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Aguirre NC, Villalba PV, García MN, Filippi CV, Rivas JG, Martínez MC, Acuña CV, López AJ, López JA, Pathauer P, Palazzini D, Harrand L, Oberschelp J, Marcó MA, Cisneros EF, Carreras R, Martins Alves AM, Rodrigues JC, Hopp HE, Grattapaglia D, Cappa EP, Paniego NB, Marcucci Poltri SN. Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden). Front Genet 2024; 15:1361418. [PMID: 38606359 PMCID: PMC11008695 DOI: 10.3389/fgene.2024.1361418] [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: 12/26/2023] [Accepted: 02/19/2024] [Indexed: 04/13/2024] Open
Abstract
Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.
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Affiliation(s)
| | | | - Martín Nahuel García
- Instituto de Agrobiotecnología y Biología Molecular, UEDD INTA-CONICET, Hurlingham, Argentina
| | - Carla Valeria Filippi
- Instituto de Agrobiotecnología y Biología Molecular, UEDD INTA-CONICET, Hurlingham, Argentina
- Laboratorio de Bioquímica, Departamento de Biología Vegetal, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay
| | - Juan Gabriel Rivas
- Instituto de Agrobiotecnología y Biología Molecular, UEDD INTA-CONICET, Hurlingham, Argentina
| | - María Carolina Martínez
- Instituto de Agrobiotecnología y Biología Molecular, UEDD INTA-CONICET, Hurlingham, Argentina
| | - Cintia Vanesa Acuña
- Instituto de Agrobiotecnología y Biología Molecular, UEDD INTA-CONICET, Hurlingham, Argentina
| | - Augusto J. López
- Estación Experimental Agropecuaria de Bella Vista, Instituto Nacional de Tecnología Agropecuaria, Bella Vista, Argentina
| | - Juan Adolfo López
- Estación Experimental Agropecuaria de Bella Vista, Instituto Nacional de Tecnología Agropecuaria, Bella Vista, Argentina
| | - Pablo Pathauer
- Instituto de Recursos Biológicos, Instituto Nacional de Tecnología Agropecuaria, Hurlingham, Argentina
| | - Dino Palazzini
- Instituto de Recursos Biológicos, Instituto Nacional de Tecnología Agropecuaria, Hurlingham, Argentina
| | - Leonel Harrand
- Estación Experimental Agropecuaria de Concordia, Instituto Nacional de Tecnología Agropecuaria, Concordia, Argentina
| | - Javier Oberschelp
- Estación Experimental Agropecuaria de Concordia, Instituto Nacional de Tecnología Agropecuaria, Concordia, Argentina
| | - Martín Alberto Marcó
- Estación Experimental Agropecuaria de Concordia, Instituto Nacional de Tecnología Agropecuaria, Concordia, Argentina
| | - Esteban Felipe Cisneros
- Facultad de Ciencias Forestales, Universidad Nacional de Santiago del Estero (UNSE), Santiago del Estero, Argentina
| | - Rocío Carreras
- Facultad de Ciencias Forestales, Universidad Nacional de Santiago del Estero (UNSE), Santiago del Estero, Argentina
| | - Ana Maria Martins Alves
- Centro de Estudos Florestais e Laboratório Associado TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, Lisboa, Portugal
| | - José Carlos Rodrigues
- Centro de Estudos Florestais e Laboratório Associado TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, Lisboa, Portugal
| | - H. Esteban Hopp
- Instituto de Agrobiotecnología y Biología Molecular, UEDD INTA-CONICET, Hurlingham, Argentina
| | - Dario Grattapaglia
- Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Recursos Genéticos e Biotecnologia, Brasilia, Brazil
| | - Eduardo Pablo Cappa
- Instituto de Recursos Biológicos, Instituto Nacional de Tecnología Agropecuaria, Hurlingham, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina
| | - Norma Beatriz Paniego
- Instituto de Agrobiotecnología y Biología Molecular, UEDD INTA-CONICET, Hurlingham, Argentina
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Burridge AJ, Winfield M, Przewieslik-Allen A, Edwards KJ, Siddique I, Barral-Arca R, Griffiths S, Cheng S, Huang Z, Feng C, Dreisigacker S, Bentley AR, Brown-Guedira G, Barker GL. Development of a next generation SNP genotyping array for wheat. PLANT BIOTECHNOLOGY JOURNAL 2024. [PMID: 38520342 DOI: 10.1111/pbi.14341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 03/05/2024] [Accepted: 03/06/2024] [Indexed: 03/25/2024]
Abstract
