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Yusuf M, Miller MD, Stefaniak TR, Haagenson D, Endelman JB, Thompson AL, Shannon LM. Genomic prediction for potato (Solanum tuberosum) quality traits improved through image analysis. THE PLANT GENOME 2024:e20507. [PMID: 39256988 DOI: 10.1002/tpg2.20507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 07/08/2024] [Accepted: 08/03/2024] [Indexed: 09/12/2024]
Abstract
Potato (Solanum tuberosum L.) is the most widely grown vegetable in the world. Consumers and processors evaluate potatoes based on quality traits such as shape and skin color, making these traits important targets for breeders. Achieving and evaluating genetic gain is facilitated by precise and accurate trait measures. Historically, quality traits have been measured using visual rating scales, which are subject to human error and necessarily lump individuals with distinct characteristics into categories. Image analysis offers a method of generating quantitative measures of quality traits. In this study, we use TubAR, an image-analysis R package, to generate quantitative measures of shape and skin color traits for use in genomic prediction. We developed and compared different genomic models based on additive and additive plus non-additive relationship matrices for two aspects of skin color, redness, and lightness, and two aspects of shape, roundness, and length-to-width ratio for fresh market red and yellow potatoes grown in Minnesota between 2020 and 2022. Similarly, we used the much larger chipping potato population grown during the same time to develop a multi-trait selection index including roundness, specific gravity, and yield. Traits ranged in heritability with shape traits falling between 0.23 and 0.85, and color traits falling between 0.34 and 0.91. Genetic effects were primarily additive with color traits showing the strongest effect (0.47), while shape traits varied based on market class. Modeling non-additive effects did not significantly improve prediction models for quality traits. The combination of image analysis and genomic prediction presents a promising avenue for improving potato quality traits.
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Affiliation(s)
- Muyideen Yusuf
- Department of Horticultural Science, University of Minnesota, Saint Paul, Minnesota, USA
| | | | - Thomas R Stefaniak
- Department of Horticultural Science, University of Minnesota, Saint Paul, Minnesota, USA
| | - Darrin Haagenson
- USDA-ARS, Edward T. Schafer Agricultural Research Center, Fargo, North Dakota, USA
| | - Jeffrey B Endelman
- Department of Plant & Agroecosystem Sciences, University of Wisconsin, Madison, Wisconsin, USA
| | - Asunta L Thompson
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota, USA
| | - Laura M Shannon
- Department of Horticultural Science, University of Minnesota, Saint Paul, Minnesota, USA
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2
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Tuttle HK, Del Rio AH, Bamberg JB, Shannon LM. Potato soup: analysis of cultivated potato gene bank populations reveals high diversity and little structure. FRONTIERS IN PLANT SCIENCE 2024; 15:1429279. [PMID: 39091313 PMCID: PMC11291250 DOI: 10.3389/fpls.2024.1429279] [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: 05/07/2024] [Accepted: 06/27/2024] [Indexed: 08/04/2024]
Abstract
Cultivated potatoes are incredibly diverse, ranging from diploid to pentaploid and encompass four different species. They are adapted to disparate environments and conditions and carry unique alleles for resistance to pests and pathogens. Describing how diversity is partitioned within and among these populations is essential to understanding the potato genome and effectively utilizing landraces in breeding. This task is complicated by the difficulty of making comparisons across cytotypes and extensive admixture within section petota. We genotyped 730 accessions from the US Potato genebank including wild diploids and cultivated diploids and tetraploids using Genotype-by-sequencing. This data set allowed us to interrogate population structure and diversity as well as generate core subsets which will support breeders in efficiently screening genebank material for biotic and abiotic stress resistance alleles. We found that even controlling for ploidy, tetraploid material exhibited higher observed and expected heterozygosity than diploid accessions. In particular group chilotanum material was the most heterozygous and the only taxa not to exhibit any inbreeding. This may in part be because group chilotanum has a history of introgression not just from wild species, but landraces as well. All group chilotanum, exhibits introgression from group andigenum except clones from Southern South America near its origin, where the two groups are not highly differentiated. Moving north, we do not observe evidence for the same level of admixture back into group andigenum. This suggests that extensive history of admixture is a particular characteristic of chilotanum.
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Affiliation(s)
- Heather K. Tuttle
- Department of Horticultural Science, University of Minnesota, St. Paul, MN, United States
| | - Alfonso H. Del Rio
- U.S. Department of Agriculture (USDA)/Agricultural Research Service, Potato Genebank, Sturgeon Bay, WI, United States
| | - John B. Bamberg
- U.S. Department of Agriculture (USDA)/Agricultural Research Service, Potato Genebank, Sturgeon Bay, WI, United States
| | - Laura M. Shannon
- Department of Horticultural Science, University of Minnesota, St. Paul, MN, United States
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3
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Sharma SK, McLean K, Hedley PE, Dale F, Daniels S, Bryan GJ. Genotyping-by-sequencing targets genic regions and improves resolution of genome-wide association studies in autotetraploid potato. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:180. [PMID: 38980417 PMCID: PMC11233353 DOI: 10.1007/s00122-024-04651-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 05/10/2024] [Indexed: 07/10/2024]
Abstract
KEY MESSAGE De novo genotyping in potato using methylation-sensitive GBS discovers SNPs largely confined to genic or gene-associated regions and displays enhanced effectiveness in estimating LD decay rates, population structure and detecting GWAS associations over 'fixed' SNP genotyping platform. Study also reports the genetic architectures including robust sequence-tagged marker-trait associations for sixteen important potato traits potentially carrying higher transferability across a wider range of germplasm. This study deploys recent advancements in polyploid analytical approaches to perform complex trait analyses in cultivated tetraploid potato. The study employs a 'fixed' SNP Infinium array platform and a 'flexible and open' genome complexity reduction-based sequencing method (GBS, genotyping-by-sequencing) to perform genome-wide association studies (GWAS) for several key potato traits including the assessment of population structure and linkage disequilibrium (LD) in the studied population. GBS SNPs discovered here were largely confined (~ 90%) to genic or gene-associated regions of the genome demonstrating the utility of using a methylation-sensitive restriction enzyme (PstI) for library construction. As compared to Infinium array SNPs, GBS SNPs displayed enhanced effectiveness in estimating LD decay rates and discriminating population subgroups. GWAS using a combined set of 30,363 SNPs identified 189 unique QTL marker-trait associations (QTL-MTAs) covering all studied traits. The majority of the QTL-MTAs were from GBS SNPs potentially illustrating the effectiveness of marker-dense de novo genotyping platforms in overcoming ascertainment bias and providing a more accurate correction for different levels of relatedness in GWAS models. GWAS also detected QTL 'hotspots' for several traits at previously known as well as newly identified genomic locations. Due to the current study exploiting genome-wide genotyping and de novo SNP discovery simultaneously on a large tetraploid panel representing a greater diversity of the cultivated potato gene pool, the reported sequence-tagged MTAs are likely to have higher transferability across a wider range of potato germplasm and increased utility for expediting genomics-assisted breeding for the several complex traits studied.
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Affiliation(s)
- Sanjeev Kumar Sharma
- Cell and Molecular Sciences, The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK.
| | - Karen McLean
- Cell and Molecular Sciences, The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK
| | - Peter E Hedley
- Cell and Molecular Sciences, The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK
| | - Finlay Dale
- Cell and Molecular Sciences, The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK
| | | | - Glenn J Bryan
- Cell and Molecular Sciences, The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK.
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Wilson S, Zheng C, Maliepaard C, Mulder HA, Visser RGF, van Eeuwijk F. Multienvironment genomic prediction in tetraploid potato. G3 (BETHESDA, MD.) 2024; 14:jkae011. [PMID: 38243613 PMCID: PMC10989893 DOI: 10.1093/g3journal/jkae011] [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: 04/27/2023] [Revised: 10/06/2023] [Accepted: 10/20/2023] [Indexed: 01/21/2024]
Abstract
Multienvironment genomic prediction was applied to tetraploid potato using 147 potato varieties, tested for 2 years, in 3 locations representative of 3 distinct regions in Europe. Different prediction scenarios were investigated to help breeders predict genotypic performance in the regions from one year to the next, for genotypes that were tested this year (scenario 1), as well as new genotypes (scenario 3). In scenario 2, we predicted new genotypes for any one of the 6 trials, using all the information that is available. The choice of prediction model required assessment of the variance-covariance matrix in a mixed model that takes into account heterogeneity of genetic variances and correlations. This was done for each analyzed trait (tuber weight, tuber length, and dry matter) where examples of both limited and higher degrees of heterogeneity was observed. This explains why dry matter did not need complex multienvironment modeling to combine environments and increase prediction ability, while prediction in tuber weight, improved only when models were flexible enough to capture the heterogeneous variances and covariances between environments. We also found that the prediction abilities in a target trial condition decreased, if trials with a low genetic correlation to the target were included when training the model. Genomic prediction in tetraploid potato can work once there is clarity about the prediction scenario, a suitable training set is created, and a multienvironment prediction model is chosen based on the patterns of G×E indicated by the genetic variances and covariances.
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Affiliation(s)
- Stefan Wilson
- Biometris, Wageningen University & Research Centre, Wageningen, PB 6708, The Netherlands
| | - Chaozhi Zheng
- Biometris, Wageningen University & Research Centre, Wageningen, PB 6708, The Netherlands
| | - Chris Maliepaard
- Plant Breeding, Wageningen University and Research, Wageningen, PB 6708, The Netherlands
| | - Han A Mulder
- Wageningen University and Research Animal Breeding and Genomics, Wageningen, AH 6700, The Netherlands
| | - Richard G F Visser
- Plant Breeding, Wageningen University and Research, Wageningen, PB 6708, The Netherlands
| | - Fred van Eeuwijk
- Biometris, Wageningen University & Research Centre, Wageningen, PB 6708, The Netherlands
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Alemu A, Åstrand J, Montesinos-López OA, Isidro Y Sánchez J, Fernández-Gónzalez J, Tadesse W, Vetukuri RR, Carlsson AS, Ceplitis A, Crossa J, Ortiz R, Chawade A. Genomic selection in plant breeding: Key factors shaping two decades of progress. MOLECULAR PLANT 2024; 17:552-578. [PMID: 38475993 DOI: 10.1016/j.molp.2024.03.007] [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: 11/03/2023] [Revised: 01/22/2024] [Accepted: 03/08/2024] [Indexed: 03/14/2024]
Abstract
Genomic selection, the application of genomic prediction (GP) models to select candidate individuals, has significantly advanced in the past two decades, effectively accelerating genetic gains in plant breeding. This article provides a holistic overview of key factors that have influenced GP in plant breeding during this period. We delved into the pivotal roles of training population size and genetic diversity, and their relationship with the breeding population, in determining GP accuracy. Special emphasis was placed on optimizing training population size. We explored its benefits and the associated diminishing returns beyond an optimum size. This was done while considering the balance between resource allocation and maximizing prediction accuracy through current optimization algorithms. The density and distribution of single-nucleotide polymorphisms, level of linkage disequilibrium, genetic complexity, trait heritability, statistical machine-learning methods, and non-additive effects are the other vital factors. Using wheat, maize, and potato as examples, we summarize the effect of these factors on the accuracy of GP for various traits. The search for high accuracy in GP-theoretically reaching one when using the Pearson's correlation as a metric-is an active research area as yet far from optimal for various traits. We hypothesize that with ultra-high sizes of genotypic and phenotypic datasets, effective training population optimization methods and support from other omics approaches (transcriptomics, metabolomics and proteomics) coupled with deep-learning algorithms could overcome the boundaries of current limitations to achieve the highest possible prediction accuracy, making genomic selection an effective tool in plant breeding.
