Person: Hash, C.T.
Loading...
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Hash
First Name
C.T.
Name
Hash, C.T.
ORCID ID
0000-0003-3138-9234 3 results
Search Results
Now showing 1 - 3 of 3
- Exploring Potential of Pearl Millet Germplasm Association Panel for Association Mapping of Drought Tolerance Traits(Public Library of Science, 2015) Sehgal, D.; Skot, L.; Singh, Richa; Srivastava, R.K.; Prasad Das, S.; Taunk, J.; Sharma, P.C.; Pal, R.; Raj, B.; Hash, C.T.; Yadav, R.S.A pearl millet inbred germplasm association panel (PMiGAP) comprising 250 inbred lines, representative of cultivated germplasm from Africa and Asia, elite improved open-pollinated cultivars, hybrid parental inbreds and inbred mapping population parents, was recently established. This study presents the first report of genetic diversity in PMiGAP and its exploitation for association mapping of drought tolerance traits. For diversity and genetic structure analysis, PMiGAP was genotyped with 37 SSR and CISP markers representing all seven linkage groups. For association analysis, it was phenotyped for yield and yield components and morpho-physiological traits under both well-watered and drought conditions, and genotyped with SNPs and InDels from seventeen genes underlying a major validated drought tolerance (DT) QTL. The average gene diversity in PMiGAP was 0.54. The STRUCTURE analysis revealed six subpopulations within PMiGAP. Significant associations were obtained for 22 SNPs and 3 InDels from 13 genes under different treatments. Seven SNPs associations from 5 genes were common under irrigated and one of the drought stress treatments. Most significantly, an important SNP in putative acetyl CoA carboxylase gene showed constitutive association with grain yield, grain harvest index and panicle yield under all treatments. An InDel in putative chlorophyll a/b binding protein gene was significantly associated with both stay-green and grain yield traits under drought stress. This can be used as a functional marker for selecting high yielding genotypes with ‘stay green’ phenotype under drought stress. The present study identified useful marker-trait associations of important agronomics traits under irrigated and drought stress conditions with genes underlying a major validated DT-QTL in pearl millet. Results suggest that PMiGAP is a useful panel for association mapping. Expression patterns of genes also shed light on some physiological mechanisms underlying pearl millet drought tolerance
Publication - Construction of genetic linkage map and QTL analysis of sink-size traits in pearl millet (Pennisetum glaucum)(Hindawi Publishing Corporation, 2013) Vengadessan, V.; Rai, K.N.; Kannan Bapu, J.R.; Hash, C.T.; Bhattacharjee, R.; Senthilvel, S.; Vinayan, M.T.; Nepolean, T.A linkage map, primarily based on SSCP-SNP markers, was constructed using 188 F2:3 mapping population progenies produced from a cross between two pearl millet inbred lines having diverse parentage. The skeleton linkage map covered 1019 cM and it comprised of 44 markers distributed across the seven linkage groups. Average adjacent-marker intervals ranged from on LG1 to on LG6, with an overall mean of . Using the F2 linkage map and phenotypic data from the F2 and F2:3 generations of the mapping population, a total of 18 putative QTLs were detected for the three sink-size components. Eight QTLs explained 42.7% of observed phenotypic variation for panicle length using the F2:3 data set. For panicle diameter, 5 QTLs explained 45.8% of observed phenotypic variation. Similarly for grain size, 5 QTLs explained 29.6% of phenotypic variation. Genomic regions associated with panicle length, panicle diameter, and grain size were comapped on LG6 between Xpsms88 and Xpsms2270, indicating the existence of a gene or gene cluster. The QTLs for panicle length on LG2 and LG6 ( in both F2 and F2:3 data sets), for panicle diameter on LG2 and LG3 ( in the F2:3 data set), and for grain size on LG3 and LG6 ( in both F2 and F2:3 data sets) were identified as promising candidates for validation prior to possible application in marker-assisted breeding.
Publication - Dissecting genome-wide association signals for loss-of-function phenotypes in sorghum flavonoid pigmentation traits(Genetics Society of America, 2013) Morris, G.P.; Rhodes, D.H.; Brenton, Z.; Punna, R.; Vinayan, M.T.; Deshpande, S.; Hash, C.T.; Acharya, C.B.; Mitchell, S.; Buckler, E.; Jianming Yu; Kresovich, S.Genome-wide association studies (GWAS) are a powerful method to dissect the genetic basis of traits, though in practice the effects of complex genetic architecture and population structure remain poorly understood. To compare mapping strategies we dissect the genetic control of flavonoid pigmentation traits in the cereal grass sorghum using high-resolution genotyping-by-sequencing (GBS) SNP markers. Studying the grain tannin trait, we find that General Linear Models (GLM) are not able to precisely map tan1-a, a known loss-of-function allele of the Tannin1 gene, with either a small panel (n = 142) or large association panel (n = 336), and that indirect associations limit the mapping of the Tannin1 locus to Mb-resolution. A GLM that accounts for population structure (Q) or standard Mixed Linear Model (MLM) that accounts for kinship (K) can identify tan1-a, while compressed MLMs performs worse than the naive GLM. Interestingly, a simple loss-of-function genome scan, for genotype-phenotype covariation only in the putative loss-of-function allele, is able to precisely identify the Tannin1 gene without considering relatedness. We also find that the tan1-a allele can be mapped with gene resolution in a biparental recombinant inbred line (RIL) family (n = 263) using GBS markers, but lower precision in the mapping of vegetative pigmentation traits suggest that consistent gene-level resolution will likely require larger families or multiple RILs. These findings highlight that complex association signals can emerge from even the simplest traits given epistasis and structured alleles, but that gene-resolution mapping of these traits is possible with high marker density and appropriate models.
Publication