The maternal history of tribal populations of Chhattisgarh India

The maternal history of tribal populations of Chhattisgarh India Shivani Dixit Jaipur National University Pankaj Shrivastava (  [email protected] ) Regional Forensic Science Laboratory Manisha Rana State Forensic Science Laboratory Pushpesh Kushwaha State Forensic Science Laboratory Divya Shrivastava Jaipur National University R. K. Kumawat State Forensic Science Laboratory Prajjval Pratap Singh Banaras Hindu University Sachin K. Tiwary Banaras Hindu University Neeraj K. Chauhan Thermo sher Scienti c India Pvt. Limited Gyaneshwer Chaubey Banaras Hindu University Article Keywords: Central India, mitogenome, tribe, phylogenetics, haplogroup Posted Date: May 19th, 2023 DOI: https://doi.org/10.21203/rs.3.rs-2757780/v1 License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/10 Abstract The central region of India is incredibly rich in tribal heritage. It is the most frequent Indian state in terms of tribal population. Understanding the genetic history of the tribal population of India may add detailed information about various demographic processes, including social upliftment. However, to understand these microevolutionary processes, high-resolution genetic analysis is warranted. Therefore, we have used cuttingedge Next-generation sequencing (NGS) techniques and sequenced the mitogenomes of 25 random samples from two major (Gond and Kanwar) tribal populations for complete mitogenome analysis. We aimed to understand the initial peopling of Chhattisgarh from a maternal perspective. The complete genome sequencing enabled us to identify several novel sub-haplogroups. Our results suggested an early expansion and proliferation of maternal ancestry rooted in the time of initial settlement of the subcontinent, which has reached near saturation during 25-30Kya. At the background of founding lineages M and N, we identi ed maternal haplogroups M2, R5 and U2 as three basal founding haplogroups of this region. Overall, we suggest a high effective (Ne) maternal population in Central India during 25Kya, sustained during the Last Glacial Maximus(LGM). Introduction The Central region of India geographically consists of Madhya Pradesh, Maharashtra and Chhattisgarh. All these states have more than 40 designated tribal populations(1, 2). The major tribals of this region are Kol, Bhil, Gond, Kolam, Oraon, Korku, Saharia and Varlis. In 2000, Madhya Pradesh was partitioned, andtheregion with 10 Chhattisgarhi and six Gondi-speaking districts is now known as Chhattisgarh. Currently, this state has ve divisions and thirty-one districts. Chhattisgarh has a thirty million overall population of nearly 34% of the Scheduled Tribes (3). This state shares borders with the seven states of India (Fig. 1). Physiographically, this region is divided into Chhattisgarh Plain, Rimland and Bastar Plateau. The plain part has the Mahanadi River, whereas the Rim lands consist of hills and plateaus. The river Godavari and its tributaries drain the Bastar plateau. Historically, the studied region was once an essential part of the Mahabharata and the Ramayana. It was known as the Dandakaranya and is a signi cant portion of the ancient empire of southern Kosala(4). Geographically, the region is divided into three groups based on cultural zone. The northern cultural zone is politically known as the Surguja division; the Central cultural zone is politically known as the Bilaspur division, and the Southern cultural zone is politically known as the Baster division. This region is an overlapping zone of Indo-Aryan, Dravidian and Austroasiatic language groups(5). The tribes Oraon, Kanwar, Munda, Nagesia, Korwa, Bhuinhar, Bhumia, Dhanwar, Saunta, Biar, Majhwar, Majhi, Kharia, Savra, Birhor, Kondh, Khairwar, Gond, Baiga and Agaria are the tribal group of Chhattisgarh. Among these, the Gond and subcaste (4.2 million), Kanwar (0.9 million) and Oraon (0.8 million) are majority (1). As per the 2011 census, the total population of tribes in the state is 30.60%. The region under observation is densely inhabited by the tribes Gond, Halba, Dhurvaa, Abujhmadia, Bison Horn Maria and Muria. STR (Short Tandem Repeat) markers are the most commonly used markers for forensic investigation because of their high information potential for establishing identity(6). Regardless of their potential, interpretations of DNA typing