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Xu S, Osorio Y Fortéa J. Recombination fraction in pre-recombinant inbred lines (PRERIL) - revisiting a century old problem in genetics. BMC Genomics 2024; 25:822. [PMID: 39223519 PMCID: PMC11367787 DOI: 10.1186/s12864-024-10699-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 08/09/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Traditional recombinant inbred lines (RILs) are generated from repeated self-fertilization or brother-sister mating from the F1 hybrid of two inbred parents. Compared with the F2 population, RILs cumulate more crossovers between loci and thus increase the number of recombinants, resulting in an increased resolution of genetic mapping. Since they are inbred to the isogenic stage, another consequence of the heterozygosity reduction is the increased genetic variance and thus the increased power of QTL detection. Self-fertilization is the primary form of developing RILs in plants. Brother-sister mating is another way to develop RILs but in small laboratory animals. To ensure that the RILs have at least 98% of homozygosity, we need about seven generations of self-fertilization or 20 generations of brother-sister mating. Prior to homozygosity, these lines are called pre-recombinant inbred lines (PRERIL). Phenotypic values of traits in PRERILs are often collected but not used in QTL mapping. To perform QTL mapping in PRERILs, we need the recombination fraction between two markers at generation t for t < 7 (selfing) or t < 20 (brother-sister mating) so that the genotypes of QTL flanked by the markers can be inferred. RESULTS In this study, we developed formulas to calculate the recombination fractions of PRERILs at generation t in self-fertilization, brother-sister mating, and random mating. In contrast to existing works in this topic, we used computer code to construct the transition matrix to form the Markov chain of genotype array between consecutive generations, the so-called recurrent equations. CONCLUSIONS We provide R functions to calculate the recombination fraction using the newly developed recurrent equations of ordered genotype array. With the recurrent equations and the R code, users can perform QTL mapping in PRERILs. Substantial time and effort can be saved compared with QTL mapping in RILs.
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Affiliation(s)
- Shizhong Xu
- Department of Botany and Plant Sciences, University of California, Riverside, CA, 92521, USA.
| | - José Osorio Y Fortéa
- Limagrain Vegetable Seeds, Vilmorin & Cie, 28 Route d'Ennezat, Chappes, Zip 63720, France
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Lorenzo CD, Blasco-Escámez D, Beauchet A, Wytynck P, Sanches M, Garcia Del Campo JR, Inzé D, Nelissen H. Maize mutant screens: from classical methods to new CRISPR-based approaches. THE NEW PHYTOLOGIST 2024. [PMID: 39212458 DOI: 10.1111/nph.20084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 08/13/2024] [Indexed: 09/04/2024]
Abstract
Mutations play a pivotal role in shaping the trajectory and outcomes of a species evolution and domestication. Maize (Zea mays) has been a major staple crop and model for genetic research for more than 100 yr. With the arrival of site-directed mutagenesis and genome editing (GE) driven by the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), maize mutational research is once again in the spotlight. If we combine the powerful physiological and genetic characteristics of maize with the already available and ever increasing toolbox of CRISPR-Cas, prospects for its future trait engineering are very promising. This review aimed to give an overview of the progression and learnings of maize screening studies analyzing forward genetics, natural variation and reverse genetics to focus on recent GE approaches. We will highlight how each strategy and resource has contributed to our understanding of maize natural and induced trait variability and how this information could be used to design the next generation of mutational screenings.
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Affiliation(s)
- Christian Damian Lorenzo
- Center for Plant Systems Biology, VIB, B-9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium
| | - David Blasco-Escámez
- Center for Plant Systems Biology, VIB, B-9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium
| | - Arthur Beauchet
- Center for Plant Systems Biology, VIB, B-9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium
| | - Pieter Wytynck
- Center for Plant Systems Biology, VIB, B-9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium
| | - Matilde Sanches
- Center for Plant Systems Biology, VIB, B-9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium
| | - Jose Rodrigo Garcia Del Campo
- Center for Plant Systems Biology, VIB, B-9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium
| | - Dirk Inzé
- Center for Plant Systems Biology, VIB, B-9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium
| | - Hilde Nelissen
- Center for Plant Systems Biology, VIB, B-9052, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052, Ghent, Belgium
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3
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Kumar R, Brar MS, Kunduru B, Ackerman AJ, Yang Y, Luo F, Saski CA, Bridges WC, de Leon N, McMahan C, Kaeppler SM, Sekhon RS. Genetic architecture of source-sink-regulated senescence in maize. PLANT PHYSIOLOGY 2023; 193:2459-2479. [PMID: 37595026 DOI: 10.1093/plphys/kiad460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 07/12/2023] [Accepted: 07/21/2023] [Indexed: 08/20/2023]
Abstract
Source and sink interactions play a critical but mechanistically poorly understood role in the regulation of senescence. To disentangle the genetic and molecular mechanisms underlying source-sink-regulated senescence (SSRS), we performed a phenotypic, transcriptomic, and systems genetics analysis of senescence induced by the lack of a strong sink in maize (Zea mays). Comparative analysis of genotypes with contrasting SSRS phenotypes revealed that feedback inhibition of photosynthesis, a surge in reactive oxygen species, and the resulting endoplasmic reticulum (ER) stress were the earliest outcomes of weakened sink demand. Multienvironmental evaluation of a biparental population and a diversity panel identified 12 quantitative trait loci and 24 candidate genes, respectively, underlying SSRS. Combining the natural diversity and coexpression networks analyses identified 7 high-confidence candidate genes involved in proteolysis, photosynthesis, stress response, and protein folding. The role of a cathepsin B like protease 4 (ccp4), a candidate gene supported by systems genetic analysis, was validated by analysis of natural alleles in maize and heterologous analyses in Arabidopsis (Arabidopsis thaliana). Analysis of natural alleles suggested that a 700-bp polymorphic promoter region harboring multiple ABA-responsive elements is responsible for differential transcriptional regulation of ccp4 by ABA and the resulting variation in SSRS phenotype. We propose a model for SSRS wherein feedback inhibition of photosynthesis, ABA signaling, and oxidative stress converge to induce ER stress manifested as programed cell death and senescence. These findings provide a deeper understanding of signals emerging from loss of sink strength and offer opportunities to modify these signals to alter senescence program and enhance crop productivity.
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Affiliation(s)
- Rohit Kumar
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA
| | - Manwinder S Brar
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA
| | - Bharath Kunduru
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA
| | - Arlyn J Ackerman
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA
| | - Yuan Yang
- School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC 29634, USA
| | - Feng Luo
- School of Computing, Clemson University, Clemson, SC 29634, USA
| | - Christopher A Saski
- Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634, USA
| | - William C Bridges
- School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC 29634, USA
| | - Natalia de Leon
- Department of Agronomy, University of Wisconsin, Madison, WI 53706, USA
| | - Christopher McMahan
- School of Mathematical and Statistical Sciences, Clemson University, Clemson, SC 29634, USA
| | - Shawn M Kaeppler
- Department of Agronomy, University of Wisconsin, Madison, WI 53706, USA
| | - Rajandeep S Sekhon
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC 29634, USA
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4
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Hao Y, Hu Y, Jaqueth J, Lin J, He C, Lin G, Zhao M, Ren J, Tamang TM, Park S, Robertson AE, White FF, Fu J, Li B, Liu S. Genetic and transcriptomic dissection of host defense to Goss's bacterial wilt and leaf blight of maize. G3 (BETHESDA, MD.) 2023; 13:jkad197. [PMID: 37652038 PMCID: PMC10627284 DOI: 10.1093/g3journal/jkad197] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 01/28/2023] [Accepted: 08/22/2023] [Indexed: 09/02/2023]
Abstract
Goss's wilt, caused by the Gram-positive actinobacterium Clavibacter nebraskensis, is an important bacterial disease of maize. The molecular and genetic mechanisms of resistance to the bacterium, or, in general, Gram-positive bacteria causing plant diseases, remain poorly understood. Here, we examined the genetic basis of Goss's wilt through differential gene expression, standard genome-wide association mapping (GWAS), extreme phenotype (XP) GWAS using highly resistant (R) and highly susceptible (S) lines, and quantitative trait locus (QTL) mapping using 3 bi-parental populations, identifying 11 disease association loci. Three loci were validated using near-isogenic lines or recombinant inbred lines. Our analysis indicates that Goss's wilt resistance is highly complex and major resistance genes are not commonly present. RNA sequencing of samples separately pooled from R and S lines with or without bacterial inoculation was performed, enabling identification of common and differential gene responses in R and S lines. Based on expression, in both R and S lines, the photosynthesis pathway was silenced upon infection, while stress-responsive pathways and phytohormone pathways, namely, abscisic acid, auxin, ethylene, jasmonate, and gibberellin, were markedly activated. In addition, 65 genes showed differential responses (up- or down-regulated) to infection in R and S lines. Combining genetic mapping and transcriptional data, individual candidate genes conferring Goss's wilt resistance were identified. Collectively, aspects of the genetic architecture of Goss's wilt resistance were revealed, providing foundational data for mechanistic studies.
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Affiliation(s)
- Yangfan Hao
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Ying Hu
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | | | - Jinguang Lin
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Cheng He
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Guifang Lin
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Mingxia Zhao
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Jie Ren
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Tej Man Tamang
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
| | - Sunghun Park
- Department of Horticulture and Natural Resources, Kansas State University, Manhattan, KS 66506, USA
| | - Alison E Robertson
- Department of Plant Pathology, Entomology and Microbiology, Iowa State University, Ames, IA 50010, USA
| | - Frank F White
- Department of Plant Pathology, University of Florida, Gainesville, FL 32611, USA
| | - Junjie Fu
- Chinese Academy of Agricultural Sciences, Institute of Crop Science, Beijing 100081, China
| | - Bailin Li
- Corteva Agriscience, Johnston, IA 50131, USA
| | - Sanzhen Liu
- Department of Plant Pathology, Kansas State University, Manhattan, KS 66506, USA
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5
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Chen J, Wang Z, Tan K, Huang W, Shi J, Li T, Hu J, Wang K, Wang C, Xin B, Zhao H, Song W, Hufford MB, Schnable JC, Jin W, Lai J. A complete telomere-to-telomere assembly of the maize genome. Nat Genet 2023:10.1038/s41588-023-01419-6. [PMID: 37322109 DOI: 10.1038/s41588-023-01419-6] [Citation(s) in RCA: 60] [Impact Index Per Article: 60.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 05/05/2023] [Indexed: 06/17/2023]
Abstract
A complete telomere-to-telomere (T2T) finished genome has been the long pursuit of genomic research. Through generating deep coverage ultralong Oxford Nanopore Technology (ONT) and PacBio HiFi reads, we report here a complete genome assembly of maize with each chromosome entirely traversed in a single contig. The 2,178.6 Mb T2T Mo17 genome with a base accuracy of over 99.99% unveiled the structural features of all repetitive regions of the genome. There were several super-long simple-sequence-repeat arrays having consecutive thymine-adenine-guanine (TAG) tri-nucleotide repeats up to 235 kb. The assembly of the entire nucleolar organizer region of the 26.8 Mb array with 2,974 45S rDNA copies revealed the enormously complex patterns of rDNA duplications and transposon insertions. Additionally, complete assemblies of all ten centromeres enabled us to precisely dissect the repeat compositions of both CentC-rich and CentC-poor centromeres. The complete Mo17 genome represents a major step forward in understanding the complexity of the highly recalcitrant repetitive regions of higher plant genomes.
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Affiliation(s)
- Jian Chen
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Zijian Wang
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Kaiwen Tan
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Wei Huang
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Junpeng Shi
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Tong Li
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Jiang Hu
- Grandomics Biosciences, Wuhan, P. R. China
| | - Kai Wang
- Grandomics Biosciences, Wuhan, P. R. China
| | - Chao Wang
- Grandomics Biosciences, Wuhan, P. R. China
| | - Beibei Xin
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Haiming Zhao
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Weibin Song
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA
| | - James C Schnable
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Weiwei Jin
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China
| | - Jinsheng Lai
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China.
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, P. R. China.
- Sanya Institute of China Agricultural University, Sanya, P. R. China.
- Hainan Yazhou Bay Seed Laboratory, Sanya, P. R. China.
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6
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Shikha K, Madhumal Thayil V, Shahi JP, Zaidi PH, Seetharam K, Nair SK, Singh R, Tosh G, Singamsetti A, Singh S, Sinha B. Genomic-regions associated with cold stress tolerance in Asia-adapted tropical maize germplasm. Sci Rep 2023; 13:6297. [PMID: 37072497 PMCID: PMC10113201 DOI: 10.1038/s41598-023-33250-8] [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: 11/24/2022] [Accepted: 04/10/2023] [Indexed: 05/03/2023] Open
Abstract
Maize is gaining impetus in non-traditional and non-conventional seasons such as off-season, primarily due to higher demand and economic returns. Maize varieties directed for growing in the winter season of South Asia must have cold resilience as an important trait due to the low prevailing temperatures and frequent cold snaps observed during this season in most parts of the lowland tropics of Asia. The current study involved screening of a panel of advanced tropically adapted maize lines to cold stress during vegetative and flowering stage under field conditions. A suite of significant genomic loci (28) associated with grain yield along and agronomic traits such as flowering (15) and plant height (6) under cold stress environments. The haplotype regression revealed 6 significant haplotype blocks for grain yield under cold stress across the test environments. Haplotype blocks particularly on chromosomes 5 (bin5.07), 6 (bin6.02), and 9 (9.03) co-located to regions/bins that have been identified to contain candidate genes involved in membrane transport system that would provide essential tolerance to the plant. The regions on chromosome 1 (bin1.04), 2 (bin 2.07), 3 (bin 3.05-3.06), 5 (bin5.03), 8 (bin8.05-8.06) also harboured significant SNPs for the other agronomic traits. In addition, the study also looked at the plausibility of identifying tropically adapted maize lines from the working germplasm with cold resilience across growth stages and identified four lines that could be used as breeding starts in the tropical maize breeding pipelines.
