Identifying Novel Candidate Defense Genes Against Rice Blast By Disease-Resistance Transcriptome Analysis

biorxiv(2022)

引用 0|浏览4
暂无评分
摘要
A blast-resistance rice mutant, GR978, generated by gamma-irradiation of indica cultivar IR64 was used to characterize the disease resistance transcriptome of rice to gain a better understanding of genes or chromosomal regions contributing to broad-spectrum disease resistance. GR978 was selected from the IR64 mutant collection at IRRI. To facilitate phenotypic characterization of the collection, a set of controlled vocabularies (CV) documenting mutant phenotypes in ∼3,700 entries was developed. In collaboration with the Tos17 rice mutant group at National Institute of Agrobiological Sciences, Japan, a merged CV set with 91 descriptions that map onto public ontology databases (PO, TO, OBO) is implemented in the IR64 mutant database. To better characterize the disease resistance transcriptome of rice, gene expression data from a blast resistant cultivar, SHZ-2, was incorporated in the analysis. Disease resistance transcriptome parameters, including differentially expressed genes (DEGs), regions of correlated gene expression (RCEs), and associations between DEGs and RCEs were determined statistically within and between genotypes using MAANOVA, correlation, and fixed ratio analysis. Twelve DEGs were found within the inferred physical location of the recessive gene locus on a ∼3.8MB region of chromosome 12 defined by genetic analysis of GR978. Highly expressed DEGs (≥ 2fold difference) in GR978 or SHZ-2 and in common between the two, are mostly defense-response related, suggesting that most of the DEGs participate in causing the resistance phenotype. Comparing RCEs between SHZ-2 and GR978 showed that most RCEs between genotypes did not overlap. However, an 8-gene RCE in chromosome 11 was in common between SHZ2 and GR978. Gene annotations and GO enrichment analysis showed a high association with resistance response. This region has no DEGs nor is it associated with known blast resistance QTLs. Association analyses between RCEs and DEGs show that there was no enrichment of DEGs in the RCEs within a genotype and across genotypes as well. Association analysis of blast-resistance QTL (Bl-QTLs) regions (assembled from published literature; data courtesy of R. Wisser, pers comm., Cornell University) with DEGs and RCEs showed that while Bl- QTLs are not significantly associated with DEGs, they are associated with genotype-specific RCEs; GR978- RCEs are enriched within Bl-QTLs. The analysis suggested that examining patterns of correlated gene expression patterns in a chromosomal context (rather than the expression levels of individual genes) can yield additional insights into the causal relationship between gene expression and phenotype. Based on these results, we put forward a hypothesis that QTLs with small or moderate effects are represented by genomic regions in which the genes show correlated expression. It implies that gene expression within such a region is regulated by a common mechanism, and that coordinated expression of the region contributes to phenotypic effects. This hypothesis is testable by co segregation analysis of the expression patterns in well-characterized backcross and recombinant inbred lines. ### Competing Interest Statement The authors have declared no competing interest. * Bl-QTL : Rice-Blast specific QTL CDE : Constitutively Differentially Expressed DEG : Differentially Expressed Gene DI : Differentially Induced FL-cDNA : Full-Length complementary DNA GO : Gene Ontology HCL : Hierarchical Clustering KOME : Knowledge-based Oryza Molecular biological Encyclopedia MAANOVA : Microarray Analysis of Variance QTL : Quantitative Trait Locus RCE : Regions of Correlated gene Expression SHZ-2 : Sanhuangzhan 2
更多
查看译文
关键词
novel candidate defense genes,rice blast,disease-resistance
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要