High-throughput genotyping arrays have provided a cost-effective, reliable and interoperable system for genotyping hexaploid wheat and its relatives. Existing, highly cited arrays including our 35K Wheat Breeder's array and the Illumina 90K array were designed based on a limited amount of varietal sequence diversity and with imperfect knowledge of SNP positions. Recent progress in wheat sequencing has given us access to a vast pool of SNP diversity, whilst technological improvements have allowed us to fit significantly more probes onto a 384-well format Axiom array than previously possible. Here we describe a novel Axiom genotyping array, the 'Triticum aestivum Next Generation' array (TaNG), largely derived from whole genome skim sequencing of 204 elite wheat lines and 111 wheat landraces taken from the Watkins 'Core Collection'. We used a novel haplotype optimization approach to select SNPs with the highest combined varietal discrimination and a design iteration step to test and replace SNPs which failed to convert to reliable markers. The final design with 43 372 SNPs contains a combination of haplotype-optimized novel SNPs and legacy cross-platform markers. We show that this design has an improved distribution of SNPs compared to previous arrays and can be used to generate genetic maps with a significantly higher number of distinct bins than our previous array. We also demonstrate the improved performance of TaNGv1.1 for Genome-wide association studies (GWAS) and its utility for Copy Number Variation (CNV) analysis. The array is commercially available with supporting marker annotations and initial genotyping results freely available.
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Affiliation(s)
| | - Mark Winfield
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - Keith J Edwards
- School of Biological Sciences, University of Bristol, Bristol, UK
| | - Imteaz Siddique
- Thermo Fisher Scientific, 3450 Central Expressway, Santa Clara, CA, USA
| | - Ruth Barral-Arca
- Thermo Fisher Scientific, 3450 Central Expressway, Santa Clara, CA, USA
| | | | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zejian Huang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Cong Feng
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | | | | | - Gina Brown-Guedira
- Plant Science Research Unit, USDA Agricultural Research Service, Raleigh, NC, USA
| | - Gary L Barker
- School of Biological Sciences, University of Bristol, Bristol, UK
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3
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Estravis Barcala M, van der Valk T, Chen Z, Funda T, Chaudhary R, Klingberg A, Fundova I, Suontama M, Hallingbäck H, Bernhardsson C, Nystedt B, Ingvarsson PK, Sherwood E, Street N, Gyllensten U, Nilsson O, Wu HX. Whole-genome resequencing facilitates the development of a 50K single nucleotide polymorphism genotyping array for Scots pine (Pinus sylvestris L.) and its transferability to other pine species. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024; 117:944-955. [PMID: 37947292 DOI: 10.1111/tpj.16535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/12/2023]
Abstract
Scots pine (Pinus sylvestris L.) is one of the most widespread and economically important conifer species in the world. Applications like genomic selection and association studies, which could help accelerate breeding cycles, are challenging in Scots pine because of its large and repetitive genome. For this reason, genotyping tools for conifer species, and in particular for Scots pine, are commonly based on transcribed regions of the genome. In this article, we present the Axiom Psyl50K array, the first single nucleotide polymorphism (SNP) genotyping array for Scots pine based on whole-genome resequencing, that represents both genic and intergenic regions. This array was designed following a two-step procedure: first, 192 trees were sequenced, and a 430K SNP screening array was constructed. Then, 480 samples, including haploid megagametophytes, full-sib family trios, breeding population, and range-wide individuals from across Eurasia were genotyped with the screening array. The best 50K SNPs were selected based on quality, replicability, distribution across the draft genome assembly, balance between genic and intergenic regions, and genotype-environment and genotype-phenotype associations. Of the final 49 877 probes tiled in the array, 20 372 (40.84%) occur inside gene models, while the rest lie in intergenic regions. We also show that the Psyl50K array can yield enough high-confidence SNPs for genetic studies in pine species from North America and Eurasia. This new genotyping tool will be a valuable resource for high-throughput fundamental and applied research of Scots pine and other pine species.