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Affiliation(s)
- Kumari Shikha
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
| | - Vinayan Madhumal Thayil
- International Maize and Wheat Improvement Centre (CIMMYT), ICRISAT Campus, Patancheru, Telangana, India.
| | - J P Shahi
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
| | - P H Zaidi
- International Maize and Wheat Improvement Centre (CIMMYT), ICRISAT Campus, Patancheru, Telangana, India
| | - Kaliyamoorthy Seetharam
- International Maize and Wheat Improvement Centre (CIMMYT), ICRISAT Campus, Patancheru, Telangana, India
| | - Sudha K Nair
- International Maize and Wheat Improvement Centre (CIMMYT), ICRISAT Campus, Patancheru, Telangana, India
| | - Raju Singh
- Borlaug Institute for South Asia (BISA), Ludhiana, Punjab, India
| | - Garg Tosh
- Punjab Agricultural University (PAU), Ludhiana, India
| | - Ashok Singamsetti
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
| | - Saurabh Singh
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
| | - B Sinha
- Department of Genetics and Plant Breeding, Banaras Hindu University (BHU), Varanasi, India
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7
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Mano NA, Madore B, Mickelbart MV. Different Leaf Anatomical Responses to Water Deficit in Maize and Soybean. Life (Basel) 2023; 13:life13020290. [PMID: 36836647 PMCID: PMC9966819 DOI: 10.3390/life13020290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 01/13/2023] [Accepted: 01/16/2023] [Indexed: 01/22/2023] Open
Abstract
The stomata on leaf surfaces control gas exchange and water loss, closing during dry periods to conserve water. The distribution and size of stomatal complexes is determined by epidermal cell differentiation and expansion during leaf growth. Regulation of these processes in response to water deficit may result in stomatal anatomical plasticity as part of the plant acclimation to drought. We quantified the leaf anatomical plasticity under water-deficit conditions in maize and soybean over two experiments. Both species produced smaller leaves in response to the water deficit, partly due to the reductions in the stomata and pavement cell size, although this response was greater in soybean, which also produced thicker leaves under severe stress, whereas the maize leaf thickness did not change. The stomata and pavement cells were smaller with the reduced water availability in both species, resulting in higher stomatal densities. Stomatal development (measured as stomatal index, SI) was suppressed in both species at the lowest water availability, but to a greater extent in maize than in soybean. The result of these responses is that in maize leaves, the stomatal area fraction (fgc) was consistently reduced in the plants grown under severe but not moderate water deficit, whereas the fgc did not decrease in the water-stressed soybean leaves. The water deficit resulted in the reduced expression of one of two (maize) or three (soybean) SPEECHLESS orthologs, and the expression patterns were correlated with SI. The vein density (VD) increased in both species in response to the water deficit, although the effect was greater in soybean. This study establishes a mechanism of stomatal development plasticity that can be applied to other species and genotypes to develop or investigate stomatal development plasticity.
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Affiliation(s)
- Noel Anthony Mano
- Department of Botany and Plant Pathology, Center for Plant Biology, Purdue University, West Lafayette, IN 47907, USA
| | - Bethany Madore
- Department of Botany and Plant Pathology, Center for Plant Biology, Purdue University, West Lafayette, IN 47907, USA
| | - Michael V. Mickelbart
- Department of Botany and Plant Pathology, Center for Plant Biology, Purdue University, West Lafayette, IN 47907, USA
- Department of Horticulture and Landscape Architecture, Purdue University, West Lafayette, IN 47907, USA
- Correspondence:
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González-Rodríguez T, Pérez-Limón S, Peniche-Pavía H, Rellán-Álvarez R, Sawers RJH, Winkler R. Genetic mapping of maize metabolites using high-throughput mass profiling. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2023; 326:111530. [PMID: 36368482 DOI: 10.1016/j.plantsci.2022.111530] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
Plant metabolites are the basis of human nutrition and have biological relevance in ecology. Farmers selected plants with favorable characteristics since prehistoric times and improved the cultivars, but without knowledge of underlying mechanisms. Understanding the genetic basis of metabolite production can facilitate the successful breeding of plants with augmented nutritional value. To identify genetic factors related to the metabolic composition in maize, we generated mass profiles of 198 recombinant inbred lines (RILs) and their parents (B73 and Mo17) using direct-injection electrospray ionization mass spectrometry (DLI-ESI MS). Mass profiling allowed the correct clustering of samples according to genotype. We quantified 71 mass features from grains and 236 mass features from leaf extracts. For the corresponding ions, we identified tissue-specific metabolic 'Quantitative Trait Loci' (mQTLs) distributed across the maize genome. These genetic regions could regulate multiple metabolite biosynthesis pathways. Our findings demonstrate that DLI-ESI MS has sufficient analytical resolution to map mQTLs. These identified genetic loci will be helpful in metabolite-focused maize breeding. Mass profiling is a powerful tool for detecting mQTLs in maize and enables the high-throughput screening of loci responsible for metabolite biosynthesis.
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Affiliation(s)
- Tzitziki González-Rodríguez
- Center for Research and Advanced Studies (CINVESTAV) Irapuato, Department of Biotechnology and Biochemistry, Mexico
| | - Sergio Pérez-Limón
- The Pennsylvania State University, Department of Plant Science, State College, PA, USA
| | - Héctor Peniche-Pavía
- Center for Research and Advanced Studies (CINVESTAV) Irapuato, Department of Biotechnology and Biochemistry, Mexico
| | - Rubén Rellán-Álvarez
- North Carolina State University, Department of Molecular and Structural Biochemistry, USA; Unidad de Genómica Avanzada (UGA) - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), Km. 9.6 Libramiento Norte Carr. Irapuato-León, 36824 Irapuato Gto, Mexico
| | - Ruairidh J H Sawers
- The Pennsylvania State University, Department of Plant Science, State College, PA, USA; Unidad de Genómica Avanzada (UGA) - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), Km. 9.6 Libramiento Norte Carr. Irapuato-León, 36824 Irapuato Gto, Mexico
| | - Robert Winkler
- Center for Research and Advanced Studies (CINVESTAV) Irapuato, Department of Biotechnology and Biochemistry, Mexico; Unidad de Genómica Avanzada (UGA) - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), Km. 9.6 Libramiento Norte Carr. Irapuato-León, 36824 Irapuato Gto, Mexico.
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9
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Vidal A, Gauthier F, Rodrigez W, Guiglielmoni N, Leroux D, Chevrolier N, Jasson S, Tourrette E, Martin OC, Falque M. SeSAM: software for automatic construction of order-robust linkage maps. BMC Bioinformatics 2022; 23:499. [PMCID: PMC9675223 DOI: 10.1186/s12859-022-05045-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 11/08/2022] [Indexed: 11/21/2022] Open
Abstract
Background Genotyping and sequencing technologies produce increasingly large numbers of genetic markers with potentially high rates of missing or erroneous data. Therefore, the construction of linkage maps is more and more complex. Moreover, the size of segregating populations remains constrained by cost issues and is less and less commensurate with the numbers of SNPs available. Thus, guaranteeing a statistically robust marker order requires that maps include only a carefully selected subset of SNPs. Results In this context, the SeSAM software allows automatic genetic map construction using seriation and placement approaches, to produce (1) a high-robustness framework map which includes as many markers as possible while keeping the order robustness beyond a given statistical threshold, and (2) a high-density total map including the framework plus almost all polymorphic markers. During this process, care is taken to limit the impact of genotyping errors and of missing data on mapping quality. SeSAM can be used with a wide range of biparental populations including from outcrossing species for which phases are inferred on-the-fly by maximum-likelihood during map elongation. The package also includes functions to simulate data sets, convert data formats, detect putative genotyping errors, visualize data and map quality (including graphical genotypes), and merge several maps into a consensus. SeSAM is also suitable for interactive map construction, by providing lower-level functions for 2-point and multipoint EM analyses. The software is implemented in a R package including functions in C++. Conclusions SeSAM is a fully automatic linkage mapping software designed to (1) produce a framework map as robust as desired by optimizing the selection of a subset of markers, and (2) produce a high-density map including almost all polymorphic markers. The software can be used with a wide range of biparental mapping populations including cases from outcrossing. SeSAM is freely available under a GNU GPL v3 license and works on Linux, Windows, and macOS platforms. It can be downloaded together with its user-manual and quick-start tutorial from ForgeMIA (SeSAM project) at https://forgemia.inra.fr/gqe-acep/sesam/-/releases Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-05045-7.
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Affiliation(s)
- Adrien Vidal
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Franck Gauthier
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Willy Rodrigez
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Nadège Guiglielmoni
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Damien Leroux
- grid.507621.7INRAE, Unité de Mathématiques et Informatique Appliquées - Toulouse, Toulouse, France
| | - Nicolas Chevrolier
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Sylvain Jasson
- grid.507621.7INRAE, Unité de Mathématiques et Informatique Appliquées - Toulouse, Toulouse, France
| | - Elise Tourrette
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Olivier C. Martin
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France ,grid.503243.3Université Paris-Saclay, CNRS, INRAE, Université Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91190 Gif-sur-Yvette, France ,Université Paris Cité, CNRS, INRAE, Univ Evry, Institute of Plant Sciences Paris-Saclay (IPS2), 91190 Gif-sur-Yvette, France
| | - Matthieu Falque
- grid.460789.40000 0004 4910 6535Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
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10
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Bheemanahalli R, Ramamoorthy P, Poudel S, Samiappan S, Wijewardane N, Reddy KR. Effects of drought and heat stresses during reproductive stage on pollen germination, yield, and leaf reflectance properties in maize ( Zea mays L.). PLANT DIRECT 2022; 6:e434. [PMID: 35959217 PMCID: PMC9360560 DOI: 10.1002/pld3.434] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 06/28/2022] [Accepted: 07/19/2022] [Indexed: 05/24/2023]
Abstract
Drought and heat stresses are the major abiotic stress factors detrimental to maize (Zea mays L.) production. Much attention has been directed toward plant responses to heat or drought stress. However, maize reproductive stage responses to combined heat and drought remain less explored. Therefore, this study aimed to quantify the impact of optimum daytime (30°C, control) and warmer daytime temperatures (35°C, heat stress) on pollen germination, morpho-physiology, and yield potential using two maize genotypes ("Mo17" and "B73") under contrasting soil moisture content, that is, 100% and 40% irrigation during flowering. Pollen germination of both genotypes decreased under combined stresses (42%), followed by heat stress (30%) and drought stress (19%). Stomatal conductance and transpiration were comparable between control and heat stress but significantly decreased under combined stresses (83% and 72%) and drought stress (52% and 47%) compared with the control. Genotype "Mo17" reduced its green leaf area to minimize the water loss, which appears to be one of the adaptive strategies of "Mo17" under stress conditions. The leaf reflectance of both genotypes varied across treatments. Vegetation indices associated with pigments (chlorophyll index of green, chlorophyll index of red edge, and carotenoid index) and plant health (normalized difference red-edge index) were found to be highly sensitive to drought and combined stressors than heat stress. Combined drought and heat stresses caused a significant reduction in yield and yield components in both Mo17 (49%) and B73 (86%) genotypes. The harvest index of genotype "B73" was extremely low, indicating poor partitioning efficiency. At least when it comes to "B73," the cause of yield reduction appears to be the result of reduced sink number rather than the pollen and source size. To the best of our awareness, this is the first study that showed how the leaf-level spectra, yield, and quality parameters respond to the short duration of independent and combined stresses during flowering in inbred maize. Further studies are required to validate the responses of potential traits involving diverse maize genotypes under field conditions. This study suggests the need to develop maize with improved tolerance to combined stresses to sustain production under increasing temperatures and low rainfall conditions.
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Affiliation(s)
- Raju Bheemanahalli
- Department of Plant and Soil SciencesMississippi State UniversityMississippi StateMSUSA
| | | | - Sadikshya Poudel
- Department of Plant and Soil SciencesMississippi State UniversityMississippi StateMSUSA
| | | | - Nuwan Wijewardane
- Department of Agricultural & Biological EngineeringMississippi State UniversityMississippi StateMSUSA
| | - K. Raja Reddy
- Department of Plant and Soil SciencesMississippi State UniversityMississippi StateMSUSA
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11
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Xu Q, Wang X, Wang Y, Zhang H, Zhang H, Di H, Zhang L, Dong L, Zeng X, Liu X, Lee M, Wang Z, Zhou Y. Combined QTL mapping and RNA-Seq pro-filing reveal candidate genes related to low-temperature tolerance in maize. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:33. [PMID: 37312966 PMCID: PMC10248625 DOI: 10.1007/s11032-022-01297-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 05/16/2022] [Indexed: 06/15/2023]
Abstract
Maize (Zea mays L.) is the most important food crop in the world, with significant acreage and production across the globe. However, it is affected by low temperatures throughout its growth process, especially during germination. Therefore, it is important to identify more QTLs or genes associated with germination under low-temperature conditions. For the QTL analysis of traits related to low-temperature germination, we used a high-res genetic map of 213 lines of the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, which had 6618 bin markers. We detected 28 QTLs of eight phenotypic characteristics associated with low-temperature germination, while they explained the phenotypic contribution rate of 5.4 ~ 13.34%. Additionally, 14 overlapping QTLs produced six QTL clusters on every chromosome, except for 8 and 10. RNA-Seq found six genes related to low-temperature tolerance in these QTLs, while qRT-PCR analysis demonstrated that the expression trends of the Zm00001d045568 gene in the LT_BvsLT_M group and the CK_BvsCK_M group were highly significantly different at all four-time points (P < 0.01), and encoded the RING zinc finger protein. It was located on qRTL9-2 and qRSVI9-1 and is related to the total length and simple vitality index. These results provided potential candidate genes for further gene cloning and improving the low-temperature tolerance of maize. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01297-6.
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Affiliation(s)
- Qingyu Xu
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Xuerui Wang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Yuhe Wang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Hong Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Hongzhou Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Hong Di
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Lin Zhang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Ling Dong
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Xing Zeng
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Xianjun Liu
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Michael Lee
- Department of Agronomy, Iowa State University, Ames, IA 50011 USA
| | - Zhenhua Wang
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
| | - Yu Zhou
- Key Laboratory of Germplasm Enhancement, Physiology and Ecology of Food Crops in Cold Region, Department of Agriculture, Northeast Agricultural University, HarbinHeilongjiang, 150030 China
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12
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Yu T, Zhang J, Cao J, Cao S, Li W, Yang G. A meta analysis of low temperature tolerance QTL in maize. ELECTRON J BIOTECHN 2022. [DOI: 10.1016/j.ejbt.2022.05.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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13
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Casale F, Van Inghelandt D, Weisweiler M, Li J, Stich B. Genomic prediction of the recombination rate variation in barley - A route to highly recombinogenic genotypes. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:676-690. [PMID: 34783155 PMCID: PMC8989500 DOI: 10.1111/pbi.13746] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 10/06/2021] [Accepted: 11/07/2021] [Indexed: 06/13/2023]
Abstract
Meiotic recombination is not only fundamental to the adaptation of sexually reproducing eukaryotes in nature but increased recombination rates facilitate the combination of favourable alleles into a single haplotype in breeding programmes. The main objectives of this study were to (i) assess the extent and distribution of the recombination rate variation in cultivated barley (Hordeum vulgare L.), (ii) quantify the importance of the general and specific recombination effects, and (iii) evaluate a genomic selection approach's ability to predict the recombination rate variation. Genetic maps were created for the 45 segregating populations that were derived from crosses among 23 spring barley inbreds with origins across the world. The genome-wide recombination rate among populations ranged from 0.31 to 0.73 cM/Mbp. The crossing design used in this study allowed to separate the general recombination effects (GRE) of individual parental inbreds from the specific recombination effects (SRE) caused by the combinations of parental inbreds. The variance of the genome-wide GRE was found to be about eight times the variance of the SRE. This finding indicated that parental inbreds differ in the efficiency of their recombination machinery. The ability to predict the chromosome or genome-wide recombination rate of an inbred ranged from 0.80 to 0.85. These results suggest that a reliable screening of large genetic materials for their potential to cause a high extent of genetic recombination in their progeny is possible, allowing to systematically manipulate the recombination rate using natural variation.
