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Silva P, Galaverni M, Ortega-Del Vecchyo D, Fan Z, Caniglia R, Fabbri E, Randi E, Wayne R, Godinho R. Genomic evidence for the Old divergence of Southern European wolf populations. Proc Biol Sci 2020; 287:20201206. [PMID: 32693716 PMCID: PMC7423677 DOI: 10.1098/rspb.2020.1206] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The grey wolf (Canis lupus) is one of the most widely distributed mammals in which a variety of distinct populations have been described. However, given their currently fragmented distribution and recent history of human-induced population decline, little is known about the events that led to their differentiation. Based on the analysis of whole canid genomes, we examined the divergence times between Southern European wolf populations and their ancient demographic history. We found that all present-day Eurasian wolves share a common ancestor ca 36 000 years ago, supporting the hypothesis that all extant wolves derive from a single population that subsequently expanded after the Last Glacial Maximum. We also estimated that the currently isolated European populations of the Iberian Peninsula, Italy and the Dinarics-Balkans diverged very closely in time, ca 10 500 years ago, and maintained negligible gene flow ever since. This indicates that the current genetic and morphological distinctiveness of Iberian and Italian wolves can be attributed to their isolation dating back to the end of the Pleistocene, predating the recent human-induced extinction of wolves in Central Europe by several millennia.
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Affiliation(s)
- Pedro Silva
- CIBIO/InBIO - Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, 4485-661 Vairão, Portugal
| | - Marco Galaverni
- Conservation Unit, WWF Italia, Via Po 25/c - 00198 Roma, Italy
| | - Diego Ortega-Del Vecchyo
- International Laboratory for Human Genome Research, National Autonomous University of Mexico, Santiago de Querétaro, Querétaro 76230, Mexico
| | - Zhenxin Fan
- Key Laboratory of Bioresources and Ecoenvironment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, People's Republic of China
| | - Romolo Caniglia
- Unit for Conservation Genetics (BIO-CGE), Department for the Monitoring and Protection of the Environment and for Biodiversity Conservation, Italian Institute for Environmental Protection and Research (ISPRA), Via Cà Fornacetta 9, 40064 Ozzano dell'Emilia (Bo), Italy
| | - Elena Fabbri
- Unit for Conservation Genetics (BIO-CGE), Department for the Monitoring and Protection of the Environment and for Biodiversity Conservation, Italian Institute for Environmental Protection and Research (ISPRA), Via Cà Fornacetta 9, 40064 Ozzano dell'Emilia (Bo), Italy
| | - Ettore Randi
- Department of Biological, Geological and Environmental Sciences, University of Bologna, Via Selmi 3, Bologna 40126, Italy.,Department of Chemistry and Bioscience, Faculty of Engineering and Science, University of Aalborg, Aalborg, Denmark
| | - Robert Wayne
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA
| | - Raquel Godinho
- CIBIO/InBIO - Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, 4485-661 Vairão, Portugal.,Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, 4169-007 Porto, Portugal.,Department of Zoology, Faculty of Sciences, University of Johannesburg, Auckland Park 2006, South Africa
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2
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Abstract
Genomic sequence data for non-model organisms are increasingly available requiring the development of efficient and reproducible workflows. Here, we develop the first genomic resources and reproducible workflows for two threatened members of the reef-building coral genus Acropora We generated genomic sequence data from multiple samples of the Caribbean A. cervicornis (staghorn coral) and A. palmata (elkhorn coral), and predicted millions of nucleotide variants among these two species and the Pacific A. digitifera A subset of predicted nucleotide variants were verified using restriction length polymorphism assays and proved useful in distinguishing the two Caribbean acroporids and the hybrid they form ("A. prolifera"). Nucleotide variants are freely available from the Galaxy server (usegalaxy.org), and can be analyzed there with computational tools and stored workflows that require only an internet browser. We describe these data and some of the analysis tools, concentrating on fixed differences between A. cervicornis and A. palmata In particular, we found that fixed amino acid differences between these two species were enriched in proteins associated with development, cellular stress response, and the host's interactions with associated microbes, for instance in the ABC transporters and superoxide dismutase. Identified candidate genes may underlie functional differences in how these threatened species respond to changing environments. Users can expand the presented analyses easily by adding genomic data from additional species, as they become available.