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Affiliation(s)
- Maximiliano Estravis Barcala
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Tom van der Valk
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Zhiqiang Chen
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Tomas Funda
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Rajiv Chaudhary
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Adam Klingberg
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, Umeå, Sweden
- Skogforsk, Sävar, Uppsala, Sweden
| | - Irena Fundova
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, Umeå, Sweden
| | | | | | - Carolina Bernhardsson
- Department of Organismal Biology, Human Evolution, Uppsala University, Uppsala, Sweden
- Department of Plant Biology, Linnean Centre for Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Björn Nystedt
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Pär K Ingvarsson
- Department of Plant Biology, Linnean Centre for Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Ellen Sherwood
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
- Department of Gene Technology, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Nathaniel Street
- Department of Plant Physiology, Umeå Plant Science Centre (UPSC), Umeå University, Umeå, Sweden
| | - Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Ove Nilsson
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Harry X Wu
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre (UPSC), Swedish University of Agricultural Sciences, Umeå, Sweden
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4
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Wood Formation under Changing Environment: Omics Approaches to Elucidate the Mechanisms Driving the Early-to-Latewood Transition in Conifers. FORESTS 2022. [DOI: 10.3390/f13040608] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The global change scenarios highlight the urgency of clarifying the mechanisms driving the determination of wood traits in forest trees. Coniferous xylem is characterized by the alternation between earlywood (EW) and latewood (LW), on which proportions the wood density depend, one of the most important mechanical xylem qualities. However, the molecular mechanisms triggering the transition between the production of cells with the typical features of EW to the LW are still far from being completely elucidated. The increasing availability of omics resources for conifers, e.g., genomes and transcriptomes, would lay the basis for the comprehension of wood formation dynamics, boosting both breeding and gene-editing approaches. This review is intended to introduce the importance of wood formation dynamics and xylem traits of conifers in a changing environment. Then, an up-to-date overview of the omics resources available for conifers was reported, focusing on both genomes and transcriptomes. Later, an analysis of wood formation studies using omics approaches was conducted, with the aim of elucidating the main metabolic pathways involved in EW and LW determination. Finally, the future perspectives and the urgent needs on this research topic were highlighted.
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Kastally C, Niskanen AK, Perry A, Kujala ST, Avia K, Cervantes S, Haapanen M, Kesälahti R, Kumpula TA, Mattila TM, Ojeda DI, Tyrmi JS, Wachowiak W, Cavers S, Kärkkäinen K, Savolainen O, Pyhäjärvi T. Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 109:1337-1350. [PMID: 34897859 PMCID: PMC9303803 DOI: 10.1111/tpj.15628] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/05/2021] [Accepted: 12/02/2021] [Indexed: 06/14/2023]
Abstract
Pinus sylvestris (Scots pine) is the most widespread coniferous tree in the boreal forests of Eurasia, with major economic and ecological importance. However, its large and repetitive genome presents a challenge for conducting genome-wide analyses such as association studies, genetic mapping and genomic selection. We present a new 50K single-nucleotide polymorphism (SNP) genotyping array for Scots pine research, breeding and other applications. To select the SNP set, we first genotyped 480 Scots pine samples on a 407 540 SNP screening array and identified 47 712 high-quality SNPs for the final array (called 'PiSy50k'). Here, we provide details of the design and testing, as well as allele frequency estimates from the discovery panel, functional annotation, tissue-specific expression patterns and expression level information for the SNPs or corresponding genes, when available. We validated the performance of the PiSy50k array using samples from Finland and Scotland. Overall, 39 678 (83.2%) SNPs showed low error rates (mean = 0.9%). Relatedness estimates based on array genotypes were consistent with the expected pedigrees, and the level of Mendelian error was negligible. In addition, array genotypes successfully discriminate between Scots pine populations of Finnish and Scottish origins. The PiSy50k SNP array will be a valuable tool for a wide variety of future genetic studies and forestry applications.
