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Featured researches published by Nivedita Singh.


PLOS ONE | 2013

Comparison of SSR and SNP markers in estimation of genetic diversity and population structure of Indian rice varieties.

Nivedita Singh; Debjani Roy Choudhury; Amit Singh; Sundeep Kumar; Kalyani Srinivasan; R. K. Tyagi; Neelima Singh; Rakesh Singh

Simple sequence repeat (SSR) and Single Nucleotide Polymorphic (SNP), the two most robust markers for identifying rice varieties were compared for assessment of genetic diversity and population structure. Total 375 varieties of rice from various regions of India archived at the Indian National GeneBank, NBPGR, New Delhi, were analyzed using thirty six genetic markers, each of hypervariable SSR (HvSSR) and SNP which were distributed across 12 rice chromosomes. A total of 80 alleles were amplified with the SSR markers with an average of 2.22 alleles per locus whereas, 72 alleles were amplified with SNP markers. Polymorphic information content (PIC) values for HvSSR ranged from 0.04 to 0.5 with an average of 0.25. In the case of SNP markers, PIC values ranged from 0.03 to 0.37 with an average of 0.23. Genetic relatedness among the varieties was studied; utilizing an unrooted tree all the genotypes were grouped into three major clusters with both SSR and SNP markers. Analysis of molecular variance (AMOVA) indicated that maximum diversity was partitioned between and within individual level but not between populations. Principal coordinate analysis (PCoA) with SSR markers showed that genotypes were uniformly distributed across the two axes with 13.33% of cumulative variation whereas, in case of SNP markers varieties were grouped into three broad groups across two axes with 45.20% of cumulative variation. Population structure were tested using K values from 1 to 20, but there was no clear population structure, therefore Ln(PD) derived Δk was plotted against the K to determine the number of populations. In case of SSR maximum Δk was at K=5 whereas, in case of SNP maximum Δk was found at K=15, suggesting that resolution of population was higher with SNP markers, but SSR were more efficient for diversity analysis.


PLOS ONE | 2014

Analysis of Genetic Diversity and Population Structure of Rice Germplasm from North-Eastern Region of India and Development of a Core Germplasm Set

Debjani Roy Choudhury; Nivedita Singh; Amit Singh; Sundeep Kumar; Kalyani Srinivasan; R. K. Tyagi; Altaf Ahmad; Neelima Singh; Rakesh Kumar Singh

The North-Eastern region (NER) of India, comprising of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland and Tripura, is a hot spot for genetic diversity and the most probable origin of rice. North-east rice collections are known to possess various agronomically important traits like biotic and abiotic stress tolerance, unique grain and cooking quality. The genetic diversity and associated population structure of 6,984 rice accessions, originating from NER, were assessed using 36 genome wide unlinked single nucleotide polymorphism (SNP) markers distributed across the 12 rice chromosomes. All of the 36 SNP loci were polymorphic and bi-allelic, contained five types of base substitutions and together produced nine types of alleles. The polymorphic information content (PIC) ranged from 0.004 for Tripura to 0.375 for Manipur and major allele frequency ranged from 0.50 for Assam to 0.99 for Tripura. Heterozygosity ranged from 0.002 in Nagaland to 0.42 in Mizoram and gene diversity ranged from 0.006 in Arunachal Pradesh to 0.50 in Manipur. The genetic relatedness among the rice accessions was evaluated using an unrooted phylogenetic tree analysis, which grouped all accessions into three major clusters. For determining population structure, populations Ku200a=u200a1 to Ku200a=u200a20 were tested and population Ku200a=u200a3 was present in all the states, with the exception of Meghalaya and Manipur where, Ku200a=u200a5 and Ku200a=u200a4 populations were present, respectively. Principal Coordinate Analysis (PCoA) showed that accessions were distributed according to their population structure. AMOVA analysis showed that, maximum diversity was partitioned at the individual accession level (73% for Nagaland, 58% for Arunachal Pradesh and 57% for Tripura). Using POWERCORE software, a core set of 701 accessions was obtained, which accounted for approximately 10% of the total NE India collections, representing 99.9% of the allelic diversity. The rice core set developed will be a valuable resource for future genomic studies and crop improvement strategies.


Leprosy Review | 1997

Lymphostimulatory and delayed-type hypersensitivity responses to a candidate leprosy vaccine strain: Mycobacterium habana.

Nivedita Singh; Himanshu Gupta; Anil Srivastava; Hema Kandpal; U. M. L. Srivastava

Lymphostimulatory and delayed-type hypersensitivity (DTH) immune responses to a candidate antileprosy vaccine Mycobacterium habana have been quantified in inbred AKR mice. M. habana vaccine in three physical states, live, heat-killed and gamma-irradiated, was given intradermally to separate groups of mice and after 28 days these mice were given subcutaneous challenge with heat-killed M. leprae and heat-killed M. habana in the left hind footpad. Live BCG vaccine alone and in combination with gamma-irradiated M. habana were also compared similarly. A sufficient degree of DTH response was generated in mice by M. habana vaccine in all physical forms against two challenge antigens (lepromin and habanin). The BCG combination with M. habana did not increase the DTH response indicating internal adjuvanticity endowed in M. habana. The active hypersensitivity of immunized mice was transferable to syngeneic mice by the transfer of sensitized cells from the donor to the recipient mice intravenously. M. leprae-infected Rhesus monkey PBMC have shown comparable stimulatory response with M. habana (sonicate), and M. leprae (sonicate) antigens. The possibility of developing M. habana as a candidate antileprosy vaccine is discussed.


