1
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Bolognini D, Halgren A, Lou RN, Raveane A, Rocha JL, Guarracino A, Soranzo N, Chin CS, Garrison E, Sudmant PH. Recurrent evolution and selection shape structural diversity at the amylase locus. Nature 2024:10.1038/s41586-024-07911-1. [PMID: 39232174 DOI: 10.1038/s41586-024-07911-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 08/06/2024] [Indexed: 09/06/2024]
Abstract
The adoption of agriculture triggered a rapid shift towards starch-rich diets in human populations1. Amylase genes facilitate starch digestion, and increased amylase copy number has been observed in some modern human populations with high-starch intake2, although evidence of recent selection is lacking3,4. Here, using 94 long-read haplotype-resolved assemblies and short-read data from approximately 5,600 contemporary and ancient humans, we resolve the diversity and evolutionary history of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in agricultural populations than in fishing, hunting and pastoral populations. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each underwent multiple duplication/deletion events with mutation rates up to more than 10,000-fold the single-nucleotide polymorphism mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome-based approach, we infer structural haplotypes across thousands of humans identifying extensively duplicated haplotypes at higher frequency in modern agricultural populations. Leveraging 533 ancient human genomes, we find that duplication-containing haplotypes (with more gene copies than the ancestral haplotype) have rapidly increased in frequency over the past 12,000 years in West Eurasians, suggestive of positive selection. Together, our study highlights the potential effects of the agricultural revolution on human genomes and the importance of structural variation in human adaptation.
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Affiliation(s)
| | - Alma Halgren
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | - Runyang Nicolas Lou
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | | | - Joana L Rocha
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | - Andrea Guarracino
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Nicole Soranzo
- Human Technopole, Milan, Italy
- Wellcome Sanger Institute, Hinxton, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- Department of Haematology, Cambridge Biomedical Campus, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
| | - Chen-Shan Chin
- Foundation for Biological Data Science, Belmont, CA, USA
| | - Erik Garrison
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.
| | - Peter H Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA.
- Center for Computational Biology, University of California Berkeley, Berkeley, CA, USA.
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2
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Nguyen AK, Schall PZ, Kidd JM. A map of canine sequence variation relative to a Greenland wolf outgroup. Mamm Genome 2024:10.1007/s00335-024-10056-1. [PMID: 39088040 DOI: 10.1007/s00335-024-10056-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 07/25/2024] [Indexed: 08/02/2024]
Abstract
For over 15 years, canine genetics research relied on a reference assembly from a Boxer breed dog named Tasha (i.e., canFam3.1). Recent advances in long-read sequencing and genome assembly have led to the development of numerous high-quality assemblies from diverse canines. These assemblies represent notable improvements in completeness, contiguity, and the representation of gene promoters and gene models. Although genome graph and pan-genome approaches have promise, most genetic analyses in canines rely upon the mapping of Illumina sequencing reads to a single reference. The Dog10K consortium, and others, have generated deep catalogs of genetic variation through an alignment of Illumina sequencing reads to a reference genome obtained from a German Shepherd Dog named Mischka (i.e., canFam4, UU_Cfam_GSD_1.0). However, alignment to a breed-derived genome may introduce bias in genotype calling across samples. Since the use of an outgroup reference genome may remove this effect, we have reprocessed 1929 samples analyzed by the Dog10K consortium using a Greenland wolf (mCanLor1.2) as the reference. We efficiently performed remapping and variant calling using a GPU-implementation of common analysis tools. The resulting call set removes the variability in genetic differences seen across samples and breed relationships revealed by principal component analysis are not affected by the choice of reference genome. Using this sequence data, we inferred the history of population sizes and found that village dog populations experienced a 9-13 fold reduction in historic effective population size relative to wolves.