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Affiliation(s)
- Chedly Kastally
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Alina K. Niskanen
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Annika Perry
- UK Centre for Ecology & HydrologyBush EstatePenicuikMidlothianEH26 0QBUK
| | - Sonja T. Kujala
- Natural Resources Institute Finland (Luke)Paavo Havaksen tie 390570OuluFinland
| | - Komlan Avia
- Université de StrasbourgINRAESVQV UMR‐A 1131F‐68000ColmarFrance
| | - Sandra Cervantes
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Matti Haapanen
- Natural Resources Institute Finland (Luke)Latokartanonkaari 9FI‐00790HelsinkiFinland
| | - Robert Kesälahti
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Timo A. Kumpula
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Tiina M. Mattila
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
- Department of Organismal BiologyEBCUppsala UniversityNorbyvägen 18 AUppsala752 36Sweden
| | - Dario I. Ojeda
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
- Norwegian Institute of Bioeconomy ResearchP.O. Box 115Ås1431Norway
| | - Jaakko S. Tyrmi
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Witold Wachowiak
- Institute of Environmental BiologyFaculty of BiologyAdam Mickiewicz University in PoznańUniwersytetu Poznańskiego 661‐614PoznańPoland
| | - Stephen Cavers
- UK Centre for Ecology & HydrologyBush EstatePenicuikMidlothianEH26 0QBUK
| | - Katri Kärkkäinen
- Natural Resources Institute Finland (Luke)Paavo Havaksen tie 390570OuluFinland
| | - Outi Savolainen
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Tanja Pyhäjärvi
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
- Department of Forest SciencesUniversity of HelsinkiP.O. Box 2700014HelsinkiFinland
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6
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Development and Validation of a 36K SNP Array for Radiata Pine (Pinus radiata D.Don). FORESTS 2022. [DOI: 10.3390/f13020176] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Radiata pine (Pinus radiata D.Don) is one of the world’s most domesticated pines and a key economic species in New Zealand. Thus, the development of genomic resources for radiata pine has been a high priority for both research and commercial breeding. Leveraging off a previously developed exome capture panel, we tested the performance of 438,744 single nucleotide polymorphisms (SNPs) on a screening array (NZPRAD01) and then selected 36,285 SNPs for a final genotyping array (NZPRAD02). These SNPs aligned to 15,372 scaffolds from the Pinus taeda L. v. 1.01e assembly, and 20,039 contigs from the radiata pine transcriptome assembly. The genotyping array was tested on more than 8000 samples, including material from archival progenitors, current breeding trials, nursery material, clonal lines, and material from Australia. Our analyses indicate that the array is performing well, with sample call rates greater than 98% and a sample reproducibility of 99.9%. Genotyping in two linkage mapping families indicated that the SNPs are well distributed across the 12 linkage groups. Using genotypic data from this array, we were also able to differentiate representatives of the five recognized provenances of radiata pine, Año Nuevo, Monterey, Cambria, Cedros and Guadalupe. Furthermore, principal component analysis of genotyped trees revealed clear patterns of population structure, with the primary axis of variation driven by provenance ancestry and the secondary axis reflecting breeding activities. This represents the first commercial use of genomics in a radiata pine breeding program.
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Perry A, Wachowiak W, Beaton J, Iason G, Cottrell J, Cavers S. Identifying and testing marker‐trait associations for growth and phenology in three pine species: implications for genomic prediction. Evol Appl 2022; 15:330-348. [PMID: 35233251 PMCID: PMC8867712 DOI: 10.1111/eva.13345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 12/08/2021] [Accepted: 12/09/2021] [Indexed: 12/02/2022] Open
Abstract
In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker–trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 single nucleotide polymorphisms (SNPs) from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034–0.037) and negatively associated with budburst timing at the other (YA: r = −0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments.
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Affiliation(s)
- Annika Perry
- UK Centre for Ecology & Hydrology Edinburgh Penicuik Midlothian EH26 0QB UK
| | - Witold Wachowiak
- Institute of Environmental Biology Faculty of Biology Adam Mickiewicz University Poznań Poland
| | - Joan Beaton
- James Hutton Institute Craigiebuckler, Aberdeen AB15 8QH UK
| | - Glenn Iason
- James Hutton Institute Craigiebuckler, Aberdeen AB15 8QH UK
| | - Joan Cottrell
- Northern Research Station, Forest Research Roslin EH25 9SY UK
| | - Stephen Cavers
- UK Centre for Ecology & Hydrology Edinburgh Penicuik Midlothian EH26 0QB UK
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8
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Ahmar S, Ballesta P, Ali M, Mora-Poblete F. Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing. Int J Mol Sci 2021; 22:10583. [PMID: 34638922 PMCID: PMC8508745 DOI: 10.3390/ijms221910583] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 12/23/2022] Open
Abstract
Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.
