1
|
Unneberg P, Larsson M, Olsson A, Wallerman O, Petri A, Bunikis I, Vinnere Pettersson O, Papetti C, Gislason A, Glenner H, Cartes JE, Blanco-Bercial L, Eriksen E, Meyer B, Wallberg A. Ecological genomics in the Northern krill uncovers loci for local adaptation across ocean basins. Nat Commun 2024; 15:6297. [PMID: 39090106 PMCID: PMC11294593 DOI: 10.1038/s41467-024-50239-7] [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: 12/06/2023] [Accepted: 05/15/2024] [Indexed: 08/04/2024] Open
Abstract
Krill are vital as food for many marine animals but also impacted by global warming. To learn how they and other zooplankton may adapt to a warmer world we studied local adaptation in the widespread Northern krill (Meganyctiphanes norvegica). We assemble and characterize its large genome and compare genome-scale variation among 74 specimens from the colder Atlantic Ocean and warmer Mediterranean Sea. The 19 Gb genome likely evolved through proliferation of retrotransposons, now targeted for inactivation by extensive DNA methylation, and contains many duplicated genes associated with molting and vision. Analysis of 760 million SNPs indicates extensive homogenizing gene-flow among populations. Nevertheless, we detect signatures of adaptive divergence across hundreds of genes, implicated in photoreception, circadian regulation, reproduction and thermal tolerance, indicating polygenic adaptation to light and temperature. The top gene candidate for ecological adaptation was nrf-6, a lipid transporter with a Mediterranean variant that may contribute to early spring reproduction. Such variation could become increasingly important for fitness in Atlantic stocks. Our study underscores the widespread but uneven distribution of adaptive variation, necessitating characterization of genetic variation among natural zooplankton populations to understand their adaptive potential, predict risks and support ocean conservation in the face of climate change.
Collapse
Affiliation(s)
- Per Unneberg
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Mårten Larsson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Anna Olsson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden
| | - Anna Petri
- Uppsala Genome Center, Department of Immunology, Genetics and Pathology, Uppsala University, National Genomics Infrastructure hosted by SciLifeLab, Uppsala, Sweden
| | - Ignas Bunikis
- Uppsala Genome Center, Department of Immunology, Genetics and Pathology, Uppsala University, National Genomics Infrastructure hosted by SciLifeLab, Uppsala, Sweden
| | - Olga Vinnere Pettersson
- Uppsala Genome Center, Department of Immunology, Genetics and Pathology, Uppsala University, National Genomics Infrastructure hosted by SciLifeLab, Uppsala, Sweden
| | | | - Astthor Gislason
- Marine and Freshwater Research Institute, Pelagic Division, Reykjavik, Iceland
| | - Henrik Glenner
- Department of Biological Sciences, University of Bergen, Bergen, Norway
- Center for Macroecology, Evolution and Climate Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Joan E Cartes
- Instituto de Ciencias del Mar (ICM-CSIC), Barcelona, Spain
| | | | | | - Bettina Meyer
- Section Polar Biological Oceanography, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
- Institute for Chemistry and Biology of the Marine Environment, Carlvon Ossietzky University of Oldenburg, Oldenburg, Germany
- Helmholtz Institute for Functional Marine Biodiversity (HIFMB), University of Oldenburg, Oldenburg, Germany
| | - Andreas Wallberg
- Department of Medical Biochemistry and Microbiology, Uppsala University, Husargatan 3, 751 23, Uppsala, Sweden.
| |
Collapse
|
2
|
Ghaly TM, Focardi A, Elbourne LDH, Sutcliffe B, Humphreys WF, Jaschke PR, Tetu SG, Paulsen IT. Exploring virus-host-environment interactions in a chemotrophic-based underground estuary. ENVIRONMENTAL MICROBIOME 2024; 19:9. [PMID: 38291480 PMCID: PMC10829341 DOI: 10.1186/s40793-024-00549-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/08/2024] [Indexed: 02/01/2024]
Abstract
BACKGROUND Viruses play important roles in modulating microbial communities and influencing global biogeochemistry. There is now growing interest in characterising their ecological roles across diverse biomes. However, little is known about viral ecology in low-nutrient, chemotrophic-based environments. In such ecosystems, virus-driven manipulation of nutrient cycles might have profound impacts across trophic levels. In particular, anchialine environments, which are low-energy underground estuaries sustained by chemotrophic processes, represent ideal model systems to study novel virus-host-environment interactions. RESULTS Here, we employ metagenomic sequencing to investigate the viral community in Bundera Sinkhole, an anchialine ecosystem rich in endemic species supported by microbial chemosynthesis. We find that the viruses are highly novel, with less than 2% representing described viruses, and are hugely abundant, making up as much as 12% of microbial intracellular DNA. These highly abundant viruses largely infect important prokaryotic taxa that drive key metabolic processes in the sinkhole. Further, the abundance of viral auxiliary metabolic genes (AMGs) involved in nucleotide and protein synthesis was strongly correlated with declines in environmental phosphate and sulphate concentrations. These AMGs encoded key enzymes needed to produce sulphur-containing amino acids, and phosphorus metabolic enzymes involved in purine and pyrimidine nucleotide synthesis. We hypothesise that this correlation is either due to selection of these AMGs under low phosphate and sulphate concentrations, highlighting the dynamic interactions between viruses, their hosts, and the environment; or, that these AMGs are driving increased viral nucleotide and protein synthesis via manipulation of host phosphorus and sulphur metabolism, consequently driving nutrient depletion in the surrounding water. CONCLUSION This study represents the first metagenomic investigation of viruses in anchialine ecosystems, and provides new hypotheses and insights into virus-host-environment interactions in such 'dark', low-energy environments. This is particularly important since anchialine ecosystems are characterised by diverse endemic species, both in their microbial and faunal assemblages, which are primarily supported by microbial chemosynthesis. Thus, virus-host-environment interactions could have profound effects cascading through all trophic levels.
Collapse
Affiliation(s)
- Timothy M Ghaly
- School of Natural Sciences, Macquarie University, Sydney, Australia.
| | - Amaranta Focardi
- Climate Change Cluster (C3), University of Technology Sydney, Sydney, Australia
| | - Liam D H Elbourne
- School of Natural Sciences, Macquarie University, Sydney, Australia
- ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, Australia
| | | | - William F Humphreys
- School of Biological Sciences, University of Western Australia, Perth, Australia
| | - Paul R Jaschke
- School of Natural Sciences, Macquarie University, Sydney, Australia
- ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, Australia
| | - Sasha G Tetu
- School of Natural Sciences, Macquarie University, Sydney, Australia.
- ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, Australia.
| | - Ian T Paulsen
- School of Natural Sciences, Macquarie University, Sydney, Australia.
- ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, Australia.
| |
Collapse
|
3
|
Cheng H, Zhang H, Song J, Jiang J, Chen S, Chen F, Wang L. GERDH: an interactive multi-omics database for cross-species data mining in horticultural crops. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 116:1018-1029. [PMID: 37310261 DOI: 10.1111/tpj.16350] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/07/2023] [Accepted: 06/07/2023] [Indexed: 06/14/2023]
Abstract
Horticultural plants contribute immensely to the quality of human's life. The rapid development of omics studies on horticultural plants has resulted in large volumes of valuable growth- and development-related data. Genes that are essential for growth and development are highly conserved in evolution. Cross-species data mining reduces the impact of species heterogeneity and has been extensively used for conserved gene identification. Owing to the lack of a comprehensive database for cross-species data mining using multi-omics data from all horticultural plant species, the current resources in this field are far from satisfactory. Here, we introduce GERDH (https://dphdatabase.com), a database platform for cross-species data mining among horticultural plants, based on 12 961 uniformly processed publicly available omics libraries from more than 150 horticultural plant accessions, including fruits, vegetables and ornamental plants. Important and conserved genes that are essential for a specific biological process can be obtained by cross-species analysis module with interactive web-based data analysis and visualization. Moreover, GERDH is equipped with seven online analysis tools, including gene expression, in-species analysis, epigenetic regulation, gene co-expression, enrichment/pathway and phylogenetic analysis. By interactive cross-species analysis, we identified key genes contributing to postharvest storage. By gene expression analysis, we explored new functions of CmEIN3 in flower development, which was validated by transgenic chrysanthemum analysis. We believe that GERDH will be a useful resource for key gene identification and will allow for omics big data to be more available and accessible to horticultural plant community members.
Collapse
Affiliation(s)
- Hua Cheng
- National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Landscaping, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, Nanjing Agricultural University, Nanjing, 210095, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
- College of Horticulture, Nanjing Agricultural University, Nanjing, 210095, China
| | - Hua Zhang
- National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Landscaping, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, Nanjing Agricultural University, Nanjing, 210095, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
- College of Horticulture, Nanjing Agricultural University, Nanjing, 210095, China
| | - Jing Song
- National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Landscaping, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, Nanjing Agricultural University, Nanjing, 210095, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
- College of Horticulture, Nanjing Agricultural University, Nanjing, 210095, China
| | - Jiafu Jiang
- National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Landscaping, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, Nanjing Agricultural University, Nanjing, 210095, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
- College of Horticulture, Nanjing Agricultural University, Nanjing, 210095, China
| | - Sumei Chen
- National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Landscaping, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, Nanjing Agricultural University, Nanjing, 210095, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
- College of Horticulture, Nanjing Agricultural University, Nanjing, 210095, China
| | - Fadi Chen
- National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Landscaping, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, Nanjing Agricultural University, Nanjing, 210095, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
- College of Horticulture, Nanjing Agricultural University, Nanjing, 210095, China
| | - Likai Wang
- National Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Flower Biology and Germplasm Innovation, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Landscaping, Ministry of Agriculture and Rural Affairs, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, Nanjing Agricultural University, Nanjing, 210095, China
- Zhongshan Biological Breeding Laboratory, No.50 Zhongling Street, Nanjing, 210014, China
- College of Horticulture, Nanjing Agricultural University, Nanjing, 210095, China
| |
Collapse
|
4
|
Salamzade R, Tran P, Martin C, Manson AL, Gilmore MS, Earl AM, Anantharaman K, Kalan LR. zol & fai: large-scale targeted detection and evolutionary investigation of gene clusters. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.544063. [PMID: 37333121 PMCID: PMC10274777 DOI: 10.1101/2023.06.07.544063] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Many universally and conditionally important genes are genomically aggregated within clusters. Here, we introduce fai and zol, which together enable large-scale comparative analysis of different types of gene clusters and mobile-genetic elements (MGEs), such as biosynthetic gene clusters (BGCs) or viruses. Fundamentally, they overcome a current bottleneck to reliably perform comprehensive orthology inference at large scale across broad taxonomic contexts and thousands of genomes. First, fai allows the identification of orthologous or homologous instances of a query gene cluster of interest amongst a database of target genomes. Subsequently, zol enables reliable, context-specific inference of protein-encoding ortholog groups for individual genes across gene cluster instances. In addition, zol performs functional annotation and computes a variety of statistics for each inferred ortholog group. These programs are showcased through application to: (i) longitudinal tracking of a virus in metagenomes, (ii) discovering novel population-genetic insights of two common BGCs in a fungal species, and (iii) uncovering large-scale evolutionary trends of a virulence-associated gene cluster across thousands of genomes from a diverse bacterial genus.
