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Tumas H, Ilska JJ, Gérardi S, Laroche J, A’Hara S, Boyle B, Janes M, McLean P, Lopez G, Lee SJ, Cottrell J, Gorjanc G, Bousquet J, Woolliams JA, MacKay JJ. High-density genetic linkage mapping in Sitka spruce advances the integration of genomic resources in conifers. G3 (BETHESDA, MD.) 2024; 14:jkae020. [PMID: 38366548 PMCID: PMC10989875 DOI: 10.1093/g3journal/jkae020] [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: 12/04/2023] [Accepted: 01/03/2024] [Indexed: 02/18/2024]
Abstract
In species with large and complex genomes such as conifers, dense linkage maps are a useful resource for supporting genome assembly and laying the genomic groundwork at the structural, populational, and functional levels. However, most of the 600+ extant conifer species still lack extensive genotyping resources, which hampers the development of high-density linkage maps. In this study, we developed a linkage map relying on 21,570 single nucleotide polymorphism (SNP) markers in Sitka spruce (Picea sitchensis [Bong.] Carr.), a long-lived conifer from western North America that is widely planted for productive forestry in the British Isles. We used a single-step mapping approach to efficiently combine RAD-seq and genotyping array SNP data for 528 individuals from 2 full-sib families. As expected for spruce taxa, the saturated map contained 12 linkages groups with a total length of 2,142 cM. The positioning of 5,414 unique gene coding sequences allowed us to compare our map with that of other Pinaceae species, which provided evidence for high levels of synteny and gene order conservation in this family. We then developed an integrated map for P. sitchensis and Picea glauca based on 27,052 markers and 11,609 gene sequences. Altogether, these 2 linkage maps, the accompanying catalog of 286,159 SNPs and the genotyping chip developed, herein, open new perspectives for a variety of fundamental and more applied research objectives, such as for the improvement of spruce genome assemblies, or for marker-assisted sustainable management of genetic resources in Sitka spruce and related species.
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Affiliation(s)
- Hayley Tumas
- Department of Biology, University of Oxford, Oxford OX1 3RB, UK
| | - Joana J Ilska
- The Roslin Institute, Royal (Dick) School of Veterinary Science, University of Edinburgh, Midlothian EH25 9RG, UK
| | - Sebastien Gérardi
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, QC GIV 0A6, Canada
- Institute for Systems and Integrative Biology, Université Laval, Québec, QC GIV 0A6, Canada
| | - Jerome Laroche
- Institute for Systems and Integrative Biology, Université Laval, Québec, QC GIV 0A6, Canada
| | - Stuart A’Hara
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Brian Boyle
- Institute for Systems and Integrative Biology, Université Laval, Québec, QC GIV 0A6, Canada
| | - Mateja Janes
- The Roslin Institute, Royal (Dick) School of Veterinary Science, University of Edinburgh, Midlothian EH25 9RG, UK
| | - Paul McLean
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Gustavo Lopez
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Steve J Lee
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Joan Cottrell
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Gregor Gorjanc
- The Roslin Institute, Royal (Dick) School of Veterinary Science, University of Edinburgh, Midlothian EH25 9RG, UK
| | - Jean Bousquet
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, QC GIV 0A6, Canada
- Institute for Systems and Integrative Biology, Université Laval, Québec, QC GIV 0A6, Canada
| | - John A Woolliams
- The Roslin Institute, Royal (Dick) School of Veterinary Science, University of Edinburgh, Midlothian EH25 9RG, UK
| | - John J MacKay
- Department of Biology, University of Oxford, Oxford OX1 3RB, UK
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Polyploid SNP Genotyping Using the MassARRAY System. Methods Mol Biol 2023; 2638:93-113. [PMID: 36781637 DOI: 10.1007/978-1-0716-3024-2_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
Molecular marker discovery and genotyping are major challenges in polyploid breeding programs incorporating molecular biology tools. In this context, this work describes a method for single nucleotide polymorphism (SNP) genotyping in polyploid crops using matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry, the MassARRAY System.
