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Bernatchez L, Ferchaud AL, Berger CS, Venney CJ, Xuereb A. Genomics for monitoring and understanding species responses to global climate change. Nat Rev Genet 2024; 25:165-183. [PMID: 37863940 DOI: 10.1038/s41576-023-00657-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/29/2023] [Indexed: 10/22/2023]
Abstract
All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.
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Affiliation(s)
- Louis Bernatchez
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Anne-Laure Ferchaud
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada.
- Parks Canada, Office of the Chief Ecosystem Scientist, Protected Areas Establishment, Quebec City, Quebec, Canada.
| | - Chloé Suzanne Berger
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Clare J Venney
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
| | - Amanda Xuereb
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, Quebec, Canada
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Xing W, Gai X, Xue L, Chen G. Evaluating the role of rhizosphere microbial home-field advantage in Betula luminifera adaptation to antimony mining areas. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169009. [PMID: 38040368 DOI: 10.1016/j.scitotenv.2023.169009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 11/04/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023]
Abstract
It has been established that the coevolution of plants and the rhizosphere microbiome in response to abiotic stress can result in the recruitment of specific functional microbiomes. However, the potential of inoculated rhizosphere microbiomes to enhance plant fitness and the inheritance of adaptive traits in subsequent generations remains unclear. In this study, cross-inoculation trials were conducted using seeds, rhizosphere microbiome, and in situ soil collected from areas of Betula luminifera grown in both antimony mining and control sites. Compared to the control site, plants originating from mining areas exhibited stronger adaptive traits, specifically manifested as significant increases in hundred-seed weight, specific surface area, and germination rate, as well as markedly enhanced seedling survival rate and biomass. Inoculation with mining microbiomes could enhance the fitness of plants in mining sites through a "home-field advantage" while also improving the fitness of plants originating from control sites. During the initial phase of seedling development, bacteria play a crucial role in promoting growth, primarily due to their mechanisms of metal resistance and nutrient cycling. This study provided evidence that the outcomes of long-term coevolution between plants and the rhizosphere microbiome in mining areas can be passed on to future generations. Moreover, it has been demonstrated that transgenerational inheritance and rhizosphere microbiome inoculation are important factors in improving the adaptability of plants in mining areas. The findings have important implications for vegetation restoration and ecological environment improvement in mining areas.
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Affiliation(s)
- Wenli Xing
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China; Nanjing Forestry University, Nanjing 210037, China
| | - Xu Gai
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
| | - Liang Xue
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
| | - Guangcai Chen
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China.
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Wang LL, Li Y, Zheng SS, Kozlowski G, Xu J, Song YG. Complete Chloroplast Genomes of Four Oaks from the Section Cyclobalanopsis Improve the Phylogenetic Analysis and Understanding of Evolutionary Processes in the Genus Quercus. Genes (Basel) 2024; 15:230. [PMID: 38397219 PMCID: PMC10888318 DOI: 10.3390/genes15020230] [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: 01/05/2024] [Revised: 02/06/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
Quercus is a valuable genus ecologically, economically, and culturally. They are keystone species in many ecosystems. Species delimitation and phylogenetic studies of this genus are difficult owing to frequent hybridization. With an increasing number of genetic resources, we will gain a deeper understanding of this genus. In the present study, we collected four Quercus section Cyclobalanopsis species (Q. poilanei, Q. helferiana, Q. camusiae, and Q. semiserrata) distributed in Southeast Asia and sequenced their complete genomes. Following analysis, we compared the results with those of other species in the genus Quercus. These four chloroplast genomes ranged from 160,784 bp (Q. poilanei) to 161,632 bp (Q. camusiae) in length, with an overall guanine and cytosine (GC) content of 36.9%. Their chloroplast genomic organization and order, as well as their GC content, were similar to those of other Quercus species. We identified seven regions with relatively high variability (rps16, ndhk, accD, ycf1, psbZ-trnG-GCC, rbcL-accD, and rpl32-trnL-UAG) which could potentially serve as plastid markers for further taxonomic and phylogenetic studies within Quercus. Our phylogenetic tree supported the idea that the genus Quercus forms two well-differentiated lineages (corresponding to the subgenera Quercus and Cerris). Of the three sections in the subgenus Cerris, the section Ilex was split into two clusters, each nested in the other two sections. Moreover, Q. camusiae and Q. semiserrata detected in this study diverged first in the section Cyclobalanopsis and mixed with Q. engleriana in the section Ilex. In particular, 11 protein coding genes (atpF, ndhA, ndhD, ndhF, ndhK, petB, petD, rbcL, rpl22, ycf1, and ycf3) were subjected to positive selection pressure. Overall, this study enriches the chloroplast genome resources of Quercus, which will facilitate further analyses of phylogenetic relationships in this ecologically important tree genus.
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Affiliation(s)
- Ling-Ling Wang
- School of Ecological Technology and Engineering, Shanghai Institute of Technology, Shanghai 201418, China;
- Eastern China Conservation Centre for Wild Endangered Plant Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; (Y.L.); (S.-S.Z.); (G.K.)
| | - Yu Li
- Eastern China Conservation Centre for Wild Endangered Plant Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; (Y.L.); (S.-S.Z.); (G.K.)
| | - Si-Si Zheng
- Eastern China Conservation Centre for Wild Endangered Plant Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; (Y.L.); (S.-S.Z.); (G.K.)
| | - Gregor Kozlowski
- Eastern China Conservation Centre for Wild Endangered Plant Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; (Y.L.); (S.-S.Z.); (G.K.)
- Department of Biology and Botanic Garden, University of Fribourg, 1700 Fribourg, Switzerland
- Natural History Museum Fribourg, 1700 Fribourg, Switzerland
| | - Jin Xu
- School of Ecological Technology and Engineering, Shanghai Institute of Technology, Shanghai 201418, China;
| | - Yi-Gang Song
- Eastern China Conservation Centre for Wild Endangered Plant Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China; (Y.L.); (S.-S.Z.); (G.K.)
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Decaestecker E, Van de Moortel B, Mukherjee S, Gurung A, Stoks R, De Meester L. Hierarchical eco-evo dynamics mediated by the gut microbiome. Trends Ecol Evol 2024; 39:165-174. [PMID: 37863775 DOI: 10.1016/j.tree.2023.09.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 09/16/2023] [Accepted: 09/21/2023] [Indexed: 10/22/2023]
Abstract
The concept of eco-evolutionary (eco-evo) dynamics, stating that ecological and evolutionary processes occur at similar time scales and influence each other, has contributed to our understanding of responses of populations, communities, and ecosystems to environmental change. Phenotypes, central to these eco-evo processes, can be strongly impacted by the gut microbiome. The gut microbiome shapes eco-evo dynamics in the host community through its effects on the host phenotype. Complex eco-evo feedback loops between the gut microbiome and the host communities might thus be common. Bottom-up dynamics occur when eco-evo interactions shaping the gut microbiome affect host phenotypes with consequences at population, community, and ecosystem levels. Top-down dynamics occur when eco-evo dynamics shaping the host community structure the gut microbiome.
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Affiliation(s)
- Ellen Decaestecker
- Laboratory of Aquatic Biology, Interdisciplinary Research Facility Life Sciences, KU Leuven, KULAK, Campus Kortrijk, B-8500 Kortrijk, Belgium.
| | - Broos Van de Moortel
- Laboratory of Aquatic Biology, Interdisciplinary Research Facility Life Sciences, KU Leuven, KULAK, Campus Kortrijk, B-8500 Kortrijk, Belgium
| | - Shinjini Mukherjee
- Laboratory of Aquatic Ecology, Evolution, and Conservation, KU Leuven, B-3000 Leuven, Belgium; Laboratory of Reproductive Genomics, KU Leuven, B-3000 Leuven, Belgium
| | - Aditi Gurung
- Laboratory of Aquatic Ecology, Evolution, and Conservation, KU Leuven, B-3000 Leuven, Belgium
| | - Robby Stoks
- Laboratory of Evolutionary Stress Ecology and Ecotoxicology, KU Leuven, B-3000 Leuven, Belgium
| | - Luc De Meester
- Laboratory of Aquatic Ecology, Evolution, and Conservation, KU Leuven, B-3000 Leuven, Belgium; Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), D-12587 Berlin, Germany; Institute of Biology, Freie Universität Berlin, D-14195 Berlin, Germany
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Govaert L, Hendry AP, Fattahi F, Möst M. Quantifying interspecific and intraspecific diversity effects on ecosystem functioning. Ecology 2024; 105:e4199. [PMID: 37901985 DOI: 10.1002/ecy.4199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/21/2023] [Accepted: 08/25/2023] [Indexed: 10/31/2023]
Abstract
Rapid environmental changes result in massive biodiversity loss, with detrimental consequences for the functioning of ecosystems. Recent studies suggest that intraspecific diversity can contribute to ecosystem functioning to an extent comparable to contributions of interspecific diversity. Knowledge on the relative importance of these two sources of biodiversity is essential for predicting ecosystem consequences of biodiversity loss and will aid in the prioritization of conservation targets and implementation of management measures. However, our quantitative insights into how interspecific and intraspecific biodiversity loss affects ecosystem functioning and how the effects of these two sources of biodiversity loss on ecosystem functioning can be compared are still very limited. To facilitate such quantitative insights, we extend the interspecific Price partitioning method originally introduced by J. Fox in 2006, previously used to quantify species loss and gain effects on ecosystem functioning, to also account for the effects of intraspecific diversity loss and gain on ecosystem function. Using this extended version can yield the quantitative information required for answering research questions addressing correlations between interspecific and intraspecific diversity effects on ecosystem functioning, identifying interspecific and intraspecific groups with large effects, and assessing whether intraspecific diversity can compensate for losses in interspecific diversity. Applying this method to carefully designed experiments will provide additional insights into how biodiversity loss at different ecological levels contributes to and changes ecosystem functioning.
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Affiliation(s)
- Lynn Govaert
- Department of Evolutionary and Integrative Ecology, Leibniz Institute für Gewässerökologie und Binnenfischerei (IGB), Berlin, Germany
| | - Andrew P Hendry
- Redpath Museum and Department of Biology, McGill University, Montreal, Quebec, Canada
| | | | - Markus Möst
- Department of Ecology, Universität Innsbruck, Innsbruck, Austria
- Research Department of Limnology, Universität Innsbruck, Mondsee, Austria
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Abdelwahab O, Belzile F, Torkamaneh D. Performance analysis of conventional and AI-based variant callers using short and long reads. BMC Bioinformatics 2023; 24:472. [PMID: 38097928 PMCID: PMC10720095 DOI: 10.1186/s12859-023-05596-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/04/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND The accurate detection of variants is essential for genomics-based studies. Currently, there are various tools designed to detect genomic variants, however, it has always been a challenge to decide which tool to use, especially when various major genome projects have chosen to use different tools. Thus far, most of the existing tools were mainly developed to work on short-read data (i.e., Illumina); however, other sequencing technologies (e.g. PacBio, and Oxford Nanopore) have recently shown that they can also be used for variant calling. In addition, with the emergence of artificial intelligence (AI)-based variant calling tools, there is a pressing need to compare these tools in terms of efficiency, accuracy, computational power, and ease of use. RESULTS In this study, we evaluated five of the most widely used conventional and AI-based variant calling tools (BCFTools, GATK4, Platypus, DNAscope, and DeepVariant) in terms of accuracy and computational cost using both short-read and long-read data derived from three different sequencing technologies (Illumina, PacBio HiFi, and ONT) for the same set of samples from the Genome In A Bottle project. The analysis showed that AI-based variant calling tools supersede conventional ones for calling SNVs and INDELs using both long and short reads in most aspects. In addition, we demonstrate the advantages and drawbacks of each tool while ranking them in each aspect of these comparisons. CONCLUSION This study provides best practices for variant calling using AI-based and conventional variant callers with different types of sequencing data.