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Affiliation(s)
- Admas Alemu
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden.
| | - Johanna Åstrand
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden; Lantmännen Lantbruk, Svalöv, Sweden
| | | | - Julio Isidro Y Sánchez
- Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA), Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Campus de Montegancedo-UPM, 28223 Madrid, Spain
| | - Javier Fernández-Gónzalez
- Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA), Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Campus de Montegancedo-UPM, 28223 Madrid, Spain
| | - Wuletaw Tadesse
- International Center for Agricultural Research in the Dry Areas (ICARDA), Rabat, Morocco
| | - Ramesh R Vetukuri
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Anders S Carlsson
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | | | - José Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera México-Veracruz, Texcoco, México 52640, Mexico
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden.
| | - Aakash Chawade
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
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Çelik S. Gene expression analysis of potato drought-responsive genes under drought stress in potato ( Solanum tuberosum L.) cultivars. PeerJ 2024; 12:e17116. [PMID: 38525286 PMCID: PMC10960530 DOI: 10.7717/peerj.17116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 02/26/2024] [Indexed: 03/26/2024] Open
Abstract
The potato (Solanum tuberosum L.), an important field crop consumed extensively worldwide, is adversely affected by abiotic stress factors especially drought. Therefore, it is vital to understand the genetic mechanism under drought stress to decrease loose of yield and quality . This trial aimed to screen drought-responsive gene expressions of potato and determine the drought-tolerant potato cultivar. The trial pattern is a completely randomized block design (CRBD) with four replications under greenhouse conditions. Four cultivars (Brooke, Orwell, Vr808, Shc909) were irrigated with four different water regimes (control and three stress conditions), and the gene expression levels of 10 potato genes were investigated. The stress treatments as follows: Control = 100% field capacity; slight drought = 75% field capacity; moderate drought = 50% field capacity, and severe drought 25% field capacity. To understand the gene expression under drought stress in potato genotypes, RT-qPCR analysis was performed and results showed that the genes most associated with drought tolerance were the StRD22 gene, MYB domain transcription factor, StERD7, Sucrose Synthase (SuSy), ABC Transporter, and StDHN1. The StHSP100 gene had the lowest genetic expression in all cultivars. Among the cultivars, the Orwell exhibited the highest expression of the StRD22 gene under drought stress. Overall, the cultivar with the highest gene expression was the Vr808, closely followed by the Brooke cultivar. As a result, it was determined that potato cultivars Orwell, Vr808, and Brooke could be used as parents in breeding programs to develop drought tolerant potato cultivars.
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Affiliation(s)
- Sadettin Çelik
- Genç Vocational School, Forestry Department, Bingol University, Bingol, Turkey
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Pandey J, Gautam S, Scheuring DC, Koym JW, Vales MI. Variation and genetic basis of mineral content in potato tubers and prospects for genomic selection. FRONTIERS IN PLANT SCIENCE 2023; 14:1301297. [PMID: 38186596 PMCID: PMC10766833 DOI: 10.3389/fpls.2023.1301297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 12/05/2023] [Indexed: 01/09/2024]
Abstract
Malnutrition is a major public health concern in many parts of the world. Among other nutrients, minerals are necessary in the human diet. Potato tubers are a good source of minerals; they contribute 18% of the recommended dietary allowance of potassium; 6% of copper, phosphorus, and magnesium; and 2% of calcium and zinc. Increased public interest in improving the nutritional value of foods has prompted the evaluation of mineral content in tubers of advanced genotypes from the Texas A&M Potato Breeding Program and the investigation of the genetics underlying mineral composition in tubers. The objectives of this study were to i) assess phenotypic variation for mineral content in tubers of advanced potato genotypes, ii) identify genomic regions associated with tuber mineral content, and iii) obtain genomic-estimated breeding values. A panel of 214 advanced potato genotypes and reference varieties was phenotyped in three field environments in Texas for the content of 12 minerals in tubers and genotyped using the Infinium Illumina 22K V3 single nucleotide polymorphism (SNP) Array. There was significant variation between potato genotypes for all minerals evaluated except iron. As a market group, red-skinned potatoes had the highest amount of minerals, whereas russets had the lowest mineral content. Reds had significantly higher P, K, S, and Zn than russets and significantly higher P and Mg than chippers. Russets had significantly higher Ca, Mg, and Na than chippers. However, the chippers had significantly higher K than the russets. A genome-wide association study for mineral content using GWASpoly identified three quantitative trait loci (QTL) associated with potassium and manganese content on chromosome 5 and two QTL associated with zinc content on chromosome 7. The loci identified will contribute to a better understanding of the genetic basis of mineral content in potatoes. Genomic-estimated breeding values for mineral macro and micronutrients in tubers obtained with StageWise will guide the selection of parents and the advancement of genotypes in the breeding program to increase mineral content in potato tubers.
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Affiliation(s)
- Jeewan Pandey
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, United States
| | - Sanjeev Gautam
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, United States
| | - Douglas C. Scheuring
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, United States
| | - Jeffrey W. Koym
- Texas A&M AgriLife Research and Extension Center, Lubbock, TX, United States
| | - M. Isabel Vales
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, United States
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Park J, Sathuvalli V, Yilma S, Whitworth J, Novy RG. Identification of QTL associated with plant vine characteristics and infection response to late blight, early blight, and Verticillium wilt in a tetraploid potato population derived from late blight-resistant Palisade Russet. FRONTIERS IN PLANT SCIENCE 2023; 14:1222596. [PMID: 37900754 PMCID: PMC10600477 DOI: 10.3389/fpls.2023.1222596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 09/25/2023] [Indexed: 10/31/2023]
Abstract
Potato late blight (causal agent Phytophthora infestans) is a disease of potatoes with economic importance worldwide. Control is primarily through field monitoring and the application of fungicides. Control of late blight with fungicides and host plant resistance is difficult, with documented cases of such control measures failing with the advent of new pathotypes of P. infestans. To better understand host plant resistance and to develop more durable late blight resistance, Quantitative Trait Locus/Loci (QTL) analysis was conducted on a tetraploid mapping population derived from late blight-resistant potato cultivar Palisade Russet. Additionally, QTL analyses for other traits such as Verticillium wilt and early blight resistance, vine size and maturity were performed to identify a potential relationship between multiple traits and prepare genetic resources for molecular markers useful in breeding programs. For this, one hundred ninety progenies from intercrossing Palisade Russet with a late blight susceptible breeding clone (ND028673B-2Russ) were assessed. Two parents and progenies were evaluated over a two-year period for response to infection by the US-8 genotype of P. infestans in inoculated field screenings in Corvallis, Oregon. In Aberdeen, Idaho, the same mapping population was also evaluated for phenotypic response to early blight and Verticillium wilt, and vine size and maturity in a field over a two-year period. After conducting QTL analyses with those collected phenotype data, it was observed that chromosome 5 has a significant QTL for all five traits. Verticillium wilt and vine maturity QTL were also observed on chromosome 1, and vine size QTL was also found on chromosomes 3 and 10. An early blight QTL was also detected on chromosome 2. The QTL identified in this study have the potential for converting into breeder-friendly molecular markers for marker-assisted selection.
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Affiliation(s)
- Jaebum Park
- Small Grains and Potato Germplasm Research Station, United States Department of Agriculture – Agricultural Research Service, Aberdeen, ID, United States
| | - Vidyasagar Sathuvalli
- Hermiston Agricultural Research and Extension Center, Oregon State University, Hermiston, OR, United States
- Department of Crop and Soil Science, Oregon State University, Corvallis, OR, United States
| | - Solomon Yilma
- Department of Crop and Soil Science, Oregon State University, Corvallis, OR, United States
| | - Jonathan Whitworth
- Small Grains and Potato Germplasm Research Station, United States Department of Agriculture – Agricultural Research Service, Aberdeen, ID, United States
| | - Richard G. Novy
- Small Grains and Potato Germplasm Research Station, United States Department of Agriculture – Agricultural Research Service, Aberdeen, ID, United States
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Sood S, Bhardwaj V, Bairwa A, Dalamu, Sharma S, Sharma AK, Kumar A, Lal M, Kumar V. Genome-wide association mapping and genomic prediction for late blight and potato cyst nematode resistance in potato ( Solanum tuberosum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1211472. [PMID: 37860256 PMCID: PMC10582711 DOI: 10.3389/fpls.2023.1211472] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 09/12/2023] [Indexed: 10/21/2023]
Abstract
Potatoes are an important source of food for millions of people worldwide. Biotic stresses, notably late blight and potato cyst nematodes (PCN) pose a major threat to potato production worldwide, and knowledge of genes controlling these traits is limited. A genome-wide association mapping study was conducted to identify the genomic regulators controlling these biotic stresses, and the genomic prediction accuracy was worked out using the GBLUP model of genomic selection (GS) in a panel of 222 diverse potato accessions. The phenotype data on resistance to late blight and two PCN species (Globodera pallida and G. rostochiensis) were recorded for three and two consecutive years, respectively. The potato panel was genotyped using genotyping by sequencing (GBS), and 1,20,622 SNP markers were identified. A total of 7 SNP associations for late blight resistance, 9 and 11 for G. pallida and G. rostochiensis, respectively, were detected by additive and simplex dominance models of GWAS. The associated SNPs were distributed across the chromosomes, but most of the associations were found on chromosomes 5, 10 and 11, which have been earlier reported as the hotspots of disease-resistance genes. The GS prediction accuracy estimates were low to moderate for resistance to G. pallida (0.04-0.14) and G. rostochiensis (0.14-0.21), while late blight resistance showed a high prediction accuracy of 0.42-0.51. This study provides information on the complex genetic nature of these biotic stress traits in potatoes and putative SNP markers for resistance breeding.
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Affiliation(s)
- Salej Sood
- Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute, Shimla, HP, India
| | - Vinay Bhardwaj
- Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute, Shimla, HP, India
| | - Aarti Bairwa
- Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute, Shimla, HP, India
| | - Dalamu
- Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute, Shimla, HP, India
| | - Sanjeev Sharma
- Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute, Shimla, HP, India
| | - Ashwani K. Sharma
- Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute, Shimla, HP, India
| | - Ashwani Kumar
- Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute, Shimla, HP, India
| | - Mehi Lal
- ICAR-Central Potato Research Institute, Regional Station, Modipuram, UP, India
| | - Vinod Kumar
- Indian Council of Agricultural Research (ICAR)-Central Potato Research Institute, Shimla, HP, India
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Angmo D, Sharma SP, Kalia A. Breeding strategies for late blight resistance in potato crop: recent developments. Mol Biol Rep 2023; 50:7879-7891. [PMID: 37526862 DOI: 10.1007/s11033-023-08577-0] [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: 03/05/2023] [Accepted: 06/01/2023] [Indexed: 08/02/2023]
Abstract
Late blight (LB) is a serious disease that affects potato crop and is caused by Phytophthora infestans. Fungicides are commonly used to manage this disease, but this practice has led to the development of resistant strains and it also poses serious environmental and health risks. Therefore, breeding for resistance development can be the most effective strategies to control late blight. Various Solanum species have been utilized as a source of resistance genes to combat late blight disease. Several potential resistance genes and quantitative resistance loci (QRLs) have been identified and mapped through the application of molecular techniques. Furthermore, molecular markers closely linked to resistance genes or QRLs have been utilized to hasten the breeding process. However, the use of single-gene resistance can lead to the breakdown of resistance within a short period. To address this, breeding programs are now being focused on development of durable and broad-spectrum resistant cultivars by combining multiple resistant genes and QRLs using advanced molecular breeding tools such as marker-assisted selection (MAS) and cis-genic approaches. In addition to the strategies mentioned earlier, somatic hybridization has been utilized for the development and characterization of interspecific somatic hybrids. To further broaden the scope of late blight resistance breeding, approaches such as genomic selection, RNAi silencing, and various genome editing techniques can be employed. This study provides an overview of recent advances in various breeding strategies and their applications in improving the late blight resistance breeding program.