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Gamal El‐Dien O, Shalev TJ, Yuen MMS, Stirling R, Daniels LD, Breinholt JW, Neves LG, Kirst M, Van der Merwe L, Yanchuk AD, Ritland C, Russell JH, Bohlmann J. Genomic selection reveals hidden relatedness and increased breeding efficiency in western redcedar polycross breeding. Evol Appl 2022; 15:1291-1312. [PMID: 36051463 PMCID: PMC9423091 DOI: 10.1111/eva.13463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 06/19/2022] [Accepted: 07/26/2022] [Indexed: 11/29/2022] Open
Abstract
Western redcedar (WRC) is an ecologically and economically important forest tree species characterized by low genetic diversity with high self-compatibility and high heartwood durability. Using sequence capture genotyping of target genic and non-genic regions, we genotyped 44 parent trees and 1520 offspring trees representing 26 polycross (PX) families collected from three progeny test sites using 45,378 SNPs. Trees were phenotyped for eight traits related to growth, heartwood and foliar chemistry associated with wood durability and deer browse resistance. We used the genomic realized relationship matrix for paternity assignment, maternal pedigree correction, and to estimate genetic parameters. We compared genomics-based (GBLUP) and two pedigree-based (ABLUP: polycross and reconstructed full-sib [FS] pedigrees) models. Models were extended to estimate dominance genetic effects. Pedigree reconstruction revealed significant unequal male contribution and separated the 26 PX families into 438 FS families. Traditional maternal PX pedigree analysis resulted in up to 51% overestimation in genetic gain and 44% in diversity. Genomic analysis resulted in up to 22% improvement in offspring breeding value (BV) theoretical accuracy, 35% increase in expected genetic gain for forward selection, and doubled selection intensity for backward selection. Overall, all traits showed low to moderate heritability (0.09-0.28), moderate genotype by environment interaction (type-B genetic correlation: 0.51-0.80), low to high expected genetic gain (6.01%-55%), and no significant negative genetic correlation reflecting no large trade-offs for multi-trait selection. Only three traits showed a significant dominance effect. GBLUP resulted in smaller but more accurate heritability estimates for five traits, but larger estimates for the wood traits. Comparison between all, genic-coding, genic-non-coding and intergenic SNPs showed little difference in genetic estimates. In summary, we show that GBLUP overcomes the PX limitations, successfully captures expected historical and hidden relatedness as well as linkage disequilibrium (LD), and results in increased breeding efficiency in WRC.
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Affiliation(s)
- Omnia Gamal El‐Dien
- Michael Smith LaboratoriesUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Pharmacognosy Department, Faculty of PharmacyAlexandria UniversityAlexandriaEgypt
| | - Tal J. Shalev
- Michael Smith LaboratoriesUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Macaire M. S. Yuen
- Michael Smith LaboratoriesUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | | | - Lori D. Daniels
- Department of Forest and Conservation SciencesUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Jesse W. Breinholt
- Rapid GenomicsGainesvilleFloridaUSA
- Intermountain HealthcareIntermountain Precision GenomicsSt. GeorgeUtahUSA
| | | | - Matias Kirst
- School of Forest, Fisheries and Geomatic SciencesUniversity of FloridaGainesvilleFloridaUSA
| | - Lise Van der Merwe
- British Columbia Ministry of ForestsLands and Natural Resource Operations and Rural DevelopmentVictoriaBritish ColumbiaCanada
| | - Alvin D. Yanchuk
- British Columbia Ministry of ForestsLands and Natural Resource Operations and Rural DevelopmentVictoriaBritish ColumbiaCanada
| | - Carol Ritland
- Michael Smith LaboratoriesUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of Forest and Conservation SciencesUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - John H. Russell
- British Columbia Ministry of ForestsLands and Natural Resource Operations and Rural DevelopmentVictoriaBritish ColumbiaCanada
| | - Joerg Bohlmann
- Michael Smith LaboratoriesUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of Forest and Conservation SciencesUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of BotanyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
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Beaulieu J, Lenz P, Bousquet J. Metadata analysis indicates biased estimation of genetic parameters and gains using conventional pedigree information instead of genomic-based approaches in tree breeding. Sci Rep 2022; 12:3933. [PMID: 35273188 PMCID: PMC8913692 DOI: 10.1038/s41598-022-06681-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 01/31/2022] [Indexed: 11/09/2022] Open
Abstract
Forest tree improvement helps provide adapted planting stock to ensure growth productivity, fibre quality and carbon sequestration through reforestation and afforestation activities. However, there is increasing doubt that conventional pedigree provides the most accurate estimates for selection and prediction of performance of improved planting stock. When the additive genetic relationships among relatives is estimated using pedigree information, it is not possible to take account of Mendelian sampling due to the random segregation of parental alleles. The use of DNA markers distributed genome-wide (multi-locus genotypes) makes it possible to estimate the realized additive genomic relationships, which takes account of the Mendelian sampling and possible pedigree errors. We reviewed a series of papers on conifer and broadleaf tree species in which both pedigree-based and marker-based estimates of genetic parameters have been reported. Using metadata analyses, we show that for heritability and genetic gains, the estimates obtained using only the pedigree information are generally biased upward compared to those obtained using DNA markers distributed genome-wide, and that genotype-by-environment (GxE) interaction can be underestimated for low to moderate heritability traits. As high-throughput genotyping becomes economically affordable, we recommend expanding the use of genomic selection to obtain more accurate estimates of genetic parameters and gains.