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3
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Lopez JV, Kamel B, Medina M, Collins T, Baums IB. Multiple Facets of Marine Invertebrate Conservation Genomics. Annu Rev Anim Biosci 2018; 7:473-497. [PMID: 30485758 DOI: 10.1146/annurev-animal-020518-115034] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Conservation genomics aims to preserve the viability of populations and the biodiversity of living organisms. Invertebrate organisms represent 95% of animal biodiversity; however, few genomic resources currently exist for the group. The subset of marine invertebrates includes the most ancient metazoan lineages and possesses codes for unique gene products and possible keys to adaptation. The benefits of supporting invertebrate conservation genomics research (e.g., likely discovery of novel genes, protein regulatory mechanisms, genomic innovations, and transposable elements) outweigh the various hurdles (rare, small, or polymorphic starting materials). Here we review best conservation genomics practices in the laboratory and in silico when applied to marine invertebrates and also showcase unique features in several case studies of acroporid corals, crown-of-thorns starfish, apple snails, and abalone. Marine conservation genomics should also address how diversity can lead to unique marine innovations, the impact of deleterious variation, and how genomic monitoring and profiling could positively affect broader conservation goals (e.g., value of baseline data for in situ/ex situ genomic stocks).
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Affiliation(s)
- Jose V Lopez
- Department of Biological Sciences, Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Dania Beach, Florida 33004, USA;
| | - Bishoy Kamel
- Department of Biology, Center for Evolutionary and Theoretical Immunology, University of New Mexico, Albuquerque, New Mexico 87131, USA;
| | - Mónica Medina
- Department of Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA; ,
| | - Timothy Collins
- Department of Biological Sciences, Florida International University, Miami, Florida 33199, USA;
| | - Iliana B Baums
- Department of Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA; ,
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4
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Devlin-Durante MK, Baums IB. Genome-wide survey of single-nucleotide polymorphisms reveals fine-scale population structure and signs of selection in the threatened Caribbean elkhorn coral, Acropora palmata. PeerJ 2017; 5:e4077. [PMID: 29181279 PMCID: PMC5701561 DOI: 10.7717/peerj.4077] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 10/31/2017] [Indexed: 12/18/2022] Open
Abstract
The advent of next-generation sequencing tools has made it possible to conduct fine-scale surveys of population differentiation and genome-wide scans for signatures of selection in non-model organisms. Such surveys are of particular importance in sharply declining coral species, since knowledge of population boundaries and signs of local adaptation can inform restoration and conservation efforts. Here, we use genome-wide surveys of single-nucleotide polymorphisms in the threatened Caribbean elkhorn coral, Acropora palmata, to reveal fine-scale population structure and infer the major barrier to gene flow that separates the eastern and western Caribbean populations between the Bahamas and Puerto Rico. The exact location of this break had been subject to discussion because two previous studies based on microsatellite data had come to differing conclusions. We investigate this contradiction by analyzing an extended set of 11 microsatellite markers including the five previously employed and discovered that one of the original microsatellite loci is apparently under selection. Exclusion of this locus reconciles the results from the SNP and the microsatellite datasets. Scans for outlier loci in the SNP data detected 13 candidate loci under positive selection, however there was no correlation between available environmental parameters and genetic distance. Together, these results suggest that reef restoration efforts should use local sources and utilize existing functional variation among geographic regions in ex situ crossing experiments to improve stress resistance of this species.