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Affiliation(s)
- Anthony K Nguyen
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Peter Z Schall
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jeffrey M Kidd
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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3
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Dehasque M, Morales HE, Díez-Del-Molino D, Pečnerová P, Chacón-Duque JC, Kanellidou F, Muller H, Plotnikov V, Protopopov A, Tikhonov A, Nikolskiy P, Danilov GK, Giannì M, van der Sluis L, Higham T, Heintzman PD, Oskolkov N, Gilbert MTP, Götherström A, van der Valk T, Vartanyan S, Dalén L. Temporal dynamics of woolly mammoth genome erosion prior to extinction. Cell 2024; 187:3531-3540.e13. [PMID: 38942016 DOI: 10.1016/j.cell.2024.05.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 02/08/2024] [Accepted: 05/17/2024] [Indexed: 06/30/2024]
Abstract
A number of species have recently recovered from near-extinction. Although these species have avoided the immediate extinction threat, their long-term viability remains precarious due to the potential genetic consequences of population declines, which are poorly understood on a timescale beyond a few generations. Woolly mammoths (Mammuthus primigenius) became isolated on Wrangel Island around 10,000 years ago and persisted for over 200 generations before becoming extinct around 4,000 years ago. To study the evolutionary processes leading up to the mammoths' extinction, we analyzed 21 Siberian woolly mammoth genomes. Our results show that the population recovered quickly from a severe bottleneck and remained demographically stable during the ensuing six millennia. We find that mildly deleterious mutations gradually accumulated, whereas highly deleterious mutations were purged, suggesting ongoing inbreeding depression that lasted for hundreds of generations. The time-lag between demographic and genetic recovery has wide-ranging implications for conservation management of recently bottlenecked populations.
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Affiliation(s)
- Marianne Dehasque
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691 Stockholm, Sweden; Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Box 50007, 10405 Stockholm, Sweden; Department of Zoology, Stockholm University, 10691 Stockholm, Sweden.
| | - Hernán E Morales
- Center for Evolutionary Hologenomics, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - David Díez-Del-Molino
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691 Stockholm, Sweden; Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Box 50007, 10405 Stockholm, Sweden; Department of Zoology, Stockholm University, 10691 Stockholm, Sweden
| | - Patrícia Pečnerová
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Box 50007, 10405 Stockholm, Sweden; Department of Zoology, Stockholm University, 10691 Stockholm, Sweden; Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark
| | - J Camilo Chacón-Duque
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691 Stockholm, Sweden; Department of Zoology, Stockholm University, 10691 Stockholm, Sweden; Department of Archaeology and Classical Studies, Stockholm University, Lilla Frescativägen 7, 11418 Stockholm, Sweden
| | - Foteini Kanellidou
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691 Stockholm, Sweden; Department of Zoology, Stockholm University, 10691 Stockholm, Sweden
| | - Héloïse Muller
- Master de Biologie, Ecole Normale Superieure de Lyon, Universite Claude Bernard Lyon I, Universite de Lyon, 69007 Lyon, France
| | - Valerii Plotnikov
- Academy of Sciences of Sakha Republic, Lenin Avenue 33, Yakutsk, Republic of Sakha (Yakutia), Russia
| | - Albert Protopopov
- Academy of Sciences of Sakha Republic, Lenin Avenue 33, Yakutsk, Republic of Sakha (Yakutia), Russia
| | - Alexei Tikhonov
- Zoological Institute of Russian Academy of Sciences, Saint-Petersburg, Russia
| | - Pavel Nikolskiy
- Geological Institute of the Russian Academy of Sciences, Moscow, Russia
| | - Gleb K Danilov
- Peter the Great Museum of Anthropology and Ethnography, Kunstkamera, Russian Academy of Sciences, 3 University Embankment, Box 199034, Saint-Petersburg, Russia
| | - Maddalena Giannì
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Vienna, Austria; Human Evolution and Archaeological Sciences (HEAS), University of Vienna, Vienna, Austria
| | - Laura van der Sluis
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Vienna, Austria; Human Evolution and Archaeological Sciences (HEAS), University of Vienna, Vienna, Austria
| | - Tom Higham
- Department of Evolutionary Anthropology, Faculty of Life Sciences, University of Vienna, Vienna, Austria; Human Evolution and Archaeological Sciences (HEAS), University of Vienna, Vienna, Austria
| | - Peter D Heintzman
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691 Stockholm, Sweden; Department of Geological Sciences, Stockholm University, 10691 Stockholm, Sweden
| | - Nikolay Oskolkov
- Department of Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Lund University, Lund, Sweden
| | - M Thomas P Gilbert
- Center for Evolutionary Hologenomics, The Globe Institute, University of Copenhagen, Copenhagen, Denmark; University Museum, NTNU, Trondheim, Norway
| | - Anders Götherström
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691 Stockholm, Sweden; Department of Archaeology and Classical Studies, Stockholm University, Lilla Frescativägen 7, 11418 Stockholm, Sweden
| | - Tom van der Valk
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691 Stockholm, Sweden; Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Box 50007, 10405 Stockholm, Sweden; SciLifeLab, Stockholm, Sweden
| | - Sergey Vartanyan
- North-East Interdisciplinary Scientific Research Institute N.A.N.A. Shilo, Far East Branch, Russian Academy of Sciences, Magadan, Russia
| | - Love Dalén
- Centre for Palaeogenetics, Svante Arrhenius väg 20C, 10691 Stockholm, Sweden; Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Box 50007, 10405 Stockholm, Sweden; Department of Zoology, Stockholm University, 10691 Stockholm, Sweden.