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Affiliation(s)
- Jean Beaulieu
- Canada Research Chair in Forest Genomics, Institute of Systems and Integrative Biology and Centre for Forest Research, Université Laval, 1030 Avenue de la Médecine, Quebec, QC, G1V 0A6, Canada.
| | - Patrick Lenz
- Canada Research Chair in Forest Genomics, Institute of Systems and Integrative Biology and Centre for Forest Research, Université Laval, 1030 Avenue de la Médecine, Quebec, QC, G1V 0A6, Canada.,Natural Resources Canada, Canadian Wood Fibre Centre, Quebec, QC, G1V 4C7, Canada
| | - Jean Bousquet
- Canada Research Chair in Forest Genomics, Institute of Systems and Integrative Biology and Centre for Forest Research, Université Laval, 1030 Avenue de la Médecine, Quebec, QC, G1V 0A6, Canada
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SNP-based analysis reveals unexpected features of genetic diversity, parental contributions and pollen contamination in a white spruce breeding program. Sci Rep 2021; 11:4990. [PMID: 33654140 PMCID: PMC7925517 DOI: 10.1038/s41598-021-84566-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 02/15/2021] [Indexed: 01/31/2023] Open
Abstract
Accurate monitoring of genetic diversity levels of seedlots and mating patterns of parents from seed orchards are crucial to ensure that tree breeding programs are long-lasting and will deliver anticipated genetic gains. We used SNP genotyping to characterize founder trees, five bulk seed orchard seedlots, and trees from progeny trials to assess pollen contamination and the impact of severe roguing on genetic diversity and parental contributions in a first-generation open-pollinated white spruce clonal seed orchard. After severe roguing (eliminating 65% of the seed orchard trees), we found a slight reduction in the Shannon Index and a slightly negative inbreeding coefficient, but a sharp decrease in effective population size (eightfold) concomitant with sharp increase in coancestry (eightfold). Pedigree reconstruction showed unequal parental contributions across years with pollen contamination levels between 12 and 51% (average 27%) among seedlots, and 7-68% (average 30%) among individual genotypes within a seedlot. These contamination levels were not correlated with estimates obtained using pollen flight traps. Levels of pollen contamination also showed a Pearson's correlation of 0.92 with wind direction, likely from a pollen source 1 km away from the orchard under study. The achievement of 5% genetic gain in height at rotation through eliminating two-thirds of the orchard thus generated a loss in genetic diversity as determined by the reduction in effective population size. The use of genomic profiles revealed the considerable impact of roguing on genetic diversity, and pedigree reconstruction of full-sib families showed the unanticipated impact of pollen contamination from a previously unconsidered source.
