Pardeep Kumar

Dr. Pardeep Kumar

ICAR-Indian Institute of Maize Research, Ludhiana, India
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 June 2021 in Journal of Genetics
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Journal Article
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Pardeep KumarPardeep Kumar
Pardeep Kumar
MCMukesh Choudhary
Mukesh Choudhary
BJB. S. Jat
B. S. Jat
BKBhupender Kumar
Bhupender Kumar
VSVishal Singh
Vishal Singh
SRSujay Rakshit
Sujay Rakshit

17 March 2022 in Plants
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Journal Article
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BKBhupender Kumar
Bhupender Kumar
SRSujay Rakshit
Sujay Rakshit
SKSonu Kumar
Sonu Kumar
BSBrijesh Kumar Singh
Brijesh Kumar Singh
CLChayanika Lahkar
Chayanika Lahkar
HFHossain Firoz
Hossain Firoz
Several maize breeding programs in India have developed numerous inbred lines but the lines have not been characterized using high-density molecular markers. Here, we studied the molecular diversity, population structure, and linkage disequilibrium (LD) patterns in a panel of 314 tropical normal corn, two sweet corn, and six popcorn inbred lines developed by 17 research centers in India, and 62 normal corn from the International Maize and Wheat Improvement Center (CIMMYT). The 384 inbred lines were genotyped with 60,227 polymorphic single nucleotide polymorphisms (SNPs). Most of the pair-wise relative kinship coefficients (58.5%) were equal or close to 0, which suggests the lack of redundancy in the genomic composition in the majority of inbred lines. Genetic distance among most pairs of lines (98.3%) varied from 0.20 to 0.34 as compared with just 1.7% of the pairs of lines that differed by <0.20, which suggests greater genetic variation even among sister lines. The overall average of 17% heterogeneity was observed in the panel indicated the need for further inbreeding in the high heterogeneous genotypes. The mean nucleotide diversity and frequency of polymorphic sites observed in the panel were 0.28 and 0.02, respectively. The model-based population structure, principal component analysis, and phylogenetic analysis revealed three to six groups with no clear patterns of clustering by centers-wise breeding lines, types of corn, kernel characteristics, maturity, plant height, and ear placement. However, genotypes were grouped partially based on their source germplasm from where they derived.

27 March 2022 in Genes
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SASumit Kumar Aggarwal
Sumit Kumar Aggarwal
ASAlla Singh
Alla Singh
Mukesh ChoudharyMukesh Choudhary
Mukesh Choudhary
KAKumar AUNDY
Kumar AUNDY
SRSujay Rakshit
Sujay Rakshit
Rajeev VarshneyRajeev Varshney
Rajeev Varshney
Advances in sequencing technologies and bioinformatics tools have fueled a renewed interest in whole genome sequencing efforts in many organisms. The growing availability of multiple genome sequences has advanced our understanding of the within-species diversity, in the form of a pangenome. Pangenomics has opened new avenues for future research such as allowing dissection of complex molecular mechanisms and increased confidence in genome mapping. To comprehensively capture the genetic diversity for improving plant performance, the pangenome concept is further extended from species to genus level by the inclusion of wild species, constituting a super-pangenome. Characterization of pangenome has implications for both basic and applied research. The concept of pangenome has transformed the way biological questions are addressed. From understanding evolution and adaptation to elucidating host–pathogen interactions, finding novel genes or breeding targets to aid crop improvement to design effective vaccines for human prophylaxis, the increasing availability of the pangenome has revolutionized several aspects of biological research. The future availability of high-resolution pangenomes based on reference-level near-complete genome assemblies would greatly improve our ability to address complex biological problems.

