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Pixley KV, Cairns JE, Lopez-Ridaura S, Ojiewo CO, Dawud MA, Drabo I, Mindaye T, Nebie B, Asea G, Das B, Daudi H, Desmae H, Batieno BJ, Boukar O, Mukankusi CTM, Nkalubo ST, Hearne SJ, Dhugga KS, Gandhi H, Snapp S, Zepeda-Villarreal EA. Redesigning crop varieties to win the race between climate change and food security. Mol Plant 2023; 16:1590-1611. [PMID: 37674314 DOI: 10.1016/j.molp.2023.09.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 08/17/2023] [Accepted: 09/03/2023] [Indexed: 09/08/2023]
Abstract
Climate change poses daunting challenges to agricultural production and food security. Rising temperatures, shifting weather patterns, and more frequent extreme events have already demonstrated their effects on local, regional, and global agricultural systems. Crop varieties that withstand climate-related stresses and are suitable for cultivation in innovative cropping systems will be crucial to maximize risk avoidance, productivity, and profitability under climate-changed environments. We surveyed 588 expert stakeholders to predict current and novel traits that may be essential for future pearl millet, sorghum, maize, groundnut, cowpea, and common bean varieties, particularly in sub-Saharan Africa. We then review the current progress and prospects for breeding three prioritized future-essential traits for each of these crops. Experts predict that most current breeding priorities will remain important, but that rates of genetic gain must increase to keep pace with climate challenges and consumer demands. Importantly, the predicted future-essential traits include innovative breeding targets that must also be prioritized; for example, (1) optimized rhizosphere microbiome, with benefits for P, N, and water use efficiency, (2) optimized performance across or in specific cropping systems, (3) lower nighttime respiration, (4) improved stover quality, and (5) increased early vigor. We further discuss cutting-edge tools and approaches to discover, validate, and incorporate novel genetic diversity from exotic germplasm into breeding populations with unprecedented precision, accuracy, and speed. We conclude that the greatest challenge to developing crop varieties to win the race between climate change and food security might be our innovativeness in defining and boldness to breed for the traits of tomorrow.
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Affiliation(s)
- Kevin V Pixley
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
| | - Jill E Cairns
- International Maize and Wheat Improvement Center (CIMMYT), Harare, Zimbabwe
| | | | - Chris O Ojiewo
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | | | - Inoussa Drabo
- International Maize and Wheat Improvement Center (CIMMYT), Dakar, Senegal
| | - Taye Mindaye
- Ethiopian Institute of Agricultural Research (EIAR), Addis Ababa, Ethiopia
| | - Baloua Nebie
- International Maize and Wheat Improvement Center (CIMMYT), Dakar, Senegal
| | - Godfrey Asea
- National Agricultural Research Organization (NARO), Kampala, Uganda
| | - Biswanath Das
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Happy Daudi
- Tanzania Agricultural Research Institute (TARI), Naliendele, Tanzania
| | - Haile Desmae
- International Maize and Wheat Improvement Center (CIMMYT), Dakar, Senegal
| | - Benoit Joseph Batieno
- Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | - Ousmane Boukar
- International Institute of Tropicl Agriculture (IITA), Kano, Nigeria
| | | | | | - Sarah J Hearne
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Kanwarpal S Dhugga
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Harish Gandhi
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Sieglinde Snapp
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
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Biswal AK, Alakonya AE, Mottaleb KA, Hearne SJ, Sonder K, Molnar TL, Jones AM, Pixley KV, Prasanna BM. Maize Lethal Necrosis disease: review of molecular and genetic resistance mechanisms, socio-economic impacts, and mitigation strategies in sub-Saharan Africa. BMC Plant Biol 2022; 22:542. [PMID: 36418954 PMCID: PMC9686106 DOI: 10.1186/s12870-022-03932-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 11/07/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Maize lethal necrosis (MLN) disease is a significant constraint for maize producers in sub-Saharan Africa (SSA). The disease decimates the maize crop, in some cases, causing total crop failure with far-reaching impacts on regional food security. RESULTS In this review, we analyze the impacts of MLN in Africa, finding that resource-poor farmers and consumers are the most vulnerable populations. We examine the molecular mechanism of MLN virus transmission, role of vectors and host plant resistance identifying a range of potential opportunities for genetic and phytosanitary interventions to control MLN. We discuss the likely exacerbating effects of climate change on the MLN menace and describe a sobering example of negative genetic association between tolerance to heat/drought and susceptibility to viral infection. We also review role of microRNAs in host plant response to MLN causing viruses as well as heat/drought stress that can be carefully engineered to develop resistant varieties using novel molecular techniques. CONCLUSIONS With the dual drivers of increased crop loss due to MLN and increased demand of maize for food, the development and deployment of simple and safe technologies, like resistant cultivars developed through accelerated breeding or emerging gene editing technologies, will have substantial positive impact on livelihoods in the region. We have summarized the available genetic resources and identified a few large-effect QTLs that can be further exploited to accelerate conversion of existing farmer-preferred varieties into resistant cultivars.