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Affiliation(s)
- Omar Abdelwahab
- Département de Phytologie, Université Laval, Québec, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Canada
- Centre de recherche et d'innovation sur les végétaux (CRIV), Université Laval, Québec, Canada
- Institut intelligence et données (IID), Université Laval, Québec, Canada
| | - François Belzile
- Département de Phytologie, Université Laval, Québec, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Canada
- Centre de recherche et d'innovation sur les végétaux (CRIV), Université Laval, Québec, Canada
| | - Davoud Torkamaneh
- Département de Phytologie, Université Laval, Québec, Canada.
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec, Canada.
- Centre de recherche et d'innovation sur les végétaux (CRIV), Université Laval, Québec, Canada.
- Institut intelligence et données (IID), Université Laval, Québec, Canada.
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Jia P, Dong L, Yang X, Wang B, Bush SJ, Wang T, Lin J, Wang S, Zhao X, Xu T, Che Y, Dang N, Ren L, Zhang Y, Wang X, Liang F, Wang Y, Ruan J, Xia H, Zheng Y, Shi L, Lv Y, Wang J, Ye K. Haplotype-resolved assemblies and variant benchmark of a Chinese Quartet. Genome Biol 2023; 24:277. [PMID: 38049885 PMCID: PMC10694985 DOI: 10.1186/s13059-023-03116-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 11/21/2023] [Indexed: 12/06/2023] Open
Abstract
BACKGROUND Recent state-of-the-art sequencing technologies enable the investigation of challenging regions in the human genome and expand the scope of variant benchmarking datasets. Herein, we sequence a Chinese Quartet, comprising two monozygotic twin daughters and their biological parents, using four short and long sequencing platforms (Illumina, BGI, PacBio, and Oxford Nanopore Technology). RESULTS The long reads from the monozygotic twin daughters are phased into paternal and maternal haplotypes using the parent-child genetic map and for each haplotype. We also use long reads to generate haplotype-resolved whole-genome assemblies with completeness and continuity exceeding that of GRCh38. Using this Quartet, we comprehensively catalogue the human variant landscape, generating a dataset of 3,962,453 SNVs, 886,648 indels (< 50 bp), 9726 large deletions (≥ 50 bp), 15,600 large insertions (≥ 50 bp), 40 inversions, 31 complex structural variants, and 68 de novo mutations which are shared between the monozygotic twin daughters. Variants underrepresented in previous benchmarks owing to their complexity-including those located at long repeat regions, complex structural variants, and de novo mutations-are systematically examined in this study. CONCLUSIONS In summary, this study provides high-quality haplotype-resolved assemblies and a comprehensive set of benchmarking resources for two Chinese monozygotic twin samples which, relative to existing benchmarks, offers expanded genomic coverage and insight into complex variant categories.
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Affiliation(s)
- Peng Jia
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, Center for Mathematical Medical, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Lianhua Dong
- National Institute of Metrology, Beijing, 100029, China
| | - Xiaofei Yang
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China
| | - Bo Wang
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Stephen J Bush
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Tingjie Wang
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, Center for Mathematical Medical, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Jiadong Lin
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Songbo Wang
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Xixi Zhao
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, Center for Mathematical Medical, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Tun Xu
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Yizhuo Che
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Ningxin Dang
- Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China
| | - Luyao Ren
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Yujing Zhang
- National Institute of Metrology, Beijing, 100029, China
| | - Xia Wang
- National Institute of Metrology, Beijing, 100029, China
| | - Fan Liang
- GrandOmics Biosciences, Beijing, 100089, China
| | - Yang Wang
- GrandOmics Biosciences, Beijing, 100089, China
| | - Jue Ruan
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Han Xia
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Yuanting Zheng
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Leming Shi
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences and Shanghai Cancer Center, Fudan University, Shanghai, 200438, China
| | - Yi Lv
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, Center for Mathematical Medical, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
| | - Jing Wang
- National Institute of Metrology, Beijing, 100029, China.
| | - Kai Ye
- National Local Joint Engineering Research Center for Precision Surgery & Regenerative Medicine, Center for Mathematical Medical, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
- Genome Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
- Faculty of Science, Leiden University, Leiden, 2311EZ, The Netherlands.
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Prihandini PW, Tribudi YA, Hariyono DNH, Sari APZNL, Praharani L, Handiwirawan E, Tiesnamurti B, Romjali E, Matitaputty PR, Wiyono A. Biodiversity of Indonesian indigenous buffalo: First review of the status, challenges, and development opportunities. Vet World 2023; 16:2217-2229. [PMID: 38152276 PMCID: PMC10750752 DOI: 10.14202/vetworld.2023.2217-2229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 10/03/2023] [Indexed: 12/29/2023] Open
Abstract
In Indonesia, the buffalo is important for small and marginal farmers' livelihood and economic development as a source of food, working animal, and tourist attraction. Therefore, an in-depth study is needed to examine challenges and opportunities for buffalo development in Indonesia. In Indonesia, the buffalo is divided into two types: swamp buffalo and river buffalo. The buffalo population in Indonesia has declined significantly. A decrease of approximately 39.35% was recorded from 2022 to 2017. The decline occurred due to low reproduction rate and suboptimal rearing management systems. There are three buffalo-rearing systems: Intensive, semi-intensive, and extensive. The productivity of buffalo is diverse and closely related to the characteristics of the regional agroecosystem, consistent with existing natural resources and rearing management systems. The diversity of buffalo productivity provides a good opportunity to improve productivity. Improvement of buffalo genetics is urgently needed, by improving mating management, etc., especially to reduce potential inbreeding. In recent years, genetic and molecular research on Indonesian buffalo has made progress, including use of molecular markers, such as microsatellites and single-nucleotide polymorphisms, to evaluate genetic diversity within and among buffalo populations across Indonesia. In addition, studies are being conducted on the relationship of genotype mutations that contribute to appearance and phenotypic performance (heat stress, reproduction, behavior, coat color, and production attributes) in buffaloes. Identification of genetic diversity in local buffaloes can be improved using various genetic and genomic techniques. These findings will form a basis for the targeted conservation of local buffaloes in Indonesia. This study aimed to collect information on the genetic resources of the local buffalo, particularly its status and production system and provide recommendations for developing buffalo production in Indonesia.
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Affiliation(s)
- Peni Wahyu Prihandini
- Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research and Innovation Agency, Cibinong, Bogor, 16915, Indonesia
| | - Yuli Arif Tribudi
- Department of Animal Science, Faculty of Agriculture, Universitas Tanjungpura, Pontianak, 78121, Indonesia
| | - Dwi Nur Happy Hariyono
- Department of Animal Science, Faculty of Agriculture, Universitas Khairun, Ternate, 97719, Indonesia
| | | | - Lisa Praharani
- Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research and Innovation Agency, Cibinong, Bogor, 16915, Indonesia
| | - Eko Handiwirawan
- Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research and Innovation Agency, Cibinong, Bogor, 16915, Indonesia
| | - Bess Tiesnamurti
- Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research and Innovation Agency, Cibinong, Bogor, 16915, Indonesia
| | - Endang Romjali
- Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research and Innovation Agency, Cibinong, Bogor, 16915, Indonesia
| | - Procula Rudlof Matitaputty
- Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research and Innovation Agency, Cibinong, Bogor, 16915, Indonesia
| | - Agus Wiyono
- Research Center for Veterinary Science, Research Organization for Health, National Research and Innovation Agency, Cibinong, Bogor, 16915, Indonesia
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Abstract
AbstractEvolutionary biologists have thought about the role of genetic variation during adaptation for a very long time-before we understood the organization of the genetic code, the provenance of genetic variation, and how such variation influenced the phenotypes on which natural selection acts. Half a century after the discovery of the structure of DNA and the unraveling of the genetic code, we have a rich understanding of these problems and the means to both delve deeper and widen our perspective across organisms and natural populations. The 2022 Vice Presidential Symposium of the American Society of Naturalists highlighted examples of recent insights into the role of genetic variation in adaptive processes, which are compiled in this special section. The work was conducted in different parts of the world, included theoretical and empirical studies with diverse organisms, and addressed distinct aspects of how genetic variation influences adaptation. In our introductory article to the special section, we discuss some important recent insights about the generation and maintenance of genetic variation, its impacts on phenotype and fitness, its fate in natural populations, and its role in driving adaptation. By placing the special section articles in the broader context of recent developments, we hope that this overview will also serve as a useful introduction to the field.
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10
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Qin X, Ma S, Wu M. Two-level Bayesian interaction analysis for survival data incorporating pathway information. Biometrics 2023; 79:1761-1774. [PMID: 36524727 PMCID: PMC10272285 DOI: 10.1111/biom.13811] [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: 03/08/2022] [Revised: 08/31/2022] [Accepted: 12/06/2022] [Indexed: 12/23/2022]
Abstract
Genetic interactions play an important role in the progression of complex diseases, providing explanation of variations in disease phenotype missed by main genetic effects. Comparatively, there are fewer studies on survival time, given its challenging characteristics such as censoring. In recent biomedical research, two-level analysis of both genes and their involved pathways has received much attention and been demonstrated as more effective than single-level analysis. However, such analysis is usually limited to main effects. Pathways are not isolated, and their interactions have also been suggested to have important contributions to the prognosis of complex diseases. In this paper, we develop a novel two-level Bayesian interaction analysis approach for survival data. This approach is the first to conduct the analysis of lower-level gene-gene interactions and higher-level pathway-pathway interactions simultaneously. Significantly advancing from the existing Bayesian studies based on the Markov Chain Monte Carlo (MCMC) technique, we propose a variational inference framework based on the accelerated failure time model with effective priors to accommodate two-level selection as well as censoring. Its computational efficiency is much desirable for high-dimensional interaction analysis. We examine performance of the proposed approach using extensive simulation. The application to TCGA melanoma and lung adenocarcinoma data leads to biologically sensible findings with satisfactory prediction accuracy and selection stability.
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Affiliation(s)
- Xing Qin
- School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China
| | - Shuangge Ma
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA
| | - Mengyun Wu
- School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China
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11
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Sanderson S, Bolnick DI, Kinnison MT, O'Dea RE, Gorné LD, Hendry AP, Gotanda KM. Contemporary changes in phenotypic variation, and the potential consequences for eco-evolutionary dynamics. Ecol Lett 2023; 26 Suppl 1:S127-S139. [PMID: 37840026 DOI: 10.1111/ele.14186] [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: 11/08/2022] [Revised: 01/30/2023] [Accepted: 02/01/2023] [Indexed: 10/17/2023]
Abstract
Most studies assessing rates of phenotypic change focus on population mean trait values, whereas a largely overlooked additional component is changes in population trait variation. Theoretically, eco-evolutionary dynamics mediated by such changes in trait variation could be as important as those mediated by changes in trait means. To date, however, no study has comprehensively summarised how phenotypic variation is changing in contemporary populations. Here, we explore four questions using a large database: How do changes in trait variances compare to changes in trait means? Do different human disturbances have different effects on trait variance? Do different trait types have different effects on changes in trait variance? Do studies that established a genetic basis for trait change show different patterns from those that did not? We find that changes in variation are typically small; yet we also see some very large changes associated with particular disturbances or trait types. We close by interpreting and discussing the implications of our findings in the context of eco-evolutionary studies.