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Affiliation(s)
- Federico Casale
- Institute of Quantitative Genetics and Genomics of PlantsHeinrich Heine UniversityDüsseldorfGermany
| | - Delphine Van Inghelandt
- Institute of Quantitative Genetics and Genomics of PlantsHeinrich Heine UniversityDüsseldorfGermany
| | - Marius Weisweiler
- Institute of Quantitative Genetics and Genomics of PlantsHeinrich Heine UniversityDüsseldorfGermany
| | - Jinquan Li
- Max Planck Institute for Plant Breeding ResearchKölnGermany
- Strube D&S GmbHSöllingenGermany
| | - Benjamin Stich
- Institute of Quantitative Genetics and Genomics of PlantsHeinrich Heine UniversityDüsseldorfGermany
- Max Planck Institute for Plant Breeding ResearchKölnGermany
- Cluster of Excellence on Plant SciencesFrom Complex Traits Towards Synthetic ModulesDüsseldorfGermany
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14
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Poretsky E, Ruiz M, Ahmadian N, Steinbrenner AD, Dressano K, Schmelz EA, Huffaker A. Comparative analyses of responses to exogenous and endogenous antiherbivore elicitors enable a forward genetics approach to identify maize gene candidates mediating sensitivity to herbivore-associated molecular patterns. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 108:1295-1316. [PMID: 34564909 DOI: 10.1111/tpj.15510] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 09/03/2021] [Accepted: 09/07/2021] [Indexed: 06/13/2023]
Abstract
Crop damage by herbivorous insects remains a significant contributor to annual yield reductions. Following attack, maize (Zea mays) responds to herbivore-associated molecular patterns (HAMPs) and damage-associated molecular patterns (DAMPs), activating dynamic direct and indirect antiherbivore defense responses. To define underlying signaling processes, comparative analyses between plant elicitor peptide (Pep) DAMPs and fatty acid-amino acid conjugate (FAC) HAMPs were conducted. RNA sequencing analysis of early transcriptional changes following Pep and FAC treatments revealed quantitative differences in the strength of response yet a high degree of qualitative similarity, providing evidence for shared signaling pathways. In further comparisons of FAC and Pep responses across diverse maize inbred lines, we identified Mo17 as part of a small subset of lines displaying selective FAC insensitivity. Genetic mapping for FAC sensitivity using the intermated B73 × Mo17 population identified a single locus on chromosome 4 associated with FAC sensitivity. Pursuit of multiple fine-mapping approaches further narrowed the locus to 19 candidate genes. The top candidate gene identified, termed FAC SENSITIVITY ASSOCIATED (ZmFACS), encodes a leucine-rich repeat receptor-like kinase (LRR-RLK) that belongs to the same family as a rice (Oryza sativa) receptor gene previously associated with the activation of induced responses to diverse Lepidoptera. Consistent with reduced sensitivity, ZmFACS expression was significantly lower in Mo17 as compared to B73. Transient heterologous expression of ZmFACS in Nicotiana benthamiana resulted in a significantly increased FAC-elicited response. Together, our results provide useful resources for studying early elicitor-induced antiherbivore responses in maize and approaches to discover gene candidates underlying HAMP sensitivity in grain crops.
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Affiliation(s)
- Elly Poretsky
- Division of Biology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Miguel Ruiz
- Division of Biology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Nazanin Ahmadian
- Division of Biology, University of California San Diego, La Jolla, CA, 92093, USA
| | | | - Keini Dressano
- Division of Biology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Eric A Schmelz
- Division of Biology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Alisa Huffaker
- Division of Biology, University of California San Diego, La Jolla, CA, 92093, USA
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15
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Malenica N, Dunić JA, Vukadinović L, Cesar V, Šimić D. Genetic Approaches to Enhance Multiple Stress Tolerance in Maize. Genes (Basel) 2021; 12:genes12111760. [PMID: 34828366 PMCID: PMC8617808 DOI: 10.3390/genes12111760] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 10/27/2021] [Accepted: 11/03/2021] [Indexed: 12/29/2022] Open
Abstract
The multiple-stress effects on plant physiology and gene expression are being intensively studied lately, primarily in model plants such as Arabidopsis, where the effects of six stressors have simultaneously been documented. In maize, double and triple stress responses are obtaining more attention, such as simultaneous drought and heat or heavy metal exposure, or drought in combination with insect and fungal infestation. To keep up with these challenges, maize natural variation and genetic engineering are exploited. On one hand, quantitative trait loci (QTL) associated with multiple-stress tolerance are being identified by molecular breeding and genome-wide association studies (GWAS), which then could be utilized for future breeding programs of more resilient maize varieties. On the other hand, transgenic approaches in maize have already resulted in the creation of many commercial double or triple stress resistant varieties, predominantly weed-tolerant/insect-resistant and, additionally, also drought-resistant varieties. It is expected that first generation gene-editing techniques, as well as recently developed base and prime editing applications, in combination with the routine haploid induction in maize, will pave the way to pyramiding more stress tolerant alleles in elite lines/varieties on time.
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Affiliation(s)
- Nenad Malenica
- Division of Molecular Biology, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia;
| | - Jasenka Antunović Dunić
- Department of Biology, Josip Juraj Strossmayer University, Cara Hadrijana 8/A, 31000 Osijek, Croatia; (J.A.D.); (V.C.)
| | - Lovro Vukadinović
- Agricultural Institute Osijek, Južno Predgrađe 17, 31000 Osijek, Croatia;
| | - Vera Cesar
- Department of Biology, Josip Juraj Strossmayer University, Cara Hadrijana 8/A, 31000 Osijek, Croatia; (J.A.D.); (V.C.)
- Faculty of Dental Medicine and Health, Josip Juraj Strossmayer University of Osijek, Crkvena 21, 31000 Osijek, Croatia
| | - Domagoj Šimić
- Agricultural Institute Osijek, Južno Predgrađe 17, 31000 Osijek, Croatia;
- Centre of Excellence for Biodiversity and Molecular Plant Breeding (CroP-BioDiv), Svetošimunska 25, 10000 Zagreb, Croatia
- Correspondence: ; Tel.: +385-31-515-521
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16
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Hufford MB, Seetharam AS, Woodhouse MR, Chougule KM, Ou S, Liu J, Ricci WA, Guo T, Olson A, Qiu Y, Della Coletta R, Tittes S, Hudson AI, Marand AP, Wei S, Lu Z, Wang B, Tello-Ruiz MK, Piri RD, Wang N, Kim DW, Zeng Y, O'Connor CH, Li X, Gilbert AM, Baggs E, Krasileva KV, Portwood JL, Cannon EKS, Andorf CM, Manchanda N, Snodgrass SJ, Hufnagel DE, Jiang Q, Pedersen S, Syring ML, Kudrna DA, Llaca V, Fengler K, Schmitz RJ, Ross-Ibarra J, Yu J, Gent JI, Hirsch CN, Ware D, Dawe RK. De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes. Science 2021; 373:655-662. [PMID: 34353948 PMCID: PMC8733867 DOI: 10.1126/science.abg5289] [Citation(s) in RCA: 249] [Impact Index Per Article: 83.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 06/24/2021] [Indexed: 12/24/2022]
Abstract
We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The number of pan-genes in these diverse genomes exceeds 103,000, with approximately a third found across all genotypes. The results demonstrate that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres revealed additional variation in major cytological landmarks. We show that combining structural variation with single-nucleotide polymorphisms can improve the power of quantitative mapping studies. We also document variation at the level of DNA methylation and demonstrate that unmethylated regions are enriched for cis-regulatory elements that contribute to phenotypic variation.
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Affiliation(s)
- Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Arun S Seetharam
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Genome Informatics Facility, Iowa State University, Ames, IA 50011, USA
| | - Margaret R Woodhouse
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | | | - Shujun Ou
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Jianing Liu
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - William A Ricci
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Tingting Guo
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Andrew Olson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Yinjie Qiu
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Silas Tittes
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - Asher I Hudson
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | | | - Sharon Wei
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Zhenyuan Lu
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Bo Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | | | - Rebecca D Piri
- Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA
| | - Na Wang
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Dong Won Kim
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Yibing Zeng
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - Christine H O'Connor
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN 55108, USA
| | - Xianran Li
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Amanda M Gilbert
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Erin Baggs
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - Ksenia V Krasileva
- Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA
| | - John L Portwood
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Ethalinda K S Cannon
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Carson M Andorf
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA
| | - Nancy Manchanda
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Samantha J Snodgrass
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - David E Hufnagel
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA, 50010, USA
| | - Qiuhan Jiang
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Sarah Pedersen
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Michael L Syring
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - David A Kudrna
- Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA
| | | | | | - Robert J Schmitz
- Department of Genetics, University of Georgia, Athens, GA 30602, USA
| | - Jeffrey Ross-Ibarra
- Center for Population Biology, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
- Genome Center, University of California, Davis, CA 95616, USA
| | - Jianming Yu
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Jonathan I Gent
- Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Doreen Ware
- USDA-ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, Ithaca, NY 14853, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - R Kelly Dawe
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA.
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17
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Zhang T, Jiang L, Ruan L, Qian Y, Liang S, Lin F, Lu H, Dai H, Zhao H. Heterotic quantitative trait loci analysis and genomic prediction of seedling biomass-related traits in maize triple testcross populations. PLANT METHODS 2021; 17:85. [PMID: 34330310 PMCID: PMC8325263 DOI: 10.1186/s13007-021-00785-8] [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: 09/23/2020] [Accepted: 07/23/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Heterosis has been widely used in maize breeding. However, we know little about the heterotic quantitative trait loci and their roles in genomic prediction. In this study, we sought to identify heterotic quantitative trait loci for seedling biomass-related traits using triple testcross design and compare their prediction accuracies by fitting molecular markers and heterotic quantitative trait loci. RESULTS A triple testcross population comprised of 366 genotypes was constructed by crossing each of 122 intermated B73 × Mo17 genotypes with B73, Mo17, and B73 × Mo17. The mid-parent heterosis of seedling biomass-related traits involved in leaf length, leaf width, leaf area, and seedling dry weight displayed a large range, from less than 50 to ~ 150%. Relationships between heterosis of seedling biomass-related traits showed congruency with that between performances. Based on a linkage map comprised of 1631 markers, 14 augmented additive, two augmented dominance, and three dominance × additive epistatic quantitative trait loci for heterosis of seedling biomass-related traits were identified, with each individually explaining 4.1-20.5% of the phenotypic variation. All modes of gene action, i.e., additive, partially dominant, dominant, and overdominant modes were observed. In addition, ten additive × additive and six dominance × dominance epistatic interactions were identified. By implementing the general and special combining ability model, we found that prediction accuracy ranged from 0.29 for leaf length to 0.56 for leaf width. Different number of marker analysis showed that ~ 800 markers almost capture the largest prediction accuracies. When incorporating the heterotic quantitative trait loci into the model, we did not find the significant change of prediction accuracy, with only leaf length showing the marginal improvement by 1.7%. CONCLUSIONS Our results demonstrated that the triple testcross design is suitable for detecting heterotic quantitative trait loci and evaluating the prediction accuracy. Seedling leaf width can be used as the representative trait for seedling prediction. The heterotic quantitative trait loci are not necessary for genomic prediction of seedling biomass-related traits.
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Affiliation(s)
- Tifu Zhang
- Jiangsu Provincial Key Laboratory of Agrobiology, Institute of Germplasm Resources and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Lu Jiang
- Jiangsu Provincial Key Laboratory of Agrobiology, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Long Ruan
- Institute of Tobacco, Anhui Academy of Agricultural Sciences, Hefei, 230001, China
| | - Yiliang Qian
- Institute of Tobacco, Anhui Academy of Agricultural Sciences, Hefei, 230001, China
| | - Shuaiqiang Liang
- Jiangsu Provincial Key Laboratory of Agrobiology, Institute of Germplasm Resources and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Feng Lin
- Jiangsu Provincial Key Laboratory of Agrobiology, Institute of Germplasm Resources and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Haiyan Lu
- Jiangsu Provincial Key Laboratory of Agrobiology, Institute of Germplasm Resources and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Huixue Dai
- Nanjing Institute of Vegetable Sciences, Nanjing, 210042, China
| | - Han Zhao
- Jiangsu Provincial Key Laboratory of Agrobiology, Institute of Germplasm Resources and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China.
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18
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Goering R, Larsen S, Tan J, Whelan J, Makarevitch I. QTL mapping of seedling tolerance to exposure to low temperature in the maize IBM RIL population. PLoS One 2021; 16:e0254437. [PMID: 34242344 PMCID: PMC8270210 DOI: 10.1371/journal.pone.0254437] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 06/27/2021] [Indexed: 11/19/2022] Open
Abstract
Maize is a cold sensitive crop that exhibits severe retardation of growth and development when exposed to cold spells during and right after germination, including the slowdown in development of new leaves and in formation of the photosynthetic apparatus. Improving cold tolerance in maize would allow early sowing to improve crop yield by prolonging a growing season and by decreasing the negative effects of summer drought, diseases, and pests. Two maize inbreds widely incorporated into American maize germplasm, B73 and Mo17, exhibit different levels of tolerance to low temperature exposure at seedling stage. In addition, thirty seven diverse inbred maize lines showed large variation for seedling response to low temperature exposure with lines with extremely low tolerance to seedling exposure to low temperatures falling into stiff stalk, non-stiff stalk, and tropical clades. We employed the maize intermated B73×Mo17 (IBM) recombinant inbred line population (IBM Syn4 RIL) to investigate the genetic architecture of cold stress tolerance at a young seedling stage and to identify quantitative trait loci (QTLs) controlling this variation. A panel of 97 recombinant inbred lines of IBM Syn4 were used to measure, and score based on several traits related to chlorophyll concentration, leaf color, and tissue damage. Our analysis resulted in detection of two QTLs with high additive impact, one on chromosome 1 (bin 1.02) and second on chromosome 5 (bin 5.05). Further investigation of the QTL regions using gene expression data provided a list of the candidate genes likely contributing to the variation in cold stress response. Among the genes located within QTL regions identified in this study and differentially expressed in response to low temperature exposure are the genes with putative functions related to auxin and gibberellin response, as well as general abiotic stress response, and genes coding for proteins with broad regulatory functions.