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Affiliation(s)
- Dechen Angmo
- Department of Vegetable Science, Punjab Agricultural University, Ludhiana, 141004, Punjab, India.
| | - Sat Pal Sharma
- Department of Vegetable Science, Punjab Agricultural University, Ludhiana, 141004, Punjab, India
| | - Anu Kalia
- Electron Microscopy and Nanoscience Laboratory, Department of Soil Science, Punjab Agricultural University, Ludhiana, 141004, Punjab, India
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11
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Adams J, de Vries M, van Eeuwijk F. Efficient Genomic Prediction of Yield and Dry Matter in Hybrid Potato. PLANTS (BASEL, SWITZERLAND) 2023; 12:2617. [PMID: 37514232 PMCID: PMC10385487 DOI: 10.3390/plants12142617] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 06/27/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023]
Abstract
There is an ongoing endeavor within the potato breeding sector to rapidly adapt potato from a clonal polyploid crop to a diploid hybrid potato crop. While hybrid breeding allows for the efficient generation and selection of parental lines, it also increases breeding program complexity and results in longer breeding cycles. Over the past two decades, genomic prediction has revolutionized hybrid crop breeding through shorter breeding cycles, lower phenotyping costs, and better population improvement, resulting in increased genetic gains for genetically complex traits. In order to accelerate the genetic gains in hybrid potato, the proper implementation of genomic prediction is a crucial milestone in the rapid improvement of this crop. The authors of this paper set out to test genomic prediction in hybrid potato using current genotyped material with two alternative models: one model that predicts the general combining ability effects (GCA) and another which predicts both the general and specific combining ability effects (GCA+SCA). Using a training set comprising 769 hybrids and 456 genotyped parental lines, we found that reasonable a prediction accuracy could be achieved for most phenotypes with both zero common parents (ρ=0.36-0.61) and one (ρ=0.50-0.68) common parent between the training and test sets. There was no benefit with the inclusion of non-additive genetic effects in the GCA+SCA model despite SCA variance contributing between 9% and 19% of the total genetic variance. Genotype-by-environment interactions, while present, did not appear to affect the prediction accuracy, though prediction errors did vary across the trial's targets. These results suggest that genomically estimated breeding values on parental lines are sufficient for hybrid yield prediction.
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Affiliation(s)
- James Adams
- Biometris, Mathematical and Statistical Methods, Wageningen University and Research, 6708 PB Wageningen, The Netherlands
- Solynta, Dreijenlaan 2, 6703 HA Wageningen, The Netherlands
| | | | - Fred van Eeuwijk
- Biometris, Mathematical and Statistical Methods, Wageningen University and Research, 6708 PB Wageningen, The Netherlands
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12
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Wu PY, Stich B, Renner J, Muders K, Prigge V, van Inghelandt D. Optimal implementation of genomic selection in clone breeding programs-Exemplified in potato: I. Effect of selection strategy, implementation stage, and selection intensity on short-term genetic gain. THE PLANT GENOME 2023:e20327. [PMID: 37177848 DOI: 10.1002/tpg2.20327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 03/01/2023] [Accepted: 03/03/2023] [Indexed: 05/15/2023]
Abstract
Genomic selection (GS) is used in many animal and plant breeding programs to enhance genetic gain for complex traits. However, its optimal integration in clone breeding programs, for example potato, that up to now relied on phenotypic selection (PS) requires further research. In this study, we performed computer simulations based on an empirical genomic dataset of tetraploid potato to (i) investigate under a fixed budget how the weight of GS relative to PS, the stage of implementing GS, the correlation between an auxiliary trait and the target trait, the variance components, and the prediction accuracy affect the genetic gain of the target trait, (ii) determine the optimal allocation of resources maximizing the genetic gain of the target trait, and (iii) make recommendations to breeders how to implement GS in clone and especially potato breeding programs. In our simulation results, any selection strategy involving GS had a higher short-term genetic gain for the target trait than Standard-PS. In addition, we showed that implementing GS in consecutive selection stages can largely enhance short-term genetic gain and recommend the breeders to implement GS at single hills and A clone stages. Furthermore, we observed for selection strategies involving GS that the optimal allocation of resources maximizing the genetic gain of the target trait differed considerably from those typically used in potato breeding programs and, thus, require the adjustment of the selection and phenotyping intensities. The trends are described in our study. Therefore, our study provides new insight for breeders regarding how to optimally implement GS in a commercial potato breeding program to improve the short-term genetic gain for their target trait.
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Affiliation(s)
- Po-Ya Wu
- Institute of Quantitative Genetics and Genomics of Plants, Heinrich Heine University, Düsseldorf, Germany
| | - Benjamin Stich
- Institute of Quantitative Genetics and Genomics of Plants, Heinrich Heine University, Düsseldorf, Germany
- Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich Heine University, Düsseldorf, Germany
- Max Planck Institute for Plant Breeding Research, Köln, Germany
| | - Juliane Renner
- Böhm-Nordkartoffel Agrarproduktion GmbH & Co. OHG, Hohenmocker, Germany
| | | | | | - Delphine van Inghelandt
- Institute of Quantitative Genetics and Genomics of Plants, Heinrich Heine University, Düsseldorf, Germany
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Bhattarai G, Shi A, Mou B, Correll JC. Resequencing worldwide spinach germplasm for identification of field resistance QTLs to downy mildew and assessment of genomic selection methods. HORTICULTURE RESEARCH 2022; 9:uhac205. [PMID: 36467269 PMCID: PMC9715576 DOI: 10.1093/hr/uhac205] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 09/04/2022] [Indexed: 06/16/2023]
Abstract
Downy mildew, commercially the most important disease of spinach, is caused by the obligate oomycete Peronospora effusa. In the past two decades, new pathogen races have repeatedly overcome the resistance used in newly released cultivars, urging the need for more durable resistance. Commercial spinach cultivars are bred with major R genes to impart resistance to downy mildew pathogens and are effective against some pathogen races/isolates. This work aimed to evaluate the worldwide USDA spinach germplasm collections and commercial cultivars for resistance to downy mildew pathogen in the field condition under natural inoculum pressure and conduct genome wide association analysis (GWAS) to identify resistance-associated genomic regions (alleles). Another objective was to evaluate the prediction accuracy (PA) using several genomic prediction (GP) methods to assess the potential implementation of genomic selection (GS) to improve spinach breeding for resistance to downy mildew pathogen. More than four hundred diverse spinach genotypes comprising USDA germplasm accessions and commercial cultivars were evaluated for resistance to downy mildew pathogen between 2017-2019 in Salinas Valley, California and Yuma, Arizona. GWAS was performed using single nucleotide polymorphism (SNP) markers identified via whole genome resequencing (WGR) in GAPIT and TASSEL programs; detected 14, 12, 5, and 10 significantly associated SNP markers with the resistance from four tested environments, respectively; and the QTL alleles were detected at the previously reported region of chromosome 3 in three of the four experiments. In parallel, PA was assessed using six GP models and seven unique marker datasets for field resistance to downy mildew pathogen across four tested environments. The results suggest the suitability of GS to improve field resistance to downy mildew pathogen. The QTL, SNP markers, and PA estimates provide new information in spinach breeding to select resistant plants and breeding lines through marker-assisted selection (MAS) and GS, eventually helping to accumulate beneficial alleles for durable disease resistance.
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Senger E, Osorio S, Olbricht K, Shaw P, Denoyes B, Davik J, Predieri S, Karhu S, Raubach S, Lippi N, Höfer M, Cockerton H, Pradal C, Kafkas E, Litthauer S, Amaya I, Usadel B, Mezzetti B. Towards smart and sustainable development of modern berry cultivars in Europe. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 111:1238-1251. [PMID: 35751152 DOI: 10.1111/tpj.15876] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 06/15/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
Fresh berries are a popular and important component of the human diet. The demand for high-quality berries and sustainable production methods is increasing globally, challenging breeders to develop modern berry cultivars that fulfill all desired characteristics. Since 1994, research projects have characterized genetic resources, developed modern tools for high-throughput screening, and published data in publicly available repositories. However, the key findings of different disciplines are rarely linked together, and only a limited range of traits and genotypes has been investigated. The Horizon2020 project BreedingValue will address these challenges by studying a broader panel of strawberry, raspberry and blueberry genotypes in detail, in order to recover the lost genetic diversity that has limited the aroma and flavor intensity of recent cultivars. We will combine metabolic analysis with sensory panel tests and surveys to identify the key components of taste, flavor and aroma in berries across Europe, leading to a high-resolution map of quality requirements for future berry cultivars. Traits linked to berry yields and the effect of environmental stress will be investigated using modern image analysis methods and modeling. We will also use genetic analysis to determine the genetic basis of complex traits for the development and optimization of modern breeding technologies, such as molecular marker arrays, genomic selection and genome-wide association studies. Finally, the results, raw data and metadata will be made publicly available on the open platform Germinate in order to meet FAIR data principles and provide the basis for sustainable research in the future.
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Affiliation(s)
- Elisa Senger
- Institute of Bio- and Geosciences, IBG-4 Bioinformatics, BioSC, CEPLAS, Forschungszentrum Jülich, Jülich, Germany
| | - Sonia Osorio
- Departamento de Biología Molecular y Bioquímica, Instituto de Hortofruticultura Subtropical y Mediterránea 'La Mayora', Universidad de Málaga-Consejo Superior de Investigaciones Científicas, Campus de Teatinos, Málaga, Spain
| | | | - Paul Shaw
- Department of Information and Computational Sciences, The James Hutton Institute, Invergowrie, Scotland, UK
| | - Béatrice Denoyes
- Université de Bordeaux, UMR BFP, INRAE, Villenave d'Ornon, France
| | - Jahn Davik
- Department of Molecular Plant Biology, Norwegian Institute of Bioeconomy Research (NIBIO), Ås, Norway
| | - Stefano Predieri
- Bio-Agrofood Department, Institute for Bioeconomy, IBE-CNR, Italian National Research Council, Bologna, Italy
| | - Saila Karhu
- Natural Resources Institute Finland (Luke), Turku, Finland
| | - Sebastian Raubach
- Department of Information and Computational Sciences, The James Hutton Institute, Invergowrie, Scotland, UK
| | - Nico Lippi
- Bio-Agrofood Department, Institute for Bioeconomy, IBE-CNR, Italian National Research Council, Bologna, Italy
| | - Monika Höfer
- Institute of Breeding Research on Fruit Crops, Federal Research Centre for Cultivated Plants (JKI), Dresden, Germany
| | - Helen Cockerton
- Genetics, Genomics and Breeding Department, NIAB, East Malling, UK
| | - Christophe Pradal
- CIRAD and UMR AGAP Institute, Montpellier, France
- INRIA and LIRMM, University Montpellier, CNRS, Montpellier, France
| | - Ebru Kafkas
- Department of Horticulture, Faculty of Agriculture, Çukurova University, Balcalı, Adana, Turkey
| | | | - Iraida Amaya
- Unidad Asociada deI + D + i IFAPA-CSIC Biotecnología y Mejora en Fresa, Málaga, Spain
- Laboratorio de Genómica y Biotecnología, Centro IFAPA de Málaga, Instituto Andaluz de Investigación y Formación Agraria y Pesquera, Málaga, Spain
| | - Björn Usadel
- Institute of Bio- and Geosciences, IBG-4 Bioinformatics, BioSC, CEPLAS, Forschungszentrum Jülich, Jülich, Germany
- Institute for Biological Data Science, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Bruno Mezzetti
- Department of Agricultural, Food and Environmental Sciences, Università Politecnica delle Marche, Ancona, Italy
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15
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Egan LM, Stiller WN. The Past, Present, and Future of Host Plant Resistance in Cotton: An Australian Perspective. FRONTIERS IN PLANT SCIENCE 2022; 13:895877. [PMID: 35873986 PMCID: PMC9297922 DOI: 10.3389/fpls.2022.895877] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 06/06/2022] [Indexed: 05/24/2023]
Abstract
Cotton is a key global fiber crop. However, yield potential is limited by the presence of endemic and introduced pests and diseases. The introduction of host plant resistance (HPR), defined as the purposeful use of resistant crop cultivars to reduce the impact of pests and diseases, has been a key breeding target for the Commonwealth Scientific and Industrial Research Organisation (CSIRO) cotton breeding program. The program has seen success in releasing cultivars resistant to Bacterial blight, Verticillium wilt, Fusarium wilt, and Cotton bunchy top. However, emerging biotic threats such as Black root rot and secondary pests, are becoming more frequent in Australian cotton production systems. The uptake of tools and breeding methods, such as genomic selection, high throughput phenomics, gene editing, and landscape genomics, paired with the continued utilization of sources of resistance from Gossypium germplasm, will be critical for the future of cotton breeding. This review celebrates the success of HPR breeding activities in the CSIRO cotton breeding program and maps a pathway for the future in developing resistant cultivars.
