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Nagendra Kumar Singh

dblp:223/7646 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics › genome sequencing
genome re-sequencing
0.612022
A first-generation haplotype map (HapMap-1) of tea (Camellia sinensis L. O. Kuntz) · Bioinform. 2022
Bioinformatics and computational biology
genomics
0.612022
A first-generation haplotype map (HapMap-1) of tea (Camellia sinensis L. O. Kuntz) · Bioinform. 2022

Methods — techniques the papers use, named apart from their topics

whole genome re-sequencing · 0.6indel detection · 0.6SNP calling · 0.6
YearPublicationVenuePosition
2022 A first-generation haplotype map (HapMap-1) of tea (Camellia sinensis L. O. Kuntz)
abstract
MOTIVATION: Tea is a cross-pollinated woody perennial plant, which is why, application of conventional breeding is limited for its genetic improvement. However, lack of the genome-wide high-density SNP markers and genome-wide haplotype information has greatly hampered the utilization of tea genetic resources toward fast-track tea breeding programs. To address this challenge, we have generated a first-generation haplotype map of tea (Tea HapMap-1). Out-crossing and highly heterozygous nature of tea plants, make them more complicated for DNA-level variant discovery. RESULTS: In this study, whole genome re-sequencing data of 369 tea genotypes were used to generate 2,334,564 biallelic SNPs and 1,447,985 InDels. Around 2928.04 million paired-end reads were used with an average mapping depth of ∼0.31× per accession. Identified polymorphic sites in this study will be useful in mapping the genomic regions responsible for important traits of tea. These resources lay the foundation for future research to understand the genetic diversity within tea germplasm and utilize genes that determine tea quality. This will further facilitate the understanding of tea genome evolution and tea metabolite pathways thus, offers an effective germplasm utilization for breeding the tea varieties. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Hukam C. Rawal, Ulavappa B. Angadi, Tilak Raj Sharma, Nagendra Kumar Singh, Tapan Kumar Mondal
Bioinform.5