Mapping Of QTLs For Cold Tolerance And Dominant Genic Male Sterility Gene SMS In Rice

Rice is one of the most important food crops in the world, which is the staple food for over half of the world’s population. To improve the rice yield, work should be do from two aspects. On the one hand, potential of rice’s yield should be improved, for example using hybrid vigour, on the other hand, rice’s ability to withstand adverse environment should be enhance. Therefore, we must strengthen studies the genetic basis of the traits with relation to yield and stress resistance of rice. So, We carried out the following two parts of research in the study.Part one:mapping of cold tolerance QTLs at seedling stage in rice.Low temperature is causing-10%rice yield loss in the world every year. Therefore, improvement of cold tolerance at the seedling stage (CTSS) is important for rice. CTSS in rice is a complex trait controlled by multiple genes. A number of QTLs underlying CTSS have been mapped in rice using traditional molecular marker technologies. But traditional methods of QTL mapping are labor-intensive and time-consuming. Recent studies have suggested that bulked segregant analysis (BSA) combined with next-generation sequencing (NGS)(NGS-BSA) can be a labor intensive, time-consuming and cost-effective promising way for dissecting quantitative loci for cold tolerance in rice. Therefore, in this study, we employed the NGS-BSA to map QTL conferring cold tolerance at seedling stage in rice. The main methods and results are as follows:1. Research methodsConstruction of extreme DNA pools.10,800F3seedlings from a cross between rice varieties Nipponbare and LPBG were tested for cold tolerance, from which430extremely sensitive (ES) and385extremely tolerant (ET) individuals were selected and a pair of DNA pools were constructed and sequenced with the illumina technology.Sequencing data analysis and QTL mapping. First, The raw DNA-seq reads were trimmed and filtered via a modified Mott trimming algorithm. The preprocessed reads that passed the quality control were then aligned to the published rice (Nipponbare) reference genome using Bowtie0.12.7. For uniquely mapped reads in total pool (ES and ET), SNP identification was performed using SAMTools. Last, QTL analysis was performed using the two methods G statistics and Jensen-Shannon divergence. And, to identify which parent possesses the resistant allele of a putative QTL, Nipponbare allele frequency difference (NAFD) of the Nipponbare allele frequency (fN) between the ET and ES pools was computed. In addition, to find candidate genes in the intervals including QTLs identified, The microarray data downloaded from GEO database were reanalyzed with LIMMA, and the results of which were compared with the NGS results in the study.2. The results of NGSa total of-800M were obtained, with approximately360M and440M from the ES and ET pools, respectively. After trimming and filtering, About70%of the selected reads were mapped to unique positions in the reference genome. These uniquely mapped reads covered-92%of the genome in both pools, with an average depth of-70and89in the ES and ET pools, respectively, or-158altogether. And, a total of456,777SNPs meeting the given requirements for QTL analysis were obtained.3. QTL mappingWe employed two statistical methods for QTL analysis based on these SNPs, which yielded consistent results. six QTL, qCTSS-1, qCTSS-2a, qCTSS-2b, qCTSS-5, qCTSS-8and qCTSS-10, were mapped on chromosomes1,2,5,8and10, respectively. In this study, we take two intervals for each QTL, the full interval and the most probable interval. The full intervals of the QTL were all very wide, ranging from8.68Mb to5.36Mb. The most probable interval were all much narrower than the full intervals except for qCTSS-2. The three most significant QTL, qCTSS-1, qCTSS-2b and qCTSS-8, were validated by previous studies. The other three QTL, qCTSS-2a、qCTSS-5and qCTSS-10are novel QTL identified in the study for the CTSS trait in rice. The resistant alleles of qCTSS-1, qCTSS-2and qCTSS-10were from Nipponbare, while those of qCTSS-5and qCTSS-8were from LPBG.4. candidate genes analysisWe identified the candidate genes that show amino acid variations between the parental varieties and significant responses to low temperature stress within the most probable intervals of the mapped QTL. The number of the candidate genes in the interval of six QTL changes from20(qCTSS-2a) to53(qCTSS-10).Part two:Mapping of dominant genie male sterility gene SMS in riceMale sterility is the foundation of heterosis utilization. In order to advance the cross-breeding, it is very important to fully understand the molecular mechanism of male sterility. At present, the genic male sterility genes mapped in plants almost are recessive, compared to little dominant genic male sterility genes. The mutant of "Sanming Dominant Genic Male Sterile Rice"was found in an F2population, which derived from a cross between SE21S and Basmati370under Sanming Institute of Agricultural Science in2001. We know that the male sterility of this mutant is controlled by a dominant gene (named as SMS). We carried on the SMS comparatively fine mapping and analysis of candidate genes. The main methods and results are as follows:1. Research methodsBy multiple backcrosses, this dominant male sterile allele was introduced into the genetic background of an indicarice cultivar Jiafuzhan (which was known as Jiabuyu). In order to map SMS, a mapping population was constructed by crossing Jiabuyu with a japonica cultivar Nipponbare and further crossing the F1with Jiafuzhan. By bulked segregant analysis and linkage analysis using SSR and INDEL markers, we carried out the SMS mapping. And we analysised differential expression of the candidate genes between Jiabuyu and Jiafuzhan in inflorescence through real-time PCR.2. The results of SMS mappingSMS was mapped to a99kb interval between INDEL markers ZM30and ZM9on chromosome8. We identified13candidate genes for SMS using bioinformatics analysis.3. candidate genes expression analysisThe results of expression of candidate genes showed that the gene expression of LOC_Os08g03820, was different between Jiabuyu and Jiafuzhan under twice biological replication. And LOC_Os08g03790was different at one of biological replication. candidate genes. Another candidate genes without differential expression.