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Affiliation(s)
- Sunny Ahmar
- Institute of Biological Sciences, University of Talca, 1 Poniente 1141, Talca 3460000, Chile;
| | - Paulina Ballesta
- The National Fund for Scientific and Technological Development, Av. del Agua 3895, Talca 3460000, Chile
| | - Mohsin Ali
- Department of Forestry and Range Management, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan;
| | - Freddy Mora-Poblete
- Institute of Biological Sciences, University of Talca, 1 Poniente 1141, Talca 3460000, Chile;
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9
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Cervantes S, Vuosku J, Pyhäjärvi T. Atlas of tissue-specific and tissue-preferential gene expression in ecologically and economically significant conifer Pinus sylvestris. PeerJ 2021; 9:e11781. [PMID: 34466281 PMCID: PMC8380025 DOI: 10.7717/peerj.11781] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 06/24/2021] [Indexed: 12/13/2022] Open
Abstract
Despite their ecological and economical importance, conifers genomic resources are limited, mainly due to the large size and complexity of their genomes. Additionally, the available genomic resources lack complete structural and functional annotation. Transcriptomic resources have been commonly used to compensate for these deficiencies, though for most conifer species they are limited to a small number of tissues, or capture only a fraction of the genes present in the genome. Here we provide an atlas of gene expression patterns for conifer Pinus sylvestris across five tissues: embryo, megagametophyte, needle, phloem and vegetative bud. We used a wide range of tissues and focused our analyses on the expression profiles of genes at tissue level. We provide comprehensive information of the per-tissue normalized expression level, indication of tissue preferential upregulation and tissue-specificity of expression. We identified a total of 48,001 tissue preferentially upregulated and tissue specifically expressed genes, of which 28% have annotation in the Swiss-Prot database. Even though most of the putative genes identified do not have functional information in current biological databases, the tissue-specific patterns discovered provide valuable information about their potential functions for further studies, as for example in the areas of plant physiology, population genetics and genomics in general. As we provide information on tissue specificity at both diploid and haploid life stages, our data will also contribute to the understanding of evolutionary rates of different tissue types and ploidy levels.
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Affiliation(s)
- Sandra Cervantes
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Jaana Vuosku
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland
| | - Tanja Pyhäjärvi
- Department of Ecology and Genetics, University of Oulu, Oulu, Finland.,Department of Forest Sciences, Faculty of Agriculture and Forestry, University of Helsinki, Helsinki, Finland
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10
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Olsson S, Lorenzo Z, Zabal-Aguirre M, Piotti A, Vendramin GG, González-Martínez SC, Grivet D. Evolutionary history of the mediterranean Pinus halepensis-brutia species complex using gene-resequencing and transcriptomic approaches. PLANT MOLECULAR BIOLOGY 2021; 106:367-380. [PMID: 33934278 DOI: 10.1007/s11103-021-01155-7] [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: 12/14/2020] [Accepted: 04/22/2021] [Indexed: 06/12/2023]
Abstract
Complementary gene-resequencing and transcriptomic approaches reveal contrasted evolutionary histories in a species complex. Pinus halepensis and Pinus brutia are closely related species that can intercross, but occupy different geographical ranges and bioclimates. To study the evolution of this species complex and to provide genomic resources for further research, we produce and analyze two new complementary sets of genetic resources: (i) a set of 172 re-sequenced genomic target loci analyzed in 45 individuals, and (ii) a set of 11 transcriptome assemblies. These two datasets provide insights congruent with previous studies: P. brutia displays high level of genetic diversity and no genetic sub-structure, while P. halepensis shows three main genetic clusters, the western Mediterranean and North African clusters displaying much lower genetic diversity than the eastern Mediterranean cluster, the latter cluster having similar genetic diversity to P. brutia. In addition, these datasets provide new insights on the timing of the species-complex history: the two species would have split at the end of the tertiary, and the changing climatic conditions of the Mediterranean region at the end of the Tertiary-beginning of the Quaternary, together with the distinct species tolerance to harsh climatic conditions would have resulted in different geographic distributions, demographic histories and genetic patterns of the two pines. The multiple glacial-interglacial cycles during the Quaternary would have led to the expansion of P. brutia in the Middle East, while P. halepensis would have been through bottlenecks. The last glaciations, from 0.6 Mya on, would have affected further the Western genetic pool of P. halepensis.