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Affiliation(s)
- Akshaya Kumar Biswal
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico.
| | - Amos Emitati Alakonya
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | - Khondokar Abdul Mottaleb
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | - Sarah J Hearne
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | - Kai Sonder
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
| | | | - Alan M Jones
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kevin Vail Pixley
- International Maize and Wheat Improvement Center (CIMMYT), Km. 45, Carretera Mexico-Veracruz, El Batan, Texcoco, C.P. 56237, Mexico
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3
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Martini JWR, Hearne SJ, Gardunia B, Wimmer V, Toledo FH. Editorial: Genomic Selection: Lessons Learned and Perspectives. Front Plant Sci 2022; 13:890434. [PMID: 35693181 PMCID: PMC9186467 DOI: 10.3389/fpls.2022.890434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 04/08/2022] [Indexed: 06/15/2023]
Affiliation(s)
| | - Sarah J. Hearne
- International Maize and Wheat Improvement Center, Texcoco, Mexico
- Excellence in Breeding Platform, Texcoco, Mexico
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Gholami M, Wimmer V, Sansaloni C, Petroli C, Hearne SJ, Covarrubias-Pazaran G, Rensing S, Heise J, Pérez-Rodríguez P, Dreisigacker S, Crossa J, Martini JWR. A Comparison of the Adoption of Genomic Selection Across Different Breeding Institutions. Front Plant Sci 2021; 12:728567. [PMID: 34868114 PMCID: PMC8640095 DOI: 10.3389/fpls.2021.728567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 09/30/2021] [Indexed: 06/13/2023]
Affiliation(s)
| | | | - Carolina Sansaloni
- Genetic Resources Program, International Maize and Wheat Improvement Center, Texcoco, Mexico
| | - Cesar Petroli
- Genetic Resources Program, International Maize and Wheat Improvement Center, Texcoco, Mexico
| | - Sarah J. Hearne
- Genetic Resources Program, International Maize and Wheat Improvement Center, Texcoco, Mexico
- Excellence in Breeding Platform, Consultative Group for International Agricultural Research, Texcoco, Mexico
| | | | - Stefan Rensing
- IT Solutions for Animal Production (vit - Vereinigte Informationssysteme Tierhaltung w.V.), Verden, Germany
| | - Johannes Heise
- IT Solutions for Animal Production (vit - Vereinigte Informationssysteme Tierhaltung w.V.), Verden, Germany
| | | | - Susanne Dreisigacker
- Global Wheat Program, International Maize and Wheat Improvement Center, Texcoco, Mexico
| | - José Crossa
- Genetic Resources Program, International Maize and Wheat Improvement Center, Texcoco, Mexico
- Department of Statistics, Colegio de Postgraduados, Montecillos, Mexico
| | - Johannes W. R. Martini
- Genetic Resources Program, International Maize and Wheat Improvement Center, Texcoco, Mexico
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Martini JWR, Molnar TL, Crossa J, Hearne SJ, Pixley KV. Opportunities and Challenges of Predictive Approaches for Harnessing the Potential of Genetic Resources. Front Plant Sci 2021; 12:674036. [PMID: 34276731 PMCID: PMC8281018 DOI: 10.3389/fpls.2021.674036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 05/17/2021] [Indexed: 06/13/2023]
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Li J, Chen GB, Rasheed A, Li D, Sonder K, Zavala Espinosa C, Wang J, Costich DE, Schnable PS, Hearne SJ, Li H. Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS. Mol Ecol 2019; 28:3544-3560. [PMID: 31287919 PMCID: PMC6851670 DOI: 10.1111/mec.15169] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Accepted: 06/20/2019] [Indexed: 02/01/2023]
Abstract
Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high‐quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom‐up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large‐scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding.