Collapse
Affiliation(s)
- Rauf Salamzade
- Department of Medical Microbiology and Immunology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Microbiology Doctoral Training Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Patricia Tran
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
- Freshwater and Marine Science Doctoral Program, University of Wisconsin-Madison, WI, USA
| | - Cody Martin
- Microbiology Doctoral Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Abigail L. Manson
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Michael S. Gilmore
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Ophthalmology, Harvard Medical School and Mass Eye and Ear, Boston, Massachusetts, USA
- Department of Microbiology, Harvard Medical School and Mass Eye and Ear, Boston, Massachusetts, USA
| | - Ashlee M. Earl
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | | | - Lindsay R. Kalan
- Department of Medical Microbiology and Immunology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medicine, Division of Infectious Disease, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- M.G. DeGroote Institute for Infectious Disease Research, David Braley Centre for Antibiotic Discovery, Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada
| |
Collapse
|
5
|
Watanabe T, Kure A, Horiike T. OrthoPhy: A Program to Construct Ortholog Data Sets Using Taxonomic Information. Genome Biol Evol 2023; 15:7044703. [PMID: 36799928 PMCID: PMC9991595 DOI: 10.1093/gbe/evad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 01/30/2023] [Accepted: 02/13/2023] [Indexed: 02/18/2023] Open
Abstract
Species phylogenetic trees represent the evolutionary processes of organisms, and they are fundamental in evolutionary research. Therefore, new methods have been developed to obtain more reliable species phylogenetic trees. A highly reliable method is the construction of an ortholog data set based on sequence information of genes, which is then used to infer the species phylogenetic tree. However, although methods for constructing an ortholog data set for species phylogenetic analysis have been developed, they cannot remove some paralogs, which is necessary for reliable species phylogenetic inference. To address the limitations of current methods, we developed OrthoPhy, a program that excludes paralogs and constructs highly accurate ortholog data sets using taxonomic information dividing analyzed species into monophyletic groups. OrthoPhy can remove paralogs, detecting inconsistencies between taxonomic information and phylogenetic trees of candidate ortholog groups clustered by sequence similarity. Performance tests using evolutionary simulated sequences and real sequences of 40 bacteria revealed that the precision of ortholog inference by OrthoPhy is higher than that of existing programs. Additionally, the phylogenetic analysis of species was more accurate when performed using ortholog data sets constructed by OrthoPhy than that performed using data sets constructed by existing programs. Furthermore, we performed a benchmark test of the Quest for Orthologs using real sequence data and found that the concordance rate between the phylogenetic trees of orthologs inferred by OrthoPhy and those of species was higher than the rates obtained by other ortholog inference programs. Therefore, ortholog data sets constructed using OrthoPhy enabled a more accurate phylogenetic analysis of species than those constructed using the existing programs, and OrthoPhy can be used for the phylogenetic analysis of species even for distantly related species that have experienced many evolutionary events.
Collapse
Affiliation(s)
- Tomoaki Watanabe
- United Graduate School of Agricultural Science, Gifu University, Gifu, Japan
| | - Akinori Kure
- Graduate School of Integrated Science and Technology, Shizuoka University, Shizuoka, Japan
| | - Tokumasa Horiike
- Department of Bioresource Sciences, Shizuoka University, Shizuoka, Japan
| |
Collapse
|
6
|
Zhao X, Guo Y, Kang L, Yin C, Bi A, Xu D, Zhang Z, Zhang J, Yang X, Xu J, Xu S, Song X, Zhang M, Li Y, Kear P, Wang J, Liu Z, Fu X, Lu F. Population genomics unravels the Holocene history of bread wheat and its relatives. NATURE PLANTS 2023; 9:403-419. [PMID: 36928772 DOI: 10.1038/s41477-023-01367-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 02/08/2023] [Indexed: 05/06/2023]
Abstract
Deep knowledge of crop biodiversity is essential to improving global food security. Despite bread wheat serving as a keystone crop worldwide, the population history of bread wheat and its relatives, both cultivated and wild, remains elusive. By analysing whole-genome sequences of 795 wheat accessions, we found that bread wheat originated from the southwest coast of the Caspian Sea and underwent a slow speciation process, lasting ~3,300 yr owing to persistent gene flow from its relatives. Soon after, bread wheat spread across Eurasia and reached Europe, South Asia and East Asia ~7,000 to ~5,000 yr ago, shaping a diversified but occasionally convergent adaptive landscape in novel environments. By contrast, the cultivated relatives of bread wheat experienced a population decline by ~82% over the past ~2,000 yr due to the food choice shift of humans. Further biogeographical modelling predicted a continued population shrinking of many bread wheat relatives in the coming decades because of their vulnerability to the changing climate. These findings will guide future efforts in protecting and utilizing wheat biodiversity to enhance global wheat production.
Collapse
Affiliation(s)
- Xuebo Zhao
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yafei Guo
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lipeng Kang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Changbin Yin
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Aoyue Bi
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Daxing Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhiliang Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jijin Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaohan Yang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jun Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Song Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xinyue Song
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Conservation and Utilization of Bio-Resources in Yunnan and Center for Life Sciences, School of Life Sciences, Yunnan University, Kunming, China
| | - Ming Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yiwen Li
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Philip Kear
- International Potato Center-China Center for Asia and the Pacific, Beijing, China
| | - Jing Wang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Zhiyong Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiangdong Fu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fei Lu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China.
| |
Collapse
|
7
|
Foley S, Vlasova A, Marcet-Houben M, Gabaldón T, Hinman VF. Evolutionary analyses of genes in Echinodermata offer insights towards the origin of metazoan phyla. Genomics 2022; 114:110431. [PMID: 35835427 PMCID: PMC9552553 DOI: 10.1016/j.ygeno.2022.110431] [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: 10/03/2021] [Revised: 05/10/2022] [Accepted: 07/06/2022] [Indexed: 11/24/2022]
Abstract
Despite recent studies discussing the evolutionary impacts of gene duplications and losses among metazoans, the genomic basis for the evolution of phyla remains enigmatic. Here, we employ phylogenomic approaches to search for orthologous genes without known functions among echinoderms, and subsequently use them to guide the identification of their homologs across other metazoans. Our final set of 14 genes was obtained via a suite of homology prediction tools, gene expression data, gene ontology, and generating the Strongylocentrotus purpuratus phylome. The gene set was subjected to selection pressure analyses, which indicated that they are highly conserved and under negative selection. Their presence across broad taxonomic depths suggests that genes required to form a phylum are ancestral to that phylum. Therefore, rather than de novo gene genesis, we posit that evolutionary forces such as selection on existing genomic elements over large timescales may drive divergence and contribute to the emergence of phyla.