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Affiliation(s)
- Sarah Sanderson
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
| | - Daniel I Bolnick
- Department of Ecology & Evolutionary Biology, University of Connecticut, Storrs, Connecticut, USA
| | - Michael T Kinnison
- School of Biology and Ecology and Maine Center for Genetics in the Environment, University of Maine, Orono, Maine, USA
| | | | - Lucas D Gorné
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
- Department of Biological Sciences, Brock University, St. Catharine's, Ontario, Canada
- Département de Biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada
- Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Andrew P Hendry
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
| | - Kiyoko M Gotanda
- Department of Biological Sciences, Brock University, St. Catharine's, Ontario, Canada
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12
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French CM, Bertola LD, Carnaval AC, Economo EP, Kass JM, Lohman DJ, Marske KA, Meier R, Overcast I, Rominger AJ, Staniczenko PPA, Hickerson MJ. Global determinants of insect mitochondrial genetic diversity. Nat Commun 2023; 14:5276. [PMID: 37644003 PMCID: PMC10465557 DOI: 10.1038/s41467-023-40936-0] [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: 01/20/2022] [Accepted: 08/15/2023] [Indexed: 08/31/2023] Open
Abstract
Understanding global patterns of genetic diversity is essential for describing, monitoring, and preserving life on Earth. To date, efforts to map macrogenetic patterns have been restricted to vertebrates, which comprise only a small fraction of Earth's biodiversity. Here, we construct a global map of predicted insect mitochondrial genetic diversity from cytochrome c oxidase subunit 1 sequences, derived from open data. We calculate the mitochondrial genetic diversity mean and genetic diversity evenness of insect assemblages across the globe, identify their environmental correlates, and make predictions of mitochondrial genetic diversity levels in unsampled areas based on environmental data. Using a large single-locus genetic dataset of over 2 million globally distributed and georeferenced mtDNA sequences, we find that mitochondrial genetic diversity evenness follows a quadratic latitudinal gradient peaking in the subtropics. Both mitochondrial genetic diversity mean and evenness positively correlate with seasonally hot temperatures, as well as climate stability since the last glacial maximum. Our models explain 27.9% and 24.0% of the observed variation in mitochondrial genetic diversity mean and evenness in insects, respectively, making an important step towards understanding global biodiversity patterns in the most diverse animal taxon.
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Affiliation(s)
- Connor M French
- Biology Department, City College of New York, New York, NY, USA.
- Biology Ph.D. Program, Graduate Center, City University of New York, New York, NY, USA.
| | - Laura D Bertola
- Biology Department, City College of New York, New York, NY, USA
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, N 2200, Denmark
| | - Ana C Carnaval
- Biology Department, City College of New York, New York, NY, USA
- Biology Ph.D. Program, Graduate Center, City University of New York, New York, NY, USA
| | - Evan P Economo
- Biodiversity and Biocomplexity Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa, Japan
| | - Jamie M Kass
- Biodiversity and Biocomplexity Unit, Okinawa Institute of Science and Technology Graduate University, Onna, Okinawa, Japan
- Macroecology Laboratory, Graduate School of Life Sciences, Tohoku University, Sendai, Miyagi, Japan
| | - David J Lohman
- Biology Department, City College of New York, New York, NY, USA
- Biology Ph.D. Program, Graduate Center, City University of New York, New York, NY, USA
- Entomology Section, National Museum of Natural History, Manila, Philippines
| | | | - Rudolf Meier
- Institut für Biologie, Humboldt-Universität zu Berlin, Berlin, Germany
- Center for Integrative Biodiversity Discovery, Leibniz Institute for Evolution and Biodiversity Science, Museum für Naturkunde Berlin, Berlin, Germany
| | - Isaac Overcast
- Biology Ph.D. Program, Graduate Center, City University of New York, New York, NY, USA
- Institut de Biologie de l'Ecole Normale Superieure, Paris, France
- Department of Vertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - Andrew J Rominger
- School of Biology and Ecology, University of Maine, Orono, ME, USA
- Maine Center for Genetics in the Environment, University of Maine, Orono, ME, USA
| | | | - Michael J Hickerson
- Biology Department, City College of New York, New York, NY, USA
- Biology Ph.D. Program, Graduate Center, City University of New York, New York, NY, USA
- Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
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13
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Theissinger K, Fernandes C, Formenti G, Bista I, Berg PR, Bleidorn C, Bombarely A, Crottini A, Gallo GR, Godoy JA, Jentoft S, Malukiewicz J, Mouton A, Oomen RA, Paez S, Palsbøll PJ, Pampoulie C, Ruiz-López MJ, Secomandi S, Svardal H, Theofanopoulou C, de Vries J, Waldvogel AM, Zhang G, Jarvis ED, Bálint M, Ciofi C, Waterhouse RM, Mazzoni CJ, Höglund J. How genomics can help biodiversity conservation. Trends Genet 2023:S0168-9525(23)00020-3. [PMID: 36801111 DOI: 10.1016/j.tig.2023.01.005] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 11/08/2022] [Accepted: 01/19/2023] [Indexed: 02/18/2023]
Abstract
The availability of public genomic resources can greatly assist biodiversity assessment, conservation, and restoration efforts by providing evidence for scientifically informed management decisions. Here we survey the main approaches and applications in biodiversity and conservation genomics, considering practical factors, such as cost, time, prerequisite skills, and current shortcomings of applications. Most approaches perform best in combination with reference genomes from the target species or closely related species. We review case studies to illustrate how reference genomes can facilitate biodiversity research and conservation across the tree of life. We conclude that the time is ripe to view reference genomes as fundamental resources and to integrate their use as a best practice in conservation genomics.
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Affiliation(s)
- Kathrin Theissinger
- LOEWE Centre for Translational Biodiversity Genomics, Senckenberg Biodiversity and Climate Research Centre, Georg-Voigt-Str. 14-16, 60325 Frankfurt/Main, Germany
| | - Carlos Fernandes
- CE3C - Centre for Ecology, Evolution and Environmental Changes & CHANGE - Global Change and Sustainability Institute, Departamento de Biologia Animal, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal; Faculdade de Psicologia, Universidade de Lisboa, Alameda da Universidade, 1649-013 Lisboa, Portugal
| | - Giulio Formenti
- The Rockefeller University, 1230 York Ave, New York, NY 10065, USA
| | - Iliana Bista
- Naturalis Biodiversity Center, Darwinweg 2, 2333, CR, Leiden, The Netherlands; Wellcome Sanger Institute, Tree of Life, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
| | - Paul R Berg
- NIVA - Norwegian Institute for Water Research, Økernveien, 94, 0579 Oslo, Norway; Centre for Coastal Research, University of Agder, Gimlemoen 25j, 4630 Kristiansand, Norway; Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, PO BOX 1066 Blinderm, 0316 Oslo, Norway
| | - Christoph Bleidorn
- University of Göttingen, Department of Animal Evolution and Biodiversity, Untere Karspüle, 2, 37073, Göttingen, Germany
| | | | - Angelica Crottini
- CIBIO/InBio, Centro de Investigação em Biodiversidade e Recursos Genéticos, Rua Padre Armando Quintas, 7, 4485-661, Portugal; Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, 4099-002 Porto, Portugal; BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal
| | - Guido R Gallo
- Department of Biosciences, University of Milan, Milan, Italy
| | - José A Godoy
- Estación Biológica de Doñana, CSIC, Calle Americo Vespucio 26, 41092, Sevillle, Spain
| | - Sissel Jentoft
- Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, PO BOX 1066 Blinderm, 0316 Oslo, Norway
| | - Joanna Malukiewicz
- Primate Genetics Laborator, German Primate Center, Kellnerweg 4, 37077, Göttingen, Germany
| | - Alice Mouton
- InBios - Conservation Genetics Lab, University of Liege, Chemin de la Vallée 4, 4000, Liege, Belgium
| | - Rebekah A Oomen
- Centre for Coastal Research, University of Agder, Gimlemoen 25j, 4630 Kristiansand, Norway; Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, PO BOX 1066 Blinderm, 0316 Oslo, Norway
| | - Sadye Paez
- The Rockefeller University, 1230 York Ave, New York, NY 10065, USA
| | - Per J Palsbøll
- Groningen Institute of Evolutionary Life Sciences, University of Groningen, Nijenborgh, 9747, AG, Groningen, The Netherlands; Center for Coastal Studies, 5 Holway Avenue, Provincetown, MA 02657, USA
| | - Christophe Pampoulie
- Marine and Freshwater Research Institute, Fornubúðir, 5,220, Hanafjörður, Iceland
| | - María J Ruiz-López
- Estación Biológica de Doñana, CSIC, Calle Americo Vespucio 26, 41092, Sevillle, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Spain
| | | | - Hannes Svardal
- Department of Biology, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium
| | - Constantina Theofanopoulou
- The Rockefeller University, 1230 York Ave, New York, NY 10065, USA; Hunter College, City University of New York, NY, USA
| | - Jan de Vries
- University of Goettingen, Institute for Microbiology and Genetics, Department of Applied Bioinformatics, Goettingen Center for Molecular Biosciences (GZMB), Campus Institute Data Science (CIDAS), Goldschmidtstr. 1, 37077, Goettingen, Germany
| | - Ann-Marie Waldvogel
- Institute of Zoology, University of Cologne, Zülpicherstrasse 47b, D-50674, Cologne, Germany
| | - Guojie Zhang
- Evolutionary & Organismal Biology Research Center, Zhejiang University School of Medicine, Hangzhou, 310058, China; Villum Center for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Denmark; State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Erich D Jarvis
- The Rockefeller University, 1230 York Ave, New York, NY 10065, USA
| | - Miklós Bálint
- LOEWE Centre for Translational Biodiversity Genomics, Senckenberg Biodiversity and Climate Research Centre, Georg-Voigt-Str. 14-16, 60325 Frankfurt/Main, Germany
| | - Claudio Ciofi
- University of Florence, Department of Biology, Via Madonna del Piano 6, Sesto Fiorentino, (FI) 50019, Italy
| | - Robert M Waterhouse
- University of Lausanne, Department of Ecology and Evolution, Le Biophore, UNIL-Sorge, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Camila J Mazzoni
- Leibniz Institute for Zoo and Wildlife Research (IZW), Alfred-Kowalke-Str 17, 10315 Berlin, Germany; Berlin Center for Genomics in Biodiversity Research (BeGenDiv), Koenigin-Luise-Str 6-8, 14195 Berlin, Germany
| | - Jacob Höglund
- Department of Ecology and Genetics, Uppsala University, Norbyvägen 18D, 75246, Uppsala, Sweden.
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14
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Rahayu SR, Muchlisin ZA, Fadli N, Razi NM, Ramadhaniaty M, Handayani LS, Maulida S, Nur FM, Nurlaili N, Siti-Azizah MN. Morphometric and genetic variations of two dominant species of snappers (Lutjanidae) harvested from the Northern Coast of Aceh waters, Indonesia. ZOOL ANZ 2023. [DOI: 10.1016/j.jcz.2023.01.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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15
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Evaluation of the Ecological Environment Affected by Cry1Ah1 in Poplar. Life (Basel) 2022; 12:life12111830. [DOI: 10.3390/life12111830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/03/2022] [Accepted: 11/07/2022] [Indexed: 11/11/2022] Open
Abstract
Populus is a genus of globally significant plantation trees used widely in industrial and agricultural production. Poplars are easily damaged by Micromelalopha troglodyta and Hyphantria cunea, resulting in decreasing quality. Bt toxin-encoded by the Cry gene has been widely adopted in poplar breeding because of its strong insect resistance. There is still no comprehensive and sufficient information about the effects of Cry1Ah1-modified (CM) poplars on the ecological environment. Here, we sampled the rhizosphere soils of field-grown CM and non-transgenic (NT) poplars and applied 16S rRNA and internal transcribed spacer amplicon Illumina MiSeq sequencing to determine the bacterial community associated with the CM and NT poplars. Based on the high-throughput sequencing of samples, we found that the predominant taxa included Proteobacteria (about 40% of the total bacteria), Acidobacteria (about 20% of the total bacteria), and Actinobacteria (about 20% of the total bacteria) collected from the natural rhizosphere of NT and CM poplars. In addition, studies on the microbial diversity of poplar showed that Cry1Ah1 expression has no significant influence on rhizosphere soil alkaline nitrogen, but significantly affects soil phosphorus, soil microbial biomass nitrogen, and carbon. The results exhibited a similar bacterial community structure between CM varieties affected by the expression of Cry1Ah1 and non-transgenic poplars. In addition, Cry1Ah1 expression revealed no significant influence on the composition of rhizosphere microbiomes. These results broadly reflect the effect of the Bt toxin-encoded by Cry1Ah1 on the ecology and environment and provide a clear path for researchers to continue research in this field in the future.