BMC Genetics | 2016

Genetic diversity trend in Indian rice varieties: an analysis using SSR markers

Nivedita Singh; Debjani Roy Choudhury; Gunjan Tiwari; Amit Kumar Singh; Sundeep Kumar; Kalyani Srinivasan; R. K. Tyagi; Ad Sharma; N. K. Singh; Rakesh Singh

BackgroundThe knowledge of the extent and pattern of diversity in the crop species is a prerequisite for any crop improvement as it helps breeders in deciding suitable breeding strategies for their future improvement. Rice is the main staple crop in India with the large number of varieties released every year. Studies based on the small set of rice genotypes have reported a loss in genetic diversity especially after green revolution. However, a detailed study of the trend of diversity in Indian rice varieties is lacking. SSR markers have proven to be a marker of choice for studying the genetic diversity. Therefore, the present study was undertaken with the aim to characterize and assess trends of genetic diversity in a large set of Indian rice varieties (released between 1940–2013), conserved in the National Gene Bank of India using SSR markers.ResultA set of 729 Indian rice varieties were genotyped using 36 HvSSR markers to assess the genetic diversity and genetic relationship. A total of 112 alleles was amplified with an average of 3.11 alleles per locus with mean Polymorphic Information Content (PIC) value of 0.29. Cluster analysis grouped these varieties into two clusters whereas the model based population structure divided them into three populations. AMOVA study based on hierarchical cluster and model based approach showed 3xa0% and 11xa0% variation between the populations, respectively. Decadal analysis for gene diversity and PIC showed increasing trend from 1940 to 2005, thereafter values for both the parameters showed decreasing trend between years 2006-2013. In contrast to this, allele number demonstrated increasing trend in these varieties released and notified between1940 to 1985, it remained nearly constant during 1986 to 2005 and again showed an increasing trend.ConclusionOur results demonstrated that the Indian rice varieties harbors huge amount of genetic diversity. However, the trait based improvement program in the last decades forced breeders to rely on few parents, which resulted in loss of gene diversity during 2006 to 2013. The present study indicates the need for broadening the genetic base of Indian rice varieties through the use of diverse parents in the current breeding program.


Industrial Crops and Products | 2016

Study of arbitrarily amplified (RAPD and ISSR) and gene targeted (SCoT and CBDP) markers for genetic diversity and population structure in Kalmegh [Andrographis paniculata (Burm. f.) Nees]

Gunjan Tiwari; Rakesh Singh; Nivedita Singh; Debjani Roy Choudhury; Ritu Paliwal; Ashok Kumar; Veena Gupta


International Journal of Leprosy and Other Mycobacterial Diseases | 1991

Induction of lepromin positivity in monkeys by a candidate antileprosy vaccine: Mycobacterium habana.

Nivedita Singh; Anil Srivastava; Himanshu Gupta; Ashok Kumar; Sudhir Srivastava


Indian journal of leprosy | 1988

Relative cross reactivity of habanin, lepromin and tuberculin in guinea pigs sensitized with homologous and heterologous mycobacteria.

Nivedita Singh; Anil Srivastava; Himanshu Gupta; Ashok Kumar; V. Chaturvedi


Indian journal of leprosy | 1987

Patterns of immunoglobulins in the serum of leprosy patients

Choudhary Ms; Nivedita Singh; Srivastava K; Himanshu Gupta


Indian journal of leprosy | 1986

Draining lymph node enlargement produced by immunogenic strains of cultivable mycobacteria.

Nivedita Singh; Srivastava K; Himanshu Gupta; Anil Srivastava; Mathur Is


Indian journal of leprosy | 1985

Leucocyte migration inhibition response of Mycobacterium habana with sensitized animals and cells from leprosy patients

Nivedita Singh; Himanshu Gupta; Mathur Is; Ashok Kumar; S. K. Chakraborty

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Himanshu Gupta

All India Institute of Medical Sciences

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Debjani Roy Choudhury

Indian Council of Agricultural Research

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Kalyani Srinivasan

Indian Council of Agricultural Research

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R. K. Tyagi

Indian Council of Agricultural Research

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Rakesh Singh

Indian Council of Agricultural Research

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Sundeep Kumar

Indian Council of Agricultural Research

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Gunjan Tiwari

Indian Council of Agricultural Research

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N. K. Singh

Indian Agricultural Research Institute

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Neelima Singh

Indian Agricultural Research Institute

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Rakesh Kumar Singh

Indian Institute of Space Science and Technology

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