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Torres-Rodríguez JV, Li D, Turkus J, Newton L, Davis J, Lopez-Corona L, Ali W, Sun G, Mural RV, Grzybowski MW, Zamft BM, Thompson AM, Schnable JC. Population-level gene expression can repeatedly link genes to functions in maize. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024. [PMID: 38812347 DOI: 10.1111/tpj.16801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 04/16/2024] [Accepted: 04/24/2024] [Indexed: 05/31/2024]
Abstract
Transcriptome-wide association studies (TWAS) can provide single gene resolution for candidate genes in plants, complementing genome-wide association studies (GWAS) but efforts in plants have been met with, at best, mixed success. We generated expression data from 693 maize genotypes, measured in a common field experiment, sampled over a 2-h period to minimize diurnal and environmental effects, using full-length RNA-seq to maximize the accurate estimation of transcript abundance. TWAS could identify roughly 10 times as many genes likely to play a role in flowering time regulation as GWAS conducted data from the same experiment. TWAS using mature leaf tissue identified known true-positive flowering time genes known to act in the shoot apical meristem, and trait data from a new environment enabled the identification of additional flowering time genes without the need for new expression data. eQTL analysis of TWAS-tagged genes identified at least one additional known maize flowering time gene through trans-eQTL interactions. Collectively these results suggest the gene expression resource described here can link genes to functions across different plant phenotypes expressed in a range of tissues and scored in different experiments.
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Affiliation(s)
- J Vladimir Torres-Rodríguez
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
| | - Delin Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement, Key Laboratory of Crop Gene Resource and Germplasm Enhancement, Key Laboratory of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jonathan Turkus
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
| | - Linsey Newton
- Department of Plant Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan, 48824, USA
| | - Jensina Davis
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
| | - Lina Lopez-Corona
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
| | - Waqar Ali
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
| | - Guangchao Sun
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Advanced Diagnostic Laboratory, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Ravi V Mural
- Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, South Dakota, 57007, USA
| | - Marcin W Grzybowski
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Plant Molecular Ecophysiology, Institute of Plant Experimental Biology and Biotechnology, Faculty of Biology, University of Warsaw, Warsaw, Poland
| | - Bradley M Zamft
- X, The Moonshot Factory, Mountain View, California, 94043, USA
| | - Addie M Thompson
- Department of Plant Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan, 48824, USA
- Plant Resilience Institute, Michigan State University, East Lansing, Michigan, 48824, USA
| | - James C Schnable
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
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Xu L, Hao J, Lv M, Liu P, Ge Q, Zhang S, Yang J, Niu H, Wang Y, Xue Y, Lu X, Tang J, Zheng J, Gou M. A genome-wide association study identifies genes associated with cuticular wax metabolism in maize. PLANT PHYSIOLOGY 2024; 194:2616-2630. [PMID: 38206190 DOI: 10.1093/plphys/kiae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 11/20/2023] [Accepted: 12/11/2023] [Indexed: 01/12/2024]
Abstract
The plant cuticle is essential in plant defense against biotic and abiotic stresses. To systematically elucidate the genetic architecture of maize (Zea mays L.) cuticular wax metabolism, 2 cuticular wax-related traits, the chlorophyll extraction rate (CER) and water loss rate (WLR) of 389 maize inbred lines, were investigated and a genome-wide association study (GWAS) was performed using 1.25 million single nucleotide polymorphisms (SNPs). In total, 57 nonredundant quantitative trait loci (QTL) explaining 5.57% to 15.07% of the phenotypic variation for each QTL were identified. These QTLs contained 183 genes, among which 21 strong candidates were identified based on functional annotations and previous publications. Remarkably, 3 candidate genes that express differentially during cuticle development encode β-ketoacyl-CoA synthase (KCS). While ZmKCS19 was known to be involved in cuticle wax metabolism, ZmKCS12 and ZmKCS3 functions were not reported. The association between ZmKCS12 and WLR was confirmed by resequencing 106 inbred lines, and the variation of WLR was significant between different haplotypes of ZmKCS12. In this study, the loss-of-function mutant of ZmKCS12 exhibited wrinkled leaf morphology, altered wax crystal morphology, and decreased C32 wax monomer levels, causing an increased WLR and sensitivity to drought. These results confirm that ZmKCS12 plays a vital role in maize C32 wax monomer synthesis and is critical for drought tolerance. In sum, through GWAS of 2 cuticular wax-associated traits, this study reveals comprehensively the genetic architecture in maize cuticular wax metabolism and provides a valuable reference for the genetic improvement of stress tolerance in maize.
