A germplasm assembly of 128 finger millet genotypes from 18 countries was evaluated for seedling-stage phosphorus (P) responses by growing them in P sufficient (Psuf) and P deficient (Pdef) treatments. Majority of the genotypes showed adaptive responses to low P condition. Based on phenotype behaviour using the best linear unbiased predictors for each trait, genotypes were classified into, P responsive, low P tolerant and P non-responsive types. Based on the overall phenotype performance under Pdef, 10 genotypes were identified as low P tolerants. The low P tolerant genotypes were characterised by increased shoot and root length and increased root hair induction with longer root hairs under Pdef, than under Psuf. Association mapping of P response traits using mixed linear models revealed four quantitative trait loci (QTLs). Two QTLs (qLRDW.1 and qLRDW.2) for low P response affecting root dry weight explained over 10% phenotypic variation. In silico synteny analysis across grass genomes for these QTLs identified putative candidate genes such as Ser-Thr kinase and transcription factors such as WRKY and basic helix-loop-helix (bHLH). The QTLs for response under Psuf were mapped for traits such as shoot dry weight (qHSDW.1) and root length (qHRL.1). Putative associations of these QTLs over the syntenous regions on the grass genomes revealed proximity to cytochrome P450, phosphate transporter and pectin methylesterase inhibitor (PMEI) genes. This is the first report of the extent of phenotypic variability for P response in finger millet genotypes during seedling-stage, along with the QTLs and putative candidate genes associated with P starvation tolerance.

We evaluated the genetic variation and population structure in Indian and non-Indian genotypes of finger millet using 87 genomic SSR primers. The 128 finger millet genotypes were collected and genomic DNA was isolated. Eighty-seven genomic SSR primers with 60–70 % GC contents were used for PCR analysis of 128 finger millet genotypes. The PCR products were separated and visualized on a 6 % polyacrylamide gel followed by silver staining. The data were used to estimate major allele frequency using Power Marker v3.0. Dendrograms were constructed based on the Jaccard’s similarity coefficient. Statistical fitness and population structure analyses were performed to find the genetic diversity. The mean major allele frequency was 0.92; the means of polymorphic alleles were 2.13 per primer and 1.45 per genotype; the average polymorphism was 59.94 % per primer and average PIC value was 0.44 per primer. Indian genotypes produced an additional 0.21 allele than non-Indian genotypes. Gene diversity was in the range from 0.02 to 0.35. The average heterozygosity was 0.11, close to 100 % homozygosity. The highest inbreeding coefficient was observed with SSR marker UGEP67. The Jaccard’s similarity coefficient value ranged from 0.011 to 0.836. The highest similarity value was 0.836 between genotypes DPI009-04 and GPU-45. Indian genotypes were placed in Eleusine coracana major cluster (EcMC) 1 along with 6 non-Indian genotypes. AMOVA showed that molecular variance in genotypes from various geographical regions was 4 %; among populations it was 3 % and within populations it was 93 %. PCA scatter plot analysis showed that GPU-28, GPU-45 and DPI009-04 were closely dispersed in first component axis. In structural analysis, the genotypes were divided into three subpopulations (SP1, SP2 and SP3). All the three subpopulations had an admixture of alleles and no pure line was observed. These analyses confirmed that all the genotypes were genetically diverse and had been grouped based on their geographic regions.

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Finger millet is one of the small millets with high nutritive value. This crop is vulnerable to blast disease caused by Pyricularia grisea, which occurs annually during rainy and winter seasons. Leaf blast occurs at early crop stage and is highly damaging. Mapping of resistance genes and other quantitative trait loci (QTLs) for agronomic performance can be of great use for improving finger millet genotypes. Evaluation of one hundred and twenty-eight finger millet genotypes in natural field conditions revealed that leaf blast caused severe setback on agronomic performance for susceptible genotypes, most significant traits being plant height and root length. Plant height was reduced under disease severity while root length was increased. Among the genotypes, IE4795 showed superior response in terms of both disease resistance and better agronomic performance. A total of seven unambiguous QTLs were found to be associated with various agronomic traits including leaf blast resistance by association mapping analysis. The markers, UGEP101 and UGEP95, were strongly associated with blast resistance. UGEP98 was associated with tiller number and UGEP9 was associated with root length and seed yield. Cross species validation of markers revealed that 12 candidate genes were associated with 8 QTLs in the genomes of grass species such as rice, foxtail millet, maize, Brachypodium stacei, B. distachyon, Panicum hallii and switchgrass. Several candidate genes were found proximal to orthologous sequences of the identified QTLs such as 1,4-β-glucanase for leaf blast resistance, cytokinin dehydrogenase (CKX) for tiller production, calmodulin (CaM) binding protein for seed yield and pectin methylesterase inhibitor (PMEI) for root growth and development. Most of these QTLs and their putatively associated candidate genes are reported for first time in finger millet. On validation, these novel QTLs may be utilized in future for marker assisted breeding for the development of fungal resistant and high yielding varieties of finger millet.

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