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Affiliation(s)
- Sanna Olsson
- Department of Forest Ecology & Genetics, Forest Research Centre, INIA-CSIC, Carretera de la Coruña km 7.5, 28040, Madrid, Spain.
| | - Zaida Lorenzo
- Department of Forest Ecology & Genetics, Forest Research Centre, INIA-CSIC, Carretera de la Coruña km 7.5, 28040, Madrid, Spain
| | - Mario Zabal-Aguirre
- Department of Forest Ecology & Genetics, Forest Research Centre, INIA-CSIC, Carretera de la Coruña km 7.5, 28040, Madrid, Spain
| | - Andrea Piotti
- Institute of Biosciences and Bioresources, Division of Florence, National Research Council, 50019, Sesto Fiorentino, Florence, Italy
| | - Giovanni G Vendramin
- Institute of Biosciences and Bioresources, Division of Florence, National Research Council, 50019, Sesto Fiorentino, Florence, Italy
| | - Santiago C González-Martínez
- UMR BIOGECO, INRAE, University of Bordeaux, 33610, Cestas, France
- Sustainable Forest Management Research Institute, INIA - University of Valladolid, Avda. Madrid 44, 34004, Palencia, Spain
| | - Delphine Grivet
- Department of Forest Ecology & Genetics, Forest Research Centre, INIA-CSIC, Carretera de la Coruña km 7.5, 28040, Madrid, Spain.
- Sustainable Forest Management Research Institute, INIA - University of Valladolid, Avda. Madrid 44, 34004, Palencia, Spain.
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11
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Caballero M, Lauer E, Bennett J, Zaman S, McEvoy S, Acosta J, Jackson C, Townsend L, Eckert A, Whetten RW, Loopstra C, Holliday J, Mandal M, Wegrzyn JL, Isik F. Toward genomic selection in Pinus taeda: Integrating resources to support array design in a complex conifer genome. APPLICATIONS IN PLANT SCIENCES 2021; 9:e11439. [PMID: 34268018 PMCID: PMC8272584 DOI: 10.1002/aps3.11439] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 05/21/2021] [Indexed: 05/13/2023]
Abstract
PREMISE An informatics approach was used for the construction of an Axiom genotyping array from heterogeneous, high-throughput sequence data to assess the complex genome of loblolly pine (Pinus taeda). METHODS High-throughput sequence data, sourced from exome capture and whole genome reduced-representation approaches from 2698 trees across five sequence populations, were analyzed with the improved genome assembly and annotation for the loblolly pine. A variant detection, filtering, and probe design pipeline was developed to detect true variants across and within populations. From 8.27 million variants, a total of 642,275 were evaluated and 423,695 of those were screened across a range-wide population. RESULTS The final informatics and screening approach delivered an Axiom array representing 46,439 high-confidence variants to the forest tree breeding and genetics community. Based on the annotated reference genome, 34% were located in or directly upstream or downstream of genic regions. DISCUSSION The Pita50K array represents a genome-wide resource developed from sequence data for an economically important conifer, loblolly pine. It uniquely integrates independent projects that assessed trees sampled across the native range. The challenges associated with the large and repetitive genome are addressed in the development of this resource.
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Affiliation(s)
- Madison Caballero
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut06269USA
| | - Edwin Lauer
- Department of Forestry and Environmental ResourcesNorth Carolina State UniversityRaleighNorth Carolina27695USA
| | - Jeremy Bennett
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut06269USA
| | - Sumaira Zaman
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut06269USA
| | - Susan McEvoy
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut06269USA
| | - Juan Acosta
- Department of Forestry and Environmental ResourcesNorth Carolina State UniversityRaleighNorth Carolina27695USA
| | - Colin Jackson
- Department of Forestry and Environmental ResourcesNorth Carolina State UniversityRaleighNorth Carolina27695USA
| | - Laura Townsend
- Department of Forestry and Environmental ResourcesNorth Carolina State UniversityRaleighNorth Carolina27695USA
| | - Andrew Eckert
- Department of BiologyVirginia Commonwealth UniversityRichmondVirginia23284USA
| | - Ross W. Whetten
- Department of Forestry and Environmental ResourcesNorth Carolina State UniversityRaleighNorth Carolina27695USA
| | - Carol Loopstra
- Department of Ecology and Conservation BiologyTexas A&M UniversityCollege StationTexas77843USA
| | - Jason Holliday
- Department of Forest Resources and Environmental ConservationVirginia Polytechnic Institute and State UniversityBlacksburgVirginia24061USA
| | - Mihir Mandal
- Department of BiologyClaflin UniversityOrangeburgSouth Carolina29115USA
| | - Jill L. Wegrzyn
- Department of Ecology and Evolutionary BiologyUniversity of ConnecticutStorrsConnecticut06269USA
| | - Fikret Isik
- Department of Forestry and Environmental ResourcesNorth Carolina State UniversityRaleighNorth Carolina27695USA
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12