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Affiliation(s)
- Liping Xu
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
| | - Jiaxin Hao
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Mengfan Lv
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Peipei Liu
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Qidong Ge
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Sainan Zhang
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Jianping Yang
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Hongbin Niu
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Yiru Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yadong Xue
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
| | - Xiaoduo Lu
- Institute of Advanced Agricultural Technology, Qilu Normal University, Jinan 250200, China
| | - Jihua Tang
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
| | - Jun Zheng
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Mingyue Gou
- State Key Laboratory of Wheat and Maize Crops Science, Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
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Gomez-Cano F, Rodriguez J, Zhou P, Chu YH, Magnusson E, Gomez-Cano L, Krishnan A, Springer NM, de Leon N, Grotewold E. Prioritizing Metabolic Gene Regulators through Multi-Omic Network Integration in Maize. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.26.582075. [PMID: 38464086 PMCID: PMC10925184 DOI: 10.1101/2024.02.26.582075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Elucidating gene regulatory networks (GRNs) is a major area of study within plant systems biology. Phenotypic traits are intricately linked to specific gene expression profiles. These expression patterns arise primarily from regulatory connections between sets of transcription factors (TFs) and their target genes. In this study, we integrated publicly available co-expression networks derived from more than 6,000 RNA-seq samples, 283 protein-DNA interaction assays, and 16 million of SNPs used to identify expression quantitative loci (eQTL), to construct TF-target networks. In total, we analyzed ~4.6M interactions to generate four distinct types of TF-target networks: co-expression, protein-DNA interaction (PDI), trans-expression quantitative loci (trans-eQTL), and cis-eQTL combined with PDIs. To improve the functional annotation of TFs based on its target genes, we implemented three different strategies to integrate these four types of networks. We subsequently evaluated the effectiveness of our method through loss-of function mutant and random networks. The multi-network integration allowed us to identify transcriptional regulators of hormone-, metabolic- and development-related processes. Finally, using the topological properties of the fully integrated network, we identified potentially functional redundant TF paralogs. Our findings retrieved functions previously documented for numerous TFs and revealed novel functions that are crucial for informing the design of future experiments. The approach here-described lays the foundation for the integration of multi-omic datasets in maize and other plant systems.
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Affiliation(s)
- Fabio Gomez-Cano
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824-6473, USA
- Current address: Department of Molecular, Cellular, and Development Biology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jonas Rodriguez
- Department of Plant and Agroecosystem Sciences, University of Wisconsin Madison, Madison, WI 53706, USA
| | - Peng Zhou
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN 55108
| | - Yi-Hsuan Chu
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824-6473, USA
| | - Erika Magnusson
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN 55108
| | - Lina Gomez-Cano
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824-6473, USA
| | - Arjun Krishnan
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN 55108
- Current address: Global Breeding, Bayer Crop Sciences, Chesterfield MO 63017, USA
| | - Natalia de Leon
- Department of Plant and Agroecosystem Sciences, University of Wisconsin Madison, Madison, WI 53706, USA
| | - Erich Grotewold
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824-6473, USA
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Sahito JH, Zhang H, Gishkori ZGN, Ma C, Wang Z, Ding D, Zhang X, Tang J. Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize. Int J Mol Sci 2024; 25:1918. [PMID: 38339196 PMCID: PMC10855973 DOI: 10.3390/ijms25031918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/30/2024] [Accepted: 02/02/2024] [Indexed: 02/12/2024] Open
Abstract
Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.