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Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce. Heredity (Edinb) 2020; 124:562-578. [PMID: 31969718 PMCID: PMC7080810 DOI: 10.1038/s41437-019-0290-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 11/29/2019] [Accepted: 12/08/2019] [Indexed: 11/08/2022] Open
Abstract
Genomic selection (GS) has a large potential for improving the prediction accuracy of breeding values and significantly reducing the length of breeding cycles. In this context, the choice of mating designs becomes critical to improve the efficiency of breeding operations and to obtain the largest genetic gains per time unit. Polycross mating designs have been traditionally used in tree and plant breeding to perform backward selection of the female parents. The possibility to use genetic markers for paternity identification and for building genomic prediction models should allow for a broader use of polycross tests in forward selection schemes. We compared the accuracies of genomic predictions of offspring's breeding values from a polycross and a full-sib (partial diallel) mating design with similar genetic background in white spruce (Picea glauca). Trees were phenotyped for growth and wood quality traits, and genotyped for 4092 SNPs representing as many gene loci distributed across the 12 spruce chromosomes. For the polycross progeny test, heritability estimates were smaller, but more precise using the genomic BLUP (GBLUP) model as compared with pedigree-based models accounting for the maternal pedigree or for the reconstructed full pedigree. Cross-validations showed that GBLUP predictions were 22-52% more accurate than predictions based on the maternal pedigree, and 5-7% more accurate than predictions using the reconstructed full pedigree. The accuracies of GBLUP predictions were high and in the same range for most traits between the polycross (0.61-0.70) and full-sib progeny tests (0.61-0.74). However, higher genetic gains per time unit were expected from the polycross mating design given the shorter time needed to conduct crosses. Considering the operational advantages of the polycross design in terms of easier handling of crosses and lower associated costs for test establishment, we believe that this mating scheme offers great opportunities for the development and operational application of forward GS.
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Azaiez A, Pavy N, Gérardi S, Laroche J, Boyle B, Gagnon F, Mottet MJ, Beaulieu J, Bousquet J. A catalog of annotated high-confidence SNPs from exome capture and sequencing reveals highly polymorphic genes in Norway spruce (Picea abies). BMC Genomics 2018; 19:942. [PMID: 30558528 PMCID: PMC6296092 DOI: 10.1186/s12864-018-5247-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 11/14/2018] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Norway spruce [Picea abies (L.) Karst.] is ecologically and economically one of the most important conifer worldwide. Our main goal was to develop a large catalog of annotated high confidence gene SNPs that should sustain the development of genomic tools for the conservation of natural and domesticated genetic diversity resources, and hasten tree breeding efforts in this species. RESULTS Targeted sequencing was achieved by capturing P. abies exome with probes previously designed from the sequenced transcriptome of white spruce (Picea glauca (Moench) Voss). Capture efficiency was high (74.5%) given a high level of exome conservation between the two species. Using stringent criteria, we delimited a set of 61,771 high-confidence SNPs across 13,543 genes. To validate SNPs, a high-throughput genotyping array was developed for a subset of 5571 predicted SNPs representing as many different gene loci, and was used to genotype over 1000 trees. The estimated true positive rate of the resource was 84.2%, which was comparable with the genotyping success rate obtained for P. abies control SNPs recycled from previous genotyping efforts. We also analyzed SNP abundance across various gene functional categories. Several GO terms and gene families involved in stress response were found over-represented in highly polymorphic genes. CONCLUSION The annotated high-confidence SNP catalog developed herein represents a valuable genomic resource, being representative of over 13 K genes distributed across the P. abies genome. This resource should serve a variety of population genomics and breeding applications in Norway spruce.
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Affiliation(s)
- Aïda Azaiez
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, Québec G1V 0A6 Canada
- Institute of Integrative Biology and Systems, Université Laval, Québec, Québec G1V 0A6 Canada
| | - Nathalie Pavy
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, Québec G1V 0A6 Canada
- Institute of Integrative Biology and Systems, Université Laval, Québec, Québec G1V 0A6 Canada
| | - Sébastien Gérardi
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, Québec G1V 0A6 Canada
- Institute of Integrative Biology and Systems, Université Laval, Québec, Québec G1V 0A6 Canada
| | - Jérôme Laroche
- Institute of Integrative Biology and Systems, Université Laval, Québec, Québec G1V 0A6 Canada
| | - Brian Boyle
- Institute of Integrative Biology and Systems, Université Laval, Québec, Québec G1V 0A6 Canada
| | - France Gagnon
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, Québec G1V 0A6 Canada
- Institute of Integrative Biology and Systems, Université Laval, Québec, Québec G1V 0A6 Canada
| | - Marie-Josée Mottet
- Direction de la recherche forestière, Ministère des Forêts, de la Faune et des Parcs du Québec, 2700 Einstein, Québec, Québec G1P 3W8 Canada
| | - Jean Beaulieu
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, Québec G1V 0A6 Canada
- Institute of Integrative Biology and Systems, Université Laval, Québec, Québec G1V 0A6 Canada
| | - Jean Bousquet
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, Québec G1V 0A6 Canada
- Institute of Integrative Biology and Systems, Université Laval, Québec, Québec G1V 0A6 Canada
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