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Affiliation(s)
- Raeann Goering
- Department of Biology, Hamline University, Saint Paul, Minnesota, United States of America
| | - Siri Larsen
- Department of Biology, Hamline University, Saint Paul, Minnesota, United States of America
| | - Jia Tan
- Department of Biology, Hamline University, Saint Paul, Minnesota, United States of America
| | - James Whelan
- Department of Biology, Hamline University, Saint Paul, Minnesota, United States of America
| | - Irina Makarevitch
- Department of Biology, Hamline University, Saint Paul, Minnesota, United States of America
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19
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Mural RV, Grzybowski M, Miao C, Damke A, Sapkota S, Boyles RE, Salas Fernandez MG, Schnable PS, Sigmon B, Kresovich S, Schnable JC. Meta-Analysis Identifies Pleiotropic Loci Controlling Phenotypic Trade-offs in Sorghum. Genetics 2021; 218:6294935. [PMID: 34100945 PMCID: PMC9335936 DOI: 10.1093/genetics/iyab087] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 06/07/2021] [Indexed: 01/03/2023] Open
Abstract
Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome wide association studies conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35-43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.
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Affiliation(s)
- Ravi V Mural
- Center for Plant Science Innovation and Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588 USA
| | - Marcin Grzybowski
- Center for Plant Science Innovation and Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588 USA
| | - Chenyong Miao
- Center for Plant Science Innovation and Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588 USA
| | - Alyssa Damke
- Department of Plant Pathology, University of Nebraska-Lincoln, Lincoln, NE 68588 USA
| | - Sirjan Sapkota
- Advanced Plant Technology Program, Clemson University, Clemson, SC 29634 USA.,Department of Plant and Environment Sciences, Clemson University, Clemson, SC 29634 USA
| | - Richard E Boyles
- Department of Plant and Environment Sciences, Clemson University, Clemson, SC 29634 USA.,Pee Dee Research and Education Center, Clemson University, Florence, SC 29532 USA
| | | | | | - Brandi Sigmon
- Department of Plant Pathology, University of Nebraska-Lincoln, Lincoln, NE 68588 USA
| | - Stephen Kresovich
- Department of Plant and Environment Sciences, Clemson University, Clemson, SC 29634 USA.,Feed the Future Innovation Lab for Crop Improvement Cornell University, Ithaca, NY 14850 USA
| | - James C Schnable
- Center for Plant Science Innovation and Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588 USA
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20
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Diepenbrock CH, Ilut DC, Magallanes-Lundback M, Kandianis CB, Lipka AE, Bradbury PJ, Holland JB, Hamilton JP, Wooldridge E, Vaillancourt B, Góngora-Castillo E, Wallace JG, Cepela J, Mateos-Hernandez M, Owens BF, Tiede T, Buckler ES, Rocheford T, Buell CR, Gore MA, DellaPenna D. Eleven biosynthetic genes explain the majority of natural variation in carotenoid levels in maize grain. THE PLANT CELL 2021; 33:882-900. [PMID: 33681994 PMCID: PMC8226291 DOI: 10.1093/plcell/koab032] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 01/26/2021] [Indexed: 05/03/2023]
Abstract
Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize (Zea mays) is a food staple. Extensive natural variation exists for carotenoids in maize grain. Here, to understand its genetic basis, we conducted a joint linkage and genome-wide association study of the US maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percentage of phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide an in-depth genome-level understanding of the genetic and molecular control of carotenoids in plants. In addition, these findings provide a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals.
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Affiliation(s)
| | - Daniel C Ilut
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853
| | - Maria Magallanes-Lundback
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824
| | - Catherine B Kandianis
- Present addresses: Nacre Innovations, Houston, Texas 77002 (C.B.K.); Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801 (A.E.L.); University of Michigan, Ann Arbor, MI 48109 (E.W.); Centro de Investigación Científica de Yucatan, CONACYT—Unidad de Biotecnologia, Merida, Yucatan 97200, Mexico (E.G.-C.); Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 (J.C.); Bayer, Stonington, Illinois 62567 (M.M.-H.); BASF, Dawson, Georgia 39842 (B.F.O.); and Corteva Agriscience, St. Paul, Minnesota 55108 (T.T.)
| | - Alexander E Lipka
- Present addresses: Nacre Innovations, Houston, Texas 77002 (C.B.K.); Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801 (A.E.L.); University of Michigan, Ann Arbor, MI 48109 (E.W.); Centro de Investigación Científica de Yucatan, CONACYT—Unidad de Biotecnologia, Merida, Yucatan 97200, Mexico (E.G.-C.); Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 (J.C.); Bayer, Stonington, Illinois 62567 (M.M.-H.); BASF, Dawson, Georgia 39842 (B.F.O.); and Corteva Agriscience, St. Paul, Minnesota 55108 (T.T.)
| | - Peter J Bradbury
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853
- United States Department of Agriculture—Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853
| | - James B Holland
- United States Department of Agriculture—Agricultural Research Service, Plant Science Research Unit, Department of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina 27695
| | - John P Hamilton
- Department of Plant Biology, Michigan State University, East Lansing, Michigan 48824
| | - Edmund Wooldridge
- Present addresses: Nacre Innovations, Houston, Texas 77002 (C.B.K.); Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801 (A.E.L.); University of Michigan, Ann Arbor, MI 48109 (E.W.); Centro de Investigación Científica de Yucatan, CONACYT—Unidad de Biotecnologia, Merida, Yucatan 97200, Mexico (E.G.-C.); Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 (J.C.); Bayer, Stonington, Illinois 62567 (M.M.-H.); BASF, Dawson, Georgia 39842 (B.F.O.); and Corteva Agriscience, St. Paul, Minnesota 55108 (T.T.)
| | - Brieanne Vaillancourt
- Department of Plant Biology, Michigan State University, East Lansing, Michigan 48824
| | - Elsa Góngora-Castillo
- Present addresses: Nacre Innovations, Houston, Texas 77002 (C.B.K.); Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801 (A.E.L.); University of Michigan, Ann Arbor, MI 48109 (E.W.); Centro de Investigación Científica de Yucatan, CONACYT—Unidad de Biotecnologia, Merida, Yucatan 97200, Mexico (E.G.-C.); Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 (J.C.); Bayer, Stonington, Illinois 62567 (M.M.-H.); BASF, Dawson, Georgia 39842 (B.F.O.); and Corteva Agriscience, St. Paul, Minnesota 55108 (T.T.)
| | - Jason G Wallace
- Department of Crop and Soil Sciences, University of Georgia, Athens, Georgia 30602
| | - Jason Cepela
- Present addresses: Nacre Innovations, Houston, Texas 77002 (C.B.K.); Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801 (A.E.L.); University of Michigan, Ann Arbor, MI 48109 (E.W.); Centro de Investigación Científica de Yucatan, CONACYT—Unidad de Biotecnologia, Merida, Yucatan 97200, Mexico (E.G.-C.); Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 (J.C.); Bayer, Stonington, Illinois 62567 (M.M.-H.); BASF, Dawson, Georgia 39842 (B.F.O.); and Corteva Agriscience, St. Paul, Minnesota 55108 (T.T.)
| | - Maria Mateos-Hernandez
- Present addresses: Nacre Innovations, Houston, Texas 77002 (C.B.K.); Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801 (A.E.L.); University of Michigan, Ann Arbor, MI 48109 (E.W.); Centro de Investigación Científica de Yucatan, CONACYT—Unidad de Biotecnologia, Merida, Yucatan 97200, Mexico (E.G.-C.); Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 (J.C.); Bayer, Stonington, Illinois 62567 (M.M.-H.); BASF, Dawson, Georgia 39842 (B.F.O.); and Corteva Agriscience, St. Paul, Minnesota 55108 (T.T.)
| | - Brenda F Owens
- Present addresses: Nacre Innovations, Houston, Texas 77002 (C.B.K.); Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801 (A.E.L.); University of Michigan, Ann Arbor, MI 48109 (E.W.); Centro de Investigación Científica de Yucatan, CONACYT—Unidad de Biotecnologia, Merida, Yucatan 97200, Mexico (E.G.-C.); Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 (J.C.); Bayer, Stonington, Illinois 62567 (M.M.-H.); BASF, Dawson, Georgia 39842 (B.F.O.); and Corteva Agriscience, St. Paul, Minnesota 55108 (T.T.)
| | - Tyler Tiede
- Present addresses: Nacre Innovations, Houston, Texas 77002 (C.B.K.); Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801 (A.E.L.); University of Michigan, Ann Arbor, MI 48109 (E.W.); Centro de Investigación Científica de Yucatan, CONACYT—Unidad de Biotecnologia, Merida, Yucatan 97200, Mexico (E.G.-C.); Bioinformatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 (J.C.); Bayer, Stonington, Illinois 62567 (M.M.-H.); BASF, Dawson, Georgia 39842 (B.F.O.); and Corteva Agriscience, St. Paul, Minnesota 55108 (T.T.)
| | - Edward S Buckler
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853
- United States Department of Agriculture—Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, New York 14853
| | - Torbert Rocheford
- Department of Agronomy, Purdue University, West Lafayette, Indiana 47907
| | - C Robin Buell
- Department of Plant Biology, Michigan State University, East Lansing, Michigan 48824
| | - Michael A Gore
- Authors for correspondence: (C.H.D.), (M.A.G.), and (D.D.P.)
| | - Dean DellaPenna
- Authors for correspondence: (C.H.D.), (M.A.G.), and (D.D.P.)
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21
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Zhan S, Griswold C, Lukens L. Zea mays RNA-seq estimated transcript abundances are strongly affected by read mapping bias. BMC Genomics 2021; 22:285. [PMID: 33874908 PMCID: PMC8056621 DOI: 10.1186/s12864-021-07577-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 03/30/2021] [Indexed: 11/27/2022] Open
Abstract
Background Genetic variation for gene expression is a source of phenotypic variation for natural and agricultural species. The common approach to map and to quantify gene expression from genetically distinct individuals is to assign their RNA-seq reads to a single reference genome. However, RNA-seq reads from alleles dissimilar to this reference genome may fail to map correctly, causing transcript levels to be underestimated. Presently, the extent of this mapping problem is not clear, particularly in highly diverse species. We investigated if mapping bias occurred and if chromosomal features associated with mapping bias. Zea mays presents a model species to assess these questions, given it has genotypically distinct and well-studied genetic lines. Results In Zea mays, the inbred B73 genome is the standard reference genome and template for RNA-seq read assignments. In the absence of mapping bias, B73 and a second inbred line, Mo17, would each have an approximately equal number of regulatory alleles that increase gene expression. Remarkably, Mo17 had 2–4 times fewer such positively acting alleles than did B73 when RNA-seq reads were aligned to the B73 reference genome. Reciprocally, over one-half of the B73 alleles that increased gene expression were not detected when reads were aligned to the Mo17 genome template. Genes at dissimilar chromosomal ends were strongly affected by mapping bias, and genes at more similar pericentromeric regions were less affected. Biased transcript estimates were higher in untranslated regions and lower in splice junctions. Bias occurred across software and alignment parameters. Conclusions Mapping bias very strongly affects gene transcript abundance estimates in maize, and bias varies across chromosomal features. Individual genome or transcriptome templates are likely necessary for accurate transcript estimation across genetically variable individuals in maize and other species. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07577-3.
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Affiliation(s)
- Shuhua Zhan
- Department of Plant Agriculture, University of Guelph, Guelph, Ontario, Canada
| | - Cortland Griswold
- Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada
| | - Lewis Lukens
- Department of Plant Agriculture, University of Guelph, Guelph, Ontario, Canada.
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22
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Schneider HM, Strock CF, Hanlon MT, Vanhees DJ, Perkins AC, Ajmera IB, Sidhu JS, Mooney SJ, Brown KM, Lynch JP. Multiseriate cortical sclerenchyma enhance root penetration in compacted soils. Proc Natl Acad Sci U S A 2021; 118:e2012087118. [PMID: 33536333 PMCID: PMC8017984 DOI: 10.1073/pnas.2012087118] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Mechanical impedance limits soil exploration and resource capture by plant roots. We examine the role of root anatomy in regulating plant adaptation to mechanical impedance and identify a root anatomical phene in maize (Zea mays) and wheat (Triticum aestivum) associated with penetration of hard soil: Multiseriate cortical sclerenchyma (MCS). We characterize this trait and evaluate the utility of MCS for root penetration in compacted soils. Roots with MCS had a greater cell wall-to-lumen ratio and a distinct UV emission spectrum in outer cortical cells. Genome-wide association mapping revealed that MCS is heritable and genetically controlled. We identified a candidate gene associated with MCS. Across all root classes and nodal positions, maize genotypes with MCS had 13% greater root lignin concentration compared to genotypes without MCS. Genotypes without MCS formed MCS upon exogenous ethylene exposure. Genotypes with MCS had greater lignin concentration and bending strength at the root tip. In controlled environments, MCS in maize and wheat was associated improved root tensile strength and increased penetration ability in compacted soils. Maize genotypes with MCS had root systems with 22% greater depth and 49% greater shoot biomass in compacted soils in the field compared to lines without MCS. Of the lines we assessed, MCS was present in 30 to 50% of modern maize, wheat, and barley cultivars but was absent in teosinte and wild and landrace accessions of wheat and barley. MCS merits investigation as a trait for improving plant performance in maize, wheat, and other grasses under edaphic stress.