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16
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Pirnajmedin F, Majidi MM, Taleb MH, Rostami D. Genetic parameters and selection in full-sib families of tall fescue using best linear unbiased prediction (BLUP) analysis. BMC PLANT BIOLOGY 2022; 22:293. [PMID: 35701757 PMCID: PMC9199132 DOI: 10.1186/s12870-022-03675-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 06/01/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Better understanding of genetic structure of economic traits is crucial for identification and selection of superior genotypes in specific breeding programs. Best linear unbiased prediction (BLUP) is the most efficient method in this regard, which is poorly used in forage plant breeding. The present study aimed to assess genetic variation, estimate genetic parameters, and predict breeding values of five essential traits in full sib families (recognized by EST-SSR markers) of tall fescue using REML/BLUP procedure. METHOD Forty-two full-sib families of tall fescue (included of 120 individual genotypes), recognized by EST-SSR markers along with twenty-one their corresponding parental genotypes were assessed for biomass production and agro-morphological traits at three harvests (spring, summer, and autumn) in the field during 4 years (2017-2020). RESULTS Considerable genotypic variability was observed for all traits. Low narrow-sense heritability (h2n) for dry forage yield (DFY) at three harvest indicates that non-additive gene actions may play an important role in the inheritance of this trait. Higher h2n of yield related traits and flowering time and also significant genetic correlation of these traits with forage yield, suggests that selection based on these traits may lead to indirect genetic improvement of DFY. CONCLUSION Our results showed the adequacy of REML/BLUP procedure for identification and selection of preferable parental genotypes and progenies with higher breeding values for future breeding programs such as variety development in tall fescue. Parental genotypes 21 M, 1 M, and 20 L were identified as superior and stable genotypes and could also produce the best hybrid combinations when they were mostly used as maternal parent.
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Affiliation(s)
- Fatemeh Pirnajmedin
- Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111 Iran
| | - Mohammad Mahdi Majidi
- Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111 Iran
| | - Mohammad Hadi Taleb
- Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111 Iran
| | - Davoud Rostami
- Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111 Iran
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17
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Hoopes G, Meng X, Hamilton JP, Achakkagari SR, de Alves Freitas Guesdes F, Bolger ME, Coombs JJ, Esselink D, Kaiser NR, Kodde L, Kyriakidou M, Lavrijssen B, van Lieshout N, Shereda R, Tuttle HK, Vaillancourt B, Wood JC, de Boer JM, Bornowski N, Bourke P, Douches D, van Eck HJ, Ellis D, Feldman MJ, Gardner KM, Hopman JCP, Jiang J, De Jong WS, Kuhl JC, Novy RG, Oome S, Sathuvalli V, Tan EH, Ursum RA, Vales MI, Vining K, Visser RGF, Vossen J, Yencho GC, Anglin NL, Bachem CWB, Endelman JB, Shannon LM, Strömvik MV, Tai HH, Usadel B, Buell CR, Finkers R. Phased, chromosome-scale genome assemblies of tetraploid potato reveal a complex genome, transcriptome, and predicted proteome landscape underpinning genetic diversity. MOLECULAR PLANT 2022; 15:520-536. [PMID: 35026436 DOI: 10.1016/j.molp.2022.01.003] [Citation(s) in RCA: 65] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 10/19/2021] [Accepted: 01/07/2022] [Indexed: 05/11/2023]
Abstract
Cultivated potato is a clonally propagated autotetraploid species with a highly heterogeneous genome. Phased assemblies of six cultivars including two chromosome-scale phased genome assemblies revealed extensive allelic diversity, including altered coding and transcript sequences, preferential allele expression, and structural variation that collectively result in a highly complex transcriptome and predicted proteome, which are distributed across the homologous chromosomes. Wild species contribute to the extensive allelic diversity in tetraploid cultivars, demonstrating ancestral introgressions predating modern breeding efforts. As a clonally propagated autotetraploid that undergoes limited meiosis, dysfunctional and deleterious alleles are not purged in tetraploid potato. Nearly a quarter of the loci bore mutations are predicted to have a high negative impact on protein function, complicating breeder's efforts to reduce genetic load. The StCDF1 locus controls maturity, and analysis of six tetraploid genomes revealed that 12 allelic variants of StCDF1 are correlated with maturity in a dosage-dependent manner. Knowledge of the complexity of the tetraploid potato genome with its rampant structural variation and embedded deleterious and dysfunctional alleles will be key not only to implementing precision breeding of tetraploid cultivars but also to the construction of homozygous, diploid potato germplasm containing favorable alleles to capitalize on heterosis in F1 hybrids.
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Affiliation(s)
- Genevieve Hoopes
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Xiaoxi Meng
- Department of Horticultural Science, University of Minnesota, St. Paul, MN 55108, USA
| | - John P Hamilton
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Sai Reddy Achakkagari
- Department of Plant Science, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada
| | | | - Marie E Bolger
- IBG-4 Bioinformatics, Forschungszentrum Jülich, Wilhelm Johnen Str, 52428 Jülich, Germany
| | - Joseph J Coombs
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Danny Esselink
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - Natalie R Kaiser
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA; Bayer Crop Science, Woodland, CA 95695, USA
| | - Linda Kodde
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - Maria Kyriakidou
- Department of Plant Science, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada
| | - Brian Lavrijssen
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - Natascha van Lieshout
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - Rachel Shereda
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Heather K Tuttle
- Department of Horticultural Science, University of Minnesota, St. Paul, MN 55108, USA
| | | | - Joshua C Wood
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
| | | | - Nolan Bornowski
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Peter Bourke
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - David Douches
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Herman J van Eck
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - Dave Ellis
- International Potato Center, 1895 Avenida La Molina, Lima, Peru
| | | | - Kyle M Gardner
- Agriculture and Agri-Food Canada Fredericton Research and Development Centre, Fredericton, NB E3B 4Z7, Canada
| | | | - Jiming Jiang
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA; Department of Horticulture, Michigan State University, East Lansing, MI 48824, USA
| | - Walter S De Jong
- School of Integrative Plant Science, Cornell University, Ithaca, NY 14853-1901, USA
| | - Joseph C Kuhl
- Department of Plant Sciences, University of Idaho, Moscow, ID 83844, USA
| | - Richard G Novy
- USDA-ARS, Small Grains and Potato Germplasm Research, Aberdeen, ID 83210, USA
| | - Stan Oome
- HZPC Research B.V., Edisonweg 5, 8501 XG Joure, the Netherlands
| | - Vidyasagar Sathuvalli
- Department of Crop and Soil Science, Oregon State University, Hermiston, OR 97838, USA
| | - Ek Han Tan
- School of Biology and Ecology, University of Maine, 5735 Hitchner Hall Orono, ME 04469, USA
| | - Remco A Ursum
- HZPC Research B.V., Edisonweg 5, 8501 XG Joure, the Netherlands
| | - M Isabel Vales
- Department of Horticultural Sciences, Texas A&M University, College Station, TX 77843-2133, USA
| | - Kelly Vining
- Department of Horticulture, Oregon State University, Corvallis, OR 97331, USA
| | - Richard G F Visser
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - Jack Vossen
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - G Craig Yencho
- Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609, USA
| | - Noelle L Anglin
- International Potato Center, 1895 Avenida La Molina, Lima, Peru; USDA-ARS, Small Grains and Potato Germplasm Research, Aberdeen, ID 83210, USA
| | - Christian W B Bachem
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands
| | - Jeffrey B Endelman
- Department of Horticulture, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Laura M Shannon
- Department of Horticultural Science, University of Minnesota, St. Paul, MN 55108, USA
| | - Martina V Strömvik
- Department of Plant Science, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada
| | - Helen H Tai
- Agriculture and Agri-Food Canada Fredericton Research and Development Centre, Fredericton, NB E3B 4Z7, Canada
| | - Björn Usadel
- IBG-4 Bioinformatics, Forschungszentrum Jülich, Wilhelm Johnen Str, 52428 Jülich, Germany; Institute for Biological Data Science, Heinrich Heine University, Düsseldorf, 40225 Düsseldorf, Germany
| | - C Robin Buell
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA; Plant Resilience Institute, Michigan State University, East Lansing, MI 48824, USA.
| | - Richard Finkers
- Plant Breeding, Wageningen University & Research, Plant Breeding, 6708 PB Wageningen, the Netherlands.
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Ortiz R, Crossa J, Reslow F, Perez-Rodriguez P, Cuevas J. Genome-Based Genotype × Environment Prediction Enhances Potato ( Solanum tuberosum L.) Improvement Using Pseudo-Diploid and Polysomic Tetraploid Modeling. FRONTIERS IN PLANT SCIENCE 2022; 13:785196. [PMID: 35197995 PMCID: PMC8859116 DOI: 10.3389/fpls.2022.785196] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 01/05/2022] [Indexed: 05/03/2023]
Abstract
Potato breeding must improve its efficiency by increasing the reliability of selection as well as identifying a promising germplasm for crossing. This study shows the prediction accuracy of genomic-estimated breeding values for several potato (Solanum tuberosum L.) breeding clones and the released cultivars that were evaluated at three locations in northern and southern Sweden for various traits. Three dosages of marker alleles [pseudo-diploid (A), additive tetrasomic polyploidy (B), and additive-non-additive tetrasomic polyploidy (C)] were considered in the genome-based prediction models, for single environments and multiple environments (accounting for the genotype-by-environment interaction or G × E), and for comparing two kernels, the conventional linear, Genomic Best Linear Unbiased Prediction (GBLUP) (GB), and the non-linear Gaussian kernel (GK), when used with the single-kernel genetic matrices of A, B, C, or when employing two-kernel genetic matrices in the model using the kernels from B and C for a single environment (models 1 and 2, respectively), and for multi-environments (models 3 and 4, respectively). Concerning the single site analyses, the trait with the highest prediction accuracy for all sites under A, B, C for model 1, model 2, and for GB and GK methods was tuber starch percentage. Another trait with relatively high prediction accuracy was the total tuber weight. Results show an increase in prediction accuracy of model 2 over model 1. Non-linear Gaussian kernel (GK) did not show any clear advantage over the linear kernel GBLUP (GB). Results from the multi-environments had prediction accuracy estimates (models 3 and 4) higher than those obtained from the single-environment analyses. Model 4 with GB was the best method in combination with the marker structure B for predicting most of the tuber traits. Most of the traits gave relatively high prediction accuracy under this combination of marker structure (A, B, C, and B-C), and methods GB and GK combined with the multi-environment with G × E model.
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Affiliation(s)
- Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences (SLU), Lomma, Sweden
| | - José Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Fredrik Reslow
- Department of Plant Breeding, Swedish University of Agricultural Sciences (SLU), Lomma, Sweden
| | | | - Jaime Cuevas
- División de Ciencias, Ingeniería y Tecnologías, Universidad de Quintana Roo, Chetumal, Mexico
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Tiwari JK, Buckseth T, Zinta R, Bhatia N, Dalamu D, Naik S, Poonia AK, Kardile HB, Challam C, Singh RK, Luthra SK, Kumar V, Kumar M. Germplasm, Breeding, and Genomics in Potato Improvement of Biotic and Abiotic Stresses Tolerance. FRONTIERS IN PLANT SCIENCE 2022; 13:805671. [PMID: 35197996 PMCID: PMC8859313 DOI: 10.3389/fpls.2022.805671] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 01/17/2022] [Indexed: 05/23/2023]
Abstract
Potato is one of the most important food crops in the world. Late blight, viruses, soil and tuber-borne diseases, insect-pests mainly aphids, whiteflies, and potato tuber moths are the major biotic stresses affecting potato production. Potato is an irrigated and highly fertilizer-responsive crop, and therefore, heat, drought, and nutrient stresses are the key abiotic stresses. The genus Solanum is a reservoir of genetic diversity, however, a little fraction of total diversity has been utilized in potato breeding. The conventional breeding has contributed significantly to the development of potato varieties. In recent years, a tremendous progress has been achieved in the sequencing technologies from short-reads to long-reads sequence data, genomes of Solanum species (i.e., pan-genomics), bioinformatics and multi-omics platforms such as genomics, transcriptomics, proteomics, metabolomics, ionomics, and phenomics. As such, genome editing has been extensively explored as a next-generation breeding tool. With the available high-throughput genotyping facilities and tetraploid allele calling softwares, genomic selection would be a reality in potato in the near future. This mini-review covers an update on germplasm, breeding, and genomics in potato improvement for biotic and abiotic stress tolerance.