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Affiliation(s)
- Meghann K Devlin-Durante
- Department of Biology, Pennsylvania State University, University Park, PA, United States of America
| | - Iliana B Baums
- Department of Biology, Pennsylvania State University, University Park, PA, United States of America
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5
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Edmunds SC, Li P, Hunter CI, Xiao SZ, Davidson RL, Nogoy N, Goodman L. Experiences in integrated data and research object publishing using GigaDB. INTERNATIONAL JOURNAL ON DIGITAL LIBRARIES 2016. [DOI: 10.1007/s00799-016-0174-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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6
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Agaba M, Ishengoma E, Miller WC, McGrath BC, Hudson CN, Bedoya Reina OC, Ratan A, Burhans R, Chikhi R, Medvedev P, Praul CA, Wu-Cavener L, Wood B, Robertson H, Penfold L, Cavener DR. Giraffe genome sequence reveals clues to its unique morphology and physiology. Nat Commun 2016; 7:11519. [PMID: 27187213 PMCID: PMC4873664 DOI: 10.1038/ncomms11519] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Accepted: 04/01/2016] [Indexed: 11/12/2022] Open
Abstract
The origins of giraffe's imposing stature and associated cardiovascular adaptations are unknown. Okapi, which lacks these unique features, is giraffe's closest relative and provides a useful comparison, to identify genetic variation underlying giraffe's long neck and cardiovascular system. The genomes of giraffe and okapi were sequenced, and through comparative analyses genes and pathways were identified that exhibit unique genetic changes and likely contribute to giraffe's unique features. Some of these genes are in the HOX, NOTCH and FGF signalling pathways, which regulate both skeletal and cardiovascular development, suggesting that giraffe's stature and cardiovascular adaptations evolved in parallel through changes in a small number of genes. Mitochondrial metabolism and volatile fatty acids transport genes are also evolutionarily diverged in giraffe and may be related to its unusual diet that includes toxic plants. Unexpectedly, substantial evolutionary changes have occurred in giraffe and okapi in double-strand break repair and centrosome functions. Giraffe's unique anatomy and physiology include its stature and associated cardiovascular adaptation. Here, Douglas Cavener and colleagues provide de novo genome assemblies of giraffe and its closest relative okapi and provide comparative analyses to infer insights into evolution and adaptation.
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Affiliation(s)
- Morris Agaba
- School of Life Sciences and Bioengineering, African Institute of Science and Technology, Arusha 4222, Tanzania.,Biosciences Eastern and Central Africa, International Livestock Research Institute, Nairobi GPO00100, Kenya.,Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Edson Ishengoma
- School of Life Sciences and Bioengineering, African Institute of Science and Technology, Arusha 4222, Tanzania
| | - Webb C Miller
- Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Barbara C McGrath
- Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Chelsea N Hudson
- Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Oscar C Bedoya Reina
- Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA.,MRC Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3PT, UK
| | - Aakrosh Ratan
- Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA.,Center for Public Health Genomics, Department of Computer Science, University of Virginia, Charlottesville, Virginia 22908, USA
| | - Rico Burhans
- Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Rayan Chikhi
- Center for Genomics and Bioinformatics, Department of Computer Science and Engineering, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA.,Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Paul Medvedev
- Center for Genomics and Bioinformatics, Department of Computer Science and Engineering, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA.,Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Craig A Praul
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Lan Wu-Cavener
- Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Brendan Wood
- Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | | | | | - Douglas R Cavener
- School of Life Sciences and Bioengineering, African Institute of Science and Technology, Arusha 4222, Tanzania.,Center for Genomics and Bioinformatics, Department of Biology, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
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7
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Fuller ZL, Niño EL, Patch HM, Bedoya-Reina OC, Baumgarten T, Muli E, Mumoki F, Ratan A, McGraw J, Frazier M, Masiga D, Schuster S, Grozinger CM, Miller W. Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools. BMC Genomics 2015; 16:518. [PMID: 26159619 PMCID: PMC4496815 DOI: 10.1186/s12864-015-1712-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2014] [Accepted: 06/22/2015] [Indexed: 11/10/2022] Open
Abstract
Background With the development of inexpensive, high-throughput sequencing technologies, it has become feasible to examine questions related to population genetics and molecular evolution of non-model species in their ecological contexts on a genome-wide scale. Here, we employed a newly developed suite of integrated, web-based programs to examine population dynamics and signatures of selection across the genome using several well-established tests, including FST, pN/pS, and McDonald-Kreitman. We applied these techniques to study populations of honey bees (Apis mellifera) in East Africa. In Kenya, there are several described A. mellifera subspecies, which are thought to be localized to distinct ecological regions. Results We performed whole genome sequencing of 11 worker honey bees from apiaries distributed throughout Kenya and identified 3.6 million putative single-nucleotide polymorphisms. The dense coverage allowed us to apply several computational procedures to study population structure and the evolutionary relationships among the populations, and to detect signs of adaptive evolution across the genome. While there is considerable gene flow among the sampled populations, there are clear distinctions between populations from the northern desert region and those from the temperate, savannah region. We identified several genes showing population genetic patterns consistent with positive selection within African bee populations, and between these populations and European A. mellifera or Asian Apis florea. Conclusions These results lay the groundwork for future studies of adaptive ecological evolution in honey bees, and demonstrate the use of new, freely available web-based tools and workflows (http://usegalaxy.org/r/kenyanbee) that can be applied to any model system with genomic information. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-1712-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Zachary L Fuller
- Department of Biology, Pennsylvania State University, University Park, PA, USA.
