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      Genetic diversity of native and cultivated Ugandan Robusta coffee ( Coffea canephora Pierre ex A. Froehner): Climate influences, breeding potential and diversity conservation

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          Abstract

          Wild genetic resources and their ability to adapt to environmental change are critically important in light of the projected climate change, while constituting the foundation of agricultural sustainability. To address the expected negative effects of climate change on Robusta coffee trees ( Coffea canephora), collecting missions were conducted to explore its current native distribution in Uganda over a broad climatic range. Wild material from seven forests could thus be collected. We used 19 microsatellite (SSR) markers to assess genetic diversity and structure of this material as well as material from two ex-situ collections and a feral population. The Ugandan C. canephora diversity was then positioned relative to the species’ global diversity structure. Twenty-two climatic variables were used to explore variations in climatic zones across the sampled forests. Overall, Uganda’s native C. canephora diversity differs from other known genetic groups of this species. In northwestern (NW) Uganda, four distinct genetic clusters were distinguished being from Zoka, Budongo, Itwara and Kibale forests A large southern-central (SC) cluster included Malabigambo, Mabira, and Kalangala forest accessions, as well as feral and cultivated accessions, suggesting similarity in genetic origin and strong gene flow between wild and cultivated compartments. We also confirmed the introduction of Congolese varieties into the SC region where most Robusta coffee production takes place. Identified populations occurred in divergent environmental conditions and 12 environmental variables significantly explained 16.3% of the total allelic variation across populations. The substantial genetic variation within and between Ugandan populations with different climatic envelopes might contain adaptive diversity to cope with climate change. The accessions that we collected have substantially enriched the diversity hosted in the Ugandan collections and thus contribute to ex situ conservation of this vital genetic resource. However, there is an urgent need to develop strategies to enhance complementary in-situ conservation of Coffea canephora in native forests in northwestern Uganda.

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          Detecting the number of clusters of individuals using the software structure: a simulation study

          The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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            Very high resolution interpolated climate surfaces for global land areas

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              GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update

              Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s D est and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. Contact: rod.peakall@anu.edu.au
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: ResourcesRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Writing – review & editing
                Role: Formal analysisRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Writing – review & editing
                Role: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 February 2021
                2021
                : 16
                : 2
                : e0245965
                Affiliations
                [1 ] Department of Plant Sciences, Centre for Crop Systems Analysis, Wageningen University & Research (WUR), Wageningen, The Netherlands
                [2 ] National Agricultural Research Organization (NARO), Entebbe, Uganda
                [3 ] IRD—UMR DIADE (Univ. Montpellier, CIRAD, IRD), Montpellier, France
                [4 ] EMBRAPA Coffee-INOVACAFE, Lavras, Brazil
                [5 ] Nestlé Research, Tours, France
                [6 ] Meise Botanic Garden, Meise, Belgium
                [7 ] ICCRI, Jember, Indonesia
                [8 ] CNRA, Divo, Côte d’Ivoire
                [9 ] Institute of Agricultural Genetics (AGI)—LMI RICE2, CIRAD—UMR IPME (Univ. Montpellier, CIRAD, IRD), Hanoi, Vietnam
                Chinese Academy of Sciences, CHINA
                Author notes

                Competing Interests: DC and LB are employed by Nestlé Centre Tours. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials.

                Author information
                https://orcid.org/0000-0002-1099-2846
                Article
                PONE-D-20-09152
                10.1371/journal.pone.0245965
                7870046
                33556074
                40822823-e94d-474d-b552-1f2827e8f2f8
                © 2021 Kiwuka et al

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

                History
                : 1 April 2020
                : 12 January 2021
                Page count
                Figures: 4, Tables: 2, Pages: 19
                Funding
                Funded by: Agropolis Fondation – CAPES (Labex Agro:ANR-10-LABX-0001-01 / I-SITE MUSE - ANR-16-IDEX-0006)
                Award ID: 1002-009
                Award Recipient :
                Funded by: Agropolis Fondation (Labex Agro:ANR-10-LABX-0001-01 / I-SITE MUSE - ANR-16-IDEX-0006)
                Award ID: 1402-003
                Funded by: funder-id http://dx.doi.org/10.13039/100004421, World Bank Group;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100007477, Tekke Huizinga Fonds;
                Award Recipient :
                Funded by: Alberta Mennega Stichting
                Award Recipient :
                Funded by: CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior)
                Award Recipient :
                Funded by: NARO (National Agricultural Research Organisation)
                Award Recipient :
                Funded by: Nestlé Research (FR)
                Award Recipient :
                Funded by: Nestlé Research (FR)
                Award Recipient :
                This study was partially supported by two Agropolis Foundation - CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) projects, i.e. ID 1002-009 and ID 1402-003 (CLIMCOFFEA), through the Investissements d’avenir program (Labex Agro:ANR-10-LABX-0001-01), in the framework of I-SITE MUSE (ANR-16-IDEX-0006). CK was funded by a PhD grant from the World Bank through NARO ATAAS project. EG master was funded by the Rinny Huizinga Stichting and the Alberta Mennega Stichting. SOdA was funded by a PhD grant from CAPES. DC and LB are employed by Nestlé Centre Tours. Nestlé Centre Tours provided support in the form of salary for authors DC and LB. The specific roles of these authors are articulated in the ‘author contributions’ section. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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