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Affiliation(s)
| | | | - Rasna Zinta
- ICAR-Central Potato Research Institute, Shimla, India
| | - Nisha Bhatia
- ICAR-Central Potato Research Institute, Shimla, India
- School of Biotechnology, Shoolini University, Solan, India
| | - Dalamu Dalamu
- ICAR-Central Potato Research Institute, Shimla, India
| | - Sharmistha Naik
- ICAR-Central Potato Research Institute, Shimla, India
- ICAR-National Research Centre for Grapes, Pune, India
| | - Anuj K. Poonia
- School of Biotechnology, Shoolini University, Solan, India
| | - Hemant B. Kardile
- Department of Crop and Soil Science, Oregon State University, Corvallis, OR, United States
| | - Clarissa Challam
- ICAR-Central Potato Research Institute, Regional Station, Shillong, India
| | | | - Satish K. Luthra
- ICAR-Central Potato Research Institute, Regional Station, Meerut, India
| | - Vinod Kumar
- ICAR-Central Potato Research Institute, Shimla, India
| | - Manoj Kumar
- ICAR-Central Potato Research Institute, Regional Station, Meerut, India
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20
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Selga C, Reslow F, Pérez-Rodríguez P, Ortiz R. The power of genomic estimated breeding values for selection when using a finite population size in genetic improvement of tetraploid potato. G3 (BETHESDA, MD.) 2022; 12:jkab362. [PMID: 34849763 PMCID: PMC8728039 DOI: 10.1093/g3journal/jkab362] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 10/08/2021] [Indexed: 12/02/2022]
Abstract
Potato breeding relies heavily on visual phenotypic scoring for clonal selection. Obtaining robust phenotypic data can be labor intensive and expensive, especially in the early cycles of a potato breeding program where the number of genotypes is very large. We have investigated the power of genomic estimated breeding values (GEBVs) for selection from a limited population size in potato breeding. We collected genotypic data from 669 tetraploid potato clones from all cycles of a potato breeding program, as well as phenotypic data for eight important breeding traits. The genotypes were partitioned into a training and a test population distinguished by cycle of selection in the breeding program. GEBVs for seven traits were predicted for individuals from the first stage of the breeding program (T1) which had not undergone any selection, or individuals selected at least once in the field (T2). An additional approach in which GEBVs were predicted within and across full-sib families from unselected material (T1) was tested for four breeding traits. GEBVs were obtained by using a Bayesian Ridge Regression model estimating single marker effects and phenotypic data from individuals at later stages of selection of the breeding program. Our results suggest that, for most traits included in this study, information from individuals from later stages of selection cannot be utilized to make selections based on GEBVs in earlier clonal generations. Predictions of GEBVs across full-sib families yielded similarly low prediction accuracies as across generations. The most promising approach for selection using GEBVs was found to be making predictions within full-sib families.
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Affiliation(s)
- Catja Selga
- Department of Plant Breeding, Swedish University of Agricultural Sciences (SLU), Lomma SE-23422, Sweden
| | - Fredrik Reslow
- Department of Plant Breeding, Swedish University of Agricultural Sciences (SLU), Lomma SE-23422, Sweden
| | | | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences (SLU), Lomma SE-23422, Sweden
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21
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Wang F, Zou M, Zhao L, Xia Z, Wang J. Genome-Wide Association Mapping of Late Blight Tolerance Trait in Potato ( Solanum tuberosum L.). Front Genet 2021; 12:714575. [PMID: 34659338 PMCID: PMC8517323 DOI: 10.3389/fgene.2021.714575] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 08/23/2021] [Indexed: 12/26/2022] Open
Abstract
Uncovering the genetic basis and optimizing the late blight tolerance trait in potatoes (Solanum tuberosum L.) are crucial for potato breeding. Late blight disease is one of the most significant diseases hindering potato production. The traits of late blight tolerance were evaluated for 284 potato cultivars to identify loci significantly associated with the late blight tolerance trait. Of all, 37 and 15 were the most tolerant to disease, and 107 and 30 were the most susceptible. A total of 22,489 high-quality single-nucleotide polymorphisms and indels were identified in 284 potato cultivars. All the potato cultivars were clustered into eight subgroups using population structure analysis and principal component analysis, which were consistent with the results of the phylogenetic tree analysis. The average genetic diversity for all 284 potato cultivars was 0.216, and the differentiation index of each subgroup was 0.025–0.149. Genome-wide linkage disequilibrium (LD) analysis demonstrated that the average LD was about 0.9 kb. A genome-wide association study using a mixed linear model identified 964 loci significantly associated with the late blight tolerance trait. Fourteen candidate genes for late blight tolerance traits were identified, including genes encoding late blight tolerance protein, chitinase 1, cytosolic nucleotide-binding site–leucine-rich repeat tolerance protein, protein kinase, ethylene-responsive transcription factor, and other potential plant tolerance-related proteins. This study provides novel insights into the genetic architecture of late blight tolerance traits and will be helpful for late blight tolerance in potato breeding.
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Affiliation(s)
- Fang Wang
- Academy of Agriculture and Forestry Sciences, Qinghai University, Xining, China.,National Key Laboratory of Sanjiangyuan Ecology and Plateau Agriculture and Animal Husbandry, Qinghai University, Xining, China.,Key Laboratory of Qinghai-Tibet Plateau Biotechnology Ministry of Education, Xining, China.,Qinghai Provincial Key Laboratory of Potato Breeding, Xining, China
| | - Meiling Zou
- College of Tropical Crops, Hainan University, Haikou, China.,Institute of Tropical Biosciences and Biotechnology, Chinese Academy of Tropical Agriculture Sciences, Haikou, China
| | - Long Zhao
- Academy of Agriculture and Forestry Sciences, Qinghai University, Xining, China.,National Key Laboratory of Sanjiangyuan Ecology and Plateau Agriculture and Animal Husbandry, Qinghai University, Xining, China.,Key Laboratory of Qinghai-Tibet Plateau Biotechnology Ministry of Education, Xining, China.,Qinghai Provincial Key Laboratory of Potato Breeding, Xining, China
| | - Zhiqiang Xia
- College of Tropical Crops, Hainan University, Haikou, China.,Institute of Tropical Biosciences and Biotechnology, Chinese Academy of Tropical Agriculture Sciences, Haikou, China
| | - Jian Wang
- Academy of Agriculture and Forestry Sciences, Qinghai University, Xining, China.,National Key Laboratory of Sanjiangyuan Ecology and Plateau Agriculture and Animal Husbandry, Qinghai University, Xining, China.,Key Laboratory of Qinghai-Tibet Plateau Biotechnology Ministry of Education, Xining, China.,Qinghai Provincial Key Laboratory of Potato Breeding, Xining, China
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22
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da Silva Pereira G, Mollinari M, Qu X, Thill C, Zeng ZB, Haynes K, Yencho GC. Quantitative Trait Locus Mapping for Common Scab Resistance in a Tetraploid Potato Full-Sib Population. PLANT DISEASE 2021; 105:3048-3054. [PMID: 33728960 DOI: 10.1094/pdis-10-20-2270-re] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Despite the negative impact of common scab (Streptomyces spp.) on the potato industry, little is known about the genetic architecture of resistance to this bacterial disease in the crop. We evaluated a mapping population (∼150 full sibs) derived from a cross between two tetraploid potatoes ('Atlantic' × B1829-5) in three environments (MN11, PA11, ME12) under natural common scab pressure. Three measures to common scab reaction, namely percentage of scabby tubers and disease area and lesion indices, were found to be highly correlated (>0.76). Because of the large environmental effect, heritability values were zero for all three traits in MN11, but moderate to high in PA11 and ME12 (∼0.44 to 0.79). We identified a single quantitative trait locus (QTL) for lesion index in PA11, ME12, and joint analyses on linkage group 3, explaining ∼22 to 30% of the total variation. The identification of QTL haplotypes and candidate genes contributing to disease resistance can support genomics-assisted breeding approaches in the crop.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
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Affiliation(s)
| | - Marcelo Mollinari
- Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695, U.S.A
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, U.S.A
| | - Xinshun Qu
- Department of Plant Pathology and Environmental Microbiology, The Pennsylvania State University, University Park, PA 16802, U.S.A
| | - Christian Thill
- Department of Horticultural Science, University of Minnesota, St. Paul, MN 55108, U.S.A
| | - Zhao-Bang Zeng
- Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695, U.S.A
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, U.S.A
| | - Kathleen Haynes
- Genetic Improvement of Fruits and Vegetables Laboratory, U.S. Department of Agriculture-Agricultural Research Service, Beltsville, MD 20705, U.S.A
| | - G Craig Yencho
- Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695, U.S.A
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23
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Wilson S, Zheng C, Maliepaard C, Mulder HA, Visser RGF, van der Burgt A, van Eeuwijk F. Understanding the Effectiveness of Genomic Prediction in Tetraploid Potato. FRONTIERS IN PLANT SCIENCE 2021; 12:672417. [PMID: 34434201 PMCID: PMC8381724 DOI: 10.3389/fpls.2021.672417] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 07/13/2021] [Indexed: 05/20/2023]
Abstract
Use of genomic prediction (GP) in tetraploid is becoming more common. Therefore, we think it is the right time for a comparison of GP models for tetraploid potato. GP models were compared that contrasted shrinkage with variable selection, parametric vs. non-parametric models and different ways of accounting for non-additive genetic effects. As a complement to GP, association studies were carried out in an attempt to understand the differences in prediction accuracy. We compared our GP models on a data set consisting of 147 cultivars, representing worldwide diversity, with over 39 k GBS markers and measurements on four tuber traits collected in six trials at three locations during 2 years. GP accuracies ranged from 0.32 for tuber count to 0.77 for dry matter content. For all traits, differences between GP models that utilised shrinkage penalties and those that performed variable selection were negligible. This was surprising for dry matter, as only a few additive markers explained over 50% of phenotypic variation. Accuracy for tuber count increased from 0.35 to 0.41, when dominance was included in the model. This result is supported by Genome Wide Association Study (GWAS) that found additive and dominance effects accounted for 37% of phenotypic variation, while significant additive effects alone accounted for 14%. For tuber weight, the Reproducing Kernel Hilbert Space (RKHS) model gave a larger improvement in prediction accuracy than explicitly modelling epistatic effects. This is an indication that capturing the between locus epistatic effects of tuber weight can be done more effectively using the semi-parametric RKHS model. Our results show good opportunities for GP in 4x potato.
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Affiliation(s)
- Stefan Wilson
- Biometris, Wageningen University & Research Centre, Wageningen, Netherlands
| | - Chaozhi Zheng
- Biometris, Wageningen University & Research Centre, Wageningen, Netherlands
| | - Chris Maliepaard
- Plant Breeding, Wageningen University and Research, Wageningen, Netherlands
| | - Han A. Mulder
- Wageningen University and Research Animal Breeding and Genomics Centre, Wageningen, Netherlands
| | | | | | - Fred van Eeuwijk
- Biometris, Wageningen University & Research Centre, Wageningen, Netherlands
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24
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Lindqvist-Kreuze H, De Boeck B, Unger P, Gemenet D, Li X, Pan Z, Sui Q, Qin J, Woldegjorgis G, Negash K, Seid I, Hirut B, Gastelo M, De Vega J, Bonierbale M. Global multi-environment resistance QTL for foliar late blight resistance in tetraploid potato with tropical adaptation. G3-GENES GENOMES GENETICS 2021; 11:6342414. [PMID: 34549785 PMCID: PMC8527470 DOI: 10.1093/g3journal/jkab251] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 06/29/2021] [Indexed: 11/18/2022]
Abstract
The identification of environmentally stable and globally predictable resistance to potato late blight is challenged by the clonal and polyploid nature of the crop and the rapid evolution of the pathogen. A diversity panel of tetraploid potato germplasm bred for multiple resistance and quality traits was genotyped by genotyping by sequencing (GBS) and evaluated for late blight resistance in three countries where the International Potato Center (CIP) has established breeding work. Health-indexed, in vitro plants of 380 clones and varieties were distributed from CIP headquarters and tuber seed was produced centrally in Peru, China, and Ethiopia. Phenotypes were recorded following field exposure to local isolates of Phytophthora infestans. QTL explaining resistance in four experiments conducted across the three countries were identified in chromosome IX, and environment-specific QTL were found in chromosomes III, V, and X. Different genetic models were evaluated for prediction ability to identify best performing germplasm in each and all environments. The best prediction ability (0.868) was identified with the genomic best linear unbiased predictors (GBLUPs) when using the diploid marker data and QTL-linked markers as fixed effects. Genotypes with high levels of resistance in all environments were identified from the B3, LBHT, and B3-LTVR populations. The results show that many of the advanced clones bred in Peru for high levels of late blight resistance maintain their resistance in Ethiopia and China, suggesting that the centralized selection strategy has been largely successful.