| | - Elina L Niño
- Department of Entomology, Center for Pollinator Research, Pennsylvania State University, University Park, PA, USA.
| | - Harland M Patch
- Department of Entomology, Center for Pollinator Research, Pennsylvania State University, University Park, PA, USA.
| | - Oscar C Bedoya-Reina
- Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, University Park, PA, USA.
| | - Tracey Baumgarten
- Department of Entomology, Center for Pollinator Research, Pennsylvania State University, University Park, PA, USA.
| | - Elliud Muli
- Department of Biological Sciences, South Eastern Kenya University (SEKU), P.O. Box 170-90200, Kitui, Kenya.
| | - Fiona Mumoki
- The International Center of Insect Physiology and Ecology (icipe), PO Box 30772-00100, Nairobi, Kenya.
| | - Aakrosh Ratan
- Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, University Park, PA, USA.
| | - John McGraw
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA.
| | - Maryann Frazier
- Department of Entomology, Center for Pollinator Research, Pennsylvania State University, University Park, PA, USA.
| | - Daniel Masiga
- The International Center of Insect Physiology and Ecology (icipe), PO Box 30772-00100, Nairobi, Kenya.
| | - Stephen Schuster
- Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, University Park, PA, USA.
| | - Christina M Grozinger
- Department of Entomology, Center for Pollinator Research, Pennsylvania State University, University Park, PA, USA.
| | - Webb Miller
- Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, University Park, PA, USA
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8
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Elephantid Genomes Reveal the Molecular Bases of Woolly Mammoth Adaptations to the Arctic. Cell Rep 2015; 12:217-28. [PMID: 26146078 DOI: 10.1016/j.celrep.2015.06.027] [Citation(s) in RCA: 106] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2015] [Revised: 05/18/2015] [Accepted: 06/05/2015] [Indexed: 12/30/2022] Open
Abstract
Woolly mammoths and living elephants are characterized by major phenotypic differences that have allowed them to live in very different environments. To identify the genetic changes that underlie the suite of woolly mammoth adaptations to extreme cold, we sequenced the nuclear genome from three Asian elephants and two woolly mammoths, and we identified and functionally annotated genetic changes unique to woolly mammoths. We found that genes with mammoth-specific amino acid changes are enriched in functions related to circadian biology, skin and hair development and physiology, lipid metabolism, adipose development and physiology, and temperature sensation. Finally, we resurrected and functionally tested the mammoth and ancestral elephant TRPV3 gene, which encodes a temperature-sensitive transient receptor potential (thermoTRP) channel involved in thermal sensation and hair growth, and we show that a single mammoth-specific amino acid substitution in an otherwise highly conserved region of the TRPV3 channel strongly affects its temperature sensitivity.
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9
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Song G, Dickins BJA, Demeter J, Engel S, Dunn B, Cherry JM. AGAPE (Automated Genome Analysis PipelinE) for pan-genome analysis of Saccharomyces cerevisiae. PLoS One 2015; 10:e0120671. [PMID: 25781462 PMCID: PMC4363492 DOI: 10.1371/journal.pone.0120671] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2014] [Accepted: 01/25/2015] [Indexed: 11/24/2022] Open
Abstract
The characterization and public release of genome sequences from thousands of organisms is expanding the scope for genetic variation studies. However, understanding the phenotypic consequences of genetic variation remains a challenge in eukaryotes due to the complexity of the genotype-phenotype map. One approach to this is the intensive study of model systems for which diverse sources of information can be accumulated and integrated. Saccharomyces cerevisiae is an extensively studied model organism, with well-known protein functions and thoroughly curated phenotype data. To develop and expand the available resources linking genomic variation with function in yeast, we aim to model the pan-genome of S. cerevisiae. To initiate the yeast pan-genome, we newly sequenced or re-sequenced the genomes of 25 strains that are commonly used in the yeast research community using advanced sequencing technology at high quality. We also developed a pipeline for automated pan-genome analysis, which integrates the steps of assembly, annotation, and variation calling. To assign strain-specific functional annotations, we identified genes that were not present in the reference genome. We classified these according to their presence or absence across strains and characterized each group of genes with known functional and phenotypic features. The functional roles of novel genes not found in the reference genome and associated with strains or groups of strains appear to be consistent with anticipated adaptations in specific lineages. As more S. cerevisiae strain genomes are released, our analysis can be used to collate genome data and relate it to lineage-specific patterns of genome evolution. Our new tool set will enhance our understanding of genomic and functional evolution in S. cerevisiae, and will be available to the yeast genetics and molecular biology community.