Collapse
Affiliation(s)
- Saoirse Foley
- Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA; Echinobase #6-46, Mellon Institute, 4400 Fifth Ave, Pittsburgh, PA 15213, USA.
| | - Anna Vlasova
- Barcelona Supercomputing Centre (BSC-CNS), Jordi Girona, 29, 08034 Barcelona, Spain; Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Marina Marcet-Houben
- Barcelona Supercomputing Centre (BSC-CNS), Jordi Girona, 29, 08034 Barcelona, Spain; Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Toni Gabaldón
- Barcelona Supercomputing Centre (BSC-CNS), Jordi Girona, 29, 08034 Barcelona, Spain; Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Veronica F Hinman
- Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA; Echinobase #6-46, Mellon Institute, 4400 Fifth Ave, Pittsburgh, PA 15213, USA
| |
Collapse
|
8
|
Cay SB, Cinar YU, Kuralay SC, Inal B, Zararsiz G, Ciftci A, Mollman R, Obut O, Eldem V, Bakir Y, Erol O. Genome skimming approach reveals the gene arrangements in the chloroplast genomes of the highly endangered Crocus L. species: Crocus istanbulensis (B.Mathew) Rukšāns. PLoS One 2022; 17:e0269747. [PMID: 35704623 PMCID: PMC9200356 DOI: 10.1371/journal.pone.0269747] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 05/27/2022] [Indexed: 11/19/2022] Open
Abstract
Crocus istanbulensis (B.Mathew) Rukšāns is one of the most endangered Crocus species in the world and has an extremely limited distribution range in Istanbul. Our recent field work indicates that no more than one hundred individuals remain in the wild. In the present study, we used genome skimming to determine the complete chloroplast (cp) genome sequences of six C. istanbulensis individuals collected from the locus classicus. The cp genome of C. istanbulensis has 151,199 base pairs (bp), with a large single-copy (LSC) (81,197 bp), small single copy (SSC) (17,524 bp) and two inverted repeat (IR) regions of 26,236 bp each. The cp genome contains 132 genes, of which 86 are protein-coding (PCGs), 8 are rRNA and 38 are tRNA genes. Most of the repeats are found in intergenic spacers of Crocus species. Mononucleotide repeats were most abundant, accounting for over 80% of total repeats. The cp genome contained four palindrome repeats and one forward repeat. Comparative analyses among other Iridaceae species identified one inversion in the terminal positions of LSC region and three different gene (psbA, rps3 and rpl22) arrangements in C. istanbulensis that were not reported previously. To measure selective pressure in the exons of chloroplast coding sequences, we performed a sequence analysis of plastome-encoded genes. A total of seven genes (accD, rpoC2, psbK, rps12, ccsA, clpP and ycf2) were detected under positive selection in the cp genome. Alignment-free sequence comparison showed an extremely low sequence diversity across naturally occurring C. istanbulensis specimens. All six sequenced individuals shared the same cp haplotype. In summary, this study will aid further research on the molecular evolution and development of ex situ conservation strategies of C. istanbulensis.
Collapse
Affiliation(s)
- Selahattin Baris Cay
- Department of Biology, Faculty of Sciences, Istanbul University, Istanbul, Turkey
| | - Yusuf Ulas Cinar
- Department of Biology, Faculty of Sciences, Istanbul University, Istanbul, Turkey
| | - Selim Can Kuralay
- Department of Biology, Faculty of Sciences, Istanbul University, Istanbul, Turkey
| | - Behcet Inal
- Department of Agricultural Biotechnology, Faculty of Agriculture, University of Siirt, Siirt, Turkey
| | - Gokmen Zararsiz
- Department of Biostatistics, Erciyes University, Kayseri, Turkey
- Drug Application and Research Center (ERFARMA), Erciyes University, Kayseri, Turkey
| | - Almila Ciftci
- Department of Biology, Faculty of Sciences, Istanbul University, Istanbul, Turkey
| | - Rachel Mollman
- Department of Biology, Faculty of Sciences, Istanbul University, Istanbul, Turkey
| | - Onur Obut
- Department of Biology, Faculty of Sciences, Istanbul University, Istanbul, Turkey
| | - Vahap Eldem
- Department of Biology, Faculty of Sciences, Istanbul University, Istanbul, Turkey
- * E-mail:
| | - Yakup Bakir
- Department of Plant Bioactive Metabolites, ACTV Biotechnology, Inc., Istanbul, Turkey
| | - Osman Erol
- Department of Biology, Faculty of Sciences, Istanbul University, Istanbul, Turkey
| |
Collapse
|
9
|
Išerić H, Alkan C, Hach F, Numanagić I. Fast characterization of segmental duplication structure in multiple genome assemblies. Algorithms Mol Biol 2022; 17:4. [PMID: 35303886 PMCID: PMC8932185 DOI: 10.1186/s13015-022-00210-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 02/08/2022] [Indexed: 11/29/2022] Open
Abstract
Motivation The increasing availability of high-quality genome assemblies raised interest in the characterization of genomic architecture. Major architectural elements, such as common repeats and segmental duplications (SDs), increase genome plasticity that stimulates further evolution by changing the genomic structure and inventing new genes. Optimal computation of SDs within a genome requires quadratic-time local alignment algorithms that are impractical due to the size of most genomes. Additionally, to perform evolutionary analysis, one needs to characterize SDs in multiple genomes and find relations between those SDs and unique (non-duplicated) segments in other genomes. A naïve approach consisting of multiple sequence alignment would make the optimal solution to this problem even more impractical. Thus there is a need for fast and accurate algorithms to characterize SD structure in multiple genome assemblies to better understand the evolutionary forces that shaped the genomes of today. Results Here we introduce a new approach, BISER, to quickly detect SDs in multiple genomes and identify elementary SDs and core duplicons that drive the formation of such SDs. BISER improves earlier tools by (i) scaling the detection of SDs with low homology to multiple genomes while introducing further 7–33\documentclass[12pt]{minimal}
\usepackage{amsmath}
\usepackage{wasysym}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsbsy}
\usepackage{mathrsfs}
\usepackage{upgreek}
\setlength{\oddsidemargin}{-69pt}
\begin{document}$$\times$$\end{document}× speed-ups over the existing tools, and by (ii) characterizing elementary SDs and detecting core duplicons to help trace the evolutionary history of duplications to as far as 300 million years. Availability and implementation BISER is implemented in Seq programming language and is publicly available at https://github.com/0xTCG/biser.
