Transcriptome Data Mining And Software Development Based On Tillering

Bioinformatics is a cross-discipline between life science and computer science.It interactively uses biological and computational technology to detect biologically meaningful information from massive biological data.In recent years,studying plant transcriptome sequence using bioinformatics has become a research hotspot in various disciplines in the field of life sciences.This study focuses on an important agronomic trait,tillering,which determines wheat yield,and takes the transcriptome sequencing data of multiple near-isogenic lines(NILs)pairs which developed for high-low tiller number as the analysis object,starting with mRNA,lncRNA and miRNA,and screening tillering-related genetic components from a large amount of data.First,through the significance verification of expression differences between the NILs,homologous gene annotation,functional annotation and pathway analysis,we identified a set of mRNA and ncRNA which related to tillering from a large amount of wheat transcriptome sequence.Based on the co-expression network,the ceRNA network and the expression-trends/interaction-pattern of the three types ofRNA between materials,we screened multipleRNA interaction relationships related to target traits.Subsequently,based on the transcriptomes of two pairs of near-isogenic materials,this study explored the SSR markers that showed polymorphism among the NIL pairs,laying the foundation for the subsequent development of molecular markers that can distinguish high/low tiller-number genotypes.Finally,through optimizing the sequence alignment algorithms written by oneself during the development of polymorphic SSR markers,we developed an efficient,accurate and easy-to-install software that can detect polymorphic SSR loci and develop corresponding markers.The major results obtained in this study,i.e.the variousRNA data sets related to tillering,the correlation betweenRNAs,and the tool for SSR markers development,provide powerful supports for the follow-up study of wheat tillering mechanism.The developed polymorphic SSR marker mining software can be applied to genomic or transcriptomic data of other species.The main results obtained are as follows:1.Identify differentially expressed tillering-related homologus genes and provides a accurate set of genes for the research on wheat tilleringA total of 10102 wheat mRNA are differentially expressed in pairwise comparisons,15 of which are homologous to the branching and tillering genes in Arabidopsis thaliana and rice through bioinformatics analysis.Their differentially expressed characteristics could be repeated between 2 pairs of NILs,and the positive or negative relationship was consistent with the genes reported previously.There were 137 wheat genes enriched into 11tillering-related pathways.In this search,the tiller gene set was gradually reduced through screening of various analyses.2.Identify tillering-related lncRNA and fill the gap in the lack of tillering-related lncRNA.A total of 4226 ncRNAs were identified,including 4131 lncRNAs transcripts and 95 miRNAs.Thirty-six tillering related ncRNAs were extracted through pathways by differentially expressed target genes.This study not only enriched the ncRNA set in wheat species,but also filled the gap of the lack of tiller traits related lncRNA.The interaction between miRNA-lncRNA was constructed to lay a foundation for ceRNA network.3.Construct WGCNA and ceRNA networks and discover variousRNA interaction patterns related to tillering.A total of 23 expression modules were calculated,and 1 tillering-related network capable of showing lncRNA-miRNA-mRNA interaction was identified,which included tiller homologous genes,candidate lncRNA and differentially expressed miRNA.A ceRNA network was constructed,and 3 ceRNA networks containing homologous target genes of tillering were screened out.This study connects the various types ofRNAs expressed in the wheat transcriptome,and provides a multi-dimensional reference for subsequent research on tillering from different aspects ofRNA biology.4.Develop software to generate polymorphic SSR markers and serve subsequent research of tillering-related genes.Twelve SSRs linked with tillering candidate genes were identified and corresponding molecular markers were developed.These markers were polymorphic in both of the NILs pairs and were consistent with the tillering phenotypes in the two NILs pairs,respectively.A software for detecting polymorphic SSR markers has been developed.The research in this chapter not only lays the foundation for the subsequent development of molecular markers that can distinguish the genotypes of tillering,but also provides a more convenient tool for researchers who need to develop SSR markers.5.Test and compare the performance of SSRMMD software to prove that the algorithm is efficient and the calculation result is accurate.SSRMMD software has low algorithm complexity and fully supports multithreaded parallel operation.Compared with other similar software,SSRMMD has obvious advantages in operating efficiency and agility.Among 56 amplified pairs of primers,44 pairs(about 79%)found polymorphism in CS and AK58,indicating that SSRMMD has high accuracy.The software has been published and cited by other researchers.