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Affiliation(s)
- Giltae Song
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
- * E-mail:
| | - Benjamin J. A. Dickins
- School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom
| | - Janos Demeter
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
| | - Stacia Engel
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
| | - Barbara Dunn
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
| | - J. Michael Cherry
- Department of Genetics, Stanford University School of Medicine, Stanford, California, United States of America
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10
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Welch AJ, Bedoya-Reina OC, Carretero-Paulet L, Miller W, Rode KD, Lindqvist C. Polar bears exhibit genome-wide signatures of bioenergetic adaptation to life in the arctic environment. Genome Biol Evol 2015; 6:433-50. [PMID: 24504087 PMCID: PMC3942037 DOI: 10.1093/gbe/evu025] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Polar bears (Ursus maritimus) face extremely cold temperatures and periods of fasting, which might result in more severe energetic challenges than those experienced by their sister species, the brown bear (U. arctos). We have examined the mitochondrial and nuclear genomes of polar and brown bears to investigate whether polar bears demonstrate lineage-specific signals of molecular adaptation in genes associated with cellular respiration/energy production. We observed increased evolutionary rates in the mitochondrial cytochrome c oxidase I gene in polar but not brown bears. An amino acid substitution occurred near the interaction site with a nuclear-encoded subunit of the cytochrome c oxidase complex and was predicted to lead to a functional change, although the significance of this remains unclear. The nuclear genomes of brown and polar bears demonstrate different adaptations related to cellular respiration. Analyses of the genomes of brown bears exhibited substitutions that may alter the function of proteins that regulate glucose uptake, which could be beneficial when feeding on carbohydrate-dominated diets during hyperphagia, followed by fasting during hibernation. In polar bears, genes demonstrating signatures of functional divergence and those potentially under positive selection were enriched in functions related to production of nitric oxide (NO), which can regulate energy production in several different ways. This suggests that polar bears may be able to fine-tune intracellular levels of NO as an adaptive response to control trade-offs between energy production in the form of adenosine triphosphate versus generation of heat (thermogenesis).
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Affiliation(s)
- Andreanna J Welch
- Department of Biological Sciences, University at Buffalo (SUNY), Buffalo
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11
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Kim HL, Ratan A, Perry GH, Montenegro A, Miller W, Schuster SC. Khoisan hunter-gatherers have been the largest population throughout most of modern-human demographic history. Nat Commun 2014; 5:5692. [PMID: 25471224 PMCID: PMC4268704 DOI: 10.1038/ncomms6692] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2014] [Accepted: 10/29/2014] [Indexed: 11/25/2022] Open
Abstract
The Khoisan people from Southern Africa maintained ancient lifestyles as hunter-gatherers or pastoralists up to modern times, though little else is known about their early history. Here we infer early demographic histories of modern humans using whole-genome sequences of five Khoisan individuals and one Bantu speaker. Comparison with a 420 K SNP data set from worldwide individuals demonstrates that two of the Khoisan genomes from the Ju/’hoansi population contain exclusive Khoisan ancestry. Coalescent analysis shows that the Khoisan and their ancestors have been the largest populations since their split with the non-Khoisan population ~100–150 kyr ago. In contrast, the ancestors of the non-Khoisan groups, including Bantu-speakers and non-Africans, experienced population declines after the split and lost more than half of their genetic diversity. Paleoclimate records indicate that the precipitation in southern Africa increased ~80–100 kyr ago while west-central Africa became drier. We hypothesize that these climate differences might be related to the divergent-ancient histories among human populations. The expansion of Bantu agriculturalists 3,800 years ago in sub-Saharan Africa established first contact with Khoisan hunter-gatherers living in parts of Southern Africa. Sequencing the genomes of five Namibian-Khoisan hunter-gatherers and one Bantu individual tells a tale of admixture and isolation in the early history of modern human populations.
