Research On Compared Transcriptome And Small RNA Of Rhizoctonia Solani AG-1

Rhizoctonia solani AG-1, a widely existing fungus with great harm to many plants, is a serious plant pathogenic fungi which can infect nearly50species of important crops from grain and oil crops, to fruits and vegetables, such as rice, maize, barley, lettuce, sorghum, tomato. Rice sheath blight disease caused by Rhizoctonia solani AG-1IA is one of the " three serious rice diseases ", which occurs in broad area and high frequency in China. IA can infect rice from seedling stage to heading stage, and before and after the period of heading is the most serious stage. Infections occur major at the leaf and the leaf sheath, sometimes at the stalk and spreading to spike, resulting in the plant lodging or heading abnormally, or even the whole plant dead. Because of the large yield losses, how to control the occurrence and damage degree effectively and efficiently is a significant and urgent problem to solve.The purpose of this study is to provide the basis for the possibility of controlling the occurrence of disease in the level of gene regulation and protein expression. In this study, on the one hand, we observed the infection process of the three intraspecific groups of Rhizoctonia solani AG-1:IA, IB and IC, and completed their transcriptome sequencing by Illumina GA II technology. From these data, we analysed the genes expressed and annotated their functions of these three intraspecific groups. More attention were paid to small secreted proteins, especially the cysteine-rich proteins, trying to find their pathogenic proteins and genes, and the reason of difference performance during infection process on different host between these three intraspecific groups. On the other hand, we study the expression characteristics of small RNA during different periods of AG-1IA infecting rice to understand the process of the regulation of the pathogen’s infection on host, and to find key pathogenic genes and regulatory pathways. The main results are as follows:1. By determining of pathogenic and observing infection process and structure, it was observed that the different symptom on different host infected by IA, IB and IC. Furthermore, typical infectious structures, infection cushion and appressorium, and invasion direct or through pores were observed.2. Three cDNA libraries of with paired-end reads of75bp in length were constructed. IA transcriptome had6,367,931reads, IB transcriptome had6,038,800reads, IC transcriptome had5,104,515reads. After sequenced and de novo assembled using Trinity,17,020,336bp,17,354,840bp and14,807,518bp sequences of IA, IB and IC transcriptome were obtained, and21,542,20,487and18,503transcripts of IA, IB, and IC transcriptmes were identified. Among them,14,124,358bp sequences were predicted in the IA genome.3. Using three methods,20,732(96.24%),19,827(96.78%) and17,938(96.95%) ORFs were predicted in IA, IB and IC transcriptome, respectively. After aligned against databases,11129(53.68%),10886(54.90%) and10161(56.65%) transcripts were matched to known genes. Attain were paid on proteins associated with pathogenicity though KOG classification.4. Part of predicted proteins were verified by PCR, and some candidate cysteine-rich proteins were cloned and induced to expression, then tested by HR response on hosts.5. After analyzed small RNA during infection, numbers of small RNAs in IA nutrition growing period and6periods during infection(10h,18h,24h,32h,48h,72h). The total number in period2was the most, which was8to9times more than other periods. The length distribution of small RNAs in seven samples were from18to28nt, the maximum were at23or24nt. Mapping these sequences to genome, rRNA is the most type except unannotated sRNA. And these small RNA of seven samples mapped to both the sense and antisense strand of genomes at roughly equal proportions.6.246novel miRNAs and their target genes were predicted, binding, atalytic activity, cell, cell part, cellular process and metabolic process were the main kinds of the function of these target genes.7. After statistics of expression in known miRNA, differential expression between samples were analysed, and the expression pattern clustering chart were completed. These known miRNAs’ differential expressions might participated in infection process though their up-expressed or down-expressed.8. Completing target genes prediction and GO analyses of known miRNA with differential expression, the regulatory difference of miRNA during different infection stages were emerged.