Genomic portrait of Odisha, India drawn by using 21 autosomal STR markers

Sahoo, Subhasish; Samal, Rashmita; Behera, Suchismeeta; Swain, Aruna Kumar; Biswas, Sumit; Shrivastava, Pankaj; Kumawat, R. K.; Chaubey, Gyaneshwer; Dash, Hirak Ranjan

doi:10.1007/s00414-020-02281-5

Cited by 12 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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

Preprint

Self Cite

View full text Add to dashboard Cite

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.

show abstract

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

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Developing and validating STR markers was an essential step toward their use in genotyping. The validated STR markers were used to estimate their frequency in various populations worldwide [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Leukemia on the Detection of Short Tandem Repeat (STR) Markers

Alharbi¹,

Alamri²,

El-Shehawi³

2022

Cureus

View full text Add to dashboard Cite

Introduction: Short tandem repeats (STRs) have been used for various identity typing methods worldwide. They have high discrimination power in human identification in forensics, paternity testing, missed personal identification, genetic diseases, and gene regulatory functions. They have also been used to detect and monitor the stability of diseases, including various types of cancer. This study aimed to investigate the impact of leukemia on the detection and stability of STR markers.Methods: DNA was isolated from 30 participants (15 with chronic myeloid leukemia( CML) and 15 healthy controls) and used to amplify STR markers using specific primers.Results: We found that the blood of those with leukemia had more 9.3 and 9 alleles at the tyrosine hydroxylase 1 (TH01) marker than the blood of the healthy control samples. The results of this study will help researchers understand leukemia's effect on the detection and stability of STR markers in leukemic patients compared to healthy individuals. Conclusion:Our results demonstrate that STR markers could become useful in genetic studies of leukemia cases.

show abstract

“…Many terrorism and natural disasters have caused ISSN : 1411 3724 Eksakta : Berkala Ilmiah Bidang MIPA many fatalities, some of which can no longer be recognized or identified due to damage to some or all parts of the victim's body. To be able to identify victims, genetic information is needed (DNA (deoxyrebous nucleid acid) from the victim [9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…DNA is a biological fingerprint of an individual obtained from the genetic inheritance of parents [9][10][11][12][13][14][15][16][17][18][19][20] (21,22,24), DNA profile identification is carried out on DNA evidence contained in human body tissues such as hair, teeth, blood, urine, saliva, muscles and sperm (23). The DNA profile maps the genetic makeup of individuals consisting of 16 loci, namely CSF1PO, D13S317, D16S539, D18S51, D19S433, D21S11, D2S1338, D3S1358, D5S818, D7S720, D8S1179, FGA, TH01, T19X, D21S11, D2S1338, D3S1358, D5S818, D7S720, D8S1179, FGA, TH01, T19X, and D21S11, D2S1338, D3S1358, D5S818, D7S720, D8S1179, FGA, TH01, TPOX, and VWA.…”

Section: Introductionmentioning

confidence: 99%

The Similarity Measurement of Human DNA Profile Using Fuzzy Similarity

Dewi

Soedarsono

2020

Eksakta

View full text Add to dashboard Cite

This research investigated the similarity of human DNA profile using fuzzy similarity measure. The similarity measurement of DNA profile had been done by measuring the similarity between query’s DNA profile and its biological family such as father, mother, brother, sister, grandmother and grandfather. The similarity measurement had been done to the short tandem repeat (STR) alleles in sixteen loci. The result of the experiment showed that each simulation gave matching result. This research is useful for Indonesian National Police (POLRI) in identifying process of disaster victim, terrorism victim and other criminal conduct.

show abstract

Genomic portrait of Odisha, India drawn by using 21 autosomal STR markers

Cited by 12 publications

References 9 publications

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

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

The Impact of Leukemia on the Detection of Short Tandem Repeat (STR) Markers

The Similarity Measurement of Human DNA Profile Using Fuzzy Similarity

Contact Info

Product

Resources

About