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4
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Bolognini D, Halgren A, Lou RN, Raveane A, Rocha JL, Guarracino A, Soranzo N, Chin J, Garrison E, Sudmant PH. Global diversity, recurrent evolution, and recent selection on amylase structural haplotypes in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.07.579378. [PMID: 38370750 PMCID: PMC10871346 DOI: 10.1101/2024.02.07.579378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
The adoption of agriculture, first documented ~12,000 years ago in the Fertile Crescent, triggered a rapid shift toward starch-rich diets in human populations. Amylase genes facilitate starch digestion and increased salivary amylase copy number has been observed in some modern human populations with high starch intake, though evidence of recent selection is lacking. Here, using 52 long-read diploid assemblies and short read data from ~5,600 contemporary and ancient humans, we resolve the diversity, evolutionary history, and selective impact of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in populations with agricultural subsistence compared to fishing, hunting, and pastoral groups. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each exhibit multiple duplications/deletions with mutation rates >10,000-fold the SNP mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome graph-based approach to infer structural haplotypes across thousands of humans, we identify extensively duplicated haplotypes present at higher frequencies in modern day populations with traditionally agricultural diets. Leveraging 533 ancient human genomes we find that duplication-containing haplotypes (i.e. haplotypes with more amylase gene copies than the ancestral haplotype) have increased in frequency more than seven-fold over the last 12,000 years providing evidence for recent selection in West Eurasians. Together, our study highlights the potential impacts of the agricultural revolution on human genomes and the importance of long-read sequencing in identifying signatures of selection at structurally complex loci.
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Affiliation(s)
| | - Alma Halgren
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
| | - Runyang Nicolas Lou
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
| | | | - Joana L Rocha
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
| | - Andrea Guarracino
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, USA
| | | | - Jason Chin
- Foundation for Biological Data Science, Belmont, USA
| | - Erik Garrison
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, USA
| | - Peter H Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
- Center for Computational Biology, University of California Berkeley, Berkeley, USA
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5
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Hempel E, Faith JT, Preick M, de Jager D, Barish S, Hartmann S, Grau JH, Moodley Y, Gedman G, Pirovich KM, Bibi F, Kalthoff DC, Bocklandt S, Lamm B, Dalén L, Westbury MV, Hofreiter M. Colonial-driven extinction of the blue antelope despite genomic adaptation to low population size. Curr Biol 2024; 34:2020-2029.e6. [PMID: 38614080 DOI: 10.1016/j.cub.2024.03.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 02/09/2024] [Accepted: 03/25/2024] [Indexed: 04/15/2024]
Abstract
Low genomic diversity is generally indicative of small population size and is considered detrimental by decreasing long-term adaptability.1,2,3,4,5,6 Moreover, small population size may promote gene flow with congeners and outbreeding depression.7,8,9,10,11,12,13 Here, we examine the connection between habitat availability, effective population size (Ne), and extinction by generating a 40× nuclear genome from the extinct blue antelope (Hippotragus leucophaeus). Historically endemic to the relatively small Cape Floristic Region in southernmost Africa,14,15 populations were thought to have expanded and contracted across glacial-interglacial cycles, tracking suitable habitat.16,17,18 However, we found long-term low Ne, unaffected by glacial cycles, suggesting persistence with low genomic diversity for many millennia prior to extinction in ∼AD 1800. A lack of inbreeding, alongside high levels of genetic purging, suggests adaptation to this long-term low Ne and that human impacts during the colonial era (e.g., hunting and landscape transformation), rather than longer-term ecological processes, were central to its extinction. Phylogenomic analyses uncovered gene flow between roan (H. equinus) and blue antelope, as well as between roan and sable antelope (H. niger), approximately at the time of divergence of blue and sable antelope (∼1.9 Ma). Finally, we identified the LYST and ASIP genes as candidates for the eponymous bluish pelt color of the blue antelope. Our results revise numerous aspects of our understanding of the interplay between genomic diversity and evolutionary history and provide the resources for uncovering the genetic basis of this extinct species' unique traits.
