IDENTIFICATION AND CHARACTERIZATION OF QTLs CONTAINING GRAIN SHAPE AND GRAIN SIZE IN RICE (Oryza sativa L.) USING GENOMIC APPROACHES

In Pakistan, rice is the second major food crop, followed by wheat and plays a fundamental role in foreign exchange earnings by contributing 1.6% to the GDP. Grain shape and grain size are the main components in the formation of yield, directly affect the appearance quality of rice and influence on the market value of rice. Rice germplasm collection and knowledge of genetic diversity are major requirements for variety improvement. Molecular markers provide a powerful tool for for genetic variation and mapping of gene/ QTLs. To Identify gene and QTLs-controlling grain size and grain shape, both forward (QTL mapping) and reverse genetic (TILLING and EcoTILLING) approaches were used. To evaluate genetic and phenotypic diversity SSR markers were designed on 48 rice accessions. Clustering based on grain length divided the 48 accessions into two major clusters with some contractions. Genetic relationships among the 48 rice accessions were determined based on allelic diversity using Power Marker tree, population structure analyses and PCoA were performed by using 51 SSR markers located on chromosome 3 and chromosome 7. Two-dimensional PCoA scaling and Power Marker tree analysis showed high-level of differentiation between Basmati and indica rice accessions and divide these rice accessions in two distinct clusters. To apply TILLING to basmati rice for grain size and grain shape, EMS (ethyl methane sulphonate) mutated population (M2) of super basmati was developed. PCR was performed with exon specific primers of two major genes (GS3 and GW2) controlling grain size and grain shape. In the two targeted genes 14 (GS3) and 73 (GW2) point mutations were identified. In exon four of GS3 genes, 4 nonsynonymous mutations were identified out of which only haplotype that had amino acid substitution Lysine (K) to Glutamate (E) showed an increase in grain length. Numbers of mutations were identified in GW2 gene, controlling grain width and grain weight, in seventh and eight exons. To identify natural variation in basmati rice, EcoTILLING technique was used. \ud Nine basmati lines with the contrast of IR64 and Nipponbare were used in 1:1 ratio. EcoTILLING result showed the number of banding patterns in both genes (GS3 and GW2). Sequencing analysis of the amplified regions of these genes identified point mutations insertion and deletion of nucleotides. Translation of nucleotide sequence to amino acid revealed frame shift mutations in third and fourth exons of GS3, while in GW2 detected one nonsynonymous mutation in seventh exon before the frameshift mutations. The result of TILLING (Target Induces Local Lesions IN Genome) and EcoTILLING revealed that these techniques can be used for the identification of natural and artificially induced mutations in rice by using simple agarose-based method. Through EcoTILLING diversity was identified in basmati group which are genetically identical to each other. These allelic variations can be used in breeding programs of rice by designing SNP and InDel markers. A forward genetics technique QTL mapping was done by using SNP markers with the Illumina BeadXpress in F2 population of IR64 and Sadri. A population derived from the indica mega variety IR64 and high quality aromatic variety Sardi from Iran was phenotyped and 96 F2:3 families representing the phenotypic extremes were genotyped. A linkage map of 210 SNP markers was constructed. Fourteen QTLs were identified, controlling the grain length, grain width, length/width ratio and 1000 grain weight. A major QTL derived from Sadri for decreased length / width ratio and increase grain weight mapped on chromosome 8 which showing effect on all four traits with different phenotypic variance. This study demonstrated the speed and efficiency in using multiplex SNP genotyping for QTL analysis. Moreover, the novel QTLs identified for grain quality characters between an indica and aromatic varieties complemented previous indica/ japonica QTLs and will enable more precise marker assisted selection for grain weight, shape and size. More studies are required for fine mapping of this QTL to identify gene(s) in different genetic backgrounds