Collapse
|
10
|
McFarland AG, Kennedy NW, Mills CE, Tullman-Ercek D, Huttenhower C, Hartmann EM. Density-based binning of gene clusters to infer function or evolutionary history using GeneGrouper. Bioinformatics 2022; 38:612-620. [PMID: 34734968 DOI: 10.1093/bioinformatics/btab752] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 10/15/2021] [Accepted: 10/28/2021] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION Identifying variant forms of gene clusters of interest in phylogenetically proximate and distant taxa can help to infer their evolutionary histories and functions. Conserved gene clusters may differ by only a few genes, but these small differences can in turn induce substantial phenotypes, such as by the formation of pseudogenes or insertions interrupting regulation. Particularly as microbial genomes and metagenomic assemblies become increasingly abundant, unsupervised grouping of similar, but not necessarily identical, gene clusters into consistent bins can provide a population-level understanding of their gene content variation and functional homology. RESULTS We developed GeneGrouper, a command-line tool that uses a density-based clustering method to group gene clusters into bins. GeneGrouper demonstrated high recall and precision in benchmarks for the detection of the 23-gene Salmonella enterica LT2 Pdu gene cluster and four-gene Pseudomonas aeruginosa PAO1 Mex gene cluster among 435 genomes spanning mixed taxa. In a subsequent application investigating the diversity and impact of gene-complete and -incomplete LT2 Pdu gene clusters in 1130 S.enterica genomes, GeneGrouper identified a novel, frequently occurring pduN pseudogene. When investigated in vivo, introduction of the pduN pseudogene negatively impacted microcompartment formation. We next demonstrated the versatility of GeneGrouper by clustering distant homologous gene clusters and variable gene clusters found in integrative and conjugative elements. AVAILABILITY AND IMPLEMENTATION GeneGrouper software and code are publicly available at https://pypi.org/project/GeneGrouper/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Alexander G McFarland
- Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Nolan W Kennedy
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Carolyn E Mills
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Danielle Tullman-Ercek
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Curtis Huttenhower
- Harvard Chan Microbiome in Public Health Center, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Departments of Biostatistics and Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Erica M Hartmann
- Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL 60208, USA
| |
Collapse
|
11
|
Arshinoff BI, Cary GA, Karimi K, Foley S, Agalakov S, Delgado F, Lotay VS, Ku CJ, Pells TJ, Beatman TR, Kim E, Cameron RA, Vize PD, Telmer C, Croce JC, Ettensohn CA, Hinman VF. Echinobase: leveraging an extant model organism database to build a knowledgebase supporting research on the genomics and biology of echinoderms. Nucleic Acids Res 2022; 50:D970-D979. [PMID: 34791383 PMCID: PMC8728261 DOI: 10.1093/nar/gkab1005] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 10/05/2021] [Accepted: 10/13/2021] [Indexed: 12/16/2022] Open
Abstract
Echinobase (www.echinobase.org) is a third generation web resource supporting genomic research on echinoderms. The new version was built by cloning the mature Xenopus model organism knowledgebase, Xenbase, refactoring data ingestion pipelines and modifying the user interface to adapt to multispecies echinoderm content. This approach leveraged over 15 years of previous database and web application development to generate a new fully featured informatics resource in a single year. In addition to the software stack, Echinobase uses the private cloud and physical hosts that support Xenbase. Echinobase currently supports six echinoderm species, focused on those used for genomics, developmental biology and gene regulatory network analyses. Over 38 000 gene pages, 18 000 publications, new improved genome assemblies, JBrowse genome browser and BLAST + services are available and supported by the development of a new echinoderm anatomical ontology, uniformly applied formal gene nomenclature, and consistent orthology predictions. A novel feature of Echinobase is integrating support for multiple, disparate species. New genomes from the diverse echinoderm phylum will be added and supported as data becomes available. The common code development design of the integrated knowledgebases ensures parallel improvements as each resource evolves. This approach is widely applicable for developing new model organism informatics resources.
Collapse
Affiliation(s)
- Bradley I Arshinoff
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Gregory A Cary
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kamran Karimi
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Saoirse Foley
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Sergei Agalakov
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Francisco Delgado
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Vaneet S Lotay
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Carolyn J Ku
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Troy J Pells
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Thomas R Beatman
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Eugene Kim
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - R Andrew Cameron
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Peter D Vize
- Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Cheryl A Telmer
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Jenifer C Croce
- Laboratoire de Biologie du Développement de Villefranche-sur-Mer (LBDV), Institut de la Mer de Villefranche (IMEV), Sorbonne Université, CNRS, Villefranche-sur-Mer, France
| | - Charles A Ettensohn
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Veronica F Hinman
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| |
Collapse
|
12
|
Yukphan P, Charoenyingcharoen P, Kingcha Y, Likhitrattanapisal S, Muangham S, Tanasupawat S, Yamada Y. Acetobacter garciniae sp. nov., an acetic acid bacterium isolated from fermented mangosteen peel in Thailand. Int J Syst Evol Microbiol 2021; 71. [PMID: 34662265 DOI: 10.1099/ijsem.0.005052] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Two isolates, MS16-SU-2T and MS18-SU-3, obtained from fermented mangosteen peel in vinegar were suggested to constitute a new species assignable to the genus Acetobacter based on the results of 16S rRNA gene sequencing. The two isolates showed the highest sequence similarity (98.58%) to Acetobacter tropicalis NBRC 16470T and Acetobacter senegalensis LMG 23690T. However, the calculated similarity values were lower than the threshold for species demarcation. The phylogenetic analysis showed that the branches of the two isolates were separated from other Acetobacter species, and the two isolates constituted a new species in the genus Acetobacter. The genomic DNA of isolate MS16-SU-2T was sequenced. The assembled genome of the isolate was analysed, and the results showed that the highest average nucleotide identity value of 75.9 % was with Acetobacter papayae JCM 25143T and the highest digital DNA-DNA hybridization value of 25.1 % was with Acetobacter fallax LMG 1636T, which were lower than the cutoff values for species delineation. The phylogenetic tree based on the genome sequences showed that the lineage of isolate MS16-SU-2T was most closely related to A. papayae JCM 25143T and Acetobacter suratthaniensis TBRC 1719T, but separated from the branches of these two species. In addition, the two isolates could be distinguished from the type strains of closely related species by their phenotypic characteristics and MALDI-TOF profiles. Therefore, the two isolates, MS16-SU-2T (=TBRC 12339T=LMG 32243T) and MS18-SU-3 (=TBRC 12305), can be assigned to an independent species within the genus Acetobacter, and the name of Acetobacter garciniae sp. nov. is proposed for the two isolates.