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Affiliation(s)
- Jing Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Guo-Bo Chen
- Clinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Awais Rasheed
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
| | - Delin Li
- Data Biotech (Beijing) Co., Ltd, Beijing, China.,College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Kai Sonder
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | | | - Jiankang Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Denise E Costich
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Patrick S Schnable
- Data Biotech (Beijing) Co., Ltd, Beijing, China.,College of Agronomy and Biotechnology, China Agricultural University, Beijing, China.,Data2Bio LLC, Ames, IA, USA.,Department of Agronomy, Iowa State University, Ames, IA, USA
| | - Sarah J Hearne
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.,International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
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7
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Aguirre-Liguori JA, Gaut BS, Jaramillo-Correa JP, Tenaillon MI, Montes-Hernández S, García-Oliva F, Hearne SJ, Eguiarte LE. Divergence with gene flow is driven by local adaptation to temperature and soil phosphorus concentration in teosinte subspecies (Zea mays parviglumis and Zea mays mexicana). Mol Ecol 2019; 28:2814-2830. [PMID: 30980686 DOI: 10.1111/mec.15098] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 03/27/2019] [Accepted: 04/08/2019] [Indexed: 01/03/2023]
Abstract
Patterns of genomic divergence between hybridizing taxa can be heterogeneous along the genome. Both differential introgression and local adaptation may contribute to this pattern. Here, we analysed two teosinte subspecies, Zea mays ssp. parviglumis and ssp. mexicana, to test whether their divergence has occurred in the face of gene flow and to infer which environmental variables have been important drivers of their ecological differentiation. We generated 9,780 DArTseqTM SNPs for 47 populations, and used an additional data set containing 33,454 MaizeSNP50 SNPs for 49 populations. With these data, we inferred features of demographic history and performed genome wide scans to determine the number of outlier SNPs associated with climate and soil variables. The two data sets indicate that divergence has occurred or been maintained despite continuous gene flow and/or secondary contact. Most of the significant SNP associations were to temperature and to phosphorus concentration in the soil. A large proportion of these candidate SNPs were located in regions of high differentiation that had been identified previously as putative inversions. We therefore propose that genomic differentiation in teosintes has occurred by a process of adaptive divergence, with putative inversions contributing to reduced gene flow between locally adapted populations.
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Affiliation(s)
- Jonás A Aguirre-Liguori
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad de México, México
| | - Brandon S Gaut
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California
| | - Juan Pablo Jaramillo-Correa
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad de México, México
| | - Maud I Tenaillon
- Génétique Quantitative et Evolution- Le Moulon, INRA, Gif-sur-Yvette, France
| | - Salvador Montes-Hernández
- Campo Experimental Bajío, Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Celaya, México
| | - Felipe García-Oliva
- Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México, Morelia, México
| | - Sarah J Hearne
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, México
| | - Luis E Eguiarte
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad de México, México
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8
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Brandenburg JT, Mary-Huard T, Rigaill G, Hearne SJ, Corti H, Joets J, Vitte C, Charcosset A, Nicolas SD, Tenaillon MI. Independent introductions and admixtures have contributed to adaptation of European maize and its American counterparts. PLoS Genet 2017; 13:e1006666. [PMID: 28301472 PMCID: PMC5373671 DOI: 10.1371/journal.pgen.1006666] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 03/30/2017] [Accepted: 03/01/2017] [Indexed: 12/27/2022] Open
Abstract
Through the local selection of landraces, humans have guided the adaptation of crops to a vast range of climatic and ecological conditions. This is particularly true of maize, which was domesticated in a restricted area of Mexico but now displays one of the broadest cultivated ranges worldwide. Here, we sequenced 67 genomes with an average sequencing depth of 18x to document routes of introduction, admixture and selective history of European maize and its American counterparts. To avoid the confounding effects of recent breeding, we targeted germplasm (lines) directly derived from landraces. Among our lines, we discovered 22,294,769 SNPs and between 0.9% to 4.1% residual heterozygosity. Using a segmentation method, we identified 6,978 segments of unexpectedly high rate of heterozygosity. These segments point to genes potentially involved in inbreeding depression, and to a lesser extent to the presence of structural variants. Genetic structuring and inferences of historical splits revealed 5 genetic groups and two independent European introductions, with modest bottleneck signatures. Our results further revealed admixtures between distinct sources that have contributed to the establishment of 3 groups at intermediate latitudes in North America and Europe. We combined differentiation- and diversity-based statistics to identify both genes and gene networks displaying strong signals of selection. These include genes/gene networks involved in flowering time, drought and cold tolerance, plant defense and starch properties. Overall, our results provide novel insights into the evolutionary history of European maize and highlight a major role of admixture in environmental adaptation, paralleling recent findings in humans.