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Affiliation(s)
- Hannah M Schneider
- Department of Plant Science, Pennsylvania State University, University Park, PA 16802
| | - Christopher F Strock
- Department of Plant Science, Pennsylvania State University, University Park, PA 16802
| | - Meredith T Hanlon
- Department of Plant Science, Pennsylvania State University, University Park, PA 16802
| | - Dorien J Vanhees
- Division of Agricultural and Environment Sciences, School of Biosciences, University of Nottingham, Leicestershire LE12 5RD, United Kingdom
- The James Hutton Institute, Invergowrie DD2 5DA, United Kingdom
| | - Alden C Perkins
- Department of Plant Science, Pennsylvania State University, University Park, PA 16802
| | - Ishan B Ajmera
- Department of Plant Science, Pennsylvania State University, University Park, PA 16802
| | - Jagdeep Singh Sidhu
- Department of Plant Science, Pennsylvania State University, University Park, PA 16802
| | - Sacha J Mooney
- Division of Agricultural and Environment Sciences, School of Biosciences, University of Nottingham, Leicestershire LE12 5RD, United Kingdom
- Centre for Plant Integrative Biology, University of Nottingham, Leicestershire LE12 5RD, United Kingdom
| | - Kathleen M Brown
- Department of Plant Science, Pennsylvania State University, University Park, PA 16802
| | - Jonathan P Lynch
- Department of Plant Science, Pennsylvania State University, University Park, PA 16802;
- Division of Agricultural and Environment Sciences, School of Biosciences, University of Nottingham, Leicestershire LE12 5RD, United Kingdom
- Centre for Plant Integrative Biology, University of Nottingham, Leicestershire LE12 5RD, United Kingdom
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23
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Bernardo R. Reinventing quantitative genetics for plant breeding: something old, something new, something borrowed, something BLUE. Heredity (Edinb) 2020; 125:375-385. [PMID: 32296132 PMCID: PMC7784685 DOI: 10.1038/s41437-020-0312-1] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 03/23/2020] [Accepted: 03/23/2020] [Indexed: 01/19/2023] Open
Abstract
The goals of quantitative genetics differ according to its field of application. In plant breeding, the main focus of quantitative genetics is on identifying candidates with the best genotypic value for a target population of environments. Keeping quantitative genetics current requires keeping old concepts that remain useful, letting go of what has become archaic, and introducing new concepts and methods that support contemporary breeding. The core concept of continuous variation being due to multiple Mendelian loci remains unchanged. Because the entirety of germplasm available in a breeding program is not in Hardy-Weinberg equilibrium, classical concepts that assume random mating, such as the average effect of an allele and additive variance, need to be retired in plant breeding. Doing so is feasible because with molecular markers, mixed-model approaches that require minimal genetic assumptions can be used for best linear unbiased estimation (BLUE) and prediction. Plant breeding would benefit from borrowing approaches found useful in other disciplines. Examples include reliability as a new measure of the influence of genetic versus nongenetic effects, and operations research and simulation approaches for designing breeding programs. The genetic entities in such simulations should not be generic but should be represented by the pedigrees, marker data, and phenotypic data for the actual germplasm in a breeding program. Over the years, quantitative genetics in plant breeding has become increasingly empirical and computational and less grounded in theory. This trend will continue as the amount and types of data available in a breeding program increase.
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Affiliation(s)
- Rex Bernardo
- Department of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, 1991 Buford Circle, Saint Paul, MN, 55108, USA.
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24
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Scott MF, Ladejobi O, Amer S, Bentley AR, Biernaskie J, Boden SA, Clark M, Dell'Acqua M, Dixon LE, Filippi CV, Fradgley N, Gardner KA, Mackay IJ, O'Sullivan D, Percival-Alwyn L, Roorkiwal M, Singh RK, Thudi M, Varshney RK, Venturini L, Whan A, Cockram J, Mott R. Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding. Heredity (Edinb) 2020; 125:396-416. [PMID: 32616877 PMCID: PMC7784848 DOI: 10.1038/s41437-020-0336-6] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 06/16/2020] [Accepted: 06/16/2020] [Indexed: 11/21/2022] Open
Abstract
Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.
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Affiliation(s)
| | | | - Samer Amer
- University of Reading, Reading, RG6 6AH, UK
- Faculty of Agriculture, Alexandria University, Alexandria, 23714, Egypt
| | - Alison R Bentley
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Jay Biernaskie
- Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
| | - Scott A Boden
- School of Agriculture, Food and Wine, University of Adelaide, Glen Osmond, SA, 5064, Australia
| | | | | | - Laura E Dixon
- Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Carla V Filippi
- Instituto de Agrobiotecnología y Biología Molecular (IABIMO), INTA-CONICET, Nicolas Repetto y Los Reseros s/n, 1686, Hurlingham, Buenos Aires, Argentina
| | - Nick Fradgley
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Keith A Gardner
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Ian J Mackay
- SRUC, West Mains Road, Kings Buildings, Edinburgh, EH9 3JG, UK
| | | | | | - Manish Roorkiwal
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Rakesh Kumar Singh
- International Center for Biosaline Agriculture, Academic City, Dubai, United Arab Emirates
| | - Mahendar Thudi
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Rajeev Kumar Varshney
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | | | - Alex Whan
- CSIRO, GPO Box 1700, Canberra, ACT, 2601, Australia
| | - James Cockram
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, CB3 0LE, UK
| | - Richard Mott
- UCL Genetics Institute, Gower Street, London, WC1E 6BT, UK
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25
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Ding Y, Weckwerth PR, Poretsky E, Murphy KM, Sims J, Saldivar E, Christensen SA, Char SN, Yang B, Tong AD, Shen Z, Kremling KA, Buckler ES, Kono T, Nelson DR, Bohlmann J, Bakker MG, Vaughan MM, Khalil AS, Betsiashvili M, Dressano K, Köllner TG, Briggs SP, Zerbe P, Schmelz EA, Huffaker A. Genetic elucidation of interconnected antibiotic pathways mediating maize innate immunity. NATURE PLANTS 2020; 6:1375-1388. [PMID: 33106639 DOI: 10.1038/s41477-020-00787-9] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 09/11/2020] [Indexed: 05/24/2023]
Abstract
Specialized metabolites constitute key layers of immunity that underlie disease resistance in crops; however, challenges in resolving pathways limit our understanding of the functions and applications of these metabolites. In maize (Zea mays), the inducible accumulation of acidic terpenoids is increasingly considered to be a defence mechanism that contributes to disease resistance. Here, to understand maize antibiotic biosynthesis, we integrated association mapping, pan-genome multi-omic correlations, enzyme structure-function studies and targeted mutagenesis. We define ten genes in three zealexin (Zx) gene clusters that encode four sesquiterpene synthases and six cytochrome P450 proteins that collectively drive the production of diverse antibiotic cocktails. Quadruple mutants in which the ability to produce zealexins (ZXs) is blocked exhibit a broad-spectrum loss of disease resistance. Genetic redundancies ensuring pathway resiliency to single null mutations are combined with enzyme substrate promiscuity, creating a biosynthetic hourglass pathway that uses diverse substrates and in vivo combinatorial chemistry to yield complex antibiotic blends. The elucidated genetic basis of biochemical phenotypes that underlie disease resistance demonstrates a predominant maize defence pathway and informs innovative strategies for transferring chemical immunity between crops.
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Affiliation(s)
- Yezhang Ding
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Philipp R Weckwerth
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Elly Poretsky
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Katherine M Murphy
- Department of Plant Biology, University of California Davis, Davis, CA, USA
| | - James Sims
- ETH Zurich, Institute of Agricultural Sciences, Zurich, Switzerland
| | - Evan Saldivar
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Shawn A Christensen
- Chemistry Research Unit, Center for Medical, Agricultural and Veterinary Entomology, Department of Agriculture, Agricultural Research Service, Gainesville, FL, USA
| | - Si Nian Char
- Division of Plant Sciences, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
| | - Bing Yang
- Division of Plant Sciences, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
- Donald Danforth Plant Science Center, St Louis, MO, USA
| | - Anh-Dao Tong
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Zhouxin Shen
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Karl A Kremling
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, USA
| | - Edward S Buckler
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, USA
- Robert W. Holley Center for Agriculture and Health, Ithaca, US Department of Agriculture, Agricultural Research Service, New York, NY, USA
| | - Tom Kono
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - David R Nelson
- University of Tennessee Health Science Center, Memphis, TN, USA
| | - Jörg Bohlmann
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada
| | - Matthew G Bakker
- National Center for Agricultural Utilization Research, US Department of Agriculture, Agricultural Research Service, Peoria, IL, USA
- Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Martha M Vaughan
- National Center for Agricultural Utilization Research, US Department of Agriculture, Agricultural Research Service, Peoria, IL, USA
| | - Ahmed S Khalil
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Mariam Betsiashvili
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Keini Dressano
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | | | - Steven P Briggs
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Philipp Zerbe
- Department of Plant Biology, University of California Davis, Davis, CA, USA
| | - Eric A Schmelz
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA
| | - Alisa Huffaker
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, USA.
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26
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Stich B, Benke A, Schmidt M, Urbany C, Shi R, von Wirén N. The maize shoot ionome: Its interaction partners, predictive power, and genetic determinants. PLANT, CELL & ENVIRONMENT 2020; 43:2095-2111. [PMID: 32529648 DOI: 10.1111/pce.13823] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2019] [Revised: 04/05/2020] [Accepted: 04/18/2020] [Indexed: 05/28/2023]
Abstract
An improved understanding of how to manipulate the accumulation and enrichment of mineral elements in aboveground plant tissues holds promise for future resource efficient and sustainable crop production. The objectives of this study were to (a) evaluate the influence of Fe regimes on mineral element concentrations and contents in the maize shoot as well as their correlations, (b) examine the predictive ability of physiological and morphological traits of individual genotypes of the IBM population from the concentration of mineral elements, and (c) identify genetic factors influencing the mineral element composition within and across Fe regimes. We evaluated the concentration and content of 12 mineral elements in shoots of the IBM population grown in sufficient and deficient Fe regimes and found for almost all mineral elements a significant (α = 0.05) genotypic variance. Across all mineral elements, the variance of genotype*Fe regime interactions was on average even more pronounced. High prediction abilities indicated that mineral elements are powerful predictors of morphological and physiological traits. Furthermore, our results suggest that ZmHMA2/3 and ZmMOT1 are major players in the natural genetic variation of Cd and Mo concentrations and contents of maize shoots, respectively.
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Affiliation(s)
- Benjamin Stich
- Institute for Quantitative Genetics and Genomics of Plants, Heinrich Heine University, Düsseldorf, Germany
- Cluster of Excellence on Plant Sciences, Düsseldorf, Germany
- Max Planck Institute for Plant Breeding Research, Köln, Germany
| | - Andreas Benke
- Max Planck Institute for Plant Breeding Research, Köln, Germany
| | - Maria Schmidt
- Institute for Quantitative Genetics and Genomics of Plants, Heinrich Heine University, Düsseldorf, Germany
| | - Claude Urbany
- Max Planck Institute for Plant Breeding Research, Köln, Germany
| | - Rongli Shi
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Nicolaus von Wirén
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
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27
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Analysis of the genes controlling three quantitative traits in three diverse plant species reveals the molecular basis of quantitative traits. Sci Rep 2020; 10:10074. [PMID: 32572040 PMCID: PMC7308372 DOI: 10.1038/s41598-020-66271-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 04/28/2020] [Indexed: 02/08/2023] Open
Abstract
Most traits of agricultural importance are quantitative traits controlled by numerous genes. However, it remains unclear about the molecular mechanisms underpinning quantitative traits. Here, we report the molecular characteristics of the genes controlling three quantitative traits randomly selected from three diverse plant species, including ginsenoside biosynthesis in ginseng (Panax ginseng C.A. Meyer), fiber length in cotton (Gossypium hirsutum L. and G. barbadense L.) and grain yield in maize (Zea mays L.). We found that a vast majority of the genes controlling a quantitative trait were significantly more likely spliced into multiple transcripts while they expressed. Nevertheless, only one to four, but not all, of the transcripts spliced from each of the genes were significantly correlated with the phenotype of the trait. The genes controlling a quantitative trait were multiple times more likely to form a co-expression network than other genes expressed in an organ. The network varied substantially among genotypes of a species and was associated with their phenotypes. These findings indicate that the genes controlling a quantitative trait are more likely pleiotropic and functionally correlated, thus providing new insights into the molecular basis underpinning quantitative traits and knowledge necessary to develop technologies for efficient manipulation of quantitative traits.
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28
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Multi-trait Genomic Selection Methods for Crop Improvement. Genetics 2020; 215:931-945. [PMID: 32482640 DOI: 10.1534/genetics.120.303305] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 05/26/2020] [Indexed: 11/18/2022] Open
Abstract
Plant breeders make selection decisions based on multiple traits, such as yield, plant height, flowering time, and disease resistance. A commonly used approach in multi-trait genomic selection is index selection, which assigns weights to different traits relative to their economic importance. However, classical index selection only optimizes genetic gain in the next generation, requires some experimentation to find weights that lead to desired outcomes, and has difficulty optimizing nonlinear breeding objectives. Multi-objective optimization has also been used to identify the Pareto frontier of selection decisions, which represents different trade-offs across multiple traits. We propose a new approach, which maximizes certain traits while keeping others within desirable ranges. Optimal selection decisions are made using a new version of the look-ahead selection (LAS) algorithm, which was recently proposed for single-trait genomic selection, and achieved superior performance with respect to other state-of-the-art selection methods. To demonstrate the effectiveness of the new method, a case study is developed using a realistic data set where our method is compared with conventional index selection. Results suggest that the multi-trait LAS is more effective at balancing multiple traits compared with index selection.
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29
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Genetic and Physiological Characterization of a Calcium Deficiency Phenotype in Maize. G3-GENES GENOMES GENETICS 2020; 10:1963-1970. [PMID: 32238423 PMCID: PMC7263677 DOI: 10.1534/g3.120.401069] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Calcium (Ca) is an essential plant nutrient, required for signaling, cell wall fortification and growth and development. Calcium deficiency (Ca-deficiency) in maize causes leaf tip rot and a so-called “bull-whipping” or “buggy-whipping” phenotype. Seedlings of the maize line B73 displayed these Ca-deficiency-like symptoms when grown in the greenhouse with excess fertilizer during the winter months, while seedlings of the Mo17 maize line did not display these symptoms under the same conditions. These differential phenotypes could be recapitulated in ‘mini-hydroponic’ systems in the laboratory in which high ammonium, but not nitrate, levels induced the symptoms in B73 but not Mo17 seedlings. Consistent with this phenotype being caused by Ca-deficiency, addition of Ca2+ completely relieved the symptoms. These data suggest that ammonium reduces the seedling’s ability to absorb calcium, which causes the Ca-deficiency phenotype, and that this trait varies among genotypes. A recombinant inbred line (RIL) population derived from a B73 x Mo17 cross was used to map quantitative trait loci (QTL) associated with the Ca-deficiency phenotype. QTL associated with variation in susceptibility to Ca-deficiency were detected on chromosomes 1, 2, 3, 6 which explained between 3.30–9.94% of the observed variation. Several genes predicted to bind or be activated by calcium map to these QTL on chromosome 1, 2, 6. These results describe for the first time the genetics of Ca-deficiency symptoms in maize and in plants in general.
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30
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Liu J, Seetharam AS, Chougule K, Ou S, Swentowsky KW, Gent JI, Llaca V, Woodhouse MR, Manchanda N, Presting GG, Kudrna DA, Alabady M, Hirsch CN, Fengler KA, Ware D, Michael TP, Hufford MB, Dawe RK. Gapless assembly of maize chromosomes using long-read technologies. Genome Biol 2020; 21:121. [PMID: 32434565 PMCID: PMC7238635 DOI: 10.1186/s13059-020-02029-9] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Accepted: 04/23/2020] [Indexed: 12/16/2022] Open
Abstract
Creating gapless telomere-to-telomere assemblies of complex genomes is one of the ultimate challenges in genomics. We use two independent assemblies and an optical map-based merging pipeline to produce a maize genome (B73-Ab10) composed of 63 contigs and a contig N50 of 162 Mb. This genome includes gapless assemblies of chromosome 3 (236 Mb) and chromosome 9 (162 Mb), and 53 Mb of the Ab10 meiotic drive haplotype. The data also reveal the internal structure of seven centromeres and five heterochromatic knobs, showing that the major tandem repeat arrays (CentC, knob180, and TR-1) are discontinuous and frequently interspersed with retroelements.
