understanding, provides a platform for functional genomics research on crops. Herein, to get an overview of transcriptome characteristics of Yunong 3114, which is screened from the EMS mutagenized population of, a high quality Chinese winter noodle wheat, due to its different plant architecture as well as larger kernel size and higher grain weight, a high-throughput RNA sequencing based on next generation sequencing technology (Illumina) were performed. These unigenes were annotated by Blastx alignment against the NCBI non-redundant (nr), Clusters of orthologous groups (COG), gene orthology (GO), and the Kyoto Encyclopedia of Genesand Genomes (KEGG) databases. The 90.96\% of the unigenes matched with protein in the NCBI nr database. Functional analysis identified that changes in several GO categories, including recognition of pollen, apoptotic process, defense response, receptor activity, protein kinase activity, DNA integration and so forth, played crucial roles in the high-yield characteristics of the mutant. Real-time PCR analysis revealed that the recognition of pollen related gene GsSRK is significantly up-regulated in Yunong 3114. In addition, alternative splicing (AS) analysis results indicated that mutation influence AS ratio, especially the retained introns, including the pollen related genes. Furthermore, the digital gene expression spectrum (DGE) profiling data provides comprehensive information at the transcriptional level that facilitates our understanding of the molecular mechanisms of various physiological aspects including development and high-yield of wheat. Together, these studies substantially increase our knowledge of potential genes and pathways for the genetic improvement of wheat and provide new insights into the yield and breeding strategies.}, URL = {https://www.biorxiv.org/content/early/2014/05/27/005496}, eprint = {https://www.biorxiv.org/content/early/2014/05/27/005496.full.pdf}, journal = {bioRxiv} }