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Affiliation(s)
- Jean-Tristan Brandenburg
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Tristan Mary-Huard
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
- UMR 518 AgroParisTech/INRA, France
| | - Guillem Rigaill
- Institute of Plant Sciences Paris-Saclay, UMR 9213/UMR1403, CNRS, INRA, Université Paris-Sud, Université d’Evry, Université Paris-Diderot, Sorbonne Paris-Cité, France
| | - Sarah J. Hearne
- CIMMYT (International Maize and Wheat Improvement Centre), El Batan, Texcoco, Edo de Mexico, Mexico
| | - Hélène Corti
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Johann Joets
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Clémentine Vitte
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Alain Charcosset
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Stéphane D. Nicolas
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
| | - Maud I. Tenaillon
- Génétique Quantitative et Evolution – Le Moulon, Institut National de la Recherche agronomique, Université Paris-Sud, Centre National de la Recherche Scientifique, AgroParisTech, Université Paris-Saclay, France
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9
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Faux AM, Gorjanc G, Gaynor RC, Battagin M, Edwards SM, Wilson DL, Hearne SJ, Gonen S, Hickey JM. AlphaSim: Software for Breeding Program Simulation. Plant Genome 2016; 9. [PMID: 27902803 DOI: 10.3835/plantgenome2016.02.0013] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
This paper describes AlphaSim, a software package for simulating plant and animal breeding programs. AlphaSim enables the simulation of multiple aspects of breeding programs with a high degree of flexibility. AlphaSim simulates breeding programs in a series of steps: (i) simulate haplotype sequences and pedigree; (ii) drop haplotypes into the base generation of the pedigree and select single-nucleotide polymorphism (SNP) and quantitative trait nucleotide (QTN); (iii) assign QTN effects, calculate genetic values, and simulate phenotypes; (iv) drop haplotypes into the burn-in generations; and (v) perform selection and simulate new generations. The program is flexible in terms of historical population structure and diversity, recent pedigree structure, trait architecture, and selection strategy. It integrates biotechnologies such as doubled-haploids (DHs) and gene editing and allows the user to simulate multiple traits and multiple environments, specify recombination hot spots and cold spots, specify gene jungles and deserts, perform genomic predictions, and apply optimal contribution selection. AlphaSim also includes restart functionalities, which increase its flexibility by allowing the simulation process to be paused so that the parameters can be changed or to import an externally created pedigree, trial design, or results of an analysis of previously simulated data. By combining the options, a user can simulate simple or complex breeding programs with several generations, variable population structures and variable breeding decisions over time. In conclusion, AlphaSim is a flexible and computationally efficient software package to simulate biotechnology enhanced breeding programs with the aim of performing rapid, low-cost, and objective in silico comparison of breeding technologies.
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Chen J, Zavala C, Ortega N, Petroli C, Franco J, Burgueño J, Costich DE, Hearne SJ. The Development of Quality Control Genotyping Approaches: A Case Study Using Elite Maize Lines. PLoS One 2016; 11:e0157236. [PMID: 27280295 PMCID: PMC4900658 DOI: 10.1371/journal.pone.0157236] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Accepted: 05/26/2016] [Indexed: 02/07/2023] Open
Abstract
Quality control (QC) of germplasm identity and purity is a critical component of breeding and conservation activities. SNP genotyping technologies and increased availability of markers provide the opportunity to employ genotyping as a low-cost and robust component of this QC. In the public sector available low-cost SNP QC genotyping methods have been developed from a very limited panel of markers of 1,000 to 1,500 markers without broad selection of the most informative SNPs. Selection of optimal SNPs and definition of appropriate germplasm sampling in addition to platform section impact on logistical and resource-use considerations for breeding and conservation applications when mainstreaming QC. In order to address these issues, we evaluated the selection and use of SNPs for QC applications from large DArTSeq data sets generated from CIMMYT maize inbred lines (CMLs). Two QC genotyping strategies were developed, the first is a “rapid QC”, employing a small number of SNPs to identify potential mislabeling of seed packages or plots, the second is a “broad QC”, employing a larger number of SNP, used to identify each germplasm entry and to measure heterogeneity. The optimal marker selection strategies combined the selection of markers with high minor allele frequency, sampling of clustered SNP in proportion to marker cluster distance and selecting markers that maintain a uniform genomic distribution. The rapid and broad QC SNP panels selected using this approach were further validated using blind test assessments of related re-generation samples. The influence of sampling within each line was evaluated. Sampling 192 individuals would result in close to 100% possibility of detecting a 5% contamination in the entry, and approximately a 98% probability to detect a 2% contamination of the line. These results provide a framework for the establishment of QC genotyping. A comparison of financial and time costs for use of these approaches across different platforms is discussed providing a framework for institutions involved in maize conservation and breeding to assess the resource use effectiveness of QC genotyping. Application of these research findings, in combination with existing QC approaches, will ensure the regeneration, distribution and use in breeding of true to type inbred germplasm. These findings also provide an effective approach to optimize SNP selection for QC genotyping in other species.