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Affiliation(s)
- Hie Lim Kim
- 1] Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, 310 Wartik Lab, University Park, Pennsylvania 16802, USA [2] Singapore Centre on Environmental Life Sciences Engineering, Nanyang Technological University, 60 Nanyang Drive, SBS-01N-27, Singapore 637551, Singapore
| | - Aakrosh Ratan
- 1] Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, 310 Wartik Lab, University Park, Pennsylvania 16802, USA [2] Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia 22908, USA
| | - George H Perry
- Departments of Anthropology and Biology, Pennsylvania State University, 513 Carpenter Building, University Park, Pennsylvania 16802, USA
| | - Alvaro Montenegro
- 1] Department of Geography, Ohio State University, 154 North Oval Mall, Columbus, Ohio 43210, USA [2] Campus do Litoral Paulista, Unesp-Univ Estadual Paulista, São Vicente 11330-900, Brazil
| | - Webb Miller
- Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, 310 Wartik Lab, University Park, Pennsylvania 16802, USA
| | - Stephan C Schuster
- 1] Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, 310 Wartik Lab, University Park, Pennsylvania 16802, USA [2] Singapore Centre on Environmental Life Sciences Engineering, Nanyang Technological University, 60 Nanyang Drive, SBS-01N-27, Singapore 637551, Singapore
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12
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Rajala HLM, Olson T, Clemente MJ, Lagström S, Ellonen P, Lundan T, Hamm DE, Zaman SAU, Lopez Marti JM, Andersson EI, Jerez A, Porkka K, Maciejewski JP, Loughran TP, Mustjoki S. The analysis of clonal diversity and therapy responses using STAT3 mutations as a molecular marker in large granular lymphocytic leukemia. Haematologica 2014; 100:91-9. [PMID: 25281507 DOI: 10.3324/haematol.2014.113142] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
T-cell large granular lymphocytic leukemia and chronic lymphoproliferative disorder of natural killer cells are intriguing entities between benign and malignant lymphoproliferation. The molecular pathogenesis has partly been uncovered by the recent discovery of somatic activating STAT3 and STAT5b mutations. Here we show that 43% (75/174) of patients with T-cell large granular lymphocytic leukemia and 18% (7/39) with chronic lymphoproliferative disorder of natural killer cells harbor STAT3 mutations when analyzed by quantitative deep amplicon sequencing. Surprisingly, 17% of the STAT3-mutated patients carried multiple STAT3 mutations, which were located in different lymphocyte clones. The size of the mutated clone correlated well with the degree of clonal expansion of the T-cell repertoire analyzed by T-cell receptor beta chain deep sequencing. The analysis of sequential samples suggested that current immunosuppressive therapy is not able to reduce the level of the mutated clone in most cases, thus warranting the search for novel targeted therapies. Our findings imply that the clonal landscape of large granular lymphocytic leukemia is more complex than considered before, and a substantial number of patients have multiple lymphocyte subclones harboring different STAT3 mutations, thus mimicking the situation in acute leukemia.