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Affiliation(s)
- Elisabeth Hempel
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, Faculty of Science, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany; Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Invalidenstraße 43, 10115 Berlin, Germany.
| | - J Tyler Faith
- Natural History Museum of Utah, University of Utah, 301 Wakara Way, Salt Lake City, UT 84108, USA; Department of Anthropology, University of Utah, 260 South Central Campus Drive, Salt Lake City, UT 84112, USA; Origins Centre, University of the Witwatersrand, 2000 Johannesburg, Republic of South Africa
| | - Michaela Preick
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, Faculty of Science, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany
| | - Deon de Jager
- Globe Institute, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | | | - Stefanie Hartmann
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, Faculty of Science, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany
| | - José H Grau
- Center for Species Survival, Smithsonian Conservation Biology Institute, Washington, DC 20008, USA; Amedes Genetics, Amedes Medizinische Dienstleistungen GmbH, 10117 Berlin, Germany
| | - Yoshan Moodley
- Department of Biological Sciences, University of Venda, Private Bag X5050, Thohoyandou 0950, Republic of South Africa
| | | | | | - Faysal Bibi
- Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Invalidenstraße 43, 10115 Berlin, Germany
| | - Daniela C Kalthoff
- Swedish Museum of Natural History, Department of Zoology, Box 50007, 10405 Stockholm, Sweden
| | | | - Ben Lamm
- Colossal Biosciences, Dallas, TX 75247, USA
| | - Love Dalén
- Swedish Museum of Natural History, Department of Bioinformatics and Genetics, Box 50007, 10405 Stockholm, Sweden; Centre for Palaeogenetics, Svante Arrhenius väg 20c, 10691 Stockholm, Sweden; Department of Zoology, Stockholm University, 10691 Stockholm, Sweden.
| | - Michael V Westbury
- Globe Institute, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark.
| | - Michael Hofreiter
- Evolutionary Adaptive Genomics, Institute of Biochemistry and Biology, Faculty of Science, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany.
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6
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Lu J, Toro C, Adams DR, Moreno CAM, Lee WP, Leung YY, Harms MB, Vardarajan B, Heinzen EL. LUSTR: a new customizable tool for calling genome-wide germline and somatic short tandem repeat variants. BMC Genomics 2024; 25:115. [PMID: 38279154 PMCID: PMC10811831 DOI: 10.1186/s12864-023-09935-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 12/21/2023] [Indexed: 01/28/2024] Open
Abstract
BACKGROUND Short tandem repeats (STRs) are widely distributed across the human genome and are associated with numerous neurological disorders. However, the extent that STRs contribute to disease is likely under-estimated because of the challenges calling these variants in short read next generation sequencing data. Several computational tools have been developed for STR variant calling, but none fully address all of the complexities associated with this variant class. RESULTS Here we introduce LUSTR which is designed to address some of the challenges associated with STR variant calling by enabling more flexibility in defining STR loci, allowing for customizable modules to tailor analyses, and expanding the capability to call somatic and multiallelic STR variants. LUSTR is a user-friendly and easily customizable tool for targeted or unbiased genome-wide STR variant screening that can use either predefined or novel genome builds. Using both simulated and real data sets, we demonstrated that LUSTR accurately infers germline and somatic STR expansions in individuals with and without diseases. CONCLUSIONS LUSTR offers a powerful and user-friendly approach that allows for the identification of STR variants and can facilitate more comprehensive studies evaluating the role of pathogenic STR variants across human diseases.