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Affiliation(s)
- Jiafa Chen
- International Maize and Wheat Improvement Center (CIMMYT); Texcoco; Edo. De Mexico; Mexico CP 56237
| | - Cristian Zavala
- International Maize and Wheat Improvement Center (CIMMYT); Texcoco; Edo. De Mexico; Mexico CP 56237
| | - Noemi Ortega
- International Maize and Wheat Improvement Center (CIMMYT); Texcoco; Edo. De Mexico; Mexico CP 56237
| | - Cesar Petroli
- International Maize and Wheat Improvement Center (CIMMYT); Texcoco; Edo. De Mexico; Mexico CP 56237
| | - Jorge Franco
- International Maize and Wheat Improvement Center (CIMMYT); Texcoco; Edo. De Mexico; Mexico CP 56237
- Departamento de Biometría, Universidad de la Republica, Paysandú; Uruguay CP 60000
| | - Juan Burgueño
- International Maize and Wheat Improvement Center (CIMMYT); Texcoco; Edo. De Mexico; Mexico CP 56237
| | - Denise E. Costich
- International Maize and Wheat Improvement Center (CIMMYT); Texcoco; Edo. De Mexico; Mexico CP 56237
- * E-mail: (DEC); (SJH)
| | - Sarah J. Hearne
- International Maize and Wheat Improvement Center (CIMMYT); Texcoco; Edo. De Mexico; Mexico CP 56237
- * E-mail: (DEC); (SJH)
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11
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Gorjanc G, Jenko J, Hearne SJ, Hickey JM. Initiating maize pre-breeding programs using genomic selection to harness polygenic variation from landrace populations. BMC Genomics 2016; 17:30. [PMID: 26732811 PMCID: PMC4702314 DOI: 10.1186/s12864-015-2345-z] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Accepted: 12/21/2015] [Indexed: 11/23/2022] Open
Abstract
Background The limited genetic diversity of elite maize germplasms raises concerns about the potential to breed for new challenges. Initiatives have been formed over the years to identify and utilize useful diversity from landraces to overcome this issue. The aim of this study was to evaluate the proposed designs to initiate a pre-breeding program within the Seeds of Discovery (SeeD) initiative with emphasis on harnessing polygenic variation from landraces using genomic selection. We evaluated these designs with stochastic simulation to provide decision support about the effect of several design factors on the quality of resulting (pre-bridging) germplasm. The evaluated design factors were: i) the approach to initiate a pre-breeding program from the selected landraces, doubled haploids of the selected landraces, or testcrosses of the elite hybrid and selected landraces, ii) the genetic parameters of landraces and phenotypes, and iii) logistical factors related to the size and management of a pre-breeding program. Results The results suggest a pre-breeding program should be initiated directly from landraces. Initiating from testcrosses leads to a rapid reconstruction of the elite donor genome during further improvement of the pre-bridging germplasm. The analysis of accuracy of genomic predictions across the various design factors indicate the power of genomic selection for pre-breeding programs with large genetic diversity and constrained resources for data recording. The joint effect of design factors was summarized with decision trees with easy to follow guidelines to optimize pre-breeding efforts of SeeD and similar initiatives. Conclusions Results of this study provide guidelines for SeeD and similar initiatives on how to initiate pre-breeding programs that aim to harness polygenic variation from landraces. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2345-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gregor Gorjanc
- Biotechnical Faculty, University of Ljubljana, 1000, Ljubljana, Slovenia. .,The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.
| | - Janez Jenko
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK. .,Agricultural Institute of Slovenia, 1000, Ljubljana, Slovenia.
| | - Sarah J Hearne
- Genetic Resources Program, International Maize and Wheat Improvement Center (CIMMYT), Apdo, 06600, México, D.F., México.
| | - John M Hickey
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK.