Collapse
Affiliation(s)
- Pattaraporn Yukphan
- Microbial Diversity and Utilization Research Team, Thailand Bioresource Research Center (TBRC), National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand
| | - Piyanat Charoenyingcharoen
- Microbial Diversity and Utilization Research Team, Thailand Bioresource Research Center (TBRC), National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand
| | - Yutthana Kingcha
- Food Biotechnology Research Team, Functional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand
| | - Somsak Likhitrattanapisal
- Microbial Systems and Computational Biology Research Team, Thailand Bioresource Research Center (TBRC), National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand
| | - Supattra Muangham
- Microbial Diversity and Utilization Research Team, Thailand Bioresource Research Center (TBRC), National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand.,Department of Microbiology, Faculty of Science, Kasetsart University, Chatuchak, Bangkok 10900, Thailand
| | - Somboon Tanasupawat
- Department of Biochemistry and Microbiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, 254 Phayathai Road, Wangmai, Pathumwan, Bangkok 10330, Thailand
| | - Yuzo Yamada
- Microbial Diversity and Utilization Research Team, Thailand Bioresource Research Center (TBRC), National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand.,Japan International Cooperation Agency (JICA Senior Overseas Volunteer), Shibuya-ku, Tokyo 151-8558, Japan.,Laboratory of Applied Microbiology (Professor Emeritus), Department of Applied Biological Chemistry, Faculty of Agriculture, Shizuoka University, Suruga-ku, Shizuoka 422-8529, Japan
| |
Collapse
|
13
|
Beatman TR, Buckley KM, Cary GA, Hinman VF, Ettensohn CA. A nomenclature for echinoderm genes. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2021; 2021:6350312. [PMID: 34386815 PMCID: PMC8361234 DOI: 10.1093/database/baab052] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/02/2021] [Accepted: 08/02/2021] [Indexed: 12/16/2022]
Abstract
Echinoderm embryos and larvae are prominent experimental model systems for studying developmental mechanisms. High-quality, assembled, annotated genome sequences are now available for several echinoderm species, including representatives from most classes. The increased availability of these data necessitates the development of a nomenclature that assigns universally interpretable gene symbols to echinoderm genes to facilitate cross-species comparisons of gene functions, both within echinoderms and across other phyla. This paper describes the implementation of an improved set of echinoderm gene nomenclature guidelines that both communicates meaningful orthology information in protein-coding gene symbols and names and establishes continuity with nomenclatures developed for major vertebrate model organisms, including humans. Differences between the echinoderm gene nomenclature guidelines and vertebrate guidelines are examined and explained. This nomenclature incorporates novel solutions to allow for several types of orthologous relationships, including the single echinoderm genes with multiple vertebrate co-orthologs that result from whole-genome-duplication events. The current version of the Echinoderm Gene Nomenclature Guidelines can be found at https://www.echinobase.org/gene/static/geneNomenclature.jsp Database URL https://www.echinobase.org/
Collapse
Affiliation(s)
- Thomas R Beatman
- Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA.,Echinobase, #646 Mellon Institute, 4400 Fifth Ave, Pittsburgh, PA 15213, USA
| | - Katherine M Buckley
- Department of Biological Sciences, Auburn University, 101 Rouse Life Sciences, Auburn, AL 36849, USA
| | - Gregory A Cary
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA
| | - Veronica F Hinman
- Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA.,Echinobase, #646 Mellon Institute, 4400 Fifth Ave, Pittsburgh, PA 15213, USA
| | - Charles A Ettensohn
- Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA.,Echinobase, #646 Mellon Institute, 4400 Fifth Ave, Pittsburgh, PA 15213, USA
| |
Collapse
|
14
|
Foley S, Ku C, Arshinoff B, Lotay V, Karimi K, Vize PD, Hinman V. Integration of 1:1 orthology maps and updated datasets into Echinobase. Database (Oxford) 2021; 2021:baab030. [PMID: 34010390 PMCID: PMC8132956 DOI: 10.1093/database/baab030] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 04/23/2021] [Accepted: 04/30/2021] [Indexed: 12/24/2022]
Abstract
Echinobase (https://echinobase.org) is a central online platform that generates, manages and hosts genomic data relevant to echinoderm research. While the resource primarily serves the echinoderm research community, the recent release of an excellent quality genome for the frequently studied purple sea urchin (Strongylocentrotus purpuratus genome, v5.0) has provided an opportunity to adapt to the needs of a broader research community across other model systems. To this end, establishing pipelines to identify orthologous genes between echinoderms and other species has become a priority in many contexts including nomenclature, linking to data in other model organisms, and in internal functionality where data gathered in one hosted species can be associated with genes in other hosted echinoderms. This paper describes the orthology pipelines currently employed by Echinobase and how orthology data are processed to yield 1:1 ortholog mappings between a variety of echinoderms and other model taxa. We also describe functions of interest that have recently been included on the resource, including an updated developmental time course for S.purpuratus, and additional tracks for genome browsing. These data enhancements will increase the accessibility of the resource to non-echinoderm researchers and simultaneously expand the data quality and quantity available to core Echinobase users. Database URL: https://echinobase.org.
Collapse
Affiliation(s)
- Saoirse Foley
- Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
- Echinobase #6-46, Mellon Institute, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Carolyn Ku
- Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
- Echinobase #6-46, Mellon Institute, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Brad Arshinoff
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta TN2 1N4, Canada
| | - Vaneet Lotay
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta TN2 1N4, Canada
| | - Kamran Karimi
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta TN2 1N4, Canada
| | - Peter D Vize
- Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta TN2 1N4, Canada
| | - Veronica Hinman
- Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
- Echinobase #6-46, Mellon Institute, 4400 Fifth Avenue, Pittsburgh, PA 15213, USA
| |
Collapse
|
15
|
Linard B, Ebersberger I, McGlynn SE, Glover N, Mochizuki T, Patricio M, Lecompte O, Nevers Y, Thomas PD, Gabaldón T, Sonnhammer E, Dessimoz C, Uchiyama I. Ten Years of Collaborative Progress in the Quest for Orthologs. Mol Biol Evol 2021; 38:3033-3045. [PMID: 33822172 PMCID: PMC8321534 DOI: 10.1093/molbev/msab098] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 02/07/2021] [Accepted: 04/01/2021] [Indexed: 12/19/2022] Open
Abstract
Accurate determination of the evolutionary relationships between genes is a foundational challenge in biology. Homology-evolutionary relatedness-is in many cases readily determined based on sequence similarity analysis. By contrast, whether or not two genes directly descended from a common ancestor by a speciation event (orthologs) or duplication event (paralogs) is more challenging, yet provides critical information on the history of a gene. Since 2009, this task has been the focus of the Quest for Orthologs (QFO) Consortium. The sixth QFO meeting took place in Okazaki, Japan in conjunction with the 67th National Institute for Basic Biology conference. Here, we report recent advances, applications, and oncoming challenges that were discussed during the conference. Steady progress has been made toward standardization and scalability of new and existing tools. A feature of the conference was the presentation of a panel of accessible tools for phylogenetic profiling and several developments to bring orthology beyond the gene unit-from domains to networks. This meeting brought into light several challenges to come: leveraging orthology computations to get the most of the incoming avalanche of genomic data, integrating orthology from domain to biological network levels, building better gene models, and adapting orthology approaches to the broad evolutionary and genomic diversity recognized in different forms of life and viruses.
