Genetic and QTL analyses of sink size traits in pearl millet (Pennisetum glaucum (L.) R. Br.)

Present study was carried out to characterize the genetic architecture of three sink size component traits (panicle length, panicle diameter and grain size) through genetic and QTL analyses. The plant materials for genetic analysis consisted of two crosses for the generation means and variance analyses, and one cross for triple test cross (TTC) analysis for each of three traits. The material for QTL analysis consisted of 188 F2 and their F2:3 progeny mapping populations of a cross between the two inbred lines. The plant materials were developed during the 2005-06 and the field experiments were conducted during the 2006 rainy and 2007 summer seasons. Scaling and joint scaling tests revealed that a simplistic additive-dominance model did not adequately explain the observed variation for all the three traits in both seasons, providing an evidence for the presence of epistasis. The six-parameter model and the TTC analysis revealed significance of both additive and dominance effects for cross 1 of panicle length, panicle diameter and grain size. However, cross 2 of panicle length and panicle diameter revealed only additive effects and grain size showed the presence of both additive and dominance gene effects. All three types of interactions (additive x additive, additive x dominance and dominance x dominance) were found to be significant in cross 1 for all the traits across seasons using generation means analysis. However, TTC analysis revealed the presence of all types of epistasis for panicle length and panicle diameter. For grain size, it revealed the presence of only additive x dominance and dominance x dominance (j + l) epistasis. In cross 2, additive x additive (i) interaction alone was significant for panicle length and panicle diameter, whereas for grain size, dominance x dominance (l) followed by additive x dominance (j) contributed significantly across seasons. The estimates of broad and narrow-sense heritability were high for all the traits. Correlation coefficient estimates revealed that panicle length, panicle diameter and grain size were positively and significantly associated with grain yield in their respective trait-specific crosses. The linkage map constructed using 44 markers (SNP, SSR, EST-SSR and STS markers) with 188 F2:3 progenies had a total length of 1018.7 cM. The average distance between the marker pairs was 23 cM. QTL analysis performed as composite interval mapping (CIM) identified eight genomic regions for panicle length, one each on LG 1, 2, 4 and 7; and two each on LG 3 and 6. The variation explained by these QTLs ranged from 6.1 to 18.2%. For panicle diameter, five QTLs were found across LG 2, 3, 5, 6 and 7 and the variation explained by these individual QTLs ranged from 6.3 to 30.2%. For grain size also five QTLs were identified across LG 1, 3, 5, 6 and 7 and the individual QTLs explained 6.1 to 21.2% of the observed phenotypic variation across F2 and F2:3 data sets. From the mapped QTLs, one QTL on LG 2 for panicle length, two QTLs each on LG 2 and 3 for panicle diameter and one QTL on LG 3 for grain size are identified as candidate QTLs for marker-assisted selection

Construction of genetic linkage map and QTL analysis of sinksize traits in pearl millet (Pennisetum glaucum)

A linkage map, primarily based on SSCP-SNP markers, was constructed using 188 F2:3 (F2-derived F3) mapping population progenies derived from a cross between two pearl millet inbred lines having diverse pedigrees. The parents had large differences for two sink size traits (grain size and panicle diameter), and also differed for panicle length. The skeleton linkage map covered 1019 cM and it comprised of 44 loci (detected with 24 SSCP-SNP, 10 genomic SSR, 6 EST-SSR and 4 STS primer pairs) distributed across the seven linkage groups. Average adjacent-marker intervals ranged from 14 cM on LG1 to 38 cM on LG6, with an overall mean of 23 cM. Using the F2 linkage map and phenotypic data collected 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, with individual QTLs explaining 6.1 to 18.2% using the F2:3 data set. For panicle diameter, 5 QTLs explained 45.8% of observed phenotypic variation with individual QTLs accounting for 6.3 to 30.2%. Similarly for grain size, 5 QTLs explained 29.6% of phenotypic variation with individual QTLs accounting for 6.1 to 8.9%. Genomic regions associated with panicle length, panicle diameter and grain size co-mapped on LG6 between Xpsms88 and Xpsms2270, indicating the existence of a gene or gene cluster with major effects involved in the control of significant proportions of the phenotypic variation for all three sink-size traits. The QTLs for panicle length on LG2 and LG6 (LOD>3 in both F2 and F2:3 data sets), for panicle diameter on LG2 and LG3 (LOD>14 in the F2:3 data set) and for grain size on LG3 and LG6 (LOD>3 in both F2 and F2:3 data sets) were identified as promising candidates for validation prior to possible application in marker-assisted breeding