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Ferguson ME, Hearne SJ, Close TJ, Wanamaker S, Moskal WA, Town CD, de Young J, Marri PR, Rabbi IY, de Villiers EP. Identification, validation and high-throughput genotyping of transcribed gene SNPs in cassava. Theor Appl Genet 2012; 124:685-95. [PMID: 22069119 DOI: 10.1007/s00122-011-1739-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2011] [Accepted: 10/18/2011] [Indexed: 05/05/2023]
Abstract
The availability of genomic resources can facilitate progress in plant breeding through the application of advanced molecular technologies for crop improvement. This is particularly important in the case of less researched crops such as cassava, a staple and food security crop for more than 800 million people. Here, expressed sequence tags (ESTs) were generated from five drought stressed and well-watered cassava varieties. Two cDNA libraries were developed: one from root tissue (CASR), the other from leaf, stem and stem meristem tissue (CASL). Sequencing generated 706 contigs and 3,430 singletons. These sequences were combined with those from two other EST sequencing initiatives and filtered based on the sequence quality. Quality sequences were aligned using CAP3 and embedded in a Windows browser called HarvEST:Cassava which is made available. HarvEST:Cassava consists of a Unigene set of 22,903 quality sequences. A total of 2,954 putative SNPs were identified. Of these 1,536 SNPs from 1,170 contigs and 53 cassava genotypes were selected for SNP validation using Illumina's GoldenGate assay. As a result 1,190 SNPs were validated technically and biologically. The location of validated SNPs on scaffolds of the cassava genome sequence (v.4.1) is provided. A diversity assessment of 53 cassava varieties reveals some sub-structure based on the geographical origin, greater diversity in the Americas as opposed to Africa, and similar levels of diversity in West Africa and southern, eastern and central Africa. The resources presented allow for improved genetic dissection of economically important traits and the application of modern genomics-based approaches to cassava breeding and conservation.
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Affiliation(s)
- Morag E Ferguson
- International Institute of Tropical Agriculture (IITA), c/o ILRI, P.O. Box 30709, Nairobi, Kenya.
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Abstract
There is a wide range of existing and potential control options for Striga. This paper describes and discusses many of the control options, with a focus on technology limitations, adoption limitations (real or potential) and, in the case of novel technologies, development limitations. The paper addresses the question as to why, after many years of research, control method testing, piloting and technology dissemination, the wide-scale effective control of Striga hermonthica (Del.) Benth. and Striga asiatica (L.) Kuntze is so elusive. Limitations, including variable technology reliability, poor access to control technology, costs (monetary, labour, skills) associated with control technology, limited practicality of methods and poor information, all hamper the adoption and impact of existing control methods. Some of the same issues may impact upon novel control technologies, and this needs careful consideration. Additional issues surround other potential technologies, especially so in the case of transgenic approaches. Suggestions are made as to how the impasse of effective Striga control can be overcome. More effective use of integrated control approaches, improved crop germplasm phenotyping, enhanced understanding of the host/non-host--parasite interaction and better integration and communication among the parasitic plant research, development and extension community are among the suggestions made.
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Affiliation(s)
- Sarah J Hearne
- International Institute of Tropical Agriculture (IITA), Croydon, UK
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Chason E, Sheldon BW, Freund LB, Floro JA, Hearne SJ. Origin of compressive residual stress in polycrystalline thin films. Phys Rev Lett 2002; 88:156103. [PMID: 11955209 DOI: 10.1103/physrevlett.88.156103] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2001] [Indexed: 05/23/2023]
Abstract
We present a model for compressive stress generation during thin film growth in which the driving force is an increase in the surface chemical potential caused by the deposition of atoms from the vapor. The increase in surface chemical potential induces atoms to flow into the grain boundary, creating a compressive stress in the film. We develop kinetic equations to describe the stress evolution and dependence on growth parameters. The model is used to explain measurements of relaxation when growth is terminated and the dependence of the steady-state stress on growth rate.
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Affiliation(s)
- E Chason
- Division of Engineering, Brown University, Providence, Rhode Island 02912, USA
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