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16
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Petersen HC, Hansen BW, Knott KE, Banta GT. Species and genetic diversity relationships in benthic macroinvertebrate communities along a salinity gradient. BMC Ecol Evol 2022; 22:125. [PMID: 36324063 PMCID: PMC9632067 DOI: 10.1186/s12862-022-02087-6] [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: 09/24/2021] [Accepted: 10/26/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Species- and genetic diversity can change in parallel, resulting in a species-genetic diversity correlation (SGDC) and raising the question if the same drivers influence both biological levels of diversity. The SGDC can be either positive or negative, depending on whether the species diversity and the genetic diversity of the measured species respond in the same or opposite way to drivers. Using a traditional species diversity approach together with ultra-conserved elements and high throughput sequencing, we evaluated the SGDCs in benthic macrofauna communities in the Baltic Sea, a geologically young brackish water sea characterised by its steep salinity gradient and low species richness. Assessing SGDCs from six focal marine invertebrate species from different taxonomic groups and with differing life histories and ecological functions on both a spatial and temporal scale gives a more comprehensive insight into the community dynamics of this young ecosystem and the extrinsic factors that might drive the SGDCs. RESULTS No significant correlations between species diversity and genetic diversity were found for any of the focal species. However, both negative and positive trends of SGDCs for the individual focal species were observed. When examining the environmental drivers, no common trends between the species were found, even when restricting the analysis to specific taxonomic classes. Additionally, there were no common environmental factors driving the diversity relationships for species sharing the same SGDC trend (positive or negative). Local population dynamics, together with the invasion history of the individual species and their unique adaptation to the distinctive environment of the Baltic Sea, are expected to be of major influence on the outcome of the SGDCs. CONCLUSIONS The present results highlight the importance of assessing SGDCs using multiple species, not just a single indicator species. This emphasises a need to pay attention to the ecology and life history of the focal species. This study also provides insight into the large differences in both patterns and drivers of genetic diversity, which is important when including genetic biodiversity in conservation plans. We conclude that the effects of environmental and biological factors and processes that affects diversity patterns at both the community and genetic levels are likely species dependent, even in an environment such as the Baltic Sea with strong environmental gradients.
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Affiliation(s)
- H. Cecilie Petersen
- grid.11702.350000 0001 0672 1325Department of Science and Environment, Roskilde University, Universitetsvej 1, 4000 Roskilde, Denmark ,grid.9681.60000 0001 1013 7965Department of Biological and Environmental Science, University of Jyväskylä, 40014 Jyväskylä, Finland
| | - Benni W. Hansen
- grid.11702.350000 0001 0672 1325Department of Science and Environment, Roskilde University, Universitetsvej 1, 4000 Roskilde, Denmark
| | - K. Emily Knott
- grid.9681.60000 0001 1013 7965Department of Biological and Environmental Science, University of Jyväskylä, 40014 Jyväskylä, Finland
| | - Gary T. Banta
- grid.10825.3e0000 0001 0728 0170Department of Biology, University of Southern Denmark, 5238 Odense M, Denmark
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17
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Marshall IR, Brauer CJ, Wedderburn SD, Whiterod NS, Hammer MP, Barnes TC, Attard CRM, Möller LM, Beheregaray LB. Longitudinal monitoring of neutral and adaptive genomic diversity in a reintroduction. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2022; 36:e13889. [PMID: 35023224 DOI: 10.1111/cobi.13889] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 12/16/2021] [Accepted: 12/28/2021] [Indexed: 06/14/2023]
Abstract
Restoration programs in the form of ex-situ breeding combined with reintroductions are becoming critical to counteract demographic declines and species losses. Such programs are increasingly using genetic management to improve conservation outcomes. However, the lack of long-term monitoring of genetic indicators following reintroduction prevents assessments of the trajectory and persistence of reintroduced populations. We carried out an extensive monitoring program in the wild for a threatened small-bodied fish (southern pygmy perch, Nannoperca australis) to assess the long-term genomic effects of its captive breeding and reintroduction. The species was rescued prior to its extirpation from the terminal lakes of Australia's Murray-Darling Basin, and then used for genetically informed captive breeding and reintroductions. Subsequent annual or biannual monitoring of abundance, fitness, and occupancy over a period of 11 years, combined with postreintroduction genetic sampling, revealed survival and recruitment of reintroduced fish. Genomic analyses based on data from the original wild rescued, captive born, and reintroduced cohorts revealed low inbreeding and strong maintenance of neutral and candidate adaptive genomic diversity across multiple generations. An increasing trend in the effective population size of the reintroduced population was consistent with field monitoring data in demonstrating successful re-establishment of the species. This provides a rare empirical example that the adaptive potential of a locally extinct population can be maintained during genetically informed ex-situ conservation breeding and reintroduction into the wild. Strategies to improve biodiversity restoration via ex-situ conservation should include genetic-based captive breeding and longitudinal monitoring of standing genomic variation in reintroduced populations.
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Affiliation(s)
- Imogen R Marshall
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Chris J Brauer
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Scotte D Wedderburn
- School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Nick S Whiterod
- Aquasave-Nature Glenelg Trust, Victor Harbor, South Australia, Australia
| | - Michael P Hammer
- Natural Sciences, Museum and Art Gallery of the Northern Territory, Darwin, Northern Territory, Australia
| | - Thomas C Barnes
- New South Wales Department of Primary Industries, Port Stephens Fisheries Institute, Nelson Bay, New South Wales, Australia
- Institute of Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia
| | - Catherine R M Attard
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Luciana M Möller
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
| | - Luciano B Beheregaray
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
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18
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Genomics of Adaptation and Speciation. Genes (Basel) 2022; 13:genes13071187. [PMID: 35885970 PMCID: PMC9321343 DOI: 10.3390/genes13071187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 05/18/2022] [Indexed: 02/01/2023] Open
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19
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Hunt DAGA, DiBattista JD, Hendry AP. Effects of insularity on genetic diversity within and among natural populations. Ecol Evol 2022; 12:e8887. [PMID: 35571757 PMCID: PMC9077629 DOI: 10.1002/ece3.8887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 04/15/2022] [Indexed: 11/27/2022] Open
Abstract
We conducted a quantitative literature review of genetic diversity (GD) within and among populations in relation to categorical population size and isolation (together referred to as “insularity”). Using populations from within the same studies, we were able to control for between‐study variation in methodology, as well as demographic and life histories of focal species. Contrary to typical expectations, insularity had relatively minor effects on GD within and among populations, which points to the more important role of other factors in shaping evolutionary processes. Such effects of insularity were sometimes seen—particularly in study systems where GD was already high overall. That is, insularity influenced GD in a study system when GD was high even in non‐insular populations of the same study system—suggesting an important role for the “scope” of influences on GD. These conclusions were more robust for within population GD versus among population GD, although several biases might underlie this difference. Overall, our findings indicate that population‐level genetic assumptions need to be tested rather than assumed in nature, particularly for topics underlying current conservation management practices.
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Affiliation(s)
- David A. G. A. Hunt
- Redpath Museum and Department of Biology McGill University Montreal Quebec Canada
| | - Joseph D. DiBattista
- Australian Museum Research Institute Australian Museum Sydney New South Wales Australia
| | - Andrew P. Hendry
- Redpath Museum and Department of Biology McGill University Montreal Quebec Canada
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20
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Dalongeville A, Nielsen ES, Teske PR, Heyden S. Comparative phylogeography in a marine biodiversity hotspot provides novel insights into evolutionary processes across the Atlantic‐Indian Ocean transition. DIVERS DISTRIB 2022. [DOI: 10.1111/ddi.13534] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Affiliation(s)
| | - Erica S. Nielsen
- Department of Evolution and Ecology University of California, Davis Davis California USA
| | - Peter R. Teske
- Department of Zoology Centre for Ecological Genomics and Wildlife Conservation University of Johannesburg Auckland Park South Africa
| | - Sophie Heyden
- Department of Botany and Zoology Evolutionary Genomics Group Stellenbosch University Stellenbosch South Africa
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21
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Barbour MA, Kliebenstein DJ, Bascompte J. A keystone gene underlies the persistence of an experimental food web. Science 2022; 376:70-73. [PMID: 35357912 DOI: 10.1126/science.abf2232] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Genes encode information that determines an organism's fitness. Yet we know little about whether genes of one species influence the persistence of interacting species in an ecological community. Here, we experimentally tested the effect of three plant defense genes on the persistence of an insect food web and found that a single allele at a single gene promoted coexistence by increasing plant growth rate, which in turn increased the intrinsic growth rates of species across multiple trophic levels. Our discovery of a "keystone gene" illustrates the need to bridge between biological scales, from genes to ecosystems, to understand community persistence.
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Affiliation(s)
- Matthew A Barbour
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, 8057 Zurich, Switzerland
| | | | - Jordi Bascompte
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, 8057 Zurich, Switzerland
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22
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Buckley SJ, Brauer CJ, Unmack PJ, Hammer MP, Beheregaray LB. Variation in intraspecific demography drives localised concordance but species-wide discordance in response to past climatic change. BMC Ecol Evol 2022; 22:35. [PMID: 35317750 PMCID: PMC8941757 DOI: 10.1186/s12862-022-01990-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 03/11/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Understanding how species biology may facilitate resilience to climate change remains a critical factor in detecting and protecting species at risk of extinction. Many studies have focused on the role of particular ecological traits in driving species responses, but less so on demographic history and levels of standing genetic variation. Additionally, spatial variation in the interaction of demographic and adaptive factors may further complicate prediction of species responses to environmental change. We used environmental and genomic datasets to reconstruct the phylogeographic histories of two ecologically similar and largely co-distributed freshwater fishes, the southern (Nannoperca australis) and Yarra (N. obscura) pygmy perches, to assess the degree of concordance in their responses to Plio-Pleistocene climatic changes. We described contemporary genetic diversity, phylogenetic histories, demographic histories, and historical species distributions across both species, and statistically evaluated the degree of concordance in co-occurring populations. RESULTS Marked differences in contemporary genetic diversity, historical distribution changes and historical migration were observed across the species, with a distinct lack of genetic diversity and historical range expansion suggested for N. obscura. Although several co-occurring populations within a shared climatic refugium demonstrated concordant demographic histories, idiosyncratic population size changes were found at the range edges of the more spatially restricted species. Discordant responses between species were associated with low standing genetic variation in peripheral populations. This might have hindered adaptive potential, as documented in recent demographic declines and population extinctions for the two species. CONCLUSION Our results highlight both the role of spatial scale in the degree of concordance in species responses to climate change, and the importance of standing genetic variation in facilitating range shifts. Even when ecological traits are similar between species, long-term genetic diversity and historical population demography may lead to discordant responses to ongoing and future climate change.
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Affiliation(s)
- Sean James Buckley
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Adelaide, SA, 5001, Australia
| | - Chris J Brauer
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Adelaide, SA, 5001, Australia
| | - Peter J Unmack
- Centre for Applied Water Science, Institute for Applied Ecology, University of Canberra, Canberra, ACT, 2601, Australia
| | - Michael P Hammer
- Natural Sciences, Museum and Art Gallery of the Northern Territory, Darwin, NT, 0801, Australia
| | - Luciano B Beheregaray
- Molecular Ecology Laboratory, College of Science and Engineering, Flinders University, Adelaide, SA, 5001, Australia.
