The Rice Genome Variation Revealed by DNA Sequences

Rice (Oryza sativa) is one of the most important crops in the world. Since the 1st well assembled rice pseudomolecules were published in 2005, rice study has entered the post genomic era. Taking the advantage of it, we may use the physical map, rather than genetic map, to ping point the position and function of the query sequence. Many bioinformatics tools have being invented for various jobs. In this thesis, I would like to demonstrate how to organize these tools to address the questions. In the second chapter, the purpose is to resolute the mystery of how Taichung 65 loss its photoperiod sensitivity. We used accession-specific single nucleotide olymerphism analysis to reveal the gene flow that occurred between different rice accessions decades ago and demonstrate that two landraces introgressed during the breeding process, which led to the loss of photoperiod sensitivity. Both Hd1 and Ehd1 may be important during artificial selection for flowering time, especially in a subtropical region such as Taiwan. Transgenic plant assays have been used frequently for complementation, overexpression or antisense analysis, but sequence changes caused by callus growth, Agrobacterium incubation medium, virulence genes, transformation and selection conditions are unknown. In the third chapter, we used high-throughput sequencing of DNA from rice lines derived from Tainung 67 to analyze non-transformed and transgenic rice plants for mutations caused by these parameters. From the result, we could not conclusively detect sequence changes resulting from Agrobacterium-mediated transformation in addition to those caused by tissue culture-induced somaclonal variation. However, the mutation frequencies within the two publically available tagged mutant populations, including TRIM transformants or Tos17 lines, were about 10-fold higher than the frequency of standard transformants, probably because mass production of embryogenic calli and longer callus growth periods were required to generate these large libraries. Several rice insertional mutant libraries are publicly available for systematic analysis of gene functions. However, the tagging efficiency of these mutant resources–the relationship between genotype and phenotype is very low. In the fourth chapter, we used whole-genome sequencing to analyze a T-DNA-tagged transformant, M28590, from TRIM and one regenerant. Both showed the introgression occurred from some unknown indica rice. For M0028590, the large-grain trait came from the GS3 gene of the introgressed region and the tillering dwarf phenotype came from a single nucleotide change in the D17 gene that occurred during the callus induction to regeneration of the transformant. In addition to the known sequence changes such as T-DNA integration, single nucleotide polymorphism, insertion, deletion, chromosome rearrangement and doubling, spontaneous outcrossing occurred in the rice field may also explain some mutated traits in a tagged mutant population. Thus, the co-segregation of an integration event and the phenotype should be checked when using these mutant populations. The rice Green Revolution (GR) at the 60’S had increased agricultural production by more than two fold worldwide. In the fifth chapter, we propose the opportunities to maintain the diversity of rice germplasm and mining the information of genes. The key gene for the first GR is a lost-of-function of Semi-dwarf1 (SD1) gene, came from an old Taiwan landrace, Dee-Geo-Woo-Gen (DGWG). We mined multiple Sd1 alleles using the 3K-RGP data and validate them from IRRI’s phenomics records. The result showed about five hundred accessions consisted of DGWG sd1 alleles, including some varieties from Taiwan, IRRI and countries worldwide. The Kasalath type, i.e. full-function SD1 allele, however, were present in one-third of 3K project. The Nipponbare type, i.e. partial-function SD1 allele had present in one-fourth of 3K project. That is, sd1 allele had a narrow diversity in the germplasm. Thus, we suggest rice breeders to use the widely collected genomic information for choosing parental lines to include demanded traits and keep the diversity.