Assessment of genetic variability and diversity analysis in medium duration rice accessions

A total of 64 medium duration rice accessions were evaluated for their genetic variability and genetic divergence during Rabi season 2020 at Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal. Analysis of variance revealed significant differences for all the traits considered for the study. The traits spikelets per panicle and filled grains per panicle recorded high GCV as well as PCV thereby indicating that these traits would be improved effectively through selection. Other yield component traits viz., plant height, productive tillers per plant, spikelets per panicle, filled grains per panicle, fertility per cent, grain weight and single plant yield revealed high heritability coupled with high genetic advance, indicating that simple selection could be effective for improving these characters. The D2 values and hierarchical clustering analysis grouped the 64 germplasm into seven clusters. In both the clustering methods, the genotype Gold 44 was grouped under separate clusters indicating that, this is a diverse genotype among all the genotypes taken for study. Further, genotype AD 16124 was grouped under the same cluster in both the clustering methods with the highest cluster mean for grain yield per plant. Hence, this genotype could be efficiently utilized for the yield improvement programme in rice

Construction of Genetic Linkage Map and QTL Analysis of Sink-Size Traits in Pearl Millet (Pennisetum glaucum)

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 14 cM on LG1 to 38 cM on LG6, with an overall mean of 23 cM. 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

Conventional and Molecular Breeding Approaches for Biofortification of Pearl Millet

Pearl millet [Pennisetum glaucum (L.) R. Br.] is an essential diet of more than 90 million people in the semi-arid tropics of the world where droughts and low fertility of soils cause frequent failures of other crops. It is an important nutri-rich grain cereal in the drier regions of the world grown on 26 mha by millions of farmers (IFAD 1999; Yadav and Rai 2013). This makes pearl millet the sixth most important crop in the world and fourth most important food crop of the India, next to rice, wheat, and maize with annual cultivation over an area of ~8 mha. Pearl millet is also primary food crop in sub-Saharan Africa and is grown on 15 mha (Yadav and Rai 2013). The significant increase in productivity of pearl millet in India is attributed to development and adoption of hybrids of early to medium duration maturity. More than 120 diverse hybrids/varieties have been released till date for various production environments. The heterosis breeding and improved crop management technologies increased productivity substantially achieving higher increased production of 9.80 mt in 2016–2017 from 2.60 mt in 1950–1951 in spite of declined of area under the crop by 20–30% over last two decades (Yadav et al. 2012)

Genomic Designing of Pearl Millet:A Resilient Crop for Arid and Semi-arid Environments

Pearl millet [Pennisetum glaucum (L.) R. Br.; Syn. Cenchrus americanus (L.) Morrone] is the sixth most important cereal in the world. Today, pearl millet is grown on more than 30 million ha mainly in West and Central Africa and the Indian sub-continent as a staple food for more than 90 million people in agriculturally marginal areas. It is rich in proteins and minerals and has numerous health benefits such as being gluten-free and having slow-digesting starch. It is grown as a forage crop in temperate areas. It is drought and heat tolerant, and a climate-smart crop that can withstand unpredictable variability in climate. However, research on pearl millet improvement is lagging behind other major cereals mainly due to limited investment in terms of man and money power. So far breeding achievements include the development of cytoplasmic male sterility (CMS), maintenance counterparts (rf) system and nuclear fertility restoration genes (Rf) for hybrid breeding, dwarfing genes for reduced height, improved input responsiveness, photoperiod neutrality for short growing season, and resistance to important diseases. Further improvement of pearl millet for genetic yield potential, stress tolerance, and nutritional quality traits would enhance food and nutrition security for people living in agriculturally dissolute environments. Application of molecular technology in the pearl millet breeding program has a promise in enhancing the selection efficiency while shortening the lengthy phenotypic selection process ultimately improving the rate of genetic gains. Linkage analysis and genome-wide association studies based on different marker systems in detecting quantitative trait loci (QTLs) for important agronomic traits are well demonstrated. Genetic resources including wild relatives have been categorized into primary, secondary and tertiary gene pools based on the level of genetic barriers and ease of gene introgression into pearl millet. A draft on pearl millet whole genome sequence was recently published with an estimated 38,579 genes annotated to establish genomic-assisted breeding. Resequencing a large number of germplasm lines and several population genomic studies provided a valuable insight into population structure, genetic diversity and domestication history of the crop. Successful improvement in combination with modern genomic/genetic resources, tools and technologies and adoption of pearl millet will not only improve the resilience of global food system through on-farm diversification but also dietary intake which depends on diminishingly fewer crops