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Data on haplotype diversity in the hypervariable region I, II and III of mtDNA amongst the Brahmin population of Haryana.

ABSTRACT: Human mitochondrial DNA (mtDNA) is routinely analysed for pathogenic mutations, evolutionary studies, estimation of time of divergence within or between species, phylogenetic studies and identification of degraded remains. The data on various regions of human mtDNA has added enormously to the knowledge pool of population genetics as well as forensic genetics. The displacement-loop (D-loop) in the control region of mtDNA is rated as the most rapidly evolving part, due to the presence of variations in this region. The control region consists of three hypervariable regions. These hypervariable regions (HVI, HVII and HVIII) tend to mutate 5-10 times faster than nuclear DNA. The high mutation rate of these hypervariable regions is used in population genetic studies and human identity testing. In the present data, potentially informative hypervariable regions of mitochondrial DNA (mtDNA) i.e. HVI (np 16024-16365), HVII (np 73-340) and HVIII (np 438-576) were estimated to understand the genetic diversity amongst Brahmin population of Haryana. Blood samples had been collected from maternally unrelated individuals from the different districts of Haryana. An array of parameters comprising of polymorphic sites, transitions, transversions, deletions, gene diversity, nucleotide diversity, pairwise differences, Tajima's D test, Fu's Fs test, mismatch observed variance and expected heterozygosity were estimated. The observed polymorphisms with their respective haplogroups in comparison to rCRS were assigned.

SUBMITTER: Verma K

PROVIDER: S-EPMC5988218 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Human identification of unknown samples following disaster and mass casualty events is essential, especially to bring closure to family and friends of the deceased. Unfortunately, victim identification is often challenging for forensic investigators as analysis becomes complicated when biological samples are degraded or of poor quality as a result of exposure to harsh environmental factors. Mitochondrial DNA becomes the ideal option for analysis, particularly for determining the origin of the samples. In such events, the estimation of genetic parameters plays an important role in modelling and predicting genetic relatedness and is useful in assigning unknown individuals to an ethnic group. Various techniques exist for the estimation of genetic relatedness, but the use of Machine learning (ML) algorithms are novel and presently the least used in forensic genetic studies. In this study, we investigated the ability of ML algorithms to predict genetic relatedness using hypervariable region I sequences; that were retrieved from the GenBank database for three race groups, namely African, Asian and Caucasian. Four ML classification algorithms; Support vector machines (SVM), Linear discriminant analysis (LDA), Quadratic discriminant analysis (QDA) and Random Forest (RF) were hybridised with one-hot encoding, Principal component analysis (PCA) and Bags of Words (BoW), and were compared for inferring genetic relatedness. The findings from this study on WEKA showed that genetic inferences based on PCA-SVM achieved an overall accuracy of 80-90% and consistently outperformed PCA-LDA, PCA-RF and PCA-QDA, while in Python BoW-PCA-RF achieved 94.4% accuracy which outperformed BoW-PCA-SVM, BoW-PCA-LDA and BoW-PCA-QDA respectively. ML results from the use of WEKA and Python software tools displayed higher accuracies as compared to the Analysis of molecular variance results. Given the results, SVM and RF algorithms are likely to also be useful in other sequence classification applications, making it a promising tool in genetics and forensic science. The study provides evidence that ML can be utilized as a supplementary tool for forensic genetics casework analysis.

Dataset Information

Data on haplotype diversity in the hypervariable region I, II and III of mtDNA amongst the Brahmin population of Haryana.

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