Autosomal STR allele frequencies in Kahars of Uttar Pradesh, India, drawn with PowerPlex® 21 multiplex system

Batham, Mukesh Sunmansingh; Kushwaha, K.P.S.; Chauhan, Tanya; Kumawat, R. K.; Shrivastava, Pankaj

doi:10.1007/s00414-019-02046-9

Cited by 15 publications

(7 citation statements)

References 2 publications

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“…STR genotyping has been applied in forensic investigations for nearly 30 years ( Hagelberg et al, 1991 ; Kayser and de Knijff 2011 ). Nowadays, several commercial STR kits have been developed based on the expanded CODIS loci ( Oostdik et al, 2014 ; Wang et al, 2018 ; Qu et al, 2019 ; Batham et al, 2020 ; Green et al, 2021 ). However, with the rapid increase in the number of STR genotypes in forensic databases, more novel non-CODIS STRs with high genetic polymorphisms are required to minimize the incidence of adventitious matches.…”

Section: Forensic Potential Applications—development and Validation O...mentioning

confidence: 99%

Editorial: Forensic investigative genetic genealogy and fine-scale structure of human populations

Wei

Wang

2023

Front. Genet.

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Section: Forensic Potential Applications—development and Validation O...mentioning

confidence: 99%

Editorial: Forensic investigative genetic genealogy and fine-scale structure of human populations

Wei

Wang

2023

Front. Genet.

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“…The genetic dataset of present study was compared with the dataset of reported indigenous populations viz., Balmiki (Punjab) 29 , Sakaldwipi Brahmin (Jharkhand) 29 , Konkanastha_Brahmin (Maharashtra) 29 , Iyengar (Tamilnadu) 29 , Kurumans (Tamilnadu) 29 , Munda (Jharkhand) 29 , Chenchu (Andhra Pradesh) 30 , Lambadi (Andhra Pradesh) 30 , Naikpod_Gond (Andhra Pradesh) 30 , Yerukula (Andhra Pradesh) 30 , Munda (Chotanagpur) 31 , Santal (Chotanagpur) 31 , Oraon (Chotanagpur) 31 , Lodha (Bengal) 32 , Kora (Bengal) 32 , Maheli (Bengal) 32 , Central Indian Population 33 , Gond (MP) 34 , Gond_2 (MP) 35 , Gond_1 (MP) 29 , Oraon (Chhattishgarh) 36 , Population of Jharkhand 37 , Jat Sikh (Punjab) 38 , Baniya (Punjab) 38 , Khatri (Punjab) 38 , Population of Uttar Pradesh 39 , Kahar population (UP) 40 , Himachal Pradesh Population 18 , Gorkhas 41 , Tamil Population (Tamil Nadu) 42 , Population of Rajasthan 43 , Population of Odisha 44 and Bhuiyan Population (Jharkhand) 45 ;and global populations namely; Manchu Population of China 46 , Han Population of Southern China 47 , Tibetan Population (Nepal) 48 , Kathmandu 49 , Tibet 49 , Newar 49 1).…”

Section: Genetic Data Of Reported Populations For Comparisonmentioning

confidence: 99%

Genomic Insight Into 21 Hypervariable Molecular Markers in The Population of Lower Himalayan Geographical Province Himachal Pradesh, India

Sharma

Srivast

Sahajpal

et al. 2021

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A natural geographical barrier between Tibetan plateau and south Asian countries, the Himalayan Mountain range, serves as a natural barrier between these regions for genetic flow. This has lead to vast genomic divergence among the population residing in Indian Himalayan region..This study was designed with an aim to decipher the genomic diversity and molecular characterization of 21 hypervariable molecular markers in the population of geographical province of Himachal Pradesh in the lower Himalayan region. Randomly selected 401 unrelated individuals native of the lower Himalayan geographical region were included for this study. 21 hypervariable molecular markers included in the PowerPlex® 21 system were amplified and genotyped. A total of 246 alleles and 12.3 (SE 0.927) private alleles per locus were observed. Population differentiation analysis revealed that the studied population showed a genetic affinity with the population of North India, North-west India, Central India, and Uttar Pradesh rather than the population of East India, South India, East Asia, and West Asia. Heterozygosity at the studied loci was found in the range of 0.686 to 0.920. The unite discrimination power (PD) and exclusion power (PE) was found to be 1 and 0.999999998073765 respectively. The unite value of matching probability and typical paternity index was found to be 9.33x10-26 and 5.05x108 respectively for the studied population. All the tested loci were found in Hardy Weinberg Equilibrium (HWE) expectations. Overall the studied population exhibited a great extent of genomic diversity and had a greater genetic affinity with Indo-European speakers rather than Dravidian and Tibeto-Burman speakers.