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Affiliation(s)
- Hanna L M Rajala
- Hematology Research Unit, Department of Hematology, University of Helsinki and Helsinki University Central Hospital Cancer Center, Helsinki, Finland
| | - Thomas Olson
- University of Virginia Cancer Center, Charlottesville, VA, USA
| | - Michael J Clemente
- Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Sonja Lagström
- Institute for Molecular Medicine (FIMM), University of Helsinki, Finland
| | - Pekka Ellonen
- Institute for Molecular Medicine (FIMM), University of Helsinki, Finland
| | - Tuija Lundan
- Department of Clinical Chemistry and TYKSLAB, University of Turku and Turku University Central Hospital, Finland
| | | | | | | | - Emma I Andersson
- Hematology Research Unit, Department of Hematology, University of Helsinki and Helsinki University Central Hospital Cancer Center, Helsinki, Finland
| | - Andres Jerez
- Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA Hematology and Medical Oncology Department, Hospital Universitario Morales Meseguer, Universidad de Murcia, IMIB-Arrixaca, Murcia, Spain
| | - Kimmo Porkka
- Hematology Research Unit, Department of Hematology, University of Helsinki and Helsinki University Central Hospital Cancer Center, Helsinki, Finland
| | - Jaroslaw P Maciejewski
- Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA
| | | | - Satu Mustjoki
- Hematology Research Unit, Department of Hematology, University of Helsinki and Helsinki University Central Hospital Cancer Center, Helsinki, Finland
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Aguilar-Pontes MV, de Vries RP, Zhou M. (Post-)genomics approaches in fungal research. Brief Funct Genomics 2014; 13:424-39. [PMID: 25037051 DOI: 10.1093/bfgp/elu028] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
To date, hundreds of fungal genomes have been sequenced and many more are in progress. This wealth of genomic information has provided new directions to study fungal biodiversity. However, to further dissect and understand the complicated biological mechanisms involved in fungal life styles, functional studies beyond genomes are required. Thanks to the developments of current -omics techniques, it is possible to produce large amounts of fungal functional data in a high-throughput fashion (e.g. transcriptome, proteome, etc.). The increasing ease of creating -omics data has also created a major challenge for downstream data handling and analysis. Numerous databases, tools and software have been created to meet this challenge. Facing such a richness of techniques and information, hereby we provide a brief roadmap on current wet-lab and bioinformatics approaches to study functional genomics in fungi.
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14
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Sneddon TP, Zhe XS, Edmunds SC, Li P, Goodman L, Hunter CI. GigaDB: promoting data dissemination and reproducibility. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2014; 2014:bau018. [PMID: 24622612 PMCID: PMC3950661 DOI: 10.1093/database/bau018] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Often papers are published where the underlying data supporting the research are not made available because of the limitations of making such large data sets publicly and permanently accessible. Even if the raw data are deposited in public archives, the essential analysis intermediaries, scripts or software are frequently not made available, meaning the science is not reproducible. The GigaScience journal is attempting to address this issue with the associated data storage and dissemination portal, the GigaScience database (GigaDB). Here we present the current version of GigaDB and reveal plans for the next generation of improvements. However, most importantly, we are soliciting responses from you, the users, to ensure that future developments are focused on the data storage and dissemination issues that still need resolving. Database URL:http://www.gigadb.org
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Affiliation(s)
- Tam P Sneddon
- Department of Genetics, Stanford University, USA, GigaScience team, BGI HK Research Institute, 16 Dai Fu Street, Tai Po Industrial Estate, Hong Kong
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15
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Bedoya-Reina OC, Ratan A, Burhans R, Kim HL, Giardine B, Riemer C, Li Q, Olson TL, Loughran TP, Vonholdt BM, Perry GH, Schuster SC, Miller W. Galaxy tools to study genome diversity. Gigascience 2013; 2:17. [PMID: 24377391 PMCID: PMC3877877 DOI: 10.1186/2047-217x-2-17] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2013] [Accepted: 12/12/2013] [Indexed: 12/02/2022] Open
Abstract
Background Intra-species genetic variation can be used to investigate population structure, selection, and gene flow in non-model vertebrates; and due to the plummeting costs for genome sequencing, it is now possible for small labs to obtain full-genome variation data from their species of interest. However, those labs may not have easy access to, and familiarity with, computational tools to analyze those data. Results We have created a suite of tools for the Galaxy web server aimed at handling nucleotide and amino-acid polymorphisms discovered by full-genome sequencing of several individuals of the same species, or using a SNP genotyping microarray. In addition to providing user-friendly tools, a main goal is to make published analyses reproducible. While most of the examples discussed in this paper deal with nuclear-genome diversity in non-human vertebrates, we also illustrate the application of the tools to fungal genomes, human biomedical data, and mitochondrial sequences. Conclusions This project illustrates that a small group can design, implement, test, document, and distribute a Galaxy tool collection to meet the needs of a particular community of biologists.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Webb Miller
- Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, University Park, PA 16802, USA.
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