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Affiliation(s)
- Jinfeng Lu
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- The Taub Institute for Research On Alzheimer's Disease and the Aging Brain, Gertrude H. Sergievsky Center, Department of Neurology, College of Physicians and Surgeons, Columbia University, The New York Presbyterian Hospital, New York, NY, 10032, USA.
| | - Camilo Toro
- NIH Undiagnosed Diseases Program, National Human Genome Research Institute (NHGRI), National Institutes of Health, Bethesda, MD, 20892, USA
| | - David R Adams
- NIH Undiagnosed Diseases Program, National Human Genome Research Institute (NHGRI), National Institutes of Health, Bethesda, MD, 20892, USA
| | | | - Wan-Ping Lee
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory MedicinePerelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yuk Yee Leung
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory MedicinePerelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mathew B Harms
- Department of Neurology, Division of Neuromuscular Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Badri Vardarajan
- The Taub Institute for Research On Alzheimer's Disease and the Aging Brain, Gertrude H. Sergievsky Center, Department of Neurology, College of Physicians and Surgeons, Columbia University, The New York Presbyterian Hospital, New York, NY, 10032, USA
| | - Erin L Heinzen
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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7
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Rambabu M, Konageni N, Vasudevan K, Dasegowda KR, Gokul A, Jayanthi S, Rohini K. Identification of key biomarkers and associated pathways of pancreatic cancer using integrated transcriptomic and gene network analysis. Saudi J Biol Sci 2023; 30:103819. [PMID: 37860809 PMCID: PMC10582056 DOI: 10.1016/j.sjbs.2023.103819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 09/11/2023] [Accepted: 09/21/2023] [Indexed: 10/21/2023] Open
Abstract
Pancreatic cancer shows malignancy around the world standing in 4th position for causing death globally. This cancer is majorly divided into exocrine and neuroendocrine where exocrine pancreatic ductal adenocarcinoma is observed to be nearly 85% of cases. The lack of diagnosis of pancreatic cancer is considered to be one of the major drawbacks to the prognosis and treatment of pancreatic cancer patients. The survival rate after diagnosis is very low, due to the higher incidence of drug resistance to cancer which leads to an increase in the mortality rate. The transcriptome analysis for pancreatic cancer involves dataset collection from the ENA database, incorporating them into quality control analysis to the quantification process to get the summarized read counts present in collected samples and used for further differential gene expression analysis using the DESeq2 package. Additionally, explore the enriched pathways using GSEA software and represented them by utilizing the enrichment map finally, the gene network has been constructed by Cytoscape software. Furthermore, explored the hub genes that are present in the particular pathways and how they are interconnected from one pathway to another has been analyzed. Finally, we identified the CDKN1A, IL6, and MYC genes and their associated pathways can be better biomarker for the clinical processes to increase the survival rate of of pancreatic cancer.
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Affiliation(s)
- Majji Rambabu
- Department of Biotechnology, REVA University, Bengaluru, Karnataka, India
| | - Nagaraj Konageni
- Department of Biotechnology, REVA University, Bengaluru, Karnataka, India
| | - Karthick Vasudevan
- Department of Biotechnology, REVA University, Bengaluru, Karnataka, India
| | - K R Dasegowda
- Department of Biotechnology, REVA University, Bengaluru, Karnataka, India
| | - Anand Gokul
- Department of Computer Science, University of Southern California, Los Angeles, CA, USA
| | - Sivaraman Jayanthi
- Department of Biotechnology, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - Karunakaran Rohini
- Department of Bioinformatics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India
- Unit of Biochemistry, Faculty of Medicine, AIMST University, Semeling, Bedong, Malaysia
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8
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Atağ G, Vural KB, Kaptan D, Özkan M, Koptekin D, Sağlıcan E, Doğramacı S, Köz M, Yılmaz A, Söylev A, Togan İ, Somel M, Özer F. MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes. OPEN RESEARCH EUROPE 2023; 2:100. [PMID: 37829208 PMCID: PMC10565424 DOI: 10.12688/openreseurope.14936.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 09/26/2023] [Indexed: 10/14/2023]
Abstract
A major challenge in zooarchaeology is to morphologically distinguish closely related species' remains, especially using small bone fragments. Shotgun sequencing aDNA from archeological remains and comparative alignment to the candidate species' reference genomes will only apply when reference nuclear genomes of comparable quality are available, and may still fail when coverages are low. Here, we propose an alternative method, MTaxi, that uses highly accessible mitochondrial DNA (mtDNA) to distinguish between pairs of closely related species from ancient DNA sequences. MTaxi utilises mtDNA transversion-type substitutions between pairs of candidate species, assigns reads to either species, and performs a binomial test to determine the sample taxon. We tested MTaxi on sheep/goat and horse/donkey data, between which zooarchaeological classification can be challenging in ways that epitomise our case. The method performed efficiently on simulated ancient genomes down to 0.3x mitochondrial coverage for both sheep/goat and horse/donkey, with no false positives. Trials on n=18 ancient sheep/goat samples and n=10 horse/donkey samples of known species identity also yielded 100% accuracy. Overall, MTaxi provides a straightforward approach to classify closely related species that are difficult to distinguish through zooarchaeological methods using low coverage aDNA data, especially when similar quality reference genomes are unavailable. MTaxi is freely available at https://github.com/goztag/MTaxi.