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Affiliation(s)
- Jianing Liu
- Department of Genetics, University of Georgia, Athens, GA, 30602, USA
| | - Arun S Seetharam
- Genome Informatics Facility, Iowa State University, Ames, IA, 50011, USA
| | - Kapeel Chougule
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
| | - Shujun Ou
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, 50011, USA
| | - Kyle W Swentowsky
- Department of Plant Biology, University of Georgia, Athens, GA, 30602, USA
| | - Jonathan I Gent
- Department of Plant Biology, University of Georgia, Athens, GA, 30602, USA
| | - Victor Llaca
- Corteva Agriscience™, 8325 NW 62nd Ave, Johnston, IA, 50131, USA
| | | | - Nancy Manchanda
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, 50011, USA
| | - Gernot G Presting
- Molecular Biosciences and Bioengineering, University of Hawaii, Honolulu, HI, 96822, USA
| | - David A Kudrna
- Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, AZ, 85721, USA
| | - Magdy Alabady
- Department of Plant Biology, University of Georgia, Athens, GA, 30602, USA
- Georgia Genomics and Bioinformatics Core Laboratory, University of Georgia, Athens, GA, 30602, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Kevin A Fengler
- Corteva Agriscience™, 8325 NW 62nd Ave, Johnston, IA, 50131, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, 11724, USA
- USDA ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, Ithaca, NY, 14853, USA
| | - Todd P Michael
- Informatics Department, J. Craig Venter Institute, La Jolla, CA, USA
| | - Matthew B Hufford
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, 50011, USA
| | - R Kelly Dawe
- Department of Genetics, University of Georgia, Athens, GA, 30602, USA.
- Department of Plant Biology, University of Georgia, Athens, GA, 30602, USA.
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31
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Ge M, Wang Y, Liu Y, Jiang L, He B, Ning L, Du H, Lv Y, Zhou L, Lin F, Zhang T, Liang S, Lu H, Zhao H. The NIN-like protein 5 (ZmNLP5) transcription factor is involved in modulating the nitrogen response in maize. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 102:353-368. [PMID: 31793100 PMCID: PMC7217196 DOI: 10.1111/tpj.14628] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Revised: 11/01/2019] [Accepted: 11/11/2019] [Indexed: 05/12/2023]
Abstract
Maize exhibits marked growth and yield response to supplemental nitrogen (N). Here, we report the functional characterization of a maize NIN-like protein ZmNLP5 as a central hub in a molecular network associated with N metabolism. Predominantly expressed and accumulated in roots and vascular tissues, ZmNLP5 was shown to rapidly respond to nitrate treatment. Under limited N supply, compared with that of wild-type (WT) seedlings, the zmnlp5 mutant seedlings accumulated less nitrate and nitrite in the root tissues and ammonium in the shoot tissues. The zmnlp5 mutant plants accumulated less nitrogen than the WT plants in the ear leaves and seed kernels. Furthermore, the mutants carrying the transgenic ZmNLP5 cDNA fragment significantly increased the nitrate content in the root tissues compared with that of the zmnlp5 mutants. In the zmnlp5 mutant plants, loss of the ZmNLP5 function led to changes in expression for a significant number of genes involved in N signalling and metabolism. We further show that ZmNLP5 directly regulates the expression of nitrite reductase 1.1 (ZmNIR1.1) by binding to the nitrate-responsive cis-element at the 5' UTR of the gene. Interestingly, a natural loss-of-function allele of ZmNLP5 in Mo17 conferred less N accumulation in the ear leaves and seed kernels resembling that of the zmnlp5 mutant plants. Our findings show that ZmNLP5 is involved in mediating the plant response to N in maize.
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Affiliation(s)
- Min Ge
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Yuancong Wang
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Yuhe Liu
- Department of Crop SciencesUniversity of IllinoisUrbana‐ChampaignILUSA
| | - Lu Jiang
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Bing He
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Lihua Ning
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Hongyang Du
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Yuanda Lv
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Ling Zhou
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Feng Lin
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Tifu Zhang
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Shuaiqiang Liang
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Haiyan Lu
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
| | - Han Zhao
- Institute of Crop Germplasm and BiotechnologyProvincial Key Laboratory of AgrobiologyJiangsu Academy of Agricultural SciencesNanjing210014China
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32
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Ren J, A Boerman N, Liu R, Wu P, Trampe B, Vanous K, Frei UK, Chen S, Lübberstedt T. Mapping of QTL and identification of candidate genes conferring spontaneous haploid genome doubling in maize (Zea mays L.). PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2020; 293:110337. [PMID: 32081276 DOI: 10.1016/j.plantsci.2019.110337] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 11/07/2019] [Accepted: 11/19/2019] [Indexed: 05/02/2023]
Abstract
In vivo doubled haploid (DH) technology is widely used in commercial maize (Zea mays L.) breeding. Haploid genome doubling is a critical step in DH breeding. In this study, inbred lines GF1 (0.65), GF3(0.29), and GF5 (0) with high, moderate, and poor spontaneous haploid genome doubling (SHGD), respectively, were selected to develop mapping populations for SHGD. Three QTL, qshgd1, qshgd2, and qshgd3, related to SHGD were identified by selective genotyping. With the exception of qshgd3, the source of haploid genome doubling alleles were derived from GF1. Furthermore, RNA-Seq was conducted to identify putative candidate genes between GF1 and GF5 within the qshgd1 region. A differentially expressed formin-like protein 5 transcript was identified within the qshgd1 region.
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Affiliation(s)
- Jiaojiao Ren
- College of Agronomy, Xinjiang Agricultural University, Urumqi, 830052, China
| | | | - Ruixiang Liu
- Institute of Food Crops, Jiangsu Province Academy of Agricultural Sciences, Jiangsu, 210014, China
| | - Penghao Wu
- College of Agronomy, Xinjiang Agricultural University, Urumqi, 830052, China
| | - Benjamin Trampe
- Department of Agronomy, Iowa State University, Ames, Iowa, 50011, USA
| | - Kimberly Vanous
- Department of Agronomy, Iowa State University, Ames, Iowa, 50011, USA
| | - Ursula K Frei
- Department of Agronomy, Iowa State University, Ames, Iowa, 50011, USA
| | - Shaojiang Chen
- National Maize Improvement Center, China Agricultural University, Beijing, 100193, China
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33
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Recombination Pattern Characterization via Simulation Using Different Maize Populations. Int J Mol Sci 2020; 21:ijms21062222. [PMID: 32210156 PMCID: PMC7139635 DOI: 10.3390/ijms21062222] [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: 01/08/2020] [Revised: 03/10/2020] [Accepted: 03/19/2020] [Indexed: 11/27/2022] Open
Abstract
Efficient recombination is critical to both plant breeding and gene cloning. However, almost all traditional recombination studies and genetic improvements require the slow and labor-intensive population construction process, and little is known about the recombination characteristics of populations of different types, generations, and origins. Here, we provide a simple and efficient simulation method for population construction based on doubled haploid (DH) and intermated B73 × Mo17 maize (IBM) populations to predict the recombination pattern. We found that the chromosomes had 0, 1, 2, and 3 recombination events that occurred at rates of 0.16, 0.30, 0.23, and 0.15, respectively, in the DH and the recombination rate of each chromosome in the IBM population ranged from 0 to 12.1 cM per 125 kb. Based on the observed recombination parameters, we estimated the number of recombination events and constructed the linkage maps of the simulated DH and recombination inbred line (RIL) populations. These simulated populations exhibited similar recombination patterns compared with the real populations, suggesting the feasibility of this simulation approach. We then compared the recombination rates of the simulated populations of different types (DH induced or self-crossed), generations, and origins (using the 8, 16, and 32 multiparent advanced generation intercross (MAGIC) populations), and suggested a rapid and cost-effective population construction procedure for breeders and geneticists, while maintaining an optimal recombination rate. This study offers a convenient method for optimizing the population construction process and has broader implications for other crop species, thereby facilitating future population studies and genetic improvement strategies.
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34
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Falque M, Jebreen K, Paux E, Knaak C, Mezmouk S, Martin OC. CNVmap: A Method and Software To Detect and Map Copy Number Variants from Segregation Data. Genetics 2020; 214:561-576. [PMID: 31882400 PMCID: PMC7054022 DOI: 10.1534/genetics.119.302881] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 12/23/2019] [Indexed: 01/22/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) are used widely for detecting quantitative trait loci, or for searching for causal variants of diseases. Nevertheless, structural variations such as copy-number variants (CNVs) represent a large part of natural genetic diversity, and contribute significantly to trait variation. Numerous methods and softwares based on different technologies (amplicons, CGH, tiling, or SNP arrays, or sequencing) have already been developed to detect CNVs, but they bypass a wealth of information such as genotyping data from segregating populations, produced, e.g., for QTL mapping. Here, we propose an original method to both detect and genetically map CNVs using mapping panels. Specifically, we exploit the apparent heterozygous state of duplicated loci: peaks in appropriately defined genome-wide allelic profiles provide highly specific signatures that identify the nature and position of the CNVs. Our original method and software can detect and map automatically up to 33 different predefined types of CNVs based on segregation data only. We validate this approach on simulated and experimental biparental mapping panels in two maize populations and one wheat population. Most of the events found correspond to having just one extra copy in one of the parental lines, but the corresponding allelic value can be that of either parent. We also find cases with two or more additional copies, especially in wheat, where these copies locate to homeologues. More generally, our computational tool can be used to give additional value, at no cost, to many datasets produced over the past decade from genetic mapping panels.
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Affiliation(s)
- Matthieu Falque
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Kamel Jebreen
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
- Department of Mathematics, An-Najah National University, Nablus, Palestine
| | - Etienne Paux
- Université Clermont Auvergne, INRAE, GDEC, 63000 Clermont-Ferrand, France
| | | | | | - Olivier C Martin
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
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35
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Interaction Between Induced and Natural Variation at oil yellow1 Delays Reproductive Maturity in Maize. G3-GENES GENOMES GENETICS 2020; 10:797-810. [PMID: 31822516 PMCID: PMC7003087 DOI: 10.1534/g3.119.400838] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
We previously demonstrated that maize (Zea mays) locus very oil yellow1 (vey1) encodes a putative cis-regulatory expression polymorphism at the magnesium chelatase subunit I gene (aka oil yellow1) that strongly modifies the chlorophyll content of the semi-dominant Oy1-N1989 mutants. The vey1 allele of Mo17 inbred line reduces chlorophyll content in the mutants leading to reduced photosynthetic output. Oy1-N1989 mutants in B73 reached reproductive maturity four days later than wild-type siblings. Enhancement of Oy1-N1989 by the Mo17 allele at the vey1 QTL delayed maturity further, resulting in detection of a flowering time QTL in two bi-parental mapping populations crossed to Oy1-N1989. The near isogenic lines of B73 harboring the vey1 allele from Mo17 delayed flowering of Oy1-N1989 mutants by twelve days. Just as previously observed for chlorophyll content, vey1 had no effect on reproductive maturity in the absence of the Oy1-N1989 allele. Loss of chlorophyll biosynthesis in Oy1-N1989 mutants and enhancement by vey1 reduced CO2 assimilation. We attempted to separate the effects of photosynthesis on the induction of flowering from a possible impact of chlorophyll metabolites and retrograde signaling by manually reducing leaf area. Removal of leaves, independent of the Oy1-N1989 mutant, delayed flowering but surprisingly reduced chlorophyll contents of emerging leaves. Thus, defoliation did not completely separate the identity of the signal(s) that regulates flowering time from changes in chlorophyll content in the foliage. These findings illustrate the necessity to explore the linkage between metabolism and the mechanisms that connect it to flowering time regulation.
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36
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Liu J, Fernie AR, Yan J. The Past, Present, and Future of Maize Improvement: Domestication, Genomics, and Functional Genomic Routes toward Crop Enhancement. PLANT COMMUNICATIONS 2020; 1:100010. [PMID: 33404535 PMCID: PMC7747985 DOI: 10.1016/j.xplc.2019.100010] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 11/07/2019] [Accepted: 11/22/2019] [Indexed: 05/14/2023]
Abstract
After being domesticated from teosinte, cultivated maize (Zea mays ssp. mays) spread worldwide and now is one of the most important staple crops. Due to its tremendous phenotypic and genotypic diversity, maize also becomes to be one of the most widely used model plant species for fundamental research, with many important discoveries reported by maize researchers. Here, we provide an overview of the history of maize domestication and key genes controlling major domestication-related traits, review the currently available resources for functional genomics studies in maize, and discuss the functions of most of the maize genes that have been positionally cloned and can be used for crop improvement. Finally, we provide some perspectives on future directions regarding functional genomics research and the breeding of maize and other crops.
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Affiliation(s)
- Jie Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
- Corresponding author
| | - Alisdair R. Fernie
- Department of Molecular Physiology, Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
- Corresponding author
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Luo J, Wei C, Liu H, Cheng S, Xiao Y, Wang X, Yan J, Liu J. MaizeCUBIC: a comprehensive variation database for a maize synthetic population. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2020:5857845. [PMID: 32548639 PMCID: PMC7297647 DOI: 10.1093/database/baaa044] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 04/03/2020] [Accepted: 05/18/2020] [Indexed: 11/13/2022]
Abstract
MaizeCUBIC is a free database that describes genomic variations, gene expression, phenotypes and quantitative trait locus (QTLs) for a maize CUBIC population (24 founders and 1404 inbred offspring). The database not only includes information for over 14M single nucleotide polymorphism (SNPs) and 43K indels previously identified but also contains 660K structure variations (SVs) and 600M novel sequences newly identified in the present study, which represents a comprehensive high-density variant map for a diverse population. Based on these genomic variations, the database would demonstrate the mosaic structure for each progeny, reflecting a high-resolution reshuffle across parental genomes. A total of 23 agronomic traits measured on parents and progeny in five locations, where are representative of the maize main growing regions in China, were also included in the database. To further explore the genotype–phenotype relationships, two different methods of genome-wide association studies (GWAS) were employed for dissecting the genetic architecture of 23 agronomic traits. Additionally, the Basic Local Alignment Search Tool and primer design tools are developed to promote follow-up analysis and experimental verification. All the original data and corresponding analytical results can be accessed through user-friendly online queries and web interface dynamic visualization, as well as downloadable files. These data and tools provide valuable resources on genetic and genomic studies of maize and other crops.
