| Rice(Oryza sativa L.)is vital to the lives of billions of people around the world.The production of rice is challenging with wide range of environmental stresses,including biotic and abiotic stresses,which would limit rice yield.Thus,it is of great importance to perform indepth explorations on the genes that are closely associated with the stress-resistant traits in rice,in order to develop new stress-resistant rice varieties.The sequence information produced by using different sequencing technologies allows researchers to identify large numbers of molecular genetic markers which could be used in the heritable trait studies and new variety improvement.New generation sequencing(NGS)technologies are speeding up genome resequencing projects,leading to vast increase in the amount of data but also resulting in major computational challenges.Additionally,the availability of number of bioinformatics tools poses major barriers to the research community.In this research work,a new rice genomic variant analysis pipeline was developed to process the huge rice NGS data.After that,the pipeline was used to detect the stresses-resistant candidate variants from the stresses-resistant rice germplasm genome,and develop a database of rice stresses-resistant SNPs(Single Nucleotide Polymorphisms).Finally,we discovered and analysed the genomic variants from 178 rice varieties with different ability to resist blast fungus infection.The results were listed at below.1.DNA sequencing has become omnipresent technology used in life sciences as an effective method of measuring genomic variation.The increase in use of DNA-seq technology has led to the continuous development of new tools for every analysis step from alignment to downstream variant analysis.However,effective use of these analysis tools in a scalable and reproducible way can be challenging,especially for non-experts.Using the workflow management system Snakemake,we developed a user friendly,fast,efficient and comprehensive pipeline for rice genomic variant analysis.This pipeline was a workflow that combined the most popular tools to perform genomic variant analysis from raw sequencing data quality control and alignment to downstream variant analysis.It was created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities.The pipeline had been conveniently packaged such that minimal computational skills were required to download and install the required software packages.This genomic variant analysis pipeline was a comprehensive solution that performed most standard NGS data quickly and effectively with a built-in capacity for customization and expansion.In addition,it generated different intermediate sequence summary statistics.2.Rice(Oryza sativa L.)yield is limited inherently by environmental stresses,including biotic and abiotic stresses.Thus,it is of great importance to perform in-depth explorations on the genes that are closely associated with the stress-resistant traits in rice.The existing rice SNP databases have made considerable contributions to rice genomic variation information but none of them have a particular focus on integrating stress-resistant variation and related phenotype data into one web resource.Rice Stress-Resistant SNP database(http://bioinformatics.fafu.edu.cn/RSRS)mainly focuses on SNPs specific to biotic and abiotic stress-resistant ability in rice,and presents them in a unified web resource platform.The Rice Stress-Resistant SNP(RSRS)database contains over 9.5 million stress-resistant SNPs and 797 stress-resistant candidate genes in rice,which were detected from more than 400 stress-resistant rice varieties.We incorporated the SNPs function,genome annotation and phenotype information into this database.Besides,the database has a user-friendly web interface for users to query,browse and visualize a specific SNP efficiently.RSRS database allows users to query the SNP information and their relevant annotations for individual variety or more varieties.The search results can be visualized graphically in a genome browser or displayed in formatted tables.Users can also align SNPs between two or more rice accessions.RSRS database shows great utility for scientists to further characterize the function of variants related to environmental stress-resistant ability in rice.3.The foundation for the continued improvement of rice cultivars with blast-resistant ability is the rich genetic diversity within rice blast-resistant populations and wild relatives.Single Nucleotide Polymorphisms(SNPs),important resource of genetic diversity,are often used in rice cultivar improvement program.In this research work,one hundred and seventyeight rice cultivars with different resistant ability to blast fungus were used as materials,genomic wide SNPs were detected between blast-resistant and susceptible rice varieties to explore blast-resistant candidate genes in rice.A total of 1,964,811 SNPs were detected from 152 blast resistant and 26 susceptible cultivars genomes.Among these,14408 ns SNPs distributed in 5916 genes were simultaneously presented in over 5% of the tested blast-resistant rice varieties.Interestingly,we found 70% of the above blast-resistant candidate ns SNPs were located in the experimentally identified blast-resistant QTLs in rice.Moreover,by combining with the gene expression in rice under blast fungus infection,we found 112 genes with 211 blast-resistant candidate ns SNPs were up-regulated and 49 genes with 68 blast-resistant candidate genes were down-regulated by blast fungus infection.In addition,it was observed that 20% of the significantly regulated genes in the 3 RNA-seq datasets of rice under blast fungus infection contained blast-resistant candidate ns SNPs.To further refine the blastresistant candidate ns SNPs,in-silico predictors were used to identify the impact of blastresistant candidate ns SNPs on the up-regulated genes.The results showed that 73 blast resistant candidate ns SNPs in 56 genes were deleterious SNPs.Finally,we evaluated the effect of blastresistant candidate ns SNPs on the structure and function of their proteins.In summary,a new rice genomic variant analysis pipeline and a database for rice stresses-resistant SNPs were firstly developed in this research work.Secondly,the variant detection strategy combined with transcriptome analysis technology were used to identify blast-resistant candidate ns SNPs and genes in rice.The results in this study would give the clues for future experimental research work and provide a functional gene pool for markerassisted breeding to develop blast-resistant new rice varieties. |
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