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23
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Little CJ, Rizzuto M, Luhring TM, Monk JD, Nowicki RJ, Paseka RE, Stegen JC, Symons CC, Taub FB, Yen JDL. Movement with meaning: integrating information into meta‐ecology. OIKOS 2022. [DOI: 10.1111/oik.08892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Chelsea J. Little
- Biodiversity Research Centre, Univ. of British Columbia Vancouver BC Canada
- School of Environmental Science, Simon Fraser Univ. Burnaby BC Canada
| | - Matteo Rizzuto
- Dept of Biology, Memorial Univ. of Newfoundland St. John's NL Canada
| | | | - Julia D. Monk
- School of the Environment, Yale Univ. New Haven CT USA
| | - Robert J. Nowicki
- Elizabeth Moore International Center for Coral Reef Research and Restoration, Mote Marine Laboratory Summerland Key FL USA
| | - Rachel E. Paseka
- Dept of Ecology, Evolution and Behavior, Univ. of Minnesota Saint Paul MN USA
| | | | - Celia C. Symons
- Dept of Ecology and Evolutionary Biology, Univ. of California Irvine CA USA
| | - Frieda B. Taub
- School of Aquatic and Fishery Sciences, Univ. of Washington Seattle WA USA
| | - Jian D. L. Yen
- School of BioSciences, Univ. of Melbourne, Melbourne, Australia, and Arthur Rylah Inst. for Environmental Reserach Heidelberg Victoria Australia
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24
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Lee SR, Choi TY, Jung SY. Genetic Diversity on a Rare Terrestrial Orchid, Habenaria linearifolia in South Korea: Implications for Conservation Offered by Genome-Wide Single Nucleotide Polymorphisms. FRONTIERS IN PLANT SCIENCE 2022; 13:772621. [PMID: 35283866 PMCID: PMC8907889 DOI: 10.3389/fpls.2022.772621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 01/25/2022] [Indexed: 06/14/2023]
Abstract
Monitoring intraspecific diversity offers invaluable insights on conservation practices as the variation is the product of species evolution. Accordingly, the role of population genetic diversity has drawn great attention over the last century responding to the biodiversity loss induced by a series of anthropogenic changes. Orchids are one of the most diverse, yet ironically most rapidly disappearing plant groups due to the specialized habitat preferences. Thus, population-level genetic diversity studies may offer a powerful tool for orchid conservation programs. Using the 3 restriction site-associated DNA (3RAD) approach, 2,734 genome-wide single nucleotide polymorphisms (SNPs) were isolated. With the 2,734 SNPs, we investigated genetic diversity and population structure on 72 individuals of Habenaria linearifolia and Habenaria cruciformis in South Korea. Overall, the genetic diversity was well maintained in South Korean Habenaria, but high F ST values were estimated suggesting large population diversification with limited gene flow. Bayesian assignment analysis revealed a morphologically cryptic diversity pattern in Jeju Island populations, which might serve as an evolutionarily significant unit.
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Affiliation(s)
- Soo-Rang Lee
- Department of Biology Education, College of Education, Chosun University, Gwangju, South Korea
| | - Tae-Young Choi
- Department of Biology Education, College of Education, Chosun University, Gwangju, South Korea
| | - Su-Young Jung
- Division of Forest Biodiversity and Herbarium, Korea National Arboretum, Pocheon, South Korea
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25
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Stephan T, Burgess SM, Cheng H, Danko CG, Gill CA, Jarvis ED, Koepfli KP, Koltes JE, Lyons E, Ronald P, Ryder OA, Schriml LM, Soltis P, VandeWoude S, Zhou H, Ostrander EA, Karlsson EK. Darwinian genomics and diversity in the tree of life. Proc Natl Acad Sci U S A 2022; 119:e2115644119. [PMID: 35042807 PMCID: PMC8795533 DOI: 10.1073/pnas.2115644119] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Genomics encompasses the entire tree of life, both extinct and extant, and the evolutionary processes that shape this diversity. To date, genomic research has focused on humans, a small number of agricultural species, and established laboratory models. Fewer than 18,000 of ∼2,000,000 eukaryotic species (<1%) have a representative genome sequence in GenBank, and only a fraction of these have ancillary information on genome structure, genetic variation, gene expression, epigenetic modifications, and population diversity. This imbalance reflects a perception that human studies are paramount in disease research. Yet understanding how genomes work, and how genetic variation shapes phenotypes, requires a broad view that embraces the vast diversity of life. We have the technology to collect massive and exquisitely detailed datasets about the world, but expertise is siloed into distinct fields. A new approach, integrating comparative genomics with cell and evolutionary biology, ecology, archaeology, anthropology, and conservation biology, is essential for understanding and protecting ourselves and our world. Here, we describe potential for scientific discovery when comparative genomics works in close collaboration with a broad range of fields as well as the technical, scientific, and social constraints that must be addressed.
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Affiliation(s)
- Taylorlyn Stephan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20817
| | - Shawn M Burgess
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20817
| | - Hans Cheng
- Avian Disease and Oncology Laboratory, Agricultural Research Service, US Department of Agriculture, East Lansing, MI 48823
| | - Charles G Danko
- Department of Biomedical Sciences, Baker Institute for Animal Health, Cornell University, Ithaca, NY 14850
| | - Clare A Gill
- Department of Animal Science, Texas A&M University, College Station, TX 77843
| | - Erich D Jarvis
- Laboratory of Neurogenetics of Language, The Rockefeller University, New York, NY 10065
- HHMI, Chevy Chase, MD 20815
| | - Klaus-Peter Koepfli
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630
- Smithsonian Conservation Biology Institute, National Zoological Park, Washington, DC 20008
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, IA 50011
| | - Eric Lyons
- School of Plant Sciences, BIO5 Institute, University of Arizona, Tucson, AZ 85721
| | - Pamela Ronald
- Department of Plant Pathology, University of California, Davis, CA 95616
- The Genome Center, University of California, Davis, CA 95616
- The Innovative Genomics Institute, University of California, Berkeley, CA 94720
- Grass Genetics, Joint Bioenergy Institute, Emeryville, CA 94608
| | - Oliver A Ryder
- San Diego Zoo Wildlife Alliance, Escondido, CA 92027
- Department of Evolution, Behavior, and Ecology, University of California San Diego, La Jolla, CA 92093
| | - Lynn M Schriml
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201
| | - Pamela Soltis
- Florida Museum of Natural History, University of Florida, Gainesville, FL 32611
| | - Sue VandeWoude
- Department of Micro-, Immuno-, and Pathology, Colorado State University, Fort Collins, CO 80532
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, CA 95616
| | - Elaine A Ostrander
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20817
| | - Elinor K Karlsson
- Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01655;
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01655
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
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26
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Blaxter M, Archibald JM, Childers AK, Coddington JA, Crandall KA, Di Palma F, Durbin R, Edwards SV, Graves JAM, Hackett KJ, Hall N, Jarvis ED, Johnson RN, Karlsson EK, Kress WJ, Kuraku S, Lawniczak MKN, Lindblad-Toh K, Lopez JV, Moran NA, Robinson GE, Ryder OA, Shapiro B, Soltis PS, Warnow T, Zhang G, Lewin HA. Why sequence all eukaryotes? Proc Natl Acad Sci U S A 2022; 119:e2115636118. [PMID: 35042801 PMCID: PMC8795522 DOI: 10.1073/pnas.2115636118] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Life on Earth has evolved from initial simplicity to the astounding complexity we experience today. Bacteria and archaea have largely excelled in metabolic diversification, but eukaryotes additionally display abundant morphological innovation. How have these innovations come about and what constraints are there on the origins of novelty and the continuing maintenance of biodiversity on Earth? The history of life and the code for the working parts of cells and systems are written in the genome. The Earth BioGenome Project has proposed that the genomes of all extant, named eukaryotes-about 2 million species-should be sequenced to high quality to produce a digital library of life on Earth, beginning with strategic phylogenetic, ecological, and high-impact priorities. Here we discuss why we should sequence all eukaryotic species, not just a representative few scattered across the many branches of the tree of life. We suggest that many questions of evolutionary and ecological significance will only be addressable when whole-genome data representing divergences at all of the branchings in the tree of life or all species in natural ecosystems are available. We envisage that a genomic tree of life will foster understanding of the ongoing processes of speciation, adaptation, and organismal dependencies within entire ecosystems. These explorations will resolve long-standing problems in phylogenetics, evolution, ecology, conservation, agriculture, bioindustry, and medicine.
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Affiliation(s)
- Mark Blaxter
- Wellcome Sanger Institute, Hinxton, Cambridge CB10 1SA, United Kingdom;
| | - John M Archibald
- Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, NS B3H 4H7, Canada
| | - Anna K Childers
- Bee Research Laboratory, Agricultural Research Service, US Department of Agriculture (USDA), Beltsville, MD 20705
| | - Jonathan A Coddington
- Global Genome Initiative, National Museum of Natural History, Smithsonian Institution, Washington, DC 20560
| | - Keith A Crandall
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, George Washington University, Washington, DC 20052
- Department of Invertebrate Zoology, Smithsonian Institution, Washington, DC 20013
| | - Federica Di Palma
- School of Biological Sciences, University of East Anglia, Norwich NR4 7TJ, United Kingdom
| | - Richard Durbin
- Wellcome Sanger Institute, Hinxton, Cambridge CB10 1SA, United Kingdom
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, United Kingdom
| | - Scott V Edwards
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138
| | - Jennifer A M Graves
- School of Life Sciences, La Trobe University, Bundoora, VIC 751 23, Australia
- University of Canberra, Bruce, ACT 2617, Australia
| | - Kevin J Hackett
- Crop Production and Protection, Office of National Programs, Agricultural Research Service, USDA, Beltsville, MD 20705
| | - Neil Hall
- Earlham Institute, Norwich, Norfolk NR4 7UZ, United Kingdom
| | - Erich D Jarvis
- Laboratory of the Neurogenetics of Language, The Rockefeller University, New York, NY 10065
- Howard Hughes Medical Institute, Chevy Chase, MD 20815
| | - Rebecca N Johnson
- National Museum of Natural History, Smithsonian Institution, Washington, DC 20560
| | - Elinor K Karlsson
- Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - W John Kress
- Botany, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012
| | - Shigehiro Kuraku
- Department of Genomics and Evolutionary Biology, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
- Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, Hyogo 650-0047, Japan
| | | | - Kerstin Lindblad-Toh
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala 751 23, Sweden
| | - Jose V Lopez
- Department of Biological Sciences, Halmos College of Arts and Sciences, Nova Southeastern University, Dania Beach, FL 33004
- Guy Harvey Oceanographic Center, Dania Beach, FL 33004
| | - Nancy A Moran
- Integrative Biology, University of Texas at Austin, Austin, TX 78712
| | - Gene E Robinson
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
- Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Oliver A Ryder
- Conservation Genetics, Division of Biology, San Diego Zoo Wildlife Alliance, Escondido, CA 92027
- Department of Evolution, Behavior and Ecology, University of California, San Diego, La Jolla, CA 92039
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064
| | - Pamela S Soltis
- Florida Museum of Natural History, University of Florida, Gainesville, FL 32611
- Biodiversity Institute, University of Florida, Gainesville, FL 32611
| | - Tandy Warnow
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61301
| | - Guojie Zhang
- Villum Center for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark
- China National Genebank, Beijing Genomics Institute-Shenzhen, Shenzhen 518083, China
| | - Harris A Lewin
- Department of Evolution and Ecology, College of Biological Sciences, University of California, Davis, CA 95616
- Department of Population Health and Reproduction, University of California, Davis, CA 95616
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27
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A National Multi-Scale Assessment of Regeneration Deficit as an Indicator of Potential Risk of Forest Genetic Variation Loss. FORESTS 2021. [DOI: 10.3390/f13010019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Genetic diversity is essential because it provides a basis for adaptation and resilience to environmental stress and change. The fundamental importance of genetic variation is recognized by its inclusion in the Montréal Process sustainability criteria and indicators for temperate and boreal forests. The indicator that focuses on forest species at risk of losing genetic variation, however, has been difficult to address in a systematic fashion. We combined two broad-scale datasets to inform this indicator for the United States: (1) tree species occurrence data from the national Forest Inventory and Analysis (FIA) plot network and (2) climatically and edaphically defined provisional seed zones, which are proxies for among-population adaptive variation. Specifically, we calculated the estimated proportion of small trees (seedlings and saplings) relative to all trees for each species and within seed zone sub-populations, with the assumption that insufficient regeneration could lead to the loss of genetic variation. The threshold between sustainable and unsustainable proportions of small trees reflected the expectation of age–class balance at the landscape scale. We found that 46 of 280 U.S. forest tree species (16.4%) may be at risk of losing genetic variation. California and the Southeast encompassed the most at-risk species. Additionally, 39 species were potentially at risk within at least half of the seed zones in which they occurred. Seed zones in California and the Southwest had the highest proportions of tree species that may be at risk. The results could help focus conservation and management activities to prevent the loss of adaptive genetic variation within tree species.