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Affiliation(s)
| | | | - Paula Unger
- International Potato Center, CIP, Lima 15024, Peru
| | | | - Xianping Li
- ndustrial Crops Research Institute, Yunnan Academy of Agricultural Sciences (YAAS), 2238 Beijing Road, Kunming, Yunnan 650205, P.R. China
| | - Zhechao Pan
- ndustrial Crops Research Institute, Yunnan Academy of Agricultural Sciences (YAAS), 2238 Beijing Road, Kunming, Yunnan 650205, P.R. China
| | - Qinjun Sui
- ndustrial Crops Research Institute, Yunnan Academy of Agricultural Sciences (YAAS), 2238 Beijing Road, Kunming, Yunnan 650205, P.R. China
| | | | - Gebremedhin Woldegjorgis
- Ethiopian Institute of Agricultural Research, (EIAR), Holetta Agricultural research Center. P.O. Box 31, West Showa Zone, Oromia Region, Ethiopia
| | - Kassaye Negash
- Ethiopian Institute of Agricultural Research, (EIAR), Holetta Agricultural research Center. P.O. Box 31, West Showa Zone, Oromia Region, Ethiopia
| | - Ibrahim Seid
- Ethiopian Institute of Agricultural Research, (EIAR), Holetta Agricultural research Center. P.O. Box 31, West Showa Zone, Oromia Region, Ethiopia
| | - Betaw Hirut
- CIP Ethiopia, c/o ILRI Ethiopia P.O. Box 5689, Addis Ababa, Ethiopia
| | | | - Jose De Vega
- Earlham Institute (EI), Norwich Research Park, Norwich NR4 7UZ, UK
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25
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Ferrão LFV, Amadeu RR, Benevenuto J, de Bem Oliveira I, Munoz PR. Genomic Selection in an Outcrossing Autotetraploid Fruit Crop: Lessons From Blueberry Breeding. FRONTIERS IN PLANT SCIENCE 2021; 12:676326. [PMID: 34194453 PMCID: PMC8236943 DOI: 10.3389/fpls.2021.676326] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 05/12/2021] [Indexed: 05/17/2023]
Abstract
Blueberry (Vaccinium corymbosum and hybrids) is a specialty crop with expanding production and consumption worldwide. The blueberry breeding program at the University of Florida (UF) has greatly contributed to expanding production areas by developing low-chilling cultivars better adapted to subtropical and Mediterranean climates of the globe. The breeding program has historically focused on recurrent phenotypic selection. As an autopolyploid, outcrossing, perennial, long juvenile phase crop, blueberry breeding cycles are costly and time consuming, which results in low genetic gains per unit of time. Motivated by applying molecular markers for a more accurate selection in the early stages of breeding, we performed pioneering genomic selection studies and optimization for its implementation in the blueberry breeding program. We have also addressed some complexities of sequence-based genotyping and model parametrization for an autopolyploid crop, providing empirical contributions that can be extended to other polyploid species. We herein revisited some of our previous genomic selection studies and showed for the first time its application in an independent validation set. In this paper, our contribution is three-fold: (i) summarize previous results on the relevance of model parametrizations, such as diploid or polyploid methods, and inclusion of dominance effects; (ii) assess the importance of sequence depth of coverage and genotype dosage calling steps; (iii) demonstrate the real impact of genomic selection on leveraging breeding decisions by using an independent validation set. Altogether, we propose a strategy for using genomic selection in blueberry, with the potential to be applied to other polyploid species of a similar background.
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Affiliation(s)
- Luís Felipe V. Ferrão
- Blueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, United States
| | - Rodrigo R. Amadeu
- Blueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, United States
| | - Juliana Benevenuto
- Blueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, United States
| | - Ivone de Bem Oliveira
- Blueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, United States
- Hortifrut North America, Inc., Estero, FL, United States
| | - Patricio R. Munoz
- Blueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, United States
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26
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Garreta L, Cerón‐Souza I, Palacio MR, Reyes‐Herrera PH. MultiGWAS: An integrative tool for Genome Wide Association Studies in tetraploid organisms. Ecol Evol 2021; 11:7411-7426. [PMID: 34188823 PMCID: PMC8216910 DOI: 10.1002/ece3.7572] [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: 11/20/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/27/2022] Open
Abstract
The genome-wide association studies (GWASs) are essential to determine the genetic bases of either ecological or economic phenotypic variation across individuals within populations of the model and nonmodel organisms. For this research question, the GWAS replication testing different parameters and models to validate the results' reproducibility is common. However, straightforward methodologies that manage both replication and tetraploid data are still missing. To solve this problem, we designed the MultiGWAS, a tool that does GWAS for diploid and tetraploid organisms by executing in parallel four software packages, two designed for polyploid data (GWASpoly and SHEsis) and two designed for diploid data (GAPIT and TASSEL). MultiGWAS has several advantages. It runs either in the command line or in a graphical interface; it manages different genotype formats, including VCF. Moreover, it allows control for population structure, relatedness, and several quality control checks on genotype data. Besides, MultiGWAS can test for additive and dominant gene action models, and, through a proprietary scoring function, select the best model to report its associations. Finally, it generates several reports that facilitate identifying false associations from both the significant and the best-ranked association Single Nucleotide Polymorphisms (SNPs) among the four software packages. We tested MultiGWAS with public tetraploid potato data for tuber shape and several simulated data under both additive and dominant models. These tests demonstrated that MultiGWAS is better at detecting reliable associations than using each of the four software packages individually. Moreover, the parallel analysis of polyploid and diploid software that only offers MultiGWAS demonstrates its utility in understanding the best genetic model behind the SNP association in tetraploid organisms. Therefore, MultiGWAS probed to be an excellent alternative for wrapping GWAS replication in diploid and tetraploid organisms in a single analysis environment.
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Affiliation(s)
- Luis Garreta
- Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA)CI TibaitatáBogotaColombia
| | - Ivania Cerón‐Souza
- Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA)CI TibaitatáBogotaColombia
| | | | - Paula H. Reyes‐Herrera
- Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA)CI TibaitatáBogotaColombia
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27
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The recombination landscape and multiple QTL mapping in a Solanum tuberosum cv. 'Atlantic'-derived F 1 population. Heredity (Edinb) 2021; 126:817-830. [PMID: 33753876 PMCID: PMC8102480 DOI: 10.1038/s41437-021-00416-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 02/02/2021] [Accepted: 02/04/2021] [Indexed: 02/01/2023] Open
Abstract
There are many challenges involved with the genetic analyses of autopolyploid species, such as the tetraploid potato, Solanum tuberosum (2n = 4x = 48). The development of new analytical methods has made it valuable to re-analyze an F1 population (n = 156) derived from a cross involving 'Atlantic', a widely grown chipping variety in the USA. A fully integrated genetic map with 4285 single nucleotide polymorphisms, spanning 1630 cM, was constructed with MAPpoly software. We observed that bivalent configurations were the most abundant ones (51.0~72.4% depending on parent and linkage group), though multivalent configurations were also observed (2.2~39.2%). Seven traits were evaluated over four years (2006-8 and 2014) and quantitative trait loci (QTL) mapping was carried out using QTLpoly software. Based on a multiple-QTL model approach, we detected 21 QTL for 15 out of 27 trait-year combination phenotypes. A hotspot on linkage group 5 was identified with co-located QTL for maturity, plant yield, specific gravity, and internal heat necrosis resistance evaluated over different years. Additional QTL for specific gravity and dry matter were detected with maturity-corrected phenotypes. Among the genes around QTL peaks, we found those on chromosome 5 that have been previously implicated in maturity (StCDF1) and tuber formation (POTH1). These analyses have the potential to provide insights into the biology and breeding of tetraploid potato and other autopolyploid species.
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28
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Asfaw A, Aderonmu DS, Darkwa K, De Koeyer D, Agre P, Abe A, Olasanmi B, Adebola P, Asiedu R. Genetic parameters, prediction, and selection in a white Guinea yam early-generation breeding population using pedigree information. CROP SCIENCE 2021; 61:1038-1051. [PMID: 33883753 PMCID: PMC8048640 DOI: 10.1002/csc2.20382] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 10/12/2020] [Indexed: 06/12/2023]
Abstract
Better understanding of the genetic control of traits in breeding populations is crucial for the selection of superior varieties and parents. This study aimed to assess genetic parameters and breeding values for six essential traits in a white Guinea yam (Dioscorea rotundata Poir.) breeding population. For this, pedigree-based best linear unbiased prediction (P-BLUP) was used. The results revealed significant nonadditive genetic variances and medium to high (.45-.79) broad-sense heritability estimates for the traits studied. The pattern of associations among the genetic values of the traits suggests that selection based on a multiple-trait selection index has potential for identifying superior breeding lines. Parental breeding values predicted using progeny performance identified 13 clones with high genetic potential for simultaneous improvement of the measured traits in the yam breeding program. Subsets of progeny were identified for intermating or further variety testing based on additive genetic and total genetic values. Selection of the top 5% progenies based on the multi-trait index revealed positive genetic gains for fresh tuber yield (t ha-1), tuber yield (kg plant-1), and average tuber weight (kg). However, genetic gain was negative for tuber dry matter content and Yam mosaic virus resistance in comparison with standard varieties. Our results show the relevance of P-BLUP for the selection of superior parental clones and progenies with higher breeding values for interbreeding and higher genotypic value for variety development in yam.
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Affiliation(s)
- Asrat Asfaw
- International Institute of Tropical Agriculture (IITA)IbadanNigeria
| | - Dotun Samuel Aderonmu
- International Institute of Tropical Agriculture (IITA)IbadanNigeria
- International Potato Center (CIP)AbujaNigeria
- Dep. of AgronomyUniv. of IbadanIbadanNigeria
| | - Kwabena Darkwa
- International Institute of Tropical Agriculture (IITA)IbadanNigeria
- Pan African Univ., Institute of Life and Earth SciencesUniv. of IbadanIbadanNigeria
| | - David De Koeyer
- International Institute of Tropical Agriculture (IITA)IbadanNigeria
- Agriculture and Agri‐Food Canada850 Lincoln Road, PO Box 20280FrederictonNBE3B4Z7Canada
| | - Paterne Agre
- International Institute of Tropical Agriculture (IITA)IbadanNigeria
| | - Ayodeji Abe
- Dep. of AgronomyUniv. of IbadanIbadanNigeria
| | | | - Patrick Adebola
- International Institute of Tropical Agriculture (IITA)IbadanNigeria
| | - Robert Asiedu
- International Institute of Tropical Agriculture (IITA)IbadanNigeria
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29
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Selga C, Koc A, Chawade A, Ortiz R. A Bioinformatics Pipeline to Identify a Subset of SNPs for Genomics-Assisted Potato Breeding. PLANTS (BASEL, SWITZERLAND) 2020; 10:plants10010030. [PMID: 33374406 PMCID: PMC7824009 DOI: 10.3390/plants10010030] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/09/2020] [Accepted: 12/10/2020] [Indexed: 05/20/2023]
Abstract
Modern potato breeding methods following a genomic-led approach provide means for shortening breeding cycles and increasing breeding efficiency across selection cycles. Acquiring genetic data for large breeding populations remains expensive. We present a pipeline to reduce the number of single nucleotide polymorphisms (SNPs) to lower the cost of genotyping. First, we reduced the number of individuals to be genotyped with a high-throughput method according to the multi-trait variation as defined by principal component analysis of phenotypic characteristics. Next, we reduced the number of SNPs by pruning for linkage disequilibrium. By adjusting the square of the correlation coefficient between two adjacent loci, we obtained reduced subsets of SNPs. We subsequently tested these SNP subsets by two methods; (1) a genome-wide association study (GWAS) for marker identification, and (2) genomic selection (GS) to predict genomic estimated breeding values. The results indicate that both GWAS and GS can be done without loss of information after SNP reduction. The pipeline allows for creating custom SNP subsets to cover all variation found in any particular breeding population. Low-throughput genotyping will reduce the genotyping cost associated with large populations, thereby making genomic breeding methods applicable to large potato breeding populations by reducing genotyping costs.