Collapse
Affiliation(s)
- Benjamin Linard
- LIRMM, University of Montpellier, CNRS, Montpellier, France.,SPYGEN, Le Bourget-du-Lac, France
| | - Ingo Ebersberger
- Institute of Cell Biology and Neuroscience, Goethe University Frankfurt, Frankfurt, Germany.,Senckenberg Biodiversity and Climate Research Centre (S-BIKF), Frankfurt, Germany.,LOEWE Center for Translational Biodiversity Genomics (TBG), Frankfurt, Germany
| | - Shawn E McGlynn
- Earth-Life Science Institute, Tokyo Institute of Technology, Meguro, Tokyo, Japan.,Blue Marble Space Institute of Science, Seattle, WA, USA
| | - Natasha Glover
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Tomohiro Mochizuki
- Earth-Life Science Institute, Tokyo Institute of Technology, Meguro, Tokyo, Japan
| | - Mateus Patricio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Odile Lecompte
- Department of Computer Science, ICube, UMR 7357, University of Strasbourg, CNRS, Fédération de Médecine Translationnelle de Strasbourg, Strasbourg, France
| | - Yannis Nevers
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Paul D Thomas
- Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Toni Gabaldón
- Barcelona Supercomputing Centre (BCS-CNS), Jordi Girona, Barcelona, Spain.,Institute for Research in Biomedicine (IRB), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Erik Sonnhammer
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden
| | - Christophe Dessimoz
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Department of Computer Science, University College London, London, United Kingdom.,Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Ikuo Uchiyama
- Department of Theoretical Biology, National Institute for Basic Biology, National Institutes of Natural Sciences, Okazaki, Aichi, Japan
| | | |
Collapse
|
16
|
Ou J, Liu H, Nirala NK, Stukalov A, Acharya U, Green MR, Zhu LJ. dagLogo: An R/Bioconductor package for identifying and visualizing differential amino acid group usage in proteomics data. PLoS One 2020; 15:e0242030. [PMID: 33156866 PMCID: PMC7647101 DOI: 10.1371/journal.pone.0242030] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 10/23/2020] [Indexed: 11/18/2022] Open
Abstract
Sequence logos have been widely used as graphical representations of conserved nucleic acid and protein motifs. Due to the complexity of the amino acid (AA) alphabet, rich post-translational modification, and diverse subcellular localization of proteins, few versatile tools are available for effective identification and visualization of protein motifs. In addition, various reduced AA alphabets based on physicochemical, structural, or functional properties have been valuable in the study of protein alignment, folding, structure prediction, and evolution. However, there is lack of tools for applying reduced AA alphabets to the identification and visualization of statistically significant motifs. To fill this gap, we developed an R/Bioconductor package dagLogo, which has several advantages over existing tools. First, dagLogo allows various formats for input sets and provides comprehensive options to build optimal background models. It implements different reduced AA alphabets to group AAs of similar properties. Furthermore, dagLogo provides statistical and visual solutions for differential AA (or AA group) usage analysis of both large and small data sets. Case studies showed that dagLogo can better identify and visualize conserved protein sequence patterns from different types of inputs and can potentially reveal the biological patterns that could be missed by other logo generators.
Collapse
Affiliation(s)
- Jianhong Ou
- Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
- Regeneration NEXT, Duke University School of Medicine, Duke University, Durham, North Carolina, United States of America
| | - Haibo Liu
- Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
| | - Niraj K. Nirala
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
| | - Alexey Stukalov
- Institute of Virology, Technical University of Munich, Munich, Germany
| | - Usha Acharya
- Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
| | - Michael R. Green
- Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
| | - Lihua Julie Zhu
- Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America
- * E-mail:
| |
Collapse
|
17
|
Foley S, Saranathan V, Piel WH. The evolution of coloration and opsins in tarantulas. Proc Biol Sci 2020; 287:20201688. [PMID: 32962546 DOI: 10.1098/rspb.2020.1688] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Tarantulas paradoxically exhibit a diverse palette of vivid coloration despite their crepuscular to nocturnal habits. The evolutionary origin and maintenance of these colours remains mysterious. In this study, we reconstructed the ancestral states of both blue and green coloration in tarantula setae, and tested how these colours correlate with presence of stridulation, urtication and arboreality. Green coloration has probably evolved at least eight times, and blue coloration is probably an ancestral condition that appears to be lost more frequently than gained. While our results indicate that neither colour correlates with the presence of stridulation or urtication, the evolution of green coloration appears to depend upon the presence of arboreality, suggesting that it ptobably originated for and functions in crypsis through substrate matching among leaves. We also constructed a network of opsin homologues across tarantula transcriptomes. Despite their crepuscular tendencies, tarantulas express a considerable diversity of opsin genes-a finding that contradicts current consensus that tarantulas have poor colour vision on the basis of low opsin diversity. Overall, our findings raise the possibility that blue coloration could have ultimately evolved via sexual selection and perhaps proximately be used in mate choice or predation avoidance due to possible sex differences in mate-searching.