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28
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Sanderson S, Beausoleil MO, O'Dea RE, Wood ZT, Correa C, Frankel V, Gorné LD, Haines GE, Kinnison MT, Oke KB, Pelletier F, Pérez-Jvostov F, Reyes-Corral WD, Ritchot Y, Sorbara F, Gotanda KM, Hendry AP. The pace of modern life, revisited. Mol Ecol 2021; 31:1028-1043. [PMID: 34902193 DOI: 10.1111/mec.16299] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 11/15/2021] [Accepted: 11/22/2021] [Indexed: 12/28/2022]
Abstract
Wild populations must continuously respond to environmental changes or they risk extinction. Those responses can be measured as phenotypic rates of change, which can allow us to predict contemporary adaptive responses, some of which are evolutionary. About two decades ago, a database of phenotypic rates of change in wild populations was compiled. Since then, researchers have used (and expanded) this database to examine phenotypic responses to specific types of human disturbance. Here, we update the database by adding 5675 new estimates of phenotypic change. Using this newer version of the data base, now containing 7338 estimates of phenotypic change, we revisit the conclusions of four published articles. We then synthesize the expanded database to compare rates of change across different types of human disturbance. Analyses of this expanded database suggest that: (i) a small absolute difference in rates of change exists between human disturbed and natural populations, (ii) harvesting by humans results in higher rates of change than other types of disturbance, (iii) introduced populations have increased rates of change, and (iv) body size does not increase through time. Thus, findings from earlier analyses have largely held-up in analyses of our new database that encompass a much larger breadth of species, traits, and human disturbances. Lastly, we use new analyses to explore how various types of human disturbances affect rates of phenotypic change, and we call for this database to serve as a steppingstone for further analyses to understand patterns of contemporary phenotypic change.
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Affiliation(s)
- Sarah Sanderson
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
| | | | - Rose E O'Dea
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada.,Evolution & Ecology Research Centre, UNSW, Sydney, New South Wales, Australia
| | - Zachary T Wood
- School of Biology and Ecology and Maine Center for Genetics in the Environment, University of Maine, Orono, Maine, USA
| | - Cristian Correa
- Facultad de Ciencias Forestales y Recursos Naturales, Instituto de Conservación Biodiversidad y Territorio, Universidad Austral de Chile, Valdivia, Chile.,Centro de Humedales Río Cruces, Universidad Austral de Chile, Valdivia, Chile
| | - Victor Frankel
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
| | - Lucas D Gorné
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada.,Facultad de Ciencias Exactas Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, IMBiV, Córdoba, Argentina.,Department of Biological Sciences, Brock University, St. Catharines, Ontario, Canada.,Département de Biologie, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Grant E Haines
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
| | - Michael T Kinnison
- School of Biology and Ecology and Maine Center for Genetics in the Environment, University of Maine, Orono, Maine, USA
| | - Krista B Oke
- College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Juneau, Alaska, USA
| | - Fanie Pelletier
- College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Juneau, Alaska, USA
| | - Felipe Pérez-Jvostov
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
| | - Winer D Reyes-Corral
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
| | - Yanny Ritchot
- College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Juneau, Alaska, USA
| | - Freedom Sorbara
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
| | - Kiyoko M Gotanda
- Department of Biological Sciences, Brock University, St. Catharines, Ontario, Canada.,Département de Biologie, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Andrew P Hendry
- Department of Biology and Redpath Museum, McGill University, Montréal, Québec, Canada
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29
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Faske TM, Agneray AC, Jahner JP, Sheta LM, Leger EA, Parchman TL. Genomic and common garden approaches yield complementary results for quantifying environmental drivers of local adaptation in rubber rabbitbrush, a foundational Great Basin shrub. Evol Appl 2021; 14:2881-2900. [PMID: 34950235 PMCID: PMC8674890 DOI: 10.1111/eva.13323] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/17/2021] [Accepted: 11/03/2021] [Indexed: 01/21/2023] Open
Abstract
The spatial structure of genomic and phenotypic variation across populations reflects historical and demographic processes as well as evolution via natural selection. Characterizing such variation can provide an important perspective for understanding the evolutionary consequences of changing climate and for guiding ecological restoration. While evidence for local adaptation has been traditionally evaluated using phenotypic data, modern methods for generating and analyzing landscape genomic data can directly quantify local adaptation by associating allelic variation with environmental variation. Here, we analyze both genomic and phenotypic variation of rubber rabbitbrush (Ericameria nauseosa), a foundational shrub species of western North America. To quantify landscape genomic structure and provide perspective on patterns of local adaptation, we generated reduced representation sequencing data for 17 wild populations (222 individuals; 38,615 loci) spanning a range of environmental conditions. Population genetic analyses illustrated pronounced landscape genomic structure jointly shaped by geography and environment. Genetic-environment association (GEA) analyses using both redundancy analysis (RDA) and a machine-learning approach (Gradient Forest) indicated environmental variables (precipitation seasonality, slope, aspect, elevation, and annual precipitation) influenced spatial genomic structure and were correlated with allele frequency shifts indicative of local adaptation at a consistent set of genomic regions. We compared our GEA-based inference of local adaptation with phenotypic data collected by growing seeds from each population in a greenhouse common garden. Population differentiation in seed weight, emergence, and seedling traits was associated with environmental variables (e.g., precipitation seasonality) that were also implicated in GEA analyses, suggesting complementary conclusions about the drivers of local adaptation across different methods and data sources. Our results provide a baseline understanding of spatial genomic structure for E. nauseosa across the western Great Basin and illustrate the utility of GEA analyses for detecting the environmental causes and genetic signatures of local adaptation in a widely distributed plant species of restoration significance.
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Affiliation(s)
- Trevor M. Faske
- Department of BiologyUniversity of NevadaRenoNevadaUSA
- Ecology, Evolution, and Conservation Biology ProgramUniversity of NevadaRenoNevadaUSA
| | - Alison C. Agneray
- Department of BiologyUniversity of NevadaRenoNevadaUSA
- Ecology, Evolution, and Conservation Biology ProgramUniversity of NevadaRenoNevadaUSA
| | | | - Lana M. Sheta
- Department of BiologyUniversity of NevadaRenoNevadaUSA
| | - Elizabeth A. Leger
- Department of BiologyUniversity of NevadaRenoNevadaUSA
- Ecology, Evolution, and Conservation Biology ProgramUniversity of NevadaRenoNevadaUSA
| | - Thomas L. Parchman
- Department of BiologyUniversity of NevadaRenoNevadaUSA
- Ecology, Evolution, and Conservation Biology ProgramUniversity of NevadaRenoNevadaUSA
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30
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New developments in the field of genomic technologies and their relevance to conservation management. CONSERV GENET 2021. [DOI: 10.1007/s10592-021-01415-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
AbstractRecent technological advances in the field of genomics offer conservation managers and practitioners new tools to explore for conservation applications. Many of these tools are well developed and used by other life science fields, while others are still in development. Considering these technological possibilities, choosing the right tool(s) from the toolbox is crucial and can pose a challenging task. With this in mind, we strive to inspire, inform and illuminate managers and practitioners on how conservation efforts can benefit from the current genomic and biotechnological revolution. With inspirational case studies we show how new technologies can help resolve some of the main conservation challenges, while also informing how implementable the different technologies are. We here focus specifically on small population management, highlight the potential for genetic rescue, and discuss the opportunities in the field of gene editing to help with adaptation to changing environments. In addition, we delineate potential applications of gene drives for controlling invasive species. We illuminate that the genomic toolbox offers added benefit to conservation efforts, but also comes with limitations for the use of these novel emerging techniques.
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31
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Schielzeth H, Wolf JBW. Community genomics: a community-wide perspective on within-species genetic diversity. AMERICAN JOURNAL OF BOTANY 2021; 108:2108-2111. [PMID: 34767249 DOI: 10.1002/ajb2.1796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 09/07/2021] [Indexed: 06/13/2023]
Affiliation(s)
- Holger Schielzeth
- Institute of Ecology and Evolution, Friedrich Schiller University Jena, Germany
| | - Jochen B W Wolf
- Division of Evolutionary Biology, Faculty of Biology, LMU Munich, Germany
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32
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Zhang J, Zhang D, Fan Y, Li C, Xu P, Li W, Sun Q, Huang X, Zhang C, Wu L, Yang H, Wang S, Su X, Li X, Song Y, Wu ME, Lian X, Li Y. The identification of grain size genes by RapMap reveals directional selection during rice domestication. Nat Commun 2021; 12:5673. [PMID: 34584089 PMCID: PMC8478914 DOI: 10.1038/s41467-021-25961-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Accepted: 09/10/2021] [Indexed: 11/09/2022] Open
Abstract
Cloning quantitative trait locus (QTL) is time consuming and laborious, which hinders the understanding of natural variation and genetic diversity. Here, we introduce RapMap, a method for rapid multi-QTL mapping by employing F2 gradient populations (F2GPs) constructed by minor-phenotypic-difference accessions. The co-segregation standard of the single-locus genetic models ensures simultaneous integration of a three-in-one framework in RapMap i.e. detecting a real QTL, confirming its effect, and obtaining its near-isogenic line-like line (NIL-LL). We demonstrate the feasibility of RapMap by cloning eight rice grain-size genes using 15 F2GPs in three years. These genes explain a total of 75% of grain shape variation. Allele frequency analysis of these genes using a large germplasm collection reveals directional selection of the slender and long grains in indica rice domestication. In addition, major grain-size genes have been strongly selected during rice domestication. We think application of RapMap in crops will accelerate gene discovery and genomic breeding.
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Affiliation(s)
- Juncheng Zhang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Dejian Zhang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Yawei Fan
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Cuicui Li
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Pengkun Xu
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Wei Li
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Qi Sun
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xiaodong Huang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Chunyu Zhang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Linyue Wu
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Huaizhou Yang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Shiyu Wang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xiaomin Su
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xingxing Li
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Yingying Song
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Meng-En Wu
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
| | - Yibo Li
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China.
- Hubei Hongshan Laboratory, Wuhan, China.
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Lone AR, Thakur SS, Tiwari N, Olusola B. Sokefun, Yadav S. Disentangling earthworm taxonomic stumbling blocks using molecular markers. JOURNAL OF THREATENED TAXA 2021. [DOI: 10.11609/jott.6888.13.11.19566-19579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Taxonomic classification of earthworms based on anatomical features has created several challenges for systematics and population genetics. This study examines the application of molecular markers, in particular mitochondrial cytochrome oxidase (COI), to facilitate discrimination of closely related earthworm species. Molecular markers have also provided insights into population genetics by aiding assessment of genetic diversity, lineage sorting, and genealogical distributions of populations for several species. Phylogeography—a study that evaluates the geographical distribution of these genealogical lineages and the role of historical processes in shaping their distribution—has also provided insights into ecology and biodiversity. Such studies are also essential to understand the distribution patterns of invasive earthworm species that have been introduced in non-native ecosystems globally. The negative consequences of these invasions on native species include competition for food resources and altered ecosystems. We anticipate that molecular markers such as COI and DNA barcoding offer potential solutions to disentangling taxonomic impediments in earthworms and advancing their systematics and population genetics.