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“…Further, Arlequin v3.5 software [20] was also used for comparison of allele frequencies of the studied population data with the previously published population data by Fst pairwise distance. The previously reported populations, namely; Kahar Population (Uttar Pradesh) [21], Populations of Uttar Pradesh [18], Khatri (Punjab) [22], Baniya (Punjab) [22], Jatt Sikh (Punjab) [22], Population of Jharkhand [23], Oraon (Chhattishgarh) [24], Gond-1 (Madhya Pradesh) [25], Gond-2 (Madhya Pradesh) [26], Gond (Madhya Pradesh) [27], Central Indian Populations [28], Bhil (Gujrat) [29], Bhil (Madhya Pradesh) [30], Maheli (Bengal) [31], Kora (Bengal) [31], Lodha (Bengal) [31], Oraon (Chotanagpur) [32], Santhal (Chotanagpur) [32], Munda (Chotanagpur) [32], Yerukula (Andhra Pradesh) [33], Naikpod Gond (Andhra Pradesh) [33], Lambadi (Andhra Pradesh) [33], Chenchu (Andhra Pradesh) [33], Munda (Jharkhand) [25], Kurmans (Tamilnadu) [25], Iyengar (Tamilnadu) [25], Mahadev Koli (Maharashtra) [25], Konkanastha Brahmin (Maharashtra) [25], Sakaldwipi Brahmin (Jharkhand) [25], Balmiki (Punjab) [25], Population of Madhya Pradesh [34], Indian Population [35], Populations of Bangladesh [36], Han population of Southern China [37], Tibetan population (Nepal) [38], Royal Kingdom of Bhutan Population [39], Kashmiri Muslim population living in Pakistan…”

Section: Statistical Analysesmentioning

confidence: 99%

Evaluating the gene flow from East to West among various populations of Rajasthan, India

Kumawat¹,

Shrivastava²,

Shrivastava³

et al. 2020

Preprint

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Background: The genetic landscape of South Asia is distinctive, where there is a preponderance of social-cultural and genetic variability. Rajasthan is a state located in the north-western part of India and it has been cited as a major route of human migration since ancient times. The present study was conducted to find out the genetic affinity of Rajasthani population with the population living in its east and the west. In particular, we compared them with the population of Pakistan which shares the common geographical boundary with the Rajasthan while also having a look at their inter and intra population affinities with the population belonging to other Indian states. We investigated the genetic structure and population parameters of Rajasthani populations obtained for twenty polymorphic autosomal STR loci from 669 unrelated individuals belonging to its three population groups including Mina, Gujjar and the mixed population of Rajasthan.Results: The studied populations showed a wide range of genetic diversity and besides the genetic structure of the studied populations, it was found that the average heterozygosity value was highest among the populations of Rajasthan, possibly, because of gene flow from different directions.Conclusion: Various statistical analyses suggested that the Rajasthani populations had a higher affinity with the North Indian populations rather than with the Pakistani population.

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Autosomal STR allele frequencies in Kahars of Uttar Pradesh, India, drawn with PowerPlex® 21 multiplex system

Cited by 15 publications

References 2 publications

Editorial: Forensic investigative genetic genealogy and fine-scale structure of human populations

Editorial: Forensic investigative genetic genealogy and fine-scale structure of human populations

Genomic Insight Into 21 Hypervariable Molecular Markers in The Population of Lower Himalayan Geographical Province Himachal Pradesh, India

Evaluating the gene flow from East to West among various populations of Rajasthan, India

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