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Affiliation(s)
- Javed Hussain Sahito
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Hao Zhang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Zeeshan Ghulam Nabi Gishkori
- Institute of Biotechnology, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China
| | - Chenhui Ma
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Zhihao Wang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Dong Ding
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Xuehai Zhang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
| | - Jihua Tang
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou 450002, China
- The Shennong Laboratory, Zhengzhou 450002, China
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5
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Sudhabose S, Sooryakanth B, Rajan MR. Acute Toxicity, Hematological Profile, and Histopathological Effects of MgO Nanoparticles on Gills, Muscle, Liver of Mrigal, Cirrhinus mrigala. Biol Trace Elem Res 2024; 202:736-742. [PMID: 37231319 DOI: 10.1007/s12011-023-03704-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 05/13/2023] [Indexed: 05/27/2023]
Abstract
Nanotechnology is an advancing and emerging field of all environmental, medical, and industrial applications. Magnesium oxide nanoparticles have been widely used in medicine, consumer products, industrial products, textiles, ceramics, alleviation of heartburn, stomach ulcers, and bone regeneration. In the present study, acute toxicity (LC50) of MgO nanoparticles and hematological and histopathological changes in Cirrhinus mrigala was analyzed. The lethal concentration for 50% of MgO nanoparticles was 4.2321 mg/L. Hematological parameters such as white blood cells, red blood cells, hematocrit, hemoglobin, platelets, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration, as well as histopathological abnormalities in gills, muscle, and liver were observed on the 7th and 14th days of exposure. The WBC, RBC, HCT, Hb, and platelets count increased on the 14th day of exposure compared to the control and 7th day of exposure. The MCV, MCH, and MCHC levels decreased on the 7th day of exposure compared to the control and increased on the 14th day. Histopathological changes of MgO nanoparticles in gills, muscle, and liver highly damaged in the quantity of 3.6 mg/L compared to 12 mg/L on 7th and 14th days of exposure. This study finds the level of exposure in hematology and histopathological changes in tissues in relation to the exposure of MgO NPs.
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Affiliation(s)
- Shanmugam Sudhabose
- Department of Biology, The Gandhigram Rural Institute (Deemed to Be University), Dindigul District, Gandhigram, 624302, Tamil Nadu, India
| | - Balakrishnan Sooryakanth
- Department of Biology, The Gandhigram Rural Institute (Deemed to Be University), Dindigul District, Gandhigram, 624302, Tamil Nadu, India
| | - Muthuswami Ruby Rajan
- Department of Biology, The Gandhigram Rural Institute (Deemed to Be University), Dindigul District, Gandhigram, 624302, Tamil Nadu, India.
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Yanarella CF, Fattel L, Kristmundsdóttir ÁÝ, Lopez MD, Edwards JW, Campbell DA, Abel CA, Lawrence-Dill CJ. Wisconsin diversity panel phenotypes: spoken descriptions of plants and supporting data. BMC Res Notes 2024; 17:33. [PMID: 38263080 PMCID: PMC10807131 DOI: 10.1186/s13104-024-06694-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/11/2024] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVES Phenotyping plants in a field environment can involve a variety of methods including the use of automated instruments and labor-intensive manual measurement and scoring. Researchers also collect language-based phenotypic descriptions and use controlled vocabularies and structures such as ontologies to enable computation on descriptive phenotype data, including methods to determine phenotypic similarities. In this study, spoken descriptions of plants were collected and observers were instructed to use their own vocabulary to describe plant features that were present and visible. Further, these plants were measured and scored manually as part of a larger study to investigate whether spoken plant descriptions can be used to recover known biological phenomena. DATA DESCRIPTION Data comprise phenotypic observations of 686 accessions of the maize Wisconsin Diversity panel, and 25 positive control accessions that carry visible, dramatic phenotypes. The data include the list of accessions planted, field layout, data collection procedures, student participants' (whose personal data are protected for ethical reasons) and volunteers' observation transcripts, volunteers' audio data files, terrestrial and aerial images of the plants, Amazon Web Services method selection experimental data, and manually collected phenotypes (e.g., plant height, ear and tassel features, etc.; measurements and scores). Data were collected during the summer of 2021 at Iowa State University's Agricultural Engineering and Agronomy Research Farms.