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Affiliation(s)
- Jingyun Luo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Chengcheng Wei
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Haijun Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.,Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter, Vienna 1030, Austria
| | - Shikun Cheng
- College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Yingjie Xiao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaqing Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Jianxiao Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.,College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
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Dennison T, Qin W, Loneman DM, Condon SGF, Lauter N, Nikolau BJ, Yandeau-Nelson MD. Genetic and environmental variation impact the cuticular hydrocarbon metabolome on the stigmatic surfaces of maize. BMC PLANT BIOLOGY 2019; 19:430. [PMID: 31623561 PMCID: PMC6796380 DOI: 10.1186/s12870-019-2040-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 09/16/2019] [Indexed: 05/13/2023]
Abstract
BACKGROUND Simple non-isoprenoid hydrocarbons accumulate in discrete regions of the biosphere, including within bacteria and algae as a carbon and/or energy store, and the cuticles of plants and insects, where they may protect against environmental stresses. The extracellular cuticular surfaces of the stigmatic silks of maize are rich in linear hydrocarbons and therefore provide a convenient system to study the biological origins and functions of these unique metabolites. RESULTS To test the hypotheses that genetics and environment influence the accumulation of surface hydrocarbons on silks and to examine the breadth of metabolome compositions across diverse germplasm, cuticular hydrocarbons were analyzed on husk-encased silks and silks that emerged from the husk leaves from 32 genetically diverse maize inbred lines, most of which are commonly utilized in genetics experiments. Total hydrocarbon accumulation varied ~ 10-fold among inbred lines, and up to 5-fold between emerged and husk-encased silks. Alkenes accounted for 5-60% of the total hydrocarbon metabolome, and the majority of alkenes were monoenes with a double bond at either the 7th or 9th carbon atom of the alkyl chain. Total hydrocarbon accumulation was impacted to similar degrees by genotype and husk encasement status, whereas genotype predominantly impacted alkene composition. Only minor differences in the metabolome were observed on silks that were emerged into the external environment for 3- versus 6-days. The environmental influence on the metabolome was further investigated by growing inbred lines in 2 years, one of which was warmer and wetter. Inbred lines grown in the drier year accumulated up to 2-fold more hydrocarbons and up to a 22% higher relative abundance of alkenes. In summary, the surface hydrocarbon metabolome of silks is primarily governed by genotype and husk encasement status, with smaller impacts of environment and genotype-by-environment interactions. CONCLUSIONS This study reveals that the composition of the cuticular hydrocarbon metabolome on silks is affected significantly by genetic factors, and is therefore amenable to dissection using quantitative genetic approaches. Such studies will clarify the genetic mechanisms responsible for the accumulation of these metabolites, enabling detailed functional investigations of the diverse and complex protective roles of silk surface lipids against environmental stresses.
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Affiliation(s)
- Tesia Dennison
- Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, USA
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, USA
| | - Wenmin Qin
- Roy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, USA
- Present Address: GenScript, Nanjing, China
| | - Derek M. Loneman
- Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, USA
- Present Address: School of Medicine, Case Western Reserve University, Cleveland, OH USA
| | - Samson G. F. Condon
- Roy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, USA
- Present Address: Department of Biochemistry, University of Wisconsin, Madison, USA
| | - Nick Lauter
- Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, USA
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, USA
- USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, USA
| | - Basil J. Nikolau
- Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, USA
- Roy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, USA
- NSF-Engineering Research Center for Biorenewable Chemicals, Iowa State University, Ames, USA
- Center for Metabolic Biology, Iowa State University, Ames, USA
| | - Marna D. Yandeau-Nelson
- Interdepartmental Genetics and Genomics Graduate Program, Iowa State University, Ames, USA
- Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, USA
- NSF-Engineering Research Center for Biorenewable Chemicals, Iowa State University, Ames, USA
- Center for Metabolic Biology, Iowa State University, Ames, USA
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do Vale Martins L, Yu F, Zhao H, Dennison T, Lauter N, Wang H, Deng Z, Thompson A, Semrau K, Rouillard JM, Birchler JA, Jiang J. Meiotic crossovers characterized by haplotype-specific chromosome painting in maize. Nat Commun 2019; 10:4604. [PMID: 31601818 PMCID: PMC6787048 DOI: 10.1038/s41467-019-12646-z] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Accepted: 09/20/2019] [Indexed: 01/25/2023] Open
Abstract
Meiotic crossovers (COs) play a critical role in generating genetic variation and maintaining faithful segregation of homologous chromosomes during meiosis. We develop a haplotype-specific fluorescence in situ hybridization (FISH) technique that allows visualization of COs directly on metaphase chromosomes. Oligonucleotides (oligos) specific to chromosome 10 of maize inbreds B73 and Mo17, respectively, are synthesized and labeled as FISH probes. The parental and recombinant chromosome 10 in B73 x Mo17 F1 hybrids and F2 progenies can be unambiguously identified by haplotype-specific FISH. Analysis of 58 F2 plants reveals lack of COs in the entire proximal half of chromosome 10. However, we detect COs located in regions very close to the centromere in recombinant inbred lines from an intermated B73 x Mo17 population, suggesting effective accumulation of COs in recombination-suppressed chromosomal regions through intermating and the potential to generate favorable allelic combinations of genes residing in these regions. Meiotic crossovers (COs) are essential for proper chromosome segregation and generating novel combinations of alleles. Here, the authors develop haplotype-specific oligos on maize chromosome 10 for fluorescence in situ hybridization and analyze CO patterns in an intermated recombinant population derived from B73 and Mo17.
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Affiliation(s)
- Lívia do Vale Martins
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.,Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
| | - Fan Yu
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.,Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA.,National Engineering Research Center for Sugarcane, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Hainan Zhao
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.,Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
| | - Tesia Dennison
- Genetics and Genomics Graduate Program, Iowa State University, Ames, IA, 50011, USA
| | - Nick Lauter
- Genetics and Genomics Graduate Program, Iowa State University, Ames, IA, 50011, USA.,USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA, 50011, USA
| | - Haiyan Wang
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.,Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
| | - Zuhu Deng
- National Engineering Research Center for Sugarcane, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Addie Thompson
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, 48824, USA.,Michigan State University AgBioResearch, East Lansing, MI, 48824, USA
| | - Kassandra Semrau
- Arbor Biosciences, Ann Arbor, MI, 48103, USA.,Department of Natural Sciences, University of Michigan-Dearborn, Dearborn, MI, 48128, USA
| | - Jean-Marie Rouillard
- Arbor Biosciences, Ann Arbor, MI, 48103, USA.,Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - James A Birchler
- Division of Biological Sciences, University of Missouri, Columbia, MO, 65211, USA
| | - 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. .,Michigan State University AgBioResearch, East Lansing, MI, 48824, USA.
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40
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Fikas AA, Dilkes BP, Baxter I. Multivariate analysis reveals environmental and genetic determinants of element covariation in the maize grain ionome. PLANT DIRECT 2019; 3:e00139. [PMID: 31245778 PMCID: PMC6589523 DOI: 10.1002/pld3.139] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 02/25/2019] [Accepted: 04/02/2019] [Indexed: 05/06/2023]
Abstract
The integrated responses of biological systems to genetic and environmental variation result in substantial covariance in multiple phenotypes. The resultant pleiotropy, environmental effects, and genotype-by-environmental interactions (GxE) are foundational to our understanding of biology and genetics. Yet, the treatment of correlated characters, and the identification of the genes encoding functions that generate this covariance, has lagged. As a test case for analyzing the genetic basis underlying multiple correlated traits, we analyzed maize kernel ionomes from Intermated B73 x Mo17 (IBM) recombinant inbred populations grown in 10 environments. Plants obtain elements from the soil through genetic and biochemical pathways responsive to physiological state and environment. Most perturbations affect multiple elements which leads the ionome, the full complement of mineral nutrients in an organism, to vary as an integrated network rather than a set of distinct single elements. We compared quantitative trait loci (QTL) determining single-element variation to QTL that predict variation in principal components (PCs) of multiple-element covariance. Single-element and multivariate approaches detected partially overlapping sets of loci. QTL influencing trait covariation were detected at loci that were not found by mapping single-element traits. Moreover, this approach permitted testing environmental components of trait covariance, and identified multi-element traits that were determined by both genetic and environmental factors as well as genotype-by-environment interactions. Growth environment had a profound effect on the elemental profiles and multi-element phenotypes were significantly correlated with specific environmental variables.
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Affiliation(s)
- Alexandra Asaro Fikas
- Donald Danforth Plant Science CenterSt. LouisMissouri
- Washington University in St. LouisSt. LouisMissouri
| | - Brian P. Dilkes
- Department of BiochemistryPurdue UniversityWest LafayetteIndiana
| | - Ivan Baxter
- Donald Danforth Plant Science CenterSt. LouisMissouri
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Galic V, Franic M, Jambrovic A, Ledencan T, Brkic A, Zdunic Z, Simic D. Genetic Correlations Between Photosynthetic and Yield Performance in Maize Are Different Under Two Heat Scenarios During Flowering. FRONTIERS IN PLANT SCIENCE 2019; 10:566. [PMID: 31114604 PMCID: PMC6503818 DOI: 10.3389/fpls.2019.00566] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 04/15/2019] [Indexed: 05/29/2023]
Abstract
Chlorophyll fluorescence (ChlF) parameters are reliable early stress indicators in crops, but their relations with yield are still not clear. The aims of this study are to examine genetic correlations between photosynthetic performance of JIP-test during flowering and grain yield (GY) in maize grown under two heat scenarios in the field environments applying quantitative genetic analysis, and to compare efficiencies of indirect selection for GY through ChlF parameters and genomic selection for GY. The testcrosses of 221 intermated recombinant inbred lines (IRILs) of the IBM Syn4 population were evaluated in six environments at two geographically distinctive locations in 3 years. According to day/night temperatures and vapor pressure deficit (VPD), the two locations in Croatia and Turkey may be categorized to the mild heat and moderate heat scenarios, respectively. Mild heat scenario is characterized by daytime temperatures often exceeding 33°C and night temperatures lower than 20°C while in moderate heat scenario the daytime temperatures often exceeded 33°C and night temperatures were above 20°C. The most discernible differences among the scenarios were obtained for efficiency of electron transport beyond quinone A (QA) [ET/(TR-ET)], performance index on absorption basis (PIABS) and GY. Under the moderate heat scenario, there were tight positive genetic correlations between ET/(TR-ET) and GY (0.73), as well as between PIABS and GY (0.59). Associations between the traits were noticeably weaker under the mild heat scenario. Analysis of quantitative trait loci (QTL) revealed several common QTLs for photosynthetic and yield performance under the moderate heat scenario corroborating pleiotropy. Although the indirect selection with ChlF parameters is less efficient than direct selection, ET/(TR-ET) and PIABS could be efficient secondary breeding traits for selection under moderate heat stress since they seem to be genetically correlated with GY in the stressed environments and not associated with yield performance under non-stressed conditions predicting GY during flowering. Indirect selection through PIABS was also shown to be more efficient than genomic selection in moderate heat scenario.
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Affiliation(s)
- Vlatko Galic
- Department of Maize Breeding and Genetics, Agricultural Institute Osijek, Osijek, Croatia
| | - Mario Franic
- Department of Maize Breeding and Genetics, Agricultural Institute Osijek, Osijek, Croatia
| | - Antun Jambrovic
- Department of Maize Breeding and Genetics, Agricultural Institute Osijek, Osijek, Croatia
- Centre of Excellence for Biodiversity and Molecular Plant Breeding, Zagreb, Croatia
| | - Tatjana Ledencan
- Department of Maize Breeding and Genetics, Agricultural Institute Osijek, Osijek, Croatia
| | - Andrija Brkic
- Department of Maize Breeding and Genetics, Agricultural Institute Osijek, Osijek, Croatia
| | - Zvonimir Zdunic
- Department of Maize Breeding and Genetics, Agricultural Institute Osijek, Osijek, Croatia
- Centre of Excellence for Biodiversity and Molecular Plant Breeding, Zagreb, Croatia
| | - Domagoj Simic
- Department of Maize Breeding and Genetics, Agricultural Institute Osijek, Osijek, Croatia
- Centre of Excellence for Biodiversity and Molecular Plant Breeding, Zagreb, Croatia
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Andorf C, Beavis WD, Hufford M, Smith S, Suza WP, Wang K, Woodhouse M, Yu J, Lübberstedt T. Technological advances in maize breeding: past, present and future. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:817-849. [PMID: 30798332 DOI: 10.1007/s00122-019-03306-3] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Accepted: 02/05/2019] [Indexed: 05/18/2023]
Abstract
Maize has for many decades been both one of the most important crops worldwide and one of the primary genetic model organisms. More recently, maize breeding has been impacted by rapid technological advances in sequencing and genotyping technology, transformation including genome editing, doubled haploid technology, parallelled by progress in data sciences and the development of novel breeding approaches utilizing genomic information. Herein, we report on past, current and future developments relevant for maize breeding with regard to (1) genome analysis, (2) germplasm diversity characterization and utilization, (3) manipulation of genetic diversity by transformation and genome editing, (4) inbred line development and hybrid seed production, (5) understanding and prediction of hybrid performance, (6) breeding methodology and (7) synthesis of opportunities and challenges for future maize breeding.
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Affiliation(s)
| | - William D Beavis
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | - Matthew Hufford
- Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA, 50011-1010, USA
| | - Stephen Smith
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | - Walter P Suza
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | - Kan Wang
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | | | - Jianming Yu
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA
| | - Thomas Lübberstedt
- Department of Agronomy, Iowa State University, Agronomy Hall, Ames, IA, 50011-1010, USA.
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Zhou S, Zhang YK, Kremling KA, Ding Y, Bennett JS, Bae JS, Kim DK, Ackerman HH, Kolomiets MV, Schmelz EA, Schroeder FC, Buckler ES, Jander G. Ethylene signaling regulates natural variation in the abundance of antifungal acetylated diferuloylsucroses and Fusarium graminearum resistance in maize seedling roots. THE NEW PHYTOLOGIST 2019; 221:2096-2111. [PMID: 30289553 DOI: 10.1111/nph.15520] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2018] [Accepted: 09/26/2018] [Indexed: 05/20/2023]
Abstract
The production and regulation of defensive specialized metabolites play a central role in pathogen resistance in maize (Zea mays) and other plants. Therefore, identification of genes involved in plant specialized metabolism can contribute to improved disease resistance. We used comparative metabolomics to identify previously unknown antifungal metabolites in maize seedling roots, and investigated the genetic and physiological mechanisms underlying their natural variation using quantitative trait locus mapping and comparative transcriptomics approaches. Two maize metabolites, smilaside A (3,6-diferuloyl-3',6'-diacetylsucrose) and smiglaside C (3,6-diferuloyl-2',3',6'-triacetylsucrose), were identified that could contribute to maize resistance against Fusarium graminearum and other fungal pathogens. Elevated expression of an ethylene signaling gene, ETHYLENE INSENSITIVE 2 (ZmEIN2), co-segregated with a decreased smilaside A : smiglaside C ratio. Pharmacological and genetic manipulation of ethylene availability and sensitivity in vivo indicated that, whereas ethylene was required for the production of both metabolites, the smilaside A : smiglaside C ratio was negatively regulated by ethylene sensitivity. This ratio, rather than the absolute abundance of these two metabolites, was important for maize seedling root defense against F. graminearum. Ethylene signaling regulates the relative abundance of the two F. graminearum-resistance-related metabolites and affects resistance against F. graminearum in maize seedling roots.
