R. N. Sarma

Assessing the genetic diversity of rice originating from Bangladesh, Assam and West Bengal

BackgroundGenetic diversity among rice cultivars from Bangladesh and North East India was assessed using a custom 384-SNP microarray assay. A total of 511 cultivars were obtained from several sources, choosing landraces likely to be from the aus subpopulation and modern improved cultivars from Bangladesh. Cultivars from the OryzaSNP set and Rice Diversity Panel 1 (RDP1) were also included for reference.ResultsThe population analysis program STRUCTURE was used to infer putative population groups in the panel, revealing four groups: indica (76 cultivars), japonica (55) and two distinct groups within the aus subpopulation (aus-1 = 99, aus-2 = 151). Principal Component Analysis was used to confirm the four population groups identified by STRUCTURE. The analysis revealed cultivars that belonged to neither aus-1 nor aus-2 but which are clearly aus based on the combined probabilities of their membership of the two aus groups which have been termed aus-admix (96). Information obtained from the panel of 511 cultivars was used to assign rice groups to 74 additional landraces obtained from Assam and West Bengal. While both the aus-1 and aus-2 groups were represented approximately equally in India, aus-2 (which includes cultivar N 22) was more common in Bangladesh, but was not found at all in West Bengal.ConclusionsExamining the distribution of landrace names within theaus-1 and aus-2 groups suggests that aus-1 is associated with the term “boro”, a word used to describe a winter growing season in Bangladesh and Assam. The information described here has been used to select a population of 300 cultivars for Genome Wide Association studies of the aus rice subpopulation.

Variability in Grain Quality Characters of Upland Rice of Assam, India

The grain quality of 100 upland/ahu rice genotypes from Assam, India was assessed. The characteristics measured were grain length, grain width, cooked grain length, cooked grain width, grain elongation ratio after cooking, grain widening ratio after cooking, alkali spreading value, gel consistency, as well as starch, amylose, amylopectin and total soluble sugar contents. Considerable genetic variability among the 100 rice genotypes was observed for the characteristics under study. Analysis of variance revealed highly significant differences among the genotypes for all the characteristics. The difference between genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) was very small for all the characteristics analyzed. High GCV and PCV were found in the characteristic of total soluble sugar content followed by alkali spreading value. The high values for these traits signify the scope for selection to develop superior genotypes. High heritability was recorded in all the characteristics analyzed along with diverse genetic advance which varied from 9.71% to 52.83%. The characteristic of total soluble sugar content showed high heritability with high genetic advance, whereas alkali spreading value and grain widening ratio presented high heritability with moderate genetic advance. This implies that these characteristics are mainly under additive gene effects and could be relied upon further selection based on phenotypic performance. The genotypic correlation coefficient was higher than the phenotypic correlation coefficient, indicating strong inherent associations among the characteristics studied.

Genetic diversity in upland rice of Assam assessed through SSR markers

The genetic diversity in 100 upland rice germplasm of Assam, was analyzed using 120 SSR markers, of which 98 (81.66%) showed useful polymorphism with a total of 183 alleles. The number of alleles ranged from one to three with an average value of 1.867 per locus. The markers showed an average effective number of alleles to be 1.73, average Neis gene diversity was 0.393, and average Shannons Information Index was 0.556. The effective number of alleles and Shannons information index showed positive correlation with the observed number of alleles. The resolving power of the 98 SSR primers ranged from 0.72 for primer RM38 to 2.82 for primer RM592. SSR generated an average similarity of 0.460 with similarity ranging from 0.07 to 1.00. Sufficient diversity was detected among the accessions. A basic molecular database was created for upland rice genotypes, which will be useful to identify and map useful genes that are harbored by these germplasms.

QTL Analysis in Aromatic Rice of Assam, India

The study was carried out to identify quantitative trait loci (QTLs) controlling 12 morphological traits in rice using a F2 derived from Ranjit and Kola Joha cross. A framework linkage map of 1387.9cM was developed using 102 SSR markers and other few markers linked to aroma. QTL analysis based on composite interval mapping identified 24 QTLs was for 12 traits. Among them two QTLs were identified for grain aroma each on chromosome 5 and chromosome 8, out of which the QTLs between Aro1-BAD2 is in similar position with aroma gene of Basmati rice. Most of the QTLs identified in the current study, showed a range of partial to over-dominance effects, indicating complexity of the traits under consideration. Some genomic regions were associated with more than one trait, indicating linkage and/or pleiotropic effects. Marker linked to the QTLs can be considered for use in marker assisted breeding as being confirmatory to other reports.