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Candidate Genes for the High-Altitude Adaptations of Two Mountain Pine Taxa. Int J Mol Sci 2021; 22:ijms22073477. [PMID: 33801727 PMCID: PMC8036860 DOI: 10.3390/ijms22073477] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 03/23/2021] [Accepted: 03/24/2021] [Indexed: 01/26/2023] Open
Abstract
Mountain plants, challenged by vegetation time contractions and dynamic changes in environmental conditions, developed adaptations that help them to balance their growth, reproduction, survival, and regeneration. However, knowledge regarding the genetic basis of species adaptation to higher altitudes remain scarce for most plant species. Here, we attempted to identify such corresponding genomic regions of high evolutionary importance in two closely related European pines, Pinus mugo and P. uncinata, contrasting them with a reference lowland relative—P. sylvestris. We genotyped 438 samples at thousands of single nucleotide polymorphism (SNP) markers, tested their genetic differentiation and population structure followed by outlier detection and gene ontology annotations. Markers clearly differentiated the species and uncovered patterns of population structure in two of them. In P. uncinata three Pyrenean sites were grouped together, while two outlying populations constituted a separate cluster. In P. sylvestris, Spanish population appeared distinct from the remaining four European sites. Between mountain pines and the reference species, 35 candidate genes for altitude-dependent selection were identified, including such encoding proteins responsible for photosynthesis, photorespiration and cell redox homeostasis, regulation of transcription, and mRNA processing. In comparison between two mountain pines, 75 outlier SNPs were found in proteins involved mainly in the gene expression and metabolism.
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13
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Bernhardsson C, Zan Y, Chen Z, Ingvarsson PK, Wu HX. Development of a highly efficient 50K single nucleotide polymorphism genotyping array for the large and complex genome of Norway spruce (Picea abies L. Karst) by whole genome resequencing and its transferability to other spruce species. Mol Ecol Resour 2020; 21:880-896. [PMID: 33179386 PMCID: PMC7984398 DOI: 10.1111/1755-0998.13292] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 10/23/2020] [Accepted: 11/04/2020] [Indexed: 12/30/2022]
Abstract
Norway spruce (Picea abies L. Karst) is one of the most important forest tree species with significant economic and ecological impact in Europe. For decades, genomic and genetic studies on Norway spruce have been challenging due to the large and repetitive genome (19.6 Gb with more than 70% being repetitive). To accelerate genomic studies, including population genetics, genome‐wide association studies (GWAS) and genomic selection (GS), in Norway spruce and related species, we here report on the design and performance of a 50K single nucleotide polymorphism (SNP) genotyping array for Norway spruce. The array is developed based on whole genome resequencing (WGS), making it the first WGS‐based SNP array in any conifer species so far. After identifying SNPs using genome resequencing data from 29 trees collected in northern Europe, we adopted a two‐step approach to design the array. First, we built a 450K screening array and used this to genotype a population of 480 trees sampled from both natural and breeding populations across the Norway spruce distribution range. These samples were then used to select high‐confidence probes that were put on the final 50K array. The SNPs selected are distributed over 45,552 scaffolds from the P. abies version 1.0 genome assembly and target 19,954 unique gene models with an even coverage of the 12 linkage groups in Norway spruce. We show that the array has a 99.5% probe specificity, >98% Mendelian allelic inheritance concordance, an average sample call rate of 96.30% and an SNP call rate of 98.90% in family trios and haploid tissues. We also observed that 23,797 probes (50%) could be identified with high confidence in three other spruce species (white spruce [Picea glauca], black spruce [P. mariana] and Sitka spruce [P. sitchensis]). The high‐quality genotyping array will be a valuable resource for genetic and genomic studies in Norway spruce as well as in other conifer species of the same genus.
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Affiliation(s)
- Carolina Bernhardsson
- Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden.,Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Yanjun Zan
- Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Science, Umeå, Sweden
| | - Zhiqiang Chen
- Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Science, Umeå, Sweden
| | - Pär K Ingvarsson
- Linnean Centre for Plant Biology, Department of Plant Biology, Uppsala BioCenter, Swedish University of Agricultural Science, Uppsala, Sweden
| | - Harry X Wu
- Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Science, Umeå, Sweden.,Beijing Advanced Innovation Centre for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China.,Black Mountain Laboratory, CSIRO National Research Collection Australia, Canberra, ACT, Australia
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