首页> 外文期刊>Molecular biology reports >Deciphering carbohydrate metabolism during wheat grain development via integrated transcriptome and proteome dynamics
【24h】

Deciphering carbohydrate metabolism during wheat grain development via integrated transcriptome and proteome dynamics

机译:通过综合转录组和蛋白质组动力学在小麦籽粒发育过程中解入碳水化合物代谢

获取原文
获取原文并翻译 | 示例
           

摘要

Grain development of Triticum aestivum is being studied extensively using individual OMICS tools. However, integrated transcriptome and proteome studies are limited mainly due to complexity of genome. Current study focused to unravel the transcriptome-proteome coordination of key mechanisms underlying carbohydrate metabolism during whole wheat grain development. Wheat grains were manually dissected to obtain grain tissues for proteomics and transcriptomics analyses. Differentially expressed proteins and transcripts at the 11 stages of grain development were compared. Computational workflow for integration of two datasets related to carbohydrate metabolism was designed. For CM proteins, output peptide sequences of proteomic analyses (via LC-MS/MS) were used as source to search corresponding transcripts. The transcript that turned out with higher number of peptides was selected as bona fide ribonucleotide sequence for respective protein synthesis. More than 90% of hits resulted in successful identification of respective transcripts. Comparative analysis of protein and transcript expression profiles resulted in overall 32% concordance between these two series of data. However, during grain development correlation of two datasets gradually increased up to tenfold from 152 to 655 degrees Cd and then dropped down. Proteins involved in carbohydrate metabolism were divided in five categories in accordance with their functions. Enzymes involved in starch and sucrose biosynthesis showed the highest correlations between proteome-transcriptome profiles. High percentage of identification and validation of protein-transcript hits highlighted the power of omics data integration approach over existing gene functional annotation tools. We found that correlation of two datasets is highly influenced by stage of grain development. Further, gene regulatory networks would be helpful in unraveling the mechanisms underlying the complex and significant traits such as grain weight and yield.
机译:使用单个OMICS工具进行广泛研究Triticum Aestivum的谷物发展。然而,集成的转录组和蛋白质组研究主要是由于基因组的复杂性。目前的研究重点是在全小麦籽粒发育过程中解开碳水化合物代谢潜在的关键机制的转录组蛋白质组协调。手动解剖麦粒颗粒以获得蛋白质组学和转录组织分析的晶粒组织。比较了晶粒发育11阶段的差异表达的蛋白质和转录物。设计了与碳水化合物新陈代谢相关的两个数据集的计算工作流程。对于CM蛋白,用作搜索相应转录物的蛋白质组学分析(通过LC-MS / MS)的输出肽序列。选择具有较高数量的肽的转录物作为对各种蛋白质合成的真核糖核苷酸序列。超过90%的命中导致成功识别各自的成绩单。蛋白质和转录物表达谱的比较分析导致这两种数据之间的总体32%的一致性。然而,在晶粒发射期间,两个数据集的相关性从152到655摄氏度逐渐增加到十倍,然后掉下来。根据其功能,参与碳水化合物代谢的蛋白质分为五类。参与淀粉和蔗糖生物合成的酶显示出蛋白质组转录组谱之间的最大相关性。高比例的鉴定和验证蛋白质-Ragscript命中率突出显示OMICS数据集成方法对现有基因功能注释工具的功率。我们发现,两个数据集的相关性受到粮食开发阶段的高度影响。此外,基因监管网络将有助于解开诸如谷物重量和产量之类的复杂和显着性状的基础。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号