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Affiliation(s)
- Shaoqun Zhou
- Boyce Thompson Institute, 533 Tower Road, Ithaca, NY, 14853, USA
- Plant Biology Section, School of Integrated Plant Science, Cornell University, Ithaca, NY, 14853, USA
| | - Ying K Zhang
- Boyce Thompson Institute, 533 Tower Road, Ithaca, NY, 14853, USA
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, 14853, USA
| | - Karl A Kremling
- Plant Breeding and Genetics Section, Cornell University, Ithaca, NY, 14853, USA
| | - Yezhang Ding
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, 92093, USA
| | - John S Bennett
- Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77840, USA
| | - Justin S Bae
- Boyce Thompson Institute, 533 Tower Road, Ithaca, NY, 14853, USA
| | - Dean K Kim
- Boyce Thompson Institute, 533 Tower Road, Ithaca, NY, 14853, USA
| | | | - Michael V Kolomiets
- Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, 77840, USA
| | - Eric A Schmelz
- Section of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA, 92093, USA
| | | | - Edward S Buckler
- Plant Breeding and Genetics Section, Cornell University, Ithaca, NY, 14853, USA
- United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY, 14853, USA
| | - Georg Jander
- Boyce Thompson Institute, 533 Tower Road, Ithaca, NY, 14853, USA
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Vanous A, Gardner C, Blanco M, Martin-Schwarze A, Wang J, Li X, Lipka AE, Flint-Garcia S, Bohn M, Edwards J, Lübberstedt T. Stability Analysis of Kernel Quality Traits in Exotic-Derived Doubled Haploid Maize Lines. THE PLANT GENOME 2019; 12. [PMID: 30951103 DOI: 10.3835/plantgenome2017.12.0114] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Variation in kernel composition across maize ( L.) germplasm is affected by a combination of the plant's genotype, the environment in which it is grown, and the interaction between these two elements. Adapting exotic germplasm to the US Corn Belt is highly dependent on the plant's genotype, the environment where it is grown, and the interaction between these components. Phenotypic plasticity is ill-defined when specific exotic germplasm is moved over large latitudinal distances and for the adapted variants being created. Reduced plasticity (or stability) is desired for the adapted variants, as it allows for a more rapid implementation into breeding programs throughout the Corn Belt. Here, doubled haploid lines derived from exotic maize and adapted through backcrossing exotic germplasm to elite adapted lines were used in conjunction with genome-wide association studies to explore stability in four kernel composition traits. Genotypes demonstrated a response to environments that paralleled the mean response of all genotypes used across all traits, with protein content and kernel density exhibiting the highest levels of Type II stability. Genes such as , , and were identified as potential candidates within quantitative trait locus regions. The findings within this study aid in validating previously identified genomic regions and identified novel genomic regions affecting kernel quality traits.
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A Very Oil Yellow1 Modifier of the Oil Yellow1-N1989 Allele Uncovers a Cryptic Phenotypic Impact of Cis-regulatory Variation in Maize. G3-GENES GENOMES GENETICS 2019; 9:375-390. [PMID: 30518539 PMCID: PMC6385977 DOI: 10.1534/g3.118.200798] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Forward genetics determines the function of genes underlying trait variation by identifying the change in DNA responsible for changes in phenotype. Detecting phenotypically-relevant variation outside protein coding sequences and distinguishing this from neutral variants is not trivial; partly because the mechanisms by which DNA polymorphisms in the intergenic regions affect gene regulation are poorly understood. Here we utilized a dominant genetic reporter to investigate the effect of cis and trans-acting regulatory variation. We performed a forward genetic screen for natural variation that suppressed or enhanced the semi-dominant mutant allele Oy1-N1989, encoding the magnesium chelatase subunit I of maize. This mutant permits rapid phenotyping of leaf color as a reporter for chlorophyll accumulation, and mapping of natural variation in maize affecting chlorophyll metabolism. We identified a single modifier locus segregating between B73 and Mo17 that was linked to the reporter gene itself, which we call very oil yellow1 (vey1). Based on the variation in OY1 transcript abundance and genome-wide association data, vey1 is predicted to consist of multiple cis-acting regulatory sequence polymorphisms encoded at the wild-type oy1 alleles. The vey1 locus appears to be a common polymorphism in the maize germplasm that alters the expression level of a key gene in chlorophyll biosynthesis. These vey1 alleles have no discernable impact on leaf chlorophyll in the absence of the Oy1-N1989 reporter. Thus, the use of a mutant as a reporter for magnesium chelatase activity resulted in the detection of expression-level polymorphisms not readily visible in the laboratory.
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46
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Discovery of Anthocyanin Acyltransferase1 (AAT1) in Maize Using Genotyping-by-Sequencing (GBS). G3-GENES GENOMES GENETICS 2018; 8:3669-3678. [PMID: 30257861 PMCID: PMC6222571 DOI: 10.1534/g3.118.200630] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The reduced acylation phenotype describes the inability of certain accessions of maize (Zea mays [L.]) to produce significant amounts of acylated anthocyanins, which are typically the most abundant pigments. Acylated anthocyanins are important for their association with stability and are therefore important for the various industries using anthocyanins as natural colorants to replace synthetic dyes. Many anthocyanin acyltransferases have been characterized in other species; however, no anthocyanin acyltransferases have been characterized in maize. Therefore, a mapping population was developed from a cross between mutant stock 707G and wild-type acylation line B73 to identify the locus associated with the reduced acylation trait. High-performance liquid chromatography was used to assay the pigment content and composition of 129 F2 lines generated in the mapping population. Recessive alleles of Colorless1, Colored1, and the reduced acylation mutant all decreased anthocyanin content while Intensifier1 increased anthocyanin content in aleurone tissue. The association of increased proportions of acylation with increased anthocyanin content indicates acylation may be important for increasing the stability of anthocyanins in vivo. Genotyping-by-sequencing was used to create SNP markers to map the reduced acylation locus. In the QTL analysis, a segment of Chromosome 1 containing transferase family protein GRMZM2G387394 was found to be significant. A UniformMu Mu transposon knockout of GRMZM2G387394 demonstrated this gene has anthocyanidin malonyltransferase activity and will therefore be named Anthocyanin Acyltransferase1 (AAT1). AAT1 is the first anthocyanin acyltransferase characterized in a monocot species and will increase our knowledge of all acyltransferase family members.
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Empirical Comparisons of Different Statistical Models To Identify and Validate Kernel Row Number-Associated Variants from Structured Multi-parent Mapping Populations of Maize. G3-GENES GENOMES GENETICS 2018; 8:3567-3575. [PMID: 30213868 PMCID: PMC6222574 DOI: 10.1534/g3.118.200636] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Advances in next generation sequencing technologies and statistical approaches enable genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS). Although multiple statistical approaches for conducting GWAS are available, the power and cross-validation rates of many approaches have been mostly tested using simulated data. Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have not been conducted to test if a single approach or a combination of SV and MV is effective, through identification and cross-validation of trait-associated loci. In this study, kernel row number (KRN) data were collected from a set of 6,230 entries derived from the Nested Association Mapping (NAM) population and related populations. Three different types of GWAS analyses were performed: 1) single-variant (SV), 2) stepwise regression (STR) and 3) a Bayesian-based multi-variant (BMV) model. Using SV, STR, and BMV models, 257, 300, and 442 KRN-associated variants (KAVs) were identified in the initial GWAS analyses. Of these, 231 KAVs were subjected to genetic validation using three unrelated populations that were not included in the initial GWAS. Genetic validation results suggest that the three GWAS approaches are complementary. Interestingly, KAVs in low recombination regions were more likely to exhibit associations in independent populations than KAVs in recombinationally active regions, probably as a consequence of linkage disequilibrium. The KAVs identified in this study have the potential to enhance our understanding of the genetic basis of ear development.
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Liu S, Schnable JC, Ott A, Yeh CTE, Springer NM, Yu J, Muehlbauer G, Timmermans MCP, Scanlon MJ, Schnable PS. Intragenic Meiotic Crossovers Generate Novel Alleles with Transgressive Expression Levels. Mol Biol Evol 2018; 35:2762-2772. [PMID: 30184112 PMCID: PMC6231493 DOI: 10.1093/molbev/msy174] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Meiotic recombination is an evolutionary force that generates new genetic diversity upon which selection can act. Whereas multiple studies have assessed genome-wide patterns of recombination and specific cases of intragenic recombination, few studies have assessed intragenic recombination genome-wide in higher eukaryotes. We identified recombination events within or near genes in a population of maize recombinant inbred lines (RILs) using RNA-sequencing data. Our results are consistent with case studies that have shown that intragenic crossovers cluster at the 5′ ends of some genes. Further, we identified cases of intragenic crossovers that generate transgressive transcript accumulation patterns, that is, recombinant alleles displayed higher or lower levels of expression than did nonrecombinant alleles in any of ∼100 RILs, implicating intragenic recombination in the generation of new variants upon which selection can act. Thousands of apparent gene conversion events were identified, allowing us to estimate the genome-wide rate of gene conversion at SNP sites (4.9 × 10−5). The density of syntenic genes (i.e., those conserved at the same genomic locations since the divergence of maize and sorghum) exhibits a substantial correlation with crossover frequency, whereas the density of nonsyntenic genes (i.e., those which have transposed or been lost subsequent to the divergence of maize and sorghum) shows little correlation, suggesting that crossovers occur at higher rates in syntenic genes than in nonsyntenic genes. Increased rates of crossovers in syntenic genes could be either a consequence of the evolutionary conservation of synteny or a biological process that helps to maintain synteny.
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Affiliation(s)
- Sanzhen Liu
- Department of Plant Pathology, Kansas State University, Manhattan, KS.,Department of Agronomy, Iowa State University, Ames, IA
| | - James C Schnable
- Department of Agriculture and Horticulture, University of Nebraska-Lincoln, Lincoln, NE
| | - Alina Ott
- Department of Agronomy, Iowa State University, Ames, IA.,Roche Sequencing Solutions, 500 S Rosa Road, Madison, WI
| | | | - Nathan M Springer
- Department of Plant and Microbial Biology, Microbial and Plant Genomics Institute, University of Minnesota, Saint Paul, MN
| | - Jianming Yu
- Department of Agronomy, Iowa State University, Ames, IA
| | - Gary Muehlbauer
- Department of Agronomy and Plant Genetics, Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN
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Zhang M, Liu YH, Chang CS, Zhi H, Wang S, Xu W, Smith CW, Zhang HB. Quantification of gene expression while taking into account RNA alternative splicing. Genomics 2018; 111:1517-1528. [PMID: 30366041 DOI: 10.1016/j.ygeno.2018.10.009] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 10/16/2018] [Indexed: 01/05/2023]
Abstract
Gene expression has been widely used in functional genomics research; however, the gene expressions quantified with different methods have been frequently inconsistent, thus challenging the conclusions from such research. Here we have addressed this issue, while taking into account RNA alternative splicing. We found that when a gene was subjected to RNA alternative splicing, it was impossible or difficult to properly quantify the expression of a transcript of the gene or its overall expression using quantitative real-time PCR (qPCR), Northern hybridization, microarray, or serial analysis of gene expression. Shot-gun RNA-seq was the most proper to quantify the expression of a transcript or a gene in such cases. Moreover, the expressions of individual transcripts quantified by shot-gun RNA-seq were highly reproducible (r = 0.90-0.98) between individuals. Therefore, shot-gun or full-length RNA-seq should be the method of choice to properly quantify the expression of a transcript or a gene.
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Affiliation(s)
- Meiping Zhang
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, United States.
| | - Yun-Hua Liu
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, United States.
| | - Chih-Sheng Chang
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, United States
| | - Hui Zhi
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, United States
| | - Shichen Wang
- Genomics and Bioinformatics Service, Texas A&M AgriLife Research, College Station, TX, 77845, United States.
| | - Wenwei Xu
- Department of Soil and Crop Sciences, Texas A&M AgriLife Research, Lubbock, TX 79403, United States.
| | - C Wayne Smith
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, United States.
| | - Hong-Bin Zhang
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, United States.
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Cui Z, Xia A, Zhang A, Luo J, Yang X, Zhang L, Ruan Y, He Y. Linkage mapping combined with association analysis reveals QTL and candidate genes for three husk traits in maize. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:2131-2144. [PMID: 30043259 DOI: 10.1007/s00122-018-3142-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Accepted: 06/28/2018] [Indexed: 06/08/2023]
Abstract
Key message Combined linkage and association mapping analyses facilitate the emphasis on the candidate genes putatively involved in maize husk growth. The maize (Zea mays L.) husk consists of multiple leafy layers and plays important roles in protecting the ear from pathogen infection and in preventing grain dehydration. Although husk morphology varies widely among different maize inbred lines, the genetic basis of such variation is poorly understood. In this study, we used three maize recombinant inbred line (RIL) populations to dissect the genetic basis of three husk traits: i.e., husk length (HL), husk width (HW), and the number of husk layers (HN). Three husk traits in all three RIL populations showed wide phenotypic variation and high heritability. The HL showed stronger correlations with ear traits than did HW and HN. A total of 21 quantitative trait loci (QTL) were identified for the three traits in three RIL populations, and some of them were commonly observed for the same trait in different populations. The proportions of total phenotypic variation explained by QTL in three RIL populations were 31.8, 35.3, and 44.5% for HL, HW, and HN, respectively. The highest proportions of phenotypic variation explained by a single QTL were 14.7% for HL in the By815/K22 RIL population (BYK), 13.5% for HW in the By815/DE3 RIL population (BYD), and 19.4% for HN in the BYD population. A combined analysis of linkage mapping with a previous genome-wide association study revealed five candidate genes related to husk morphology situated within three QTL loci. These five genes were related to metabolism, gene expression regulation, and signal transduction.
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Affiliation(s)
- Zhenhai Cui
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China
| | - Aiai Xia
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China
| | - Ao Zhang
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Jinhong Luo
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China
| | - Xiaohong Yang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China
| | - Lijun Zhang
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Yanye Ruan
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China.
| | - Yan He
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100094, China.
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