Dr. Panjabrao Deshmukh Krishi Vidyapeeth

About: Dr. Panjabrao Deshmukh Krishi Vidyapeeth is a education organization based out in Akola, Maharashtra, India. It is known for research contribution in the topics: Population & Crop yield. The organization has 561 authors who have published 268 publications receiving 2452 citations.

Development of genic-SSR markers by deep transcriptome sequencing in pigeonpea [Cajanus cajan (L.) Millspaugh].

Abstract: Pigeonpea [Cajanus cajan (L.) Millspaugh], one of the most important food legumes of semi-arid tropical and subtropical regions, has limited genomic resources, particularly expressed sequence based (genic) markers. We report a comprehensive set of validated genic simple sequence repeat (SSR) markers using deep transcriptome sequencing, and its application in genetic diversity analysis and mapping. In this study, 43,324 transcriptome shotgun assembly unigene contigs were assembled from 1.696 million 454 GS-FLX sequence reads of separate pooled cDNA libraries prepared from leaf, root, stem and immature seed of two pigeonpea varieties, Asha and UPAS 120. A total of 3,771 genic-SSR loci, excluding homopolymeric and compound repeats, were identified; of which 2,877 PCR primer pairs were designed for marker development. Dinucleotide was the most common repeat motif with a frequency of 60.41%, followed by tri- (34.52%), hexa- (2.62%), tetra- (1.67%) and pentanucleotide (0.76%) repeat motifs. Primers were synthesized and tested for 772 of these loci with repeat lengths of ≥18 bp. Of these, 550 markers were validated for consistent amplification in eight diverse pigeonpea varieties; 71 were found to be polymorphic on agarose gel electrophoresis. Genetic diversity analysis was done on 22 pigeonpea varieties and eight wild species using 20 highly polymorphic genic-SSR markers. The number of alleles at these loci ranged from 4-10 and the polymorphism information content values ranged from 0.46 to 0.72. Neighbor-joining dendrogram showed distinct separation of the different groups of pigeonpea cultivars and wild species. Deep transcriptome sequencing of the two parental lines helped in silico identification of polymorphic genic-SSR loci to facilitate the rapid development of an intra-species reference genetic map, a subset of which was validated for expected allelic segregation in the reference mapping population. We developed 550 validated genic-SSR markers in pigeonpea using deep transcriptome sequencing. From these, 20 highly polymorphic markers were used to evaluate the genetic relationship among species of the genus Cajanus. A comprehensive set of genic-SSR markers was developed as an important genomic resource for diversity analysis and genetic mapping in pigeonpea.

The first draft of the pigeonpea genome sequence

Abstract: Pigeonpea (Cajanus cajan) is an important grain legume of the Indian subcontinent, South-East Asia and East Africa. More than eighty five percent of the world pigeonpea is produced and consumed in India where it is a key crop for food and nutritional security of the people. Here we present the first draft of the genome sequence of a popular pigeonpea variety ‘Asha’. The genome was assembled using long sequence reads of 454 GS-FLX sequencing chemistry with mean read lengths of >550 bp and >10-fold genome coverage, resulting in 510,809,477 bp of high quality sequence. Total 47,004 protein coding genes and 12,511 transposable elements related genes were predicted. We identified 1,213 disease resistance/defense response genes and 152 abiotic stress tolerance genes in the pigeonpea genome that make it a hardy crop. In comparison to soybean, pigeonpea has relatively fewer number of genes for lipid biosynthesis and larger number of genes for cellulose synthesis. The sequence contigs were arranged in to 59,681 scaffolds, which were anchored to eleven chromosomes of pigeonpea with 347 genic-SNP markers of an intra-species reference genetic map. Eleven pigeonpea chromosomes showed low but significant synteny with the twenty chromosomes of soybean. The genome sequence was used to identify large number of hypervariable ‘Arhar’ simple sequence repeat (HASSR) markers, 437 of which were experimentally validated for PCR amplification and high rate of polymorphism among pigeonpea varieties. These markers will be useful for fingerprinting and diversity analysis of pigeonpea germplasm and molecular breeding applications. This is the first plant genome sequence completed entirely through a network of Indian institutions led by the Indian Council of Agricultural Research and provides a valuable resource for the pigeonpea variety improvement.

GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data

Abstract: Sorghum [Sorghum bicolor (L.) Moench] is a very important crop in the arid and semi-arid tropics of India and African subcontinent. In the process of release of new cultivars using multi-location data major emphasis is being given on the superiority of the new cultivars over the ruling cultivars, while very less importance is being given on the genotype × environment interaction (GEI). In the present study, performance of ten Indian hybrids over 12 locations across the rainy seasons of 2008 and 2009 was investigated using GGE biplot analysis. Location attributed higher proportion of the variation in the data (59.3–89.9%), while genotype contributed only 3.9–16.8% of total variation. Genotype × location interaction contributed 5.8–25.7% of total variation. We could identify superior hybrids for grain yield, fodder yield and for harvest index using biplot graphical approach effectively. Majority of the testing locations were highly correlated. ‘Which-won-where’ study partitioned the testing locations into three mega-environments: first with eight locations with SPH 1606/1609 as the winning genotypes; second mega-environment encompassed three locations with SPH 1596 as the winning genotype, and last mega-environment represented by only one location with SPH 1603 as the winning genotype. This clearly indicates that though the testing is being conducted in many locations, similar conclusions can be drawn from one or two representatives of each mega-environment. We did not observe any correlation of these mega-environments to their geographical locations. Existence of extensive crossover GEI clearly suggests that efforts are necessary to identify location-specific genotypes over multi-year and -location data for release of hybrids and varieties rather focusing on overall performance of the entries.