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Schoemaker DL, Qiu Y, de Leon N, Hirsch CN, Kaeppler SM. Genetic analysis of pericarp pigmentation variation in Corn Belt dent maize. G3 (BETHESDA, MD.) 2023; 14:jkad256. [PMID: 37950891 PMCID: PMC10755172 DOI: 10.1093/g3journal/jkad256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/27/2023] [Accepted: 11/01/2023] [Indexed: 11/13/2023]
Abstract
The US standard for maize commercially grown for grain specifies that yellow corn can contain at maximum 5% corn of other colors. Inbred parents of commercial hybrids typically have clear pericarp, but transgressive segregants in breeding populations can display variation in pericarp pigmentation. We identified 10 doubled haploid biparental populations segregating for pigmented pericarp and evaluated qualitative genetic models using chi-square tests of observed and expected frequencies. Pigmentation ranged from light to dark brown color, and pigmentation intensity was quantitatively measured across 1,327 inbred lines using hue calculated from RGB pixel values. Genetic mapping was used to identify loci associated with pigmentation intensity. For 9 populations, pigmentation inheritance best fit a hypothesis of a 2- or 3-gene epistatic model. Significant differences in pigment intensity were observed across populations. W606S-derived inbred lines with the darkest pericarp often had clear glumes, suggesting the presence of a novel P1-rw allele, a hypothesis supported by a significant quantitative trait locus peak at P1. A separate quantitative trait locus region on chromosome 2 between 221.64 and 226.66 Mbp was identified in LH82-derived populations, and the peak near p1 was absent. A genome-wide association study using 416 inbred lines from the Wisconsin Diversity panel with full genome resequencing revealed 4 significant associations including the region near P1. This study supports that pericarp pigmentation among dent maize inbreds can arise by transgressive segregation when pigmentation in the parental generation is absent and is partially explained by functional allelic variation at the P1 locus.
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Affiliation(s)
- Dylan L Schoemaker
- Department of Plant and Agroecosystem Sciences, University of Wisconsin—Madison, Madison, WI 53706, USA
| | - Yinjie Qiu
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA
| | - Natalia de Leon
- Department of Plant and Agroecosystem Sciences, University of Wisconsin—Madison, Madison, WI 53706, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Shawn M Kaeppler
- Department of Plant and Agroecosystem Sciences, University of Wisconsin—Madison, Madison, WI 53706, USA
- Wisconsin Crop Innovation Center, University of Wisconsin—Madison, Middleton, WI 53562, USA
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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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Yu J, Song G, Guo W, Le L, Xu F, Wang T, Wang F, Wu Y, Gu X, Pu L. ZmBELL10 interacts with other ZmBELLs and recognizes specific motifs for transcriptional activation to modulate internode patterning in maize. THE NEW PHYTOLOGIST 2023; 240:577-596. [PMID: 37583092 DOI: 10.1111/nph.19192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 07/15/2023] [Indexed: 08/17/2023]
Abstract
Plant height is an important agronomic trait that affects crop yield. Elucidating the molecular mechanism underlying plant height regulation is also an important question in developmental biology. Here, we report that a BELL transcription factor, ZmBELL10, positively regulates plant height in maize (Zea mays). Loss of ZmBELL10 function resulted in shorter internodes, fewer nodes, and smaller kernels, while ZmBELL10 overexpression increased plant height and hundred-kernel weight. Transcriptome analysis and chromatin immunoprecipitation followed by sequencing showed that ZmBELL10 recognizes specific sequences in the promoter of its target genes and activates cell division- and cell elongation-related gene expression, thereby influencing node number and internode length in maize. ZmBELL10 interacted with several other ZmBELL proteins via a spatial structure in its POX domain to form protein complexes involving ZmBELL10. All interacting proteins recognized the same DNA sequences, and their interaction with ZmBELL10 increased target gene expression. We identified the key residues in the POX domain of ZmBELL10 responsible for its protein-protein interactions, but these residues did not affect its transactivation activity. Collectively, our findings shed light on the functions of ZmBELL10 protein complexes and provide potential targets for improving plant architecture and yield in maize.