8 July 2013 in Communications in Soil Science and Plant Analysis
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Journal Article
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JRJ. N. Raina
J. N. Raina
SSS. Suman
S. Suman
Pardeep KumarPardeep Kumar
Pardeep Kumar
RSR. S. Spehia
R. S. Spehia
Studies were undertaken to investigate the effect of drip fertigation and conventional fertilizations with and without mulch on the productivity of apple. Soil moisture under fertigation remained greater in the upper 0–30 cm of soil, whereas under conventional surface irrigation, deeper layers registered greater values. Mulch application resulted in 2–4% greater moisture and raised the minimum but lowered the maximum soil temperatures, especially during later growth periods. Available nitrogen (N) and potassium (K) contents under fertigation closely followed the moisture distribution pattern. Irrespective of treatments, available phosphorus (P) remained confined within upper 0- to 20-cm soil depth. Fertigation resulted in 35% greater growth and yield over conventional fertilization with irrigations besides saving 25% in irrigation water. Joint use of fertigation and mulch resulted in comparable growth and yield as unmulched condition and saved 20% in fertilizers and 15% in irrigation water.

29 March 2022 in Genes
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BKBhupender Kumar
Bhupender Kumar
Mukesh ChoudharyMukesh Choudhary
Mukesh Choudhary
Pardeep KumarPardeep Kumar
Pardeep Kumar
KKKrishan Kumar
Krishan Kumar
SKSonu Kumar
Sonu Kumar
SRSujay Rakshit
Sujay Rakshit
Maize is an important cereal crop in the world for feed, food, fodder, and raw materials of industries. Turcicum leaf blight (TLB) is a major foliar disease that can cause more than 50% yield losses in maize. Considering this, the molecular diversity, population structure, and genome-wide association study (GWAS) for TLB resistance were studied in 288 diverse inbred lines genotyped using 89 polymorphic simple sequence repeats (SSR) markers. These lines werescreened for TLB disease at two hot-spot locations under artificially inoculated conditions. The average percent disease incidence (PDI) calculated for each genotype ranged from 17 (UMI 1201) to 78% (IML 12-22) with an overall mean of 40%. The numbers of alleles detected at a locus ranged from twoto nine, with a total of 388 alleles. The polymorphic information content (PIC) of each marker ranged between 0.04 and 0.86. Out of 89 markers, 47 markers were highly polymorphic (PIC ≥ 0.60). This indicated that the SSR markers used were very informative and suitable for genetic diversity, population structure, and marker-trait association studies.The overall observed homozygosity for highly polymorphic markers was 0.98, which indicated that lines used were genetically pure. Neighbor-joining clustering, factorial analysis, and population structure studies clustered the 288 lines into 3–5 groups. The patterns of grouping were in agreement with the origin and pedigree records of the genotypesto a greater extent.A total of 94.10% lines were successfully assigned to one or another group at a membership probability of ≥0.60. An analysis of molecular variance (AMOVA) revealed highly significant differences among populations and within individuals. Linkage disequilibrium for r2 and D′ between loci ranged from 0 to 0.77 and 0 to 1, respectively. A marker trait association analysis carried out using a general linear model (GLM) and mixed linear model (MLM), identified 15 SSRs markers significantly associated with TLB resistance.These 15 markers were located on almost all chromosomes (Chr) except 7, 8, and 9. The phenotypic variation explained by these loci ranged from 6% (umc1367) to 26% (nc130, phi085). Maximum 7 associated markers were located together on Chr 2 and 5. The selected regions identified on Chr 2 and 5 corroborated the previous studies carried out in the Indian maize germplasm. Further, 11 candidate genes were identified to be associated with significant markers. The identified sources for TLB resistance and associated markers may be utilized in molecular breeding for the development of suitable genotypes.

1 July 2023 in Molecular Biology Reports
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Mukesh ChoudharyMukesh Choudhary
Mukesh Choudhary
ASAlla Singh
Alla Singh
MDMm Das
Mm Das
Pardeep KumarPardeep Kumar
Pardeep Kumar
RNRitu Naliath
Ritu Naliath
SRSujay Rakshit
Sujay Rakshit