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30
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Sood S, Bhardwaj V, Kaushik SK, Sharma S. Prediction based on estimated breeding values using genealogy for tuber yield and late blight resistance in auto-tetraploid potato ( Solanum tuberosum L.). Heliyon 2020; 6:e05624. [PMID: 33305041 PMCID: PMC7710635 DOI: 10.1016/j.heliyon.2020.e05624] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 09/08/2020] [Accepted: 11/25/2020] [Indexed: 11/05/2022] Open
Abstract
Estimated breeding values using best linear unbiased prediction (BLUP) through pedigree relationship can enhance selection efficiency and save time as well as resources in autotetraploid potato breeding program. Here, we used historical preliminary yield evaluation trials data of 469–619 breeding lines for tuber yield and late blight resistance to estimate heritability and BLUP based breeding values modelling auto-tetraploid inheritance in mixed model analysis. The pedigree file had a depth of 3–4 generations with total 370 individuals including 111 founders. Heritability estimates varied from 0.15 for marketable tuber yield to 0.47 for late blight resistance computed using A matrix. The prediction accuracy for total tuber yield, marketable tuber yield and late blight resistance (AUDPC) was 0.53 ± 0.02, 0.44 ± 0.02 and 0.81 ± 0.01, respectively. The prediction accuracy was highest for late blight resistance and moderate for total and marketable tuber yield. The prediction bias measured as regression of observed phenotype values on predicted values for late blight resistance was almost nil in comparison to total and marketable tuber yield. Moderate to high prediction accuracies for tuber yields and late blight resistance suggest the selection of genotypes based on EBVs in Indian potato breeding programme for higher genetic gain.
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Affiliation(s)
- Salej Sood
- ICAR-Central Potato Research Institute, Shimla, HP, India
| | - Vinay Bhardwaj
- ICAR-Central Potato Research Institute, Shimla, HP, India
| | - S K Kaushik
- ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
| | - Sanjeev Sharma
- ICAR-Central Potato Research Institute, Shimla, HP, India
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Hegde N, Doddamani D, Kushalappa AC. Identification and functional characterisation of late blight resistance polymorphic genes in Russet Burbank potato cultivar. FUNCTIONAL PLANT BIOLOGY : FPB 2020; 48:88-102. [PMID: 32741427 DOI: 10.1071/fp19327] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 07/14/2020] [Indexed: 06/11/2023]
Abstract
In plants, the biosynthesis of the phenylpropanoid, flavonoid and fatty acid pathway monomers, polymers and conjugated metabolites play a vital role in disease resistance. These are generally deposited to reinforce cell walls to contain the pathogen to the site of infection. Identification of sequence variants in genes that biosynthesise these resistance metabolites can explain the mechanisms of disease resistance. The resistant and susceptible genotypes inoculated with Phytophthora infestans were RNA sequenced to identify the single nucleotide polymorphisms (SNPs) and insertion/deletion (InDel) variations. The SNPs/InDels were annotated and classified into different categories based on their effect on gene functions. In the selected 25 biosynthetic genes overlapping 39 transcripts, a total of 52 SNPs/InDels were identified in the protein-coding (CDS) regions. These were categorised as deleterious based on prediction of their effects on protein structure and function. The SNPs/InDels data obtained in this study can be used in genome editing to enhance late blight resistance in Russet Burbank and other potato cultivars.
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Affiliation(s)
- Niranjan Hegde
- Department of Plant Science, McGill University, Ste.-Anne-de-Bellevue, QC, Canada
| | | | - Ajjamada C Kushalappa
- Department of Plant Science, McGill University, Ste.-Anne-de-Bellevue, QC, Canada; and Corresponding author.
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Sood S, Lin Z, Caruana B, Slater AT, Daetwyler HD. Making the most of all data: Combining non-genotyped and genotyped potato individuals with HBLUP. THE PLANT GENOME 2020; 13:e20056. [PMID: 33217206 DOI: 10.1002/tpg2.20056] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 08/03/2020] [Accepted: 08/20/2020] [Indexed: 05/20/2023]
Abstract
Using genomic information to predict phenotypes can improve the accuracy of estimated breeding values and can potentially increase genetic gain over conventional breeding. In this study, we investigated the prediction accuracies achieved by best linear unbiased prediction (BLUP) for nine potato phenotypic traits using three types of relationship matrices pedigree ABLUP, genomic GBLUP, and a hybrid matrix (H) combining pedigree and genomic information (HBLUP). Deep pedigree information was available for >3000 different potato breeding clones evaluated over four years. Genomic relationships were estimated from >180,000 informative SNPs generated using a genotyping-by-sequencing transcriptome (GBS-t) protocol for 168 cultivars, many of which were parents of clones. Two validation scenarios were implemented, namely "Genotyped Cultivars Validation" (a subset of genotyped lines as validation set) and "Non-genotyped 2009 Progenies Validation". Most of the traits showed moderate to high narrow sense heritabilities (range 0.22-0.72). In the Genotyped Cultivars Validation, HBLUP outperformed ABLUP on prediction accuracies for all traits except early blight, and outperformed GBLUP for most of the traits except tuber shape, tuber eye depth and boil after-cooking darkening. This is evidence that the in-depth relationship within the H matrix could potentially result in better prediction accuracy in comparison to using A or G matrix individually. The prediction accuracies of the Non-genotyped 2009 Progenies Validation were comparable between ABLUP and HBLUP, varying from 0.17-0.70 and 0.18-0.69, respectively. Better prediction accuracy and less bias in prediction using HBLUP is of practical utility to breeders as all breeding material is ranked on the same scale leading to improved selection decisions. In addition, our approach provides an economical alternative to utilize historic breeding data with current genotyped individuals in implementing genomic selection.
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Affiliation(s)
- Salej Sood
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia
- Division of Crop Improvement, ICAR-Central Potato Research Institute, Shimla, Himachal Pradesh, 171001, India
| | - Zibei Lin
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia
| | - Brittney Caruana
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | - Anthony T Slater
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia
| | - Hans D Daetwyler
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, 5 Ring Road, Bundoora, VIC 3083, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
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Ismail S, Jiang B, Nasimi Z, Inam-ul-Haq M, Yamamoto N, Danso Ofori A, Khan N, Arshad M, Abbas K, Zheng A. Investigation of Streptomyces scabies Causing Potato Scab by Various Detection Techniques, Its Pathogenicity and Determination of Host-Disease Resistance in Potato Germplasm. Pathogens 2020; 9:pathogens9090760. [PMID: 32957549 PMCID: PMC7559370 DOI: 10.3390/pathogens9090760] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 09/10/2020] [Accepted: 09/12/2020] [Indexed: 11/16/2022] Open
Abstract
Streptomyces scabies is a Gram-positive bacterial pathogen that causes common scab disease to several crops, particularly in the potato. It is a soil borne pathogen, a very devastating scab pathogen and difficult to manage in the field. Streptomyces has several species that cause common scab such as S. scabiei, S. acidiscabies, S. europaeiscabiei, S. luridiscabiei, S. niveiscabiei, S. puniciscabiei, S. reticuliscabiei, S. stelliscabiei, S. turgidiscabies, S. ipomoeae. Common scab disease harmfully affects potato economic and market value due to the presence of black spots on the tuber. Owing to its genetic diversity and pathogenicity, the determination of pathogen presence in potato fields is still challenging. In this study, S. scabies genetic diversity was measured by surveying five potato-growing areas of Pakistan during the growing season 2019. A total of 50 Streptomyces isolates, including S. scabies, S. acidiscabies, S. griseoflavus were isolated and identified based on morphologic, biochemical and molecular analysis. Virulent confirmation assays confirmed ten virulent strains of Streptomyces spp. On the potato cultivars Cardinal and Santee. Among the Streptomyces species, S. scabies showed the highest scab index, followed by S. acidiscabies and S. griseoflavus by exhibiting the scab-like lesions on potato tubers. Ten potato cultivars were screened against these virulent isolates of Streptomyces. The Faisalabad white variety showed the highest scab index followed By Cardinal, Tourag, Kuroda, Santee, Lady Rosetta, Asterix, Diamant, Faisalabad red and Sadaf. Moreover, genetic diversity and pathogenicity of Streptomyces spp. on potato tubers were also likely diverse in different geographical regions and also potato cultivars. This study represents a contribution to understanding the local interaction between potatoes and Streptomyces spp. in Pakistan. It will aid in supporting a solution for the management of this pathogen around the world.
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Affiliation(s)
- Sohaib Ismail
- Department of Plant Pathology, Sichuan Agricultural University, Chengdu 611130, China; (S.I.); (Z.N.); (N.Y.); (A.D.O.)
| | - Bo Jiang
- College of Lifescience and Technology, Yangtze Normal University, Chongqing 408100, China;
| | - Zohreh Nasimi
- Department of Plant Pathology, Sichuan Agricultural University, Chengdu 611130, China; (S.I.); (Z.N.); (N.Y.); (A.D.O.)
| | - M. Inam-ul-Haq
- Department of Plant Pathology, PMAS-Arid Agriculture University, Rawalpindi 44000, Pakistan;
| | - Naoki Yamamoto
- Department of Plant Pathology, Sichuan Agricultural University, Chengdu 611130, China; (S.I.); (Z.N.); (N.Y.); (A.D.O.)
| | - Andrews Danso Ofori
- Department of Plant Pathology, Sichuan Agricultural University, Chengdu 611130, China; (S.I.); (Z.N.); (N.Y.); (A.D.O.)
| | - Nawab Khan
- Department of Agricultural Economics, Sichuan Agricultural University, Chengdu 611130, China;
| | - Muhammad Arshad
- Department of Microbiology, Sichuan Agricultural University, Chengdu 611130, China;
| | - Kumail Abbas
- Institute of Horticulture, Sichuan Agricultural University, Chengdu 611130, China;
| | - Aiping Zheng
- Department of Plant Pathology, Sichuan Agricultural University, Chengdu 611130, China; (S.I.); (Z.N.); (N.Y.); (A.D.O.)
- Correspondence:
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Fofana B, Somalraju A, Fillmore S, Zaidi M, Main D, Ghose K. Comparative transcriptome expression analysis in susceptible and resistant potato (Solanum tuberosum) cultivars to common scab (Streptomyces scabies) revealed immune priming responses in the incompatible interaction. PLoS One 2020; 15:e0235018. [PMID: 32673321 PMCID: PMC7365407 DOI: 10.1371/journal.pone.0235018] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 06/05/2020] [Indexed: 11/20/2022] Open
Abstract
Common scab disease in potato has become a widespread issue in major potato production areas, leading to increasing economic losses. Varietal resistance is seen as a viable and long-term scab management strategy. However, the genes and mechanisms of varietal resistance are unknown. In the current study, a comparative RNA transcriptome sequencing and differential gene signaling and priming sensitization studies were conducted in two potato cultivars that differ by their response to common scab (Streptomyces scabies), for unraveling the genes and pathways potentially involved in resistance within this pathosystem. We report on a consistent and contrasted gene expression pattern from 1,064 annotated genes differentiating a resistant (Hindenburg) and a susceptible (Green Mountain) cultivars, and identified a set of 273 co-regulated differentially expressed genes in 34 pathways that more likely reflect the genetic differences of the cultivars and metabolic mechanisms involved in the scab pathogenesis and resistance. The data suggest that comparative transcriptomic phenotyping can be used to predict scab lesion phenotype in breeding lines using mature potato tuber. The study also showed that the resistant cultivar, Hindenburg, has developed and maintained a capacity to sense and prime itself for persistent response to scab disease over time, and suggests an immune priming reaction as a mechanism for induced-resistance in scab resistant potato cultivars. The set of genes identified, described, and discussed in the study paves the foundation for detailed characterizations towards tailoring and designing procedures for targeted gene knockout through gene editing and phenotypic evaluation.
