ABSTRACT
Sheath blight is considered the most significant disease of rice and causes enormous yield losses over the world. Breeding for resistant varieties is the only viable option to combat the disease efficiently. Seventeen diverged rice genotypes along with 17 QTL-linked SSR markers were evaluated under greenhouse conditions. Pearson's correlation showed only the flag leaf angle had a significant correlation with sheath blight resistance under greenhouse screening. Multivariate analysis based on UPGMA clustering and principal component analysis (PCA) indicated that the flag leaf angle, flag leaf length, and plant compactness were significantly associated with the following SSR marker alleles: RM209 (116,130), RM202 (176), RM224 (126), RM257 (156), RM426 (175), and RM6971 (196), which are linked to the SB QTLs: QRlh11, qSBR11-3, qSBR11-1, qSBR9-1, qShB3-2, and qSB-9. A Mantel test suggested a weak relationship between the observed phenotypes and allelic variation patterns, implying the independent nature of morphological and molecular variations. Teqing and Tetep were found to be the most resistant cultivars. IR65482-4-136-2-2, MR219-4, and MR264 showed improved resistance potentials. These results suggest that the morphological traits and QTLs which have been found to associate with sheath blight resistance are a good choice to enhance resistance through pyramiding either 2 QTLs or QTLs and traits in susceptible rice cultivars.
ABSTRACT
DNA marker-assisted selection (MAS) has become an indispensable component of breeding. Single nucleotide polymorphisms (SNP) are the most frequent polymorphism in the rice genome. However, SNP markers are not readily employed in MAS because of limitations in genotyping platforms. Here the authors report a Golden Gate SNP array that targets specific genes controlling yield-related traits and biotic stress resistance in rice. As a first step, the SNP genotypes were surveyed in 31 parental varieties using the Affymetrix Rice 44K SNP microarray. The haplotype information for 16 target genes was then converted to the Golden Gate platform with 143-plex markers. Haplotypes for the 14 useful allele are unique and can discriminate among all other varieties. The genotyping consistency between the Affymetrix microarray and the Golden Gate array was 92.8%, and the accuracy of the Golden Gate array was confirmed in 3 F2 segregating populations. The concept of the haplotype-based selection by using the constructed SNP array was proofed.
Subject(s)
Genes, Plant/genetics , Haplotypes , Oryza/genetics , Polymorphism, Single Nucleotide , Base Sequence , Gene Frequency , Genetics, Population/methods , Genome, Plant/genetics , Genotype , Genotyping Techniques/methods , Microarray Analysis/methods , Molecular Sequence Data , Oryza/classification , Plant Breeding/methods , Reproducibility of Results , Selective Breeding , Sequence Homology, Nucleic AcidABSTRACT
Cold stress at the seedling stage is a major threat to rice production. Cold tolerance is controlled by complex genetic factors. We used an F7 recombinant inbred line (RIL) population of 123 individuals derived from a cross of the cold-tolerant japonica cultivar Jinbu and the cold-susceptible indica cultivar BR29 for QTL mapping. Phenotypic evaluation of the parents and RILs in an 18/8 °C (day/night) cold stress regime revealed continuous variation for cold tolerance. Six QTLs including two on chromosome 1 and one each on chromosomes 2, 4, 10, and 11 for seedling cold tolerance were identified with phenotypic variation (R(2)) ranging from 6.1 to 16.5 %. The QTL combinations (qSCT1 and qSCT11) were detected in all stable cold-tolerant RIL groups, which explained the critical threshold of 27.1 % for the R(2) value determining cold tolerance at the seedling stage. Two QTLs (qSCT1 and qSCT11) on chromosomes 1 and 11, respectively, were fine mapped. The markers In1-c3, derived from the open reading frame (ORF) LOC_Os01g69910 encoding calmodulin-binding transcription activator (CAMTA), and In11-d1, derived from ORF LOC_Os11g37720 (Duf6 gene), co-segregated with seedling cold tolerance. The result may provide useful information on seedling cold tolerance mechanism and provide DNA markers for a marker-assisted breeding program to improve seedling cold tolerance in indica rice varieties.