Variability in Mineral Content of indica Rice Genotypes of Assam, India

Significant genetic variations for grain concentration of all 9 mineral elements were observed. The range of macro elements like, phosphorous (P), sodium (Na), potassium (K), calcium (Ca) and magnesium (Mg) were recorded in the range of 0.272–0.412 per cent, 0.051–0.065 per cent, 0.190–0.232 per cent, 0.023–0.036 per cent and 0.039–0.049 per cent, respectively. The micro elements like iron (Fe), manganese (Mn), copper (Cu) and zinc (Zn) were found to be 2.34–4.21mg/100g, 1.02–3.87 mg/100g, 0.400–1.64 mg/100g and 2.10–4.66 mg/100g respectively. On average, the nine mineral content in rice genotypes were followed an order as P>K>Na>Mg>Ca>Zn>Fe>Mn>Cu. There is a significant correlation observed among different minerals. Highest estimate of GCV and PCV was recorded for Cu, which indicate plentiful variability of Cu content for genetic improvement. High heritability coupled with high genetic advance were observed for Cu, Mn, Zn and Fe which indicate preponderance of additive genetic effect in control of these minerals, which suggested the scope of genetic improvement of these minerals based on phenotypic performance.

Variability in Grain Quality Characters of Local Winter (Sali) Rice of Assam, India

The study on rice germplasm showed considerable genetic variation in different quality characters analyzed. The grain length varied from 5.10 to 8.03 mm, grain width from 2.00 to 3.17 mm, cooked grain length from 7.40 to 12.37 mm, cooked grain width from 3.30 to 7.17 mm, grain elongation ratio from 1.29 to 2.02 and grain widening ratio from 1.37 to 3.32. On dry weight basis, moisture contents of genotypes ranged from 8.33 to 10.74 per cent, amylose from 0.05 to 29.6 per cent, starch from 70.37 to 82.83 per cent, GC from 53 to 100.03 mm, GT from 2 to 7, crude fat content from 2.64 to 3.76 per cent, crude protein content 8.10 to 10.32 and lysine content from 2.71 to 3.39 (g/100 g of protein). UPGMA based cluster analysis revealed the existence of two major clusters (A and B) with additional sub clusters within each major cluster in indica rice genotypes under study for grain quality data. The difference between GCV and PCV was less for all characters except GT, which indicate greater correspondence between phenotype and genotype and less environmental influence and greater role of genetic factors on expression of grain quality traits. Based on above results amylose content trait would be highly effective to be used in breeding programmes for improving cooking and eating quality.

Microsatellite based association studies for grain mineral content in local winter (Sali) rice of Assam

In present investigation, grains of one hundred indica rice genotypes were analyzed for nine mineral contents namely, phosphorus (P), potassium (K), sodium (Na), magnesium (Mg), calcium (Ca), zinc (Zn), iron (Fe), manganese (Mn) and copper (Cu) and genotyped using 112 SSR markers. STRUCTURE analysis identified k=4, indicating at least four distinct groups in a set of 100 rice accessions. Genomewide scanning detected a total of 10 significant markertrait associations (P<0.01), with the R2 values ranging from 8.85% to 24.25%. Three markers, RM231 on chromosome (Chr.) 3, RM234 (chr. 7) and RM162 (chr. 6), were found to be linked for Ca. Three SSR markers, RM3 (chr. 6), RM400 (chr. 6) and RM286 (chr. 11) were found to be associated with Cu content. RM 311 on chr. 10 was found to be associated with Fe content. P was found to be associated with three SSR markers, namely, RM536, RM234 and RM600 on chromosomes 11, 7 and 1, respectively. Some novel QTLs were also detected and implications of these results are discussed.

Assessment of Genetic Diversity of Indigenous Glutinous Rice Genotypes of Assam using SSR Marker

Rice is considered as the best staple food among all cereals. In the present investigation, sixty five polymorphic SSR primers generated a total of 354 alleles. The number of alleles detected by a primer ranged from 2 (RM 105 and RM 171) to 9 (RM 311) with an average of 4.75 alleles per locus. The highest PIC (0.995) was recorded in RM 206 of chromosome 6 and the lowest PIC (0.613) was recorded in RM 171 of chromosome 2. SSR generated an average similarity of 0.294 which ranged from 0.061 (between ‘Lothow Bora and Kmj Bora74) to 0.790 (between ‘Poita Bora 2 and Pakhiloga Bora). Cophenetic correlation studies revealed that SSR data had a good fit (r = 0.81170). The dendrogram classified the rice germplasm under study into two main clusters with around 19 per cent similarity. In spite of the high variability, SSR markers used could not produce unique alleles for the genotypes studied. Incorporation of more germplasm, analysis for their nutritional parameters along with good agronomic traits and use of more SSR markers would help to find suitable germplasm for the rice breeding programme.