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Affiliation(s)
- Bourlaye Fofana
- Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, Charlottetown, Prince Edward Island, Canada
- * E-mail:
| | - Ashok Somalraju
- Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, Charlottetown, Prince Edward Island, Canada
| | - Sherry Fillmore
- Kentville Research and Development Centre, Agriculture and Agri-Food Canada, Kentville, Nova Scotia, Canada
| | - Mohsin Zaidi
- Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, Charlottetown, Prince Edward Island, Canada
| | - David Main
- Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, Charlottetown, Prince Edward Island, Canada
| | - Kaushik Ghose
- Department of Plant and Soil Science, Texas Tech University, Lubbock, Texas, United States of America
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Pérez-Enciso M, Ramírez-Ayala LC, Zingaretti LM. SeqBreed: a python tool to evaluate genomic prediction in complex scenarios. Genet Sel Evol 2020; 52:7. [PMID: 32039696 PMCID: PMC7008576 DOI: 10.1186/s12711-020-0530-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 01/29/2020] [Indexed: 11/28/2022] Open
Abstract
Background Genomic prediction (GP) is a method whereby DNA polymorphism information is used to predict breeding values for complex traits. Although GP can significantly enhance predictive accuracy, it can be expensive and difficult to implement. To help design optimum breeding programs and experiments, including genome-wide association studies and genomic selection experiments, we have developed SeqBreed, a generic and flexible forward simulator programmed in python3. Results SeqBreed accommodates sex and mitochondrion chromosomes as well as autopolyploidy. It can simulate any number of complex phenotypes that are determined by any number of causal loci. SeqBreed implements several GP methods, including genomic best linear unbiased prediction (GBLUP), single-step GBLUP, pedigree-based BLUP, and mass selection. We illustrate its functionality with Drosophila genome reference panel (DGRP) sequence data and with tetraploid potato genotype data. Conclusions SeqBreed is a flexible and easy to use tool that can be used to optimize GP or genome-wide association studies. It incorporates some of the most popular GP methods and includes several visualization tools. Code is open and can be freely modified. Software, documentation, and examples are available at https://github.com/miguelperezenciso/SeqBreed.
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Affiliation(s)
- Miguel Pérez-Enciso
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, 08193, Bellaterra, Barcelona, Spain. .,ICREA, Passeig de Lluís Companys 23, 08010, Barcelona, Spain.
| | - Lino C Ramírez-Ayala
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, 08193, Bellaterra, Barcelona, Spain
| | - Laura M Zingaretti
- Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, 08193, Bellaterra, Barcelona, Spain.,Universidad Nacional de Villa María, IAPBCyA-IAPCH Villa María, Córdoba, Argentina
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Zingaretti LM, Gezan SA, Ferrão LFV, Osorio LF, Monfort A, Muñoz PR, Whitaker VM, Pérez-Enciso M. Exploring Deep Learning for Complex Trait Genomic Prediction in Polyploid Outcrossing Species. FRONTIERS IN PLANT SCIENCE 2020; 11:25. [PMID: 32117371 PMCID: PMC7015897 DOI: 10.3389/fpls.2020.00025] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 01/10/2020] [Indexed: 05/21/2023]
Abstract
Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates are predicted using genome wide marker information. Although numerous examples of GP exist in plants and animals, applications to polyploid organisms are still scarce, partly due to limited genome resources and the complexity of this system. Deep learning (DL) techniques comprise a heterogeneous collection of machine learning algorithms that have excelled at many prediction tasks. A potential advantage of DL for GP over standard linear model methods is that DL can potentially take into account all genetic interactions, including dominance and epistasis, which are expected to be of special relevance in most polyploids. In this study, we evaluated the predictive accuracy of linear and DL techniques in two important small fruits or berries: strawberry and blueberry. The two datasets contained a total of 1,358 allopolyploid strawberry (2n=8x=112) and 1,802 autopolyploid blueberry (2n=4x=48) individuals, genotyped for 9,908 and 73,045 single nucleotide polymorphism (SNP) markers, respectively, and phenotyped for five agronomic traits each. DL depends on numerous parameters that influence performance and optimizing hyperparameter values can be a critical step. Here we show that interactions between hyperparameter combinations should be expected and that the number of convolutional filters and regularization in the first layers can have an important effect on model performance. In terms of genomic prediction, we did not find an advantage of DL over linear model methods, except when the epistasis component was important. Linear Bayesian models were better than convolutional neural networks for the full additive architecture, whereas the opposite was observed under strong epistasis. However, by using a parameterization capable of taking into account these non-linear effects, Bayesian linear models can match or exceed the predictive accuracy of DL. A semiautomatic implementation of the DL pipeline is available at https://github.com/lauzingaretti/deepGP/.
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Affiliation(s)
- Laura M. Zingaretti
- Centre for Research in Agricultural Genomics (CRAG) CSIC-IRTA-UAB-UB, Campus UAB, Barcelona, Spain
| | - Salvador Alejandro Gezan
- School of Forest Resources and Conservation, University of Florida, Gainesville, FL, United States
| | - Luis Felipe V. Ferrão
- Blueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, United States
| | - Luis F. Osorio
- IFAS Gulf Coast Research and Education Center, University of Florida, Wimauma, FL, United States
| | - Amparo Monfort
- Centre for Research in Agricultural Genomics (CRAG) CSIC-IRTA-UAB-UB, Campus UAB, Barcelona, Spain
- Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Barcelona, Spain
| | - Patricio R. Muñoz
- Blueberry Breeding and Genomics Lab, Horticultural Sciences Department, University of Florida, Gainesville, FL, United States
| | - Vance M. Whitaker
- IFAS Gulf Coast Research and Education Center, University of Florida, Wimauma, FL, United States
| | - Miguel Pérez-Enciso
- Centre for Research in Agricultural Genomics (CRAG) CSIC-IRTA-UAB-UB, Campus UAB, Barcelona, Spain
- ICREA, Passeig de Lluís Companys 23, Barcelona, Spain
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Hong JP, Ro N, Lee HY, Kim GW, Kwon JK, Yamamoto E, Kang BC. Genomic Selection for Prediction of Fruit-Related Traits in Pepper ( Capsicum spp.). FRONTIERS IN PLANT SCIENCE 2020; 11:570871. [PMID: 33193503 PMCID: PMC7655793 DOI: 10.3389/fpls.2020.570871] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 09/24/2020] [Indexed: 05/09/2023]
Abstract
Pepper (Capsicum spp.) fruit-related traits are critical determinants of quality. These traits are controlled by quantitatively inherited genes for which marker-assisted selection (MAS) has proven insufficiently effective. Here, we evaluated the potential of genomic selection, in which genotype and phenotype data for a training population are used to predict phenotypes of a test population with only genotype data, for predicting fruit-related traits in pepper. We measured five fruit traits (fruit length, fruit shape, fruit width, fruit weight, and pericarp thickness) in 351 accessions from the pepper core collection, including 229 Capsicum annuum, 48 Capsicum baccatum, 48 Capsicum chinense, 25 Capsicum frutescens, and 1 Capsicum chacoense in 4 years at two different locations and genotyped these accessions using genotyping-by-sequencing. Among the whole core collection, considering its genetic distance and sexual incompatibility, we only included 302 C. annum complex (229 C. annuum, 48 C. chinense, and 25 C. frutescens) into further analysis. We used phenotypic and genotypic data to investigate genomic prediction models, marker density, and effects of population structure. Among 10 genomic prediction methods tested, Reproducing Kernel Hilbert Space (RKHS) produced the highest prediction accuracies (measured as correlation between predicted values and observed values) across the traits, with accuracies of 0.75, 0.73, 0.84, 0.83, and 0.82 for fruit length, fruit shape, fruit width, fruit weight, and pericarp thickness, respectively. Overall, prediction accuracies were positively correlated with the number of markers for fruit traits. We tested our genomic selection models in a separate population of recombinant inbred lines derived from two parental lines from the core collection. Despite the large difference in genetic diversity between the training population and the test population, we obtained moderate prediction accuracies of 0.32, 0.34, 0.50, and 0.48 for fruit length, fruit shape, fruit width, and fruit weight, respectively. This use of genomic selection for fruit-related traits demonstrates the potential use of core collections and genomic selection as tools for crop improvement.
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Affiliation(s)
- Ju-Pyo Hong
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Nayoung Ro
- National Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju, South Korea
| | - Hea-Young Lee
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Geon Woo Kim
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Jin-Kyung Kwon
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
| | - Eiji Yamamoto
- Graduate School of Agriculture, Meiji University, Tokyo, Japan
| | - Byoung-Cheorl Kang
- Department of Agriculture, Forestry and Bioresources, Research Institute of Agriculture and Life Sciences, Plant Genomics Breeding Institute, College of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea
- *Correspondence: Byoung-Cheorl Kang,
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pSBVB: A Versatile Simulation Tool To Evaluate Genomic Selection in Polyploid Species. G3-GENES GENOMES GENETICS 2019; 9:327-334. [PMID: 30573468 PMCID: PMC6385978 DOI: 10.1534/g3.118.200942] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Genomic Selection (GS) is the procedure whereby molecular information is used to predict complex phenotypes and it is standard in many animal and plant breeding schemes. However, only a small number of studies have been reported in horticultural crops, and in polyploid species in particular. In this paper, we have developed a versatile forward simulation tool, called polyploid Sequence Based Virtual Breeding (pSBVB), to evaluate GS strategies in polyploids; pSBVB is an efficient gene dropping software that can simulate any number of complex phenotypes, allowing a very flexible modeling of phenotypes suited to polyploids. As input, it takes genotype data from the founder population, which can vary from single nucleotide polymorphisms (SNP) chips up to sequence, a list of causal variants for every trait and their heritabilities, and the pedigree. Recombination rates between homeologous chromosomes can be specified, so that both allo- and autopolyploid species can be considered. The program outputs phenotype and genotype data for all individuals in the pedigree. Optionally, it can produce several genomic relationship matrices that consider exact or approximate genotype values. pSBVB can therefore be used to evaluate GS strategies in polyploid species (say varying SNP density, genetic architecture or population size, among other factors), or to optimize experimental designs for association studies. We illustrate pSBVB with SNP data from tetraploid potato and partial sequence data from octoploid strawberry, and we show that GS is a promising breeding strategy for polyploid species but that the actual advantage critically depends on the underlying genetic architecture. Source code, examples and a complete manual are freely available in GitHub https://github.com/lauzingaretti/pSBVB.
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He L, Xiao J, Rashid KY, Jia G, Li P, Yao Z, Wang X, Cloutier S, You FM. Evaluation of Genomic Prediction for Pasmo Resistance in Flax. Int J Mol Sci 2019; 20:E359. [PMID: 30654497 PMCID: PMC6359301 DOI: 10.3390/ijms20020359] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 01/06/2019] [Accepted: 01/11/2019] [Indexed: 02/06/2023] Open
Abstract
Pasmo (Septoria linicola) is a fungal disease causing major losses in seed yield and quality and stem fibre quality in flax. Pasmo resistance (PR) is quantitative and has low heritability. To improve PR breeding efficiency, the accuracy of genomic prediction (GP) was evaluated using a diverse worldwide core collection of 370 accessions. Four marker sets, including three defined by 500, 134 and 67 previously identified quantitative trait loci (QTL) and one of 52,347 PR-correlated genome-wide single nucleotide polymorphisms, were used to build ridge regression best linear unbiased prediction (RR-BLUP) models using pasmo severity (PS) data collected from field experiments performed during five consecutive years. With five-fold random cross-validation, GP accuracy as high as 0.92 was obtained from the models using the 500 QTL when the average PS was used as the training dataset. GP accuracy increased with training population size, reaching values >0.9 with training population size greater than 185. Linear regression of the observed PS with the number of positive-effect QTL in accessions provided an alternative GP approach with an accuracy of 0.86. The results demonstrate the GP models based on marker information from all identified QTL and the 5-year PS average is highly effective for PR prediction.
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Affiliation(s)
- Liqiang He
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University/JiangSu Collaborative Innovation Center for Modern Crop Production, Nanjing 210095, China.
| | - Jin Xiao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University/JiangSu Collaborative Innovation Center for Modern Crop Production, Nanjing 210095, China.
| | - Khalid Y Rashid
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada.
| | - Gaofeng Jia
- Crop Development Centre, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada.
| | - Pingchuan Li
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada.
| | - Zhen Yao
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB R6M 1Y5, Canada.
| | - Xiue Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University/JiangSu Collaborative Innovation Center for Modern Crop Production, Nanjing 210095, China.
| | - Sylvie Cloutier
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
| | - Frank M You
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON K1A 0C6, Canada.
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University/JiangSu Collaborative Innovation Center for Modern Crop Production, Nanjing 210095, China.
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