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Hoban S, Bruford MW, Funk WC, Galbusera P, Griffith MP, Grueber CE, Heuertz M, Hunter ME, Hvilsom C, Stroil BK, Kershaw F, Khoury CK, Laikre L, Lopes-Fernandes M, MacDonald AJ, Mergeay J, Meek M, Mittan C, Mukassabi TA, O'Brien D, Ogden R, Palma-Silva C, Ramakrishnan U, Segelbacher G, Shaw RE, Sjögren-Gulve P, Veličković N, Vernesi C. Global Commitments to Conserving and Monitoring Genetic Diversity Are Now Necessary and Feasible. Bioscience 2021; 71:964-976. [PMID: 34475806 PMCID: PMC8407967 DOI: 10.1093/biosci/biab054] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Global conservation policy and action have largely neglected protecting and monitoring genetic diversity—one of the three main pillars of biodiversity. Genetic diversity (diversity within species) underlies species’ adaptation and survival, ecosystem resilience, and societal innovation. The low priority given to genetic diversity has largely been due to knowledge gaps in key areas, including the importance of genetic diversity and the trends in genetic diversity change; the perceived high expense and low availability and the scattered nature of genetic data; and complicated concepts and information that are inaccessible to policymakers. However, numerous recent advances in knowledge, technology, databases, practice, and capacity have now set the stage for better integration of genetic diversity in policy instruments and conservation efforts. We review these developments and explore how they can support improved consideration of genetic diversity in global conservation policy commitments and enable countries to monitor, report on, and take action to maintain or restore genetic diversity.
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Affiliation(s)
- Sean Hoban
- The Morton Arboretum, Center for Tree Science, Lisle, Illinois, United States
| | | | - W Chris Funk
- Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, United States
| | - Peter Galbusera
- Royal Zoological Society of Antwerp, Centre for Research and Conservation, Antwerp, Belgium
| | | | - Catherine E Grueber
- University of Sydney's School of Life and Environmental Sciences, Faculty of Science, Sydney, New South Wales, Australia
| | - Myriam Heuertz
- INRAE, and the University of Bordeaux, Biogeco, Cestas, France
| | - Margaret E Hunter
- US Geological Survey's Wetland and Aquatic Research Center, Gainesville, Florida, United States
| | | | - Belma Kalamujic Stroil
- University of Sarajevo Institute for Genetic Engineering and Biotechnology, Laboratory for Molecular Genetics of Natural Resources, Sarajevo, Bosnia and Herzegovina
| | - Francine Kershaw
- Natural Resources Defense Council, New York, New York, United States
| | - Colin K Khoury
- International Center for Tropical Agriculture, Cali, Colombia
| | - Linda Laikre
- Department of Zoology, Division of Population Genetics, Stockholm University, Stockholm, Sweden
| | | | - Anna J MacDonald
- Australian National University, John Curtin School of Medical Research and Research School of Biology, Canberra, Australia
| | - Joachim Mergeay
- Research Institute for Nature and Forest, Geraardsbergen, Belgium
| | - Mariah Meek
- Michigan State University Department of Integrative Biology, AgBio Research, Ecology, Evolution, and Behavior Program, East Lansing, Michigan, United States
| | - Cinnamon Mittan
- Cornell University's Department of Ecology and Evolutionary Biology, Ithaca, New York, United States
| | - Tarek A Mukassabi
- University of Benghazi Department of Botany, Faculty of Sciences, Benghazi, Libya
| | | | - Rob Ogden
- Royal (Dick) School of Veterinary Studies and with the Roslin Institute, University of Edinburgh, Easter Bush Campus, Edinburgh, Scotland, United Kingdom
| | | | - Uma Ramakrishnan
- Department of Ecology and Evolution, National Centre for Biological Sciences, Bangalore, India
| | - Gernot Segelbacher
- Chair of wildlife ecology and management, University Freiburg, Freiburg, Germany
| | - Robyn E Shaw
- Department of Environmental and Conservation Sciences, Murdoch University, Perth, Australia
| | - Per Sjögren-Gulve
- Wildlife Analysis Unit, Swedish Environmental Protection Agency, Stockholm, Sweden
| | - Nevena Veličković
- University of Novi Sad's Faculty of Sciences, Department of Biology and Ecology, Novi Sad, Serbia
| | - Cristiano Vernesi
- Forest Ecology and Biogeochemical Fluxes Unit, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all' Adige, Italy
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Chromosome-Level Genome Assemblies Expand Capabilities of Genomics for Conservation Biology. Genes (Basel) 2021; 12:genes12091336. [PMID: 34573318 PMCID: PMC8466942 DOI: 10.3390/genes12091336] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/20/2021] [Accepted: 08/25/2021] [Indexed: 11/26/2022] Open
Abstract
Genome assemblies are in the process of becoming an increasingly important tool for understanding genetic diversity in threatened species. Unfortunately, due to limited budgets typical for the area of conservation biology, genome assemblies of threatened species, when available, tend to be highly fragmented, represented by tens of thousands of scaffolds not assigned to chromosomal locations. The recent advent of high-throughput chromosome conformation capture (Hi-C) enables more contiguous assemblies containing scaffolds spanning the length of entire chromosomes for little additional cost. These inexpensive contiguous assemblies can be generated using Hi-C scaffolding of existing short-read draft assemblies, where N50 of the draft contigs is larger than 0.1% of the estimated genome size and can greatly improve analyses and facilitate visualization of genome-wide features including distribution of genetic diversity in markers along chromosomes or chromosome-length scaffolds. We compared distribution of genetic diversity along chromosomes of eight mammalian species, including six listed as threatened by IUCN, where both draft genome assemblies and newer chromosome-level assemblies were available. The chromosome-level assemblies showed marked improvement in localization and visualization of genetic diversity, especially where the distribution of low heterozygosity across the genomes of threatened species was not uniform.
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Wynne JJ, Howarth FG, Mammola S, Ferreira RL, Cardoso P, Lorenzo TD, Galassi DMP, Medellin RA, Miller BW, Sánchez‐Fernández D, Bichuette ME, Biswas J, BlackEagle CW, Boonyanusith C, Amorim IR, Borges PAV, Boston PJ, Cal RN, Cheeptham N, Deharveng L, Eme D, Faille A, Fenolio D, Fišer C, Fišer Ž, ʻOhukaniʻōhiʻa Gon SM, Goudarzi F, Griebler C, Halse S, Hoch H, Kale E, Katz AD, Kováč Ľ, Lilley TM, Manchi S, Manenti R, Martínez A, Meierhofer MB, Miller AZ, Moldovan OT, Niemiller ML, Peck SB, Pellegrini TG, Pipan T, Phillips‐Lander CM, Poot C, Racey PA, Sendra A, Shear WA, Silva MS, Taiti S, Tian M, Venarsky MP, Pakarati SY, Zagmajster M, Zhao Y. A conservation roadmap for the subterranean biome. Conserv Lett 2021. [DOI: 10.1111/conl.12834] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Affiliation(s)
- J. Judson Wynne
- Department of Biological Sciences, Center for Adaptable Western Landscapes Northern Arizona University Flagstaff Arizona
| | | | - Stefano Mammola
- Finnish Museum of Natural History Luomus University of Helsinki Helsinki Finland
- DarkMEG—Molecular Ecology Group, Water Research Institute National Research Council of Italy Verbania Pallanza Italy
| | - Rodrigo Lopes Ferreira
- Centro de Estudos em Biologia Subterrânea, Setor de Biodiversidade Subterrânea, Departamento de Ecologia e Conservação Universidade Federal de Lavras Minas Gerais Brazil
| | - Pedro Cardoso
- Finnish Museum of Natural History Luomus University of Helsinki Helsinki Finland
| | - Tiziana Di Lorenzo
- Research Institute on Terrestrial Ecosystem of the Italian National Research Council Florence Italy
| | - Diana M. P. Galassi
- Department of Life, Health & Environmental Sciences University of L'Aquila L'Aquila Italy
| | | | - Bruce W. Miller
- Wildlife Conservation Society, Bronx Zoo, Bronx NY (Ret.) and Bat Sound Services Canadian Lakes Michigan
| | | | - Maria Elina Bichuette
- Laboratório de Estudos Subterrâneos, Departamento de Ecologia e Biologia Evolutiva Universidade Federal de São Carlos, São Carlos São Paulo Brazil
| | - Jayant Biswas
- National Cave Research and Protection Organization Raipur Chhattisgarh India
| | | | | | - Isabel R. Amorim
- Centre for Ecology Evolution and Environmental Changes/Azorean Biodiversity Group and Universidade dos Açores, Faculty of Agrarian and Environmental Sciences Azores Portugal
| | - Paulo Alexandre Vieira Borges
- Centre for Ecology Evolution and Environmental Changes/Azorean Biodiversity Group and Universidade dos Açores, Faculty of Agrarian and Environmental Sciences Azores Portugal
| | | | | | - Naowarat Cheeptham
- Department of Biological Sciences, Faculty of Science Thompson Rivers University Kamloops British Columbia Canada
| | | | - David Eme
- IFREMER Centre Atlantique Unité Ecologie et Modèles pour l'Halieutique Nantes France
| | - Arnaud Faille
- Stuttgart State Museum of Natural History Stuttgart Germany
| | - Danté Fenolio
- Center for Conservation and Research San Antonio Zoo San Antonio Texas
| | - Cene Fišer
- SubBio Lab, Department of Biology Biotechnical Faculty University of Ljubljana Slovenia
| | - Žiga Fišer
- SubBio Lab, Department of Biology Biotechnical Faculty University of Ljubljana Slovenia
| | | | - Forough Goudarzi
- Department of Environment Isfahan University of Technology Isfahan Iran
| | - Christian Griebler
- Department of Functional and Evolutionary Ecology Division of Limnology, University of Vienna Vienna Austria
| | - Stuart Halse
- Bennelongia Environmental Consultants Perth Australia
| | - Hannelore Hoch
- Department Center for Integrative Biodiversity Discovery, Museum für Naturkunde Leibniz Institute for Research on Evolution and Biodiversity Berlin Germany
| | - Enock Kale
- Ecomate Management Ltd., Boroko NCD Papua New Guinea
| | - Aron D. Katz
- Engineer Research and Development Center U.S. Army Corps of Engineers Champaign Illinois
| | - Ľubomír Kováč
- Department of Zoology, Institute of Biology and Ecology P.J. Šafárik University Košice Slovakia
| | - Thomas M. Lilley
- Finnish Museum of Natural History Luomus University of Helsinki Helsinki Finland
| | - Shirish Manchi
- Conservation Ecology Division Salim Ali Centre for Ornithology and Natural History Coimbatore India
| | - Raoul Manenti
- Department of Environmental Science and Policy Università degli Studi di Milano Milan Italy
| | - Alejandro Martínez
- DarkMEG—Molecular Ecology Group, Water Research Institute National Research Council of Italy Verbania Pallanza Italy
| | | | - Ana Z. Miller
- Laboratório HERCULES, University of Évora, Évora, Portugal and Instituto de Recursos Naturales y Agrobiología de Sevilla Consejo Superior de Investigaciones Científicas Seville Spain
| | | | - Matthew L. Niemiller
- Department of Biological Sciences The University of Alabama in Huntsville Huntsville Alabama
| | | | - Thais Giovannini Pellegrini
- Centro de Estudos em Biologia Subterrânea, Setor de Biodiversidade Subterrânea, Departamento de Ecologia e Conservação Universidade Federal de Lavras Minas Gerais Brazil
| | - Tanja Pipan
- ZRC SAZU Karst Research Institute, Ljubljana Slovenia and UNESCO Chair on Karst Education, University of Nova Gorica Vipava Slovenia
| | | | - Celso Poot
- The Belize Zoo and Tropical Education Center, Belmopan, Belize and School of Natural Resources and Environment University of Florida Gainesville Florida
| | - Paul A. Racey
- Centre for Ecology and Conservation University of Exeter UK
| | - Alberto Sendra
- Colecciones Entomológicas Torres‐Sala Servei de Patrimoni Històric, Ajuntament de València València Spain
- Departament de Didàctica de les Cièncias Experimentals i Socials, Facultat de Magisteri Universitat de València València Spain
| | - William A. Shear
- Department of Biology Hampden‐Sydney College Hampden Sydney Virginia
| | - Marconi Souza Silva
- Centro de Estudos em Biologia Subterrânea, Setor de Biodiversidade Subterrânea, Departamento de Ecologia e Conservação Universidade Federal de Lavras Minas Gerais Brazil
| | - Stefano Taiti
- Istituto di Ricerca sugli Ecosistemi Terrestri CNR‐IRET Museo di Storia Naturale, Sezione di Zoologia Firenze Italy
| | - Mingyi Tian