results from degraded samples have long been a challenge in forensics. Besides this, samples Page 2/10 which lack nuclear DNA (viz., hairs without roots) have also been a challenge for STR-based DNA technology. Because of abundance in cells, power to decipher maternal lineage and comparatively lower sensitivity towards degradation, mitochondrial DNA has been preferred over STR markers for analyzing compromised samples. Forensic analysts use Sanger sequencing to decipher mitochondrial control regions without any alternative in the preformulated kit format. Precision ID mtDNA Whole Genome Panel(Applied Biosystems) is a next-generation based sequencing approach to mitochondrial DNA (mtDNA) analysis speci cally designed for itsuse in forensic DNA typing and anthropological studies in a kit format. The kit is recently validated for forensic applications(7). Over the past few years, genetic studies using mitochondrial DNA (mtDNA) and Y chromosomal and autosomal variations have provided a substantial understanding of South Asia's human origins and dispersal patterns. So far, there is no high resolution maternal genetic study has been performed on Chhattisgarh population. As this state is a shelter for many tribal groups, it may help to test several language-gene interaction models. The archaeological studies also suggest that this state has played a vital role in peopling of the subcontinent. Seeing its central role in shaping the major episodes of peopling of South Asia, it is required to have a high-resolution study on the populations of this critical state.There are less detailed genetic studies on the populations inhabited in this region. Therefore, we have selected two major tribal populations i.e. Gond and Kanwar from this state and studied the mitogenomes from these populations. This study is an attempt at an extensive characterization of the maternal ancestry of the tribal populations using complete mitochondrial sequences and to establish the use of NGS technology in forensic applications. Material and Methods Sample Collection We have collected 2 ml of blood samples from 25 unrelated individuals belonging to Gond and Kanwar populations from Chhattisgarh state, India (Fig. 1). The samples were collected per the ethical approval from the Institutional ethics committee of Dr. H.S. Gour Vishwavidyalaya, Sagar Madhya Pradesh, India, vide its approval no. DHSGV/IE/2021/2/02 dated 3.9.21. Written informed consent was obtained from all the participants. We also con rm that all methods were performed in accordance with the relevant guidelines and regulations of the Ethical Committee. DNA isolation and quanti cation DNA was isolated and puri ed with AutoMate Express™ Forensic DNA Extraction System using PrepFiler® Express Forensic DNA Extraction Kit (Thermo Fisher Scienti c (Thermo), Waltham, MA, USA) as per the protocol of the manufacturer. DNA concentration was estimated with the Qubit 3.0 instrument applying the Qubit dsDNA HS Assay kit (Life Technologies, Invitrogen division, Darmstadt, Germany). Library preparation Genomic DNA isolated from the sample is converted to a sequencing library by targeted ampli cation of regions of interest by Precision ID mtDNA Whole Genome Panel(Thermo). Precision ID mtDNA panel is an innovative approach to mtDNA sequencing, speci cally developed for forensic applications. This mtDNA tiling Page 3/10 approach, using amplicons that are only 163 bp in average length, assists with obtaining optimal mitochondrial genome (mtGenome) coverage from highly compromised, degraded samples. The Precision ID library preparation work ow was performed on an automated system (Ion Chef System from Thermo) as per the protocol provided by the manufacturer. The system facilitates automation of up to 8 samples per run for a 2-pool panel design to generate pooled libraries ready for downstream template preparation. Template preparation Libraries prepared by automation are clonally ampli ed on the Ion Chef System by emulsion PCR of library molecules captured on beads. The Ion Chef System automates all template preparation steps, including creating the emulsion mixture, performing the PCR, carrying out the post-PCR puri cations, and loading the puri ed templated beads onto the Ion S5 chips. Sequencing A sequencing run on the Ion S5 systems is initiated by loading a reagent cartridge, buffer, cleaning solution, and waste container as per the protocol of the manufacturer. The Ion S5 chip is then loaded, and the run starts. The addition of nucleotides by the DNA polymerase results in the production of hydrogen ions; the change in pH is converted to sequencing signals through ion-sensitive wells that hold the templated beads. Converge Software for mtDNA analysis work ow The raw data obtained after sequencing was analysed using specially designed Converge software (ThermoFisher Scienti c) to determine the sequence.The Converge NGS Data Analysis module automates mtDNA analysis, leveraging optimized base calling, alignment, and quality ltering algorithms. Analysis of obtained sequences Of the 25 sequences obtained, haplogroups were assigned to each individual using the Global human mtDNA phylogenetic tree(8). We manually reconstructed the mitogenome phylogenetic tree based on the tree generated by mtphyl(https://sites.google.com/site/mtphyl/home) and the nomenclature of PhyloTree (Build 17). Coalescence ages for each haplogroup were calculated by ρ statistics(9). Standard errors were calculated as in Saillard et al. using a synonymous clock of one substitution every 7884 years and a mitogenome clock of one substitution every 3624 years(10). To evaluate the effective population size (Ne ) for the studied population, we computed Bayesian Skyline Plots (BSPs) using BEAST 1.8.0(11). We used a relaxed molecular clock, a two-parameter nucleotide evolution model, and a rate of 2.514 x 10− 8 mutations per site. We have calculated the frequency of each haplogroup in the studied population and drawn a PCA (Principal Component Analysis) plot with the other populations from the adjoining regions and states. The spatial distributions of three major haplogroups have been generated by (https://www.datawrapper.de/). Results and Discussion Based on archaeological and genetic data from South Asia, East Asia and Southeast Asia,it has been unanimously accepted that modern humans were present in this region at least 50–74 Kya (12–14). After the Page 4/10 Out-of-Africa dispersal events, the most prominent global population expansionwas thought to have taken place in South and Southeast Asia, where most of the human population might have lived 25Kya (15). The maternal analysis of remote populations living in India is necessary to understand this demographic process. Since the Central part of India has played a vital role in human migration (16), we have randomly collected samples from the Indian state of Chhattisgarh and sequenced their mitochondrial DNA (mtDNA) with NGS technology. We rst classi ed our samples into haplogroups and constructed a PCA plot (Fig. 2). The maternal PCA of India showed a clinal pattern. The geographical distribution of the population is re ected in the genetic similarities. The present study population is placed near a cluster mainly comprised of Central Indian states (Madhya Pradesh, Chhattisgarh) (Fig. 2). The PCA suggested a close genetic a nity of our studied samples with the populations of Madhya Pradesh and Chhattisgarh. In the haplogroup frequency distributions, we observed three major haplogroups in studied Chhattisgarh tribal populations. Haplogroup (hg) M2 is the major haplogroup harbouring a frequency of 0.28, followed by the haplogroups R5 and U2 (both 0.12). We have reconstructed a frequency-based geographical map to understand the spatial distribution of these haplogroups among Indian populations (Fig. 3). The spatial distribution of these haplogroups suggests their prominent presence in Central India. These haplogroups have been reported as basal haplogroups of South Asian maternal ancestry (17, 18). In order to understand the phylogenetic placement of studied individuals, we reconstructed a phylogenetic tree using the 25 complete sequences (Supplementary Fig. 1). In the phylogenetic tree, we identi ed several novel sub-haplogroups. We de ned a new branch of haplogroup M46 as M46b. In the background of haplogroup M2, we de ned sub-haplogroups M2a1a4, M2a1d, M2a3b and M2b1c. For haplogroup M63, we de ned a branch M63b. Similarly, we newly de ned various sub-haplogroups as the background of haplogroups M5, M78, R5 and U2 (supplementary Fig. 1). Altogether, we designated twelve novel sub-haplogroups in the present study. The population demographic history in this region has not been evaluated yet. Therefore, we have performed the Bayesian Skyline Analysis (BSA) (Fig. 4). In the plot, we see a gradual expansion from 55Kya with a saturation of nearly 25Kya. Thereafter, the population followed a linear growth. This supports the India-wide introduction of microlithic technology, which has supported the population linearity growth (19). However, we have not seen any dip in the population growth during the LGM in Chhattisgarh tribals which have been observed in Kashmir (20). This is likely due to distinct geographic regions which might have been differently affected during the LGM (21, 22). Thus, the complete mitogenome sequence analyses enabled us to identify at least twelve novel subhaplogroups. We suggested an early expansion of maternal ancestry in Chhattisgarh. The effective population size of this region reached saturation around 25Kya. We identi ed three basal maternal haplogroups widespread in this region. Unlike the colder regions, we have not observed any growth dip during the LGM. Declarations Page 5/10 Data availability The datasets generated and/or analysed during the current study are available (GenBank accession numbers OP718226 to OP718249) in the [NCBI] repository (https://www.ncbi.nlm.nih.gov/genbank. Acknowledgement Authors are thankful to Thermo sher Scienti c India Pvt. Limited, Gurgaon, India for providing reagents and kits used in the study. References 1. Russell RV. The tribes and castes of the Central Provinces of India. Vol. 1. Macmillan and Co., limited; 1916. 2. Singh KS. The Scheduled Tribes. Singh KS, editor. Oxford: Oxford University Press; 1997. 1266 p. (People of India; vol. III). 3. Census of India Website : O ce of the Registrar General & Census Commissioner, India [Internet]. [cited 2021 Jan 5]. Available from: https://censusindia.gov.in/2011-common/censusdata2011.html 4. Shukla HL. Tribal History: A New Interpretation. Delhi: BR Publishing Corporation; 1988. 5. Grierson G. Linguistic Survey of India (Vol. XI, Gipsy Languages). 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Mol Biol Evol. 2008 Feb;25(2):468–74. 1 . Athreya S. Was Homo heidelbergensis in South Asia? A test using the Narmada fossil from central India. In: Petraglia MD, Allchin B, editors. The evolution and history of human populations in South Asia [Internet]. Springer Verlag; 2007. p. 464. Available from: http://books.google.com/books? id=Qm9GfjNlnRwC&printsec=frontcover&dq=evolution+history+human+populations+South+Asia&ie=ISO8859-1&cd=1&source=gbs_gdata 17. Kivisild T, Rootsi S, Metspalu M, Mastana S, Kaldma K, Parik J, et al. The genetic heritage of the earliest settlers persists both in Indian tribal and caste populations. Am J Hum Genet. 2003;72(2):313–32. 1 . Quintana-Murci L, Chaix R, Wells RS, Behar DM, Sayar H, Scozzari R, et al. Where west meets east: the complex mtDNA landscape of the southwest and Central Asian corridor. Am J Hum Genet. 2004 May;74(5):827–45. 19. Petraglia M, Clarkson C, Boivin N, Haslam M, Korisettar R, Chaubey G, et al. Population increase and environmental deterioration correspond with microlithic innovations in South Asia ca. 35,000 years ago. Proc Natl Acad Sci U S A. 2009 Jul 28;106(30):12261–6. 20. Sharma I, Sharma V, Khan A, Kumar P, Rai E, Bamezai RN, et al. Ancient human migrations to and through Jammu Kashmir-India were not of males exclusively. Sci Rep. 2018;8(1):1–9. 21. Quamar MF, Bera SK. Pollen records of vegetation dynamics, climate change and ISM variability since the LGM from Chhattisgarh State, central India. Rev Palaeobot Palynol. 2020;278:104237. 22. Kumar V, Shukla T, Mishra A, Kumar A, Mehta M. Chronology and climate sensitivity of the post‐LGM glaciation in the Dunagiri valley, Dhauliganga basin, Central Himalaya, India. Boreas. 2020;49(3):594– 614. Figures Page 7/10 Figure 1 The sampling location of Chhattisgarh state. Page 8/10 Figure 2 The principal component analysis (PCA) of Indian populations of various states showing the placement of studied tribal population. Figure 3 Page 9/10 The spatial distribution of major haplogroups (haplogroups M2, R5 and U2) observed in the studied geographic region. Figure 4 The Bayesian Skyline Plot (BSP)based on complete mitogenomes of Chhattisgarh showing the population demography of tribal populations in this region. Supplementary Files This is a list of supplementary les associated with this preprint. Click to download. SuppFig.1.jpg Page 10/10