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Affiliation(s)
- Gözde Atağ
- Biological Sciences, Middle East Technical University, Ankara, Turkey
| | | | - Damla Kaptan
- Biological Sciences, Middle East Technical University, Ankara, Turkey
| | - Mustafa Özkan
- Biological Sciences, Middle East Technical University, Ankara, Turkey
| | - Dilek Koptekin
- Biological Sciences, Middle East Technical University, Ankara, Turkey
- Health Informatics, Middle East Technical University, Ankara, Turkey
| | - Ekin Sağlıcan
- Health Informatics, Middle East Technical University, Ankara, Turkey
| | - Sevcan Doğramacı
- Computer Engineering, Konya Food and Agriculture University, Konya, Turkey
| | - Mevlüt Köz
- Molecular Biology and Genetics, Konya Food and Agriculture University, Konya, Turkey
| | - Ardan Yılmaz
- Computer Engineering, Middle East Technical University, Ankara, Turkey
| | - Arda Söylev
- Computer Engineering, Konya Food and Agriculture University, Konya, Turkey
| | - İnci Togan
- Biological Sciences, Middle East Technical University, Ankara, Turkey
| | - Mehmet Somel
- Biological Sciences, Middle East Technical University, Ankara, Turkey
| | - Füsun Özer
- Anthropology, Hacettepe University, Ankara, Turkey
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9
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Lin Y, Zhou S, Liang X, Guo B, Han B, Han H, Zhang J, Lu Y, Zhang Z, Yang X, Li X, Liu W, Li L. Chromosomal mapping of a locus associated with adult-stage resistance to powdery mildew from Agropyron cristatum chromosome 6PL in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:2861-2873. [PMID: 35819492 DOI: 10.1007/s00122-022-04155-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 06/17/2022] [Indexed: 06/15/2023]
Abstract
The powdery mildew resistance locus was mapped to A. cristatum chromosome 6PL bin (0.27-0.51) and agronomic traits evaluation indicated that this locus has potential breeding application value. Agropyron cristatum (2n = 4x = 28, PPPP) is a wild relative of wheat with an abundance of biotic and abiotic stress resistance genes and is considered one of the best exogenous donor relatives for wheat breeding. A number of wheat-A. cristatum derived lines have been generated, including addition lines, translocation lines and deletion lines. In this study, the 6P disomic addition line 4844-12 (2n = 2x = 44) was confirmed to have genetic effects on powdery mildew resistance. Four 6P deletion lines (del16a, del19b, del21 and del27) and two translocation lines (WAT638a and WAT638b), derived from radiation treatment of 4844-12, were used to further assess the 6P powdery mildew resistance locus by powdery mildew resistance assessment, genomic in situ hybridization (GISH), fluorescence in situ hybridization (FISH) and 6P specific sequence-tagged-site (STS) markers. Collectively, the locus harboring the powdery mildew resistance gene was genetically mapped to a 6PL bin (0.27-0.51). The genetic effects of this chromosome segment on resistance to powdery mildew were further confirmed by del16a and del27 BC3F2 lines. Comprehensive evaluation of agronomic traits revealed that the powdery mildew resistance locus of 6PL (0.27-0.51) has potential application value in wheat breeding. A total of 22 resistant genes were annotated and 3 specific gene markers were developed for detecting chromatin of the resistant region based on genome re-sequencing. In summary, this study could broaden the powdery mildew resistance gene pool for wheat genetic improvements.
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Affiliation(s)
- Yida Lin
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Agronomy, Northwest A&F University, Yangling, 712100, China
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Shenghui Zhou
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xuezhong Liang
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Baojin Guo
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Bing Han
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Haiming Han
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jingpeng Zhang
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yuqing Lu
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Zhi Zhang
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xinming Yang
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xiuquan Li
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Weihua Liu
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Lihui Li
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Agronomy, Northwest A&F University, Yangling, 712100, China.
- National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
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