- Department of Entomology, College of Plant Protection South China Agricultural University Guangzhou China
| | - Michael P. Venarsky
- Department of Biodiversity Conservation and Attractions Government of Western Australia Washington Kensington Australia
| | - Sebastián Yancovic Pakarati
- Laboratorio de Socioecosistemas, Departamento de Ecología Universidad Autónoma de Madrid Madrid Spain
- Consejo Asesor de Monumentos Nacionales de Chile ‐ Rapa Nui Chile
- Manu Project, Rapa Nui Chile
| | - Maja Zagmajster
- SubBio Lab, Department of Biology Biotechnical Faculty University of Ljubljana Slovenia
| | - Yahui Zhao
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology Chinese Academy of Sciences Beijing China
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Kellner AWA. Amazon biodiversity - quo vadis? AN ACAD BRAS CIENC 2021; 93:e2021932. [PMID: 34259796 DOI: 10.1590/0001-376520212021932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Affiliation(s)
- Alexander W A Kellner
- Laboratório de Sistemática e Tafonomia de Vertebrados Fósseis, Departamento de Geologia e Paleontologia do Museu Nacional/UFRJ, Quinta da Boa Vista, s/n, São Cristóvão, 20940-040 Rio de Janeiro, RJ, Brazil
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Kindt R. AlleleShift: an R package to predict and visualize population-level changes in allele frequencies in response to climate change. PeerJ 2021; 9:e11534. [PMID: 34178449 PMCID: PMC8212829 DOI: 10.7717/peerj.11534] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 05/07/2021] [Indexed: 11/20/2022] Open
Abstract
Background At any particular location, frequencies of alleles that are associated with adaptive traits are expected to change in future climates through local adaption and migration, including assisted migration (human-implemented when climate change is more rapid than natural migration rates). Making the assumption that the baseline frequencies of alleles across environmental gradients can act as a predictor of patterns in changed climates (typically future but possibly paleo-climates), a methodology is provided by AlleleShift of predicting changes in allele frequencies at the population level. Methods The prediction procedure involves a first calibration and prediction step through redundancy analysis (RDA), and a second calibration and prediction step through a generalized additive model (GAM) with a binomial family. As such, the procedure is fundamentally different to an alternative approach recently proposed to predict changes in allele frequencies from canonical correspondence analysis (CCA). The RDA step is based on the Euclidean distance that is also the typical distance used in Analysis of Molecular Variance (AMOVA). Because the RDA step or CCA approach sometimes predict negative allele frequencies, the GAM step ensures that allele frequencies are in the range of 0 to 1. Results AlleleShift provides data sets with predicted frequencies and several visualization methods to depict the predicted shifts in allele frequencies from baseline to changed climates. These visualizations include 'dot plot' graphics (function shift.dot.ggplot), pie diagrams (shift.pie.ggplot), moon diagrams (shift.moon.ggplot), 'waffle' diagrams (shift.waffle.ggplot) and smoothed surface diagrams of allele frequencies of baseline or future patterns in geographical space (shift.surf.ggplot). As these visualizations were generated through the ggplot2 package, methods of generating animations for a climate change time series are straightforward, as shown in the documentation of AlleleShift and in the supplemental videos. Availability AlleleShift is available as an open-source R package from https://cran.r-project.org/package=AlleleShift and https://github.com/RoelandKindt/AlleleShift. Genetic input data is expected to be in the adegenet::genpop format, which can be generated from the adegenet::genind format. Climate data is available from various resources such as WorldClim and Envirem.
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Thomson AI, Archer FI, Coleman MA, Gajardo G, Goodall‐Copestake WP, Hoban S, Laikre L, Miller AD, O’Brien D, Pérez‐Espona S, Segelbacher G, Serrão EA, Sjøtun K, Stanley MS. Charting a course for genetic diversity in the UN Decade of Ocean Science. Evol Appl 2021; 14:1497-1518. [PMID: 34178100 PMCID: PMC8210796 DOI: 10.1111/eva.13224] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 03/04/2021] [Accepted: 03/04/2021] [Indexed: 02/06/2023] Open
Abstract
The health of the world's oceans is intrinsically linked to the biodiversity of the ecosystems they sustain. The importance of protecting and maintaining ocean biodiversity has been affirmed through the setting of the UN Sustainable Development Goal 14 to conserve and sustainably use the ocean for society's continuing needs. The decade beginning 2021-2030 has additionally been declared as the UN Decade of Ocean Science for Sustainable Development. This program aims to maximize the benefits of ocean science to the management, conservation, and sustainable development of the marine environment by facilitating communication and cooperation at the science-policy interface. A central principle of the program is the conservation of species and ecosystem components of biodiversity. However, a significant omission from the draft version of the Decade of Ocean Science Implementation Plan is the acknowledgment of the importance of monitoring and maintaining genetic biodiversity within species. In this paper, we emphasize the importance of genetic diversity to adaptive capacity, evolutionary potential, community function, and resilience within populations, as well as highlighting some of the major threats to genetic diversity in the marine environment from direct human impacts and the effects of global climate change. We then highlight the significance of ocean genetic diversity to a diverse range of socioeconomic factors in the marine environment, including marine industries, welfare and leisure pursuits, coastal communities, and wider society. Genetic biodiversity in the ocean, and its monitoring and maintenance, is then discussed with respect to its integral role in the successful realization of the 2030 vision for the Decade of Ocean Science. Finally, we suggest how ocean genetic diversity might be better integrated into biodiversity management practices through the continued interaction between environmental managers and scientists, as well as through key leverage points in industry requirements for Blue Capital financing and social responsibility.
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Affiliation(s)
| | | | - Melinda A. Coleman
- New South Wales FisheriesNational Marine Science CentreCoffs HarbourNSWAustralia
- National Marine Science CentreSouthern Cross UniversityCoffs HarbourNSWAustralia
- Oceans Institute and School of Biological SciencesUniversity of Western AustraliaCrawleyWAAustralia
| | - Gonzalo Gajardo
- Laboratory of Genetics, Aquaculture & BiodiversityUniversidad de Los LagosOsornoChile
| | | | - Sean Hoban
- Centre for Tree ScienceThe Morton ArboretumLisleILUSA
| | - Linda Laikre
- Centre for Tree ScienceThe Morton ArboretumLisleILUSA
- The Wildlife Analysis UnitThe Swedish Environmental Protection AgencyStockholmSweden
| | - Adam D. Miller
- School of Life and Environmental SciencesCentre for Integrative EcologyDeakin UniversityGeelongVicAustralia
- Deakin Genomics CentreDeakin UniversityGeelongVic.Australia
| | | | - Sílvia Pérez‐Espona
- The Royal (Dick) School of Veterinary Studies and The Roslin InstituteMidlothianUK
| | - Gernot Segelbacher
- Chair of Wildlife Ecology and ManagementUniversity FreiburgFreiburgGermany
| | - Ester A. Serrão
- CCMARCentre of Marine SciencesFaculty of Sciences and TechnologyUniversity of AlgarveFaroPortugal
| | - Kjersti Sjøtun
- Department of Biological SciencesUniversity of BergenBergenNorway
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Abstract
AbstractGenetic diversity is a fundamental component of biological diversity, and its conservation is considered key to ensure the long-term survival of natural populations and species. National and international legislation increasingly mandates a monitoring of genetic diversity. Examples are the United Nation’s Convention on Biological Diversity (CBD) Aichi target 13 and the current post-2020 negotiations to specify a new target for maintaining genetic diversity. To date, only a few pilot projects have been launched that systematically monitor genetic diversity over time in natural populations of a broad variety of wild species. The Swiss Federal Office for the Environment mandated a feasibility study in 2019 for implementing a national monitoring of genetic diversity in natural populations. To obtain information on whether stakeholders are interested in such a systematic monitoring, what they would expect from such a monitoring and where they see respective caveats, we conducted an online survey, which 138 (42% of those surveyed) Swiss stakeholders answered. We find that Swiss stakeholders are generally aware of the lacking evidence regarding the status of genetic diversity in wild populations and species. Accordingly, most stakeholders are interested in a monitoring of genetic diversity and see opportunities for the application of its results in their work. Nevertheless, stakeholders also expressed concerns regarding financial resources and that the results of a genetic diversity monitoring program would not benefit conservation practice. Our findings highlight the importance of stakeholder engagement and demonstrate the value of a detailed stakeholder analysis prior to developing and implementing a genetic diversity monitoring program. A powerful tool for examining the constellation and interactions of the different stakeholders are social network analyses (SNAs). Finally, it is particularly important to communicate transparently about the possibilities and limitations of a genetic diversity monitoring program as well as to closely involve stakeholders from the beginning to increase the acceptance of genetic diversity monitoring and facilitate its implementation.
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Blom MPK. Opportunities and challenges for high-quality biodiversity tissue archives in the age of long-read sequencing. Mol Ecol 2021; 30:5935-5948. [PMID: 33786900 DOI: 10.1111/mec.15909] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 03/06/2021] [Accepted: 03/22/2021] [Indexed: 12/11/2022]
Abstract
The technological ability to characterize genetic variation at a genome-wide scale provides an unprecedented opportunity to study the genetic underpinnings and evolutionary mechanisms that promote and sustain biodiversity. The transition from short- to long-read sequencing is particularly promising and allows a more holistic view on any changes in genetic diversity across time and space. Long-read sequencing has tremendous potential but sequencing success strongly depends on the long-range integrity of DNA molecules and therefore on the availability of high-quality tissue samples. With the scope of genomic experiments expanding and wild populations simultaneously disappearing at an unprecedented rate, access to high-quality samples may soon be a major concern for many projects. The need for high-quality biodiversity tissue archives is therefore urgent but sampling and preserving high-quality samples is not a trivial exercise. In this review, I will briefly outline how long-read sequencing can benefit the study of molecular ecology, how this will substantially increase the demand for high-quality tissues and why it is challenging to preserve DNA integrity. I will then provide an overview of preservation approaches and end with a call for support to acknowledge the efforts needed to assemble high-quality tissue archives. In doing so, I hope to simultaneously motivate field biologists to expand sampling practices and molecular biologists to develop (cost) efficient guidelines for the sampling and long-term storage of tissues. A concerted, interdisciplinary, effort is needed to catalogue the genetic variation underlying contemporary biodiversity and will eventually provide a critical resource for future studies.
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Affiliation(s)
- Mozes P K Blom
- Leibniz Institut für Evolutions- und Biodiversitätsforschung, Museum für Naturkunde, Berlin, Germany
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