Collapse
Affiliation(s)
- Saoirse Foley
- Department of Biological Sciences, National University of Singapore, Singapore 117543, Republic of Singapore.,Division of Science, Yale-NUS College, 10 College Avenue West, Singapore 138609, Republic of Singapore
| | - Vinodkumar Saranathan
- Department of Biological Sciences, National University of Singapore, Singapore 117543, Republic of Singapore.,Division of Science, Yale-NUS College, 10 College Avenue West, Singapore 138609, Republic of Singapore.,Lee Kong Chian Natural History Museum, National University of Singapore, Singapore 117377, Republic of Singapore.,NUS Nanoscience and Nanotechnology Initiative (NUSNNI-NanoCore), National University of Singapore, Singapore 117581, Republic of Singapore
| | - William H Piel
- Department of Biological Sciences, National University of Singapore, Singapore 117543, Republic of Singapore.,Division of Science, Yale-NUS College, 10 College Avenue West, Singapore 138609, Republic of Singapore.,Lee Kong Chian Natural History Museum, National University of Singapore, Singapore 117377, Republic of Singapore
| |
Collapse
|
18
|
Deutekom ES, Snel B, van Dam TJP. Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes. Brief Bioinform 2020; 22:5906198. [PMID: 32935832 PMCID: PMC8138875 DOI: 10.1093/bib/bbaa206] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 08/10/2020] [Accepted: 08/11/2020] [Indexed: 12/26/2022] Open
Abstract
Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets or expanding the analyses to larger scales. Automated orthology inference should allow such large-scale analyses, but substantial differences between orthologous groups generated by different approaches are observed. We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regard to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the last eukaryotic common ancestor’s gene content, pervasiveness of gene loss and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other. We find that most orthology methods reconstruct a large last eukaryotic common ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time, derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large-scale evaluation, the obtained orthologous groups differ vastly from one another. Availability and implementation The data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies.
Collapse
Affiliation(s)
| | - Berend Snel
- Corresponding author: Berend Snel, Padualaan 8, 358CH Utrecht, The Netherlands. Tel.: +31(0)30 253 8102; E-mail:
| | | |
Collapse
|
19
|
Massive haplotypes underlie ecotypic differentiation in sunflowers. Nature 2020; 584:602-607. [PMID: 32641831 DOI: 10.1038/s41586-020-2467-6] [Citation(s) in RCA: 177] [Impact Index Per Article: 44.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Accepted: 04/16/2020] [Indexed: 12/22/2022]
Abstract
Species often include multiple ecotypes that are adapted to different environments1. However, it is unclear how ecotypes arise and how their distinctive combinations of adaptive alleles are maintained despite hybridization with non-adapted populations2-4. Here, by resequencing 1,506 wild sunflowers from 3 species (Helianthus annuus, Helianthus petiolaris and Helianthus argophyllus), we identify 37 large (1-100 Mbp in size), non-recombining haplotype blocks that are associated with numerous ecologically relevant traits, as well as soil and climate characteristics. Limited recombination in these haplotype blocks keeps adaptive alleles together, and these regions differentiate sunflower ecotypes. For example, haplotype blocks control a 77-day difference in flowering between ecotypes of the silverleaf sunflower H. argophyllus (probably through deletion of a homologue of FLOWERING LOCUS T (FT)), and are associated with seed size, flowering time and soil fertility in dune-adapted sunflowers. These haplotypes are highly divergent, frequently associated with structural variants and often appear to represent introgressions from other-possibly now-extinct-congeners. These results highlight a pervasive role of structural variation in ecotypic adaptation.
Collapse
|
20
|
Abstract
MOTIVATION An important task in comparative genomics is to detect functional units by analyzing gene-context patterns. Colinear syntenic blocks (CSBs) are groups of genes that are consistently encoded in the same neighborhood and in the same order across a wide range of taxa. Such CSBs are likely essential for the regulation of gene expression in prokaryotes. Recent results indicate that colinearity can be conserved across multiple operons, thus motivating the discovery of multi-operon CSBs. This computational task raises scalability challenges in large datasets. RESULTS We propose an efficient algorithm for the discovery of cross-strand multi-operon CSBs in large genomic datasets. The proposed algorithm uses match-point arithmetic, which is scalable for large datasets of microbial genomes in terms of running time and space requirements. The algorithm is implemented and incorporated into a tool with a graphical user interface, called CSBFinder-S. We applied CSBFinder-S to data mine 1485 prokaryotic genomes and analyzed the identified cross-strand CSBs. Our results indicate that most of the syntenic blocks are exclusively colinear. Additional results indicate that transcriptional regulation by overlapping transcriptional genes is abundant in bacteria. We demonstrate the utility of CSBFinder-S to identify common function of the gene-pair PulEF in multiple contexts, including Type 2 Secretion System, Type 4 Pilus System and DNA uptake machinery. AVAILABILITY AND IMPLEMENTATION CSBFinder-S software and code are publicly available at https://github.com/dinasv/CSBFinder. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Dina Svetlitsky
- Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Tal Dagan
- Institute of Microbiology, Kiel University, Kiel 24118, Germany
| | - Michal Ziv-Ukelson
- Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| |
Collapse
|
21
|
Hu X, Friedberg I. SwiftOrtho: A fast, memory-efficient, multiple genome orthology classifier. Gigascience 2019; 8:giz118. [PMID: 31648300 PMCID: PMC6812468 DOI: 10.1093/gigascience/giz118] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 06/07/2019] [Accepted: 09/05/2019] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Gene homology type classification is required for many types of genome analyses, including comparative genomics, phylogenetics, and protein function annotation. Consequently, a large variety of tools have been developed to perform homology classification across genomes of different species. However, when applied to large genomic data sets, these tools require high memory and CPU usage, typically available only in computational clusters. FINDINGS Here we present a new graph-based orthology analysis tool, SwiftOrtho, which is optimized for speed and memory usage when applied to large-scale data. SwiftOrtho uses long k-mers to speed up homology search, while using a reduced amino acid alphabet and spaced seeds to compensate for the loss of sensitivity due to long k-mers. In addition, it uses an affinity propagation algorithm to reduce the memory usage when clustering large-scale orthology relationships into orthologous groups. In our tests, SwiftOrtho was the only tool that completed orthology analysis of proteins from 1,760 bacterial genomes on a computer with only 4 GB RAM. Using various standard orthology data sets, we also show that SwiftOrtho has a high accuracy. CONCLUSIONS SwiftOrtho enables the accurate comparative genomic analyses of thousands of genomes using low-memory computers. SwiftOrtho is available at https://github.com/Rinoahu/SwiftOrtho.
Collapse
Affiliation(s)
- Xiao Hu
- Department of Veterinary Microbiology and Preventive Medicine, 2118 Veterinary Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA, 50011, USA
| | - Iddo Friedberg
- Department of Veterinary Microbiology and Preventive Medicine, 2118 Veterinary Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA, 50011, USA
| |
Collapse
|