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Affiliation(s)
- Jia Yu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Guangshu Song
- Maize Research Institute, Jilin Academy of Agricultural Sciences, Gongzhuling, 136100, China
| | - Weijun Guo
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Liang Le
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Fan Xu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Ting Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Shangrao Normal University, Shangrao, 334001, China
| | - Fanhua Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yue Wu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xiaofeng Gu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Li Pu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
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10
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Karnatam KS, Mythri B, Un Nisa W, Sharma H, Meena TK, Rana P, Vikal Y, Gowda M, Dhillon BS, Sandhu S. Silage maize as a potent candidate for sustainable animal husbandry development-perspectives and strategies for genetic enhancement. Front Genet 2023; 14:1150132. [PMID: 37303948 PMCID: PMC10250641 DOI: 10.3389/fgene.2023.1150132] [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: 01/23/2023] [Accepted: 05/09/2023] [Indexed: 06/13/2023] Open
Abstract
Maize is recognized as the queen of cereals, with an ability to adapt to diverse agroecologies (from 58oN to 55oS latitude) and the highest genetic yield potential among cereals. Under contemporary conditions of global climate change, C4 maize crops offer resilience and sustainability to ensure food, nutritional security, and farmer livelihood. In the northwestern plains of India, maize is an important alternative to paddy for crop diversification in the wake of depleting water resources, reduced farm diversity, nutrient mining, and environmental pollution due to paddy straw burning. Owing to its quick growth, high biomass, good palatability, and absence of anti-nutritional components, maize is also one of the most nutritious non-legume green fodders. It is a high-energy, low-protein forage commonly used for dairy animals like cows and buffalos, often in combination with a complementary high-protein forage such as alfalfa. Maize is also preferred for silage over other fodders due to its softness, high starch content, and sufficient soluble sugars required for proper ensiling. With a rapid population increase in developing countries like China and India, there is an upsurge in meat consumption and, hence, the requirement for animal feed, which entails high usage of maize. The global maize silage market is projected to grow at a compound annual growth rate of 7.84% from 2021 to 2030. Factors such as increasing demand for sustainable and environment-friendly food sources coupled with rising health awareness are fueling this growth. With the dairy sector growing at about 4%-5% and the increasing shortage faced for fodder, demand for silage maize is expected to increase worldwide. The progress in improved mechanization for the provision of silage maize, reduced labor demand, lack of moisture-related marketing issues as associated with grain maize, early vacancy of farms for next crops, and easy and economical form of feed to sustain household dairy sector make maize silage a profitable venture. However, sustaining the profitability of this enterprise requires the development of hybrids specific for silage production. Little attention has yet been paid to breeding for a plant ideotype for silage with specific consideration of traits such as dry matter yield, nutrient yield, energy in organic matter, genetic architecture of cell wall components determining their digestibility, stalk standability, maturity span, and losses during ensiling. This review explores the available information on the underlying genetic mechanisms and gene/gene families impacting silage yield and quality. The trade-offs between yield and nutritive value in relation to crop duration are also discussed. Based on available genetic information on inheritance and molecular aspects, breeding strategies are proposed to develop maize ideotypes for silage for the development of sustainable animal husbandry.
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Affiliation(s)
- Krishna Sai Karnatam
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Bikkasani Mythri
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Wajhat Un Nisa
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Heena Sharma
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Tarun Kumar Meena
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Prabhat Rana
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Yogesh Vikal
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - M. Gowda
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Baldev Singh Dhillon
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Surinder Sandhu
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
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11
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Wang Y, Bi Y, Jiang F, Shaw RK, Sun J, Hu C, Guo R, Fan X. Mapping and Functional Analysis of QTL for Kernel Number per Row in Tropical and Temperate-Tropical Introgression Lines of Maize ( Zea mays L.). Curr Issues Mol Biol 2023; 45:4416-4430. [PMID: 37232750 DOI: 10.3390/cimb45050281] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 05/10/2023] [Accepted: 05/16/2023] [Indexed: 05/27/2023] Open
Abstract
Kernel number per row (KNR) is an essential component of maize (Zea mays L.) grain yield (GY), and understanding its genetic mechanism is crucial to improve GY. In this study, two F7 recombinant inbred line (RIL) populations were created using a temperate-tropical introgression line TML418 and a tropical inbred line CML312 as female parents and a backbone maize inbred line Ye107 as the common male parent. Bi-parental quantitative trait locus (QTL) mapping and genome-wide association analysis (GWAS) were then performed on 399 lines of the two maize RIL populations for KNR in two different environments using 4118 validated single nucleotide polymorphism (SNP) markers. This study aimed to: (1) detect molecular markers and/or the genomic regions associated with KNR; (2) identify the candidate genes controlling KNR; and (3) analyze whether the candidate genes are useful in improving GY. The authors reported a total of 7 QTLs tightly linked to KNR through bi-parental QTL mapping and identified 21 SNPs significantly associated with KNR through GWAS. Among these, a highly confident locus qKNR7-1 was detected at two locations, Dehong and Baoshan, with both mapping approaches. At this locus, three novel candidate genes (Zm00001d022202, Zm00001d022168, Zm00001d022169) were identified to be associated with KNR. These candidate genes were primarily involved in the processes related to compound metabolism, biosynthesis, protein modification, degradation, and denaturation, all of which were related to the inflorescence development affecting KNR. These three candidate genes were not reported previously and are considered new candidate genes for KNR. The progeny of the hybrid Ye107 × TML418 exhibited strong heterosis for KNR, which the authors believe might be related to qKNR7-1. This study provides a theoretical foundation for future research on the genetic mechanism underlying KNR in maize and the use of heterotic patterns to develop high-yielding hybrids.
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Affiliation(s)
- Yuling Wang
- Institute of Resource Plants, Yunnan University, Kunming 650504, China
| | - Yaqi Bi
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Fuyan Jiang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Ranjan Kumar Shaw
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Jiachen Sun
- College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650500, China
| | - Can Hu
- Institute of Resource Plants, Yunnan University, Kunming 650504, China
| | - Ruijia Guo
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
| | - Xingming Fan
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China
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12
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Wijewardane NK, Zhang H, Yang J, Schnable JC, Schachtman DP, Ge Y. A leaf-level spectral library to support high throughput plant phenotyping: Predictive accuracy and model transfer. JOURNAL OF EXPERIMENTAL BOTANY 2023:erad129. [PMID: 37018460 PMCID: PMC10400152 DOI: 10.1093/jxb/erad129] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Indexed: 06/19/2023]
Abstract
Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of plant leaf traits due to its rapid, low-cost, multi-sensing, and non-destructive nature. However, collecting samples for model calibration can still be expensive; and models show poor transferability among different datasets. This study had three specific objectives: (i) assemble a large library of leaf hyperspectral data (n=2460) from maize and sorghum, (ii) evaluate two machine-learning approaches to estimate nine leaf properties (chlorophyll, thickness, water content, nitrogen, phosphorus, potassium, calcium, magnesium, and sulfur), and (iii) investigate the usefulness of this spectral library for predicting external datasets (n=445) including soybean and camelina using extra-weighted spiking. Internal cross-validation showed satisfactory performance of the spectral library to estimate all nine traits (average R 2 0.688), with Partial Least Squares Regression outperforming Deep Neural Network models. Models calibrated solely using the spