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      Kazak mitochondrial genomes provide insights into the human population history of Central Eurasia

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          Abstract

          As a historical nomadic group in Central Asia, Kazaks have mainly inhabited the steppe zone from the Altay Mountains in the East to the Caspian Sea in the West. Fine scale characterization of the genetic profile and population structure of Kazaks would be invaluable for understanding their population history and modeling prehistoric human expansions across the Eurasian steppes. With this mind, we characterized the maternal lineages of 200 Kazaks from Jetisuu at mitochondrial genome level. Our results reveal that Jetisuu Kazaks have unique mtDNA haplotypes including those belonging to the basal branches of both West Eurasian (R0, H, HV) and East Eurasian (A, B, C, D) lineages. The great diversity observed in their maternal lineages may reflect pivotal geographic location of Kazaks in Eurasia and implies a complex history for this population. Comparative analyses of mitochondrial genomes of human populations in Central Eurasia reveal a common maternal genetic ancestry for Turko-Mongolian speakers and their expansion being responsible for the presence of East Eurasian maternal lineages in Central Eurasia. Our analyses further indicate maternal genetic affinity between the Sherpas from the Tibetan Plateau with the Turko-Mongolian speakers.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

              We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Project administrationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Methodology
                Role: Funding acquisitionRole: InvestigationRole: Project administration
                Role: Investigation
                Role: Funding acquisitionRole: Resources
                Role: Funding acquisitionRole: Resources
                Role: Funding acquisitionRole: Writing – review & editing
                Role: InvestigationRole: Project administration
                Role: Data curationRole: Methodology
                Role: Data curationRole: Formal analysis
                Role: Writing – review & editing
                Role: Funding acquisition
                Role: Data curationRole: Formal analysis
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: Project administrationRole: ResourcesRole: Software
                Role: SupervisionRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                29 November 2022
                2022
                : 17
                : 11
                : e0277771
                Affiliations
                [1 ] School of Sciences and Humanities, Nazarbayev University, Astana, Kazakhstan
                [2 ] National Center for Biotechnology, Astana, Kazakhstan
                [3 ] National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan
                [4 ] Department of Integrative Biology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
                [5 ] The Genographic Project, National Geographic Society, Washington, DC, United States of America
                [6 ] Department of Anthropology, University of Maryland, College Park, Maryland, United States of America
                [7 ] Immunogenomics and Metabolic Diseases Laboratory, National Institute of Genomic Medicine, Mexico City, Mexico
                [8 ] L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
                [9 ] Department of Anthropology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
                [10 ] School of Medicine, Nazarbayev University, Astana, Kazakhstan
                [11 ] Department of Anthropology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
                [12 ] Population Genetics Laboratory, National Institute of Genetics, Mishima, Shizuoka, Japan
                [13 ] Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo, Japan
                [14 ] Advanced Medical Research Center, Faculty of Medicine, University of the Ryukyus, Okinawa Ken, Japan
                Universitat Pompeu Fabra, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-5509-5903
                https://orcid.org/0000-0001-5064-6203
                Article
                PONE-D-22-02111
                10.1371/journal.pone.0277771
                9707748
                0df34201-603b-4ef0-a2ac-1757d5d321cf
                © 2022 Askapuli et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 January 2022
                : 3 November 2022
                Page count
                Figures: 11, Tables: 4, Pages: 32
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100012632, Nazarbayev University;
                Award ID: 090118FD5332
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100012632, Nazarbayev University;
                Award ID: 091019CRP2119
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004561, Ministry of Education and Science of the Republic of Kazakhstan;
                Funded by: funder-id http://dx.doi.org/10.13039/501100004561, Ministry of Education and Science of the Republic of Kazakhstan;
                Award ID: AP08855823
                Fieldwork and DNA preparation parts of the project were supported by a Targeted Funding Program for 2014-2017 from the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant No. not available). Center for Life Sciences, National Laboratory Astana, Nazarbayev University received the grant. https://www.gov.kz/memleket/entities/edu?lang=en Part of the data analysis was funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant No. AP08855823), that was received by the National Center for Biotechnology, Kazakhstan. https://www.gov.kz/memleket/entities/edu?lang=en Part of the data analysis was supported by grants from Nazarbayev University, Kazakhstan (Grant Award Numbers: 090118FD5332 and 091019CRP2119). US received the grants. https://nu.edu.kz The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Haplogroups
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                Population Genetics
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                DNA
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                Custom metadata
                Mitochondrial genome sequences of 120 Kazak individuals were submitted to Genbank, with accession numbers: OM194220 - OM194339 The mitochondrial microarray SNP data used for generating pseudo-mitochondrial genomes (N = 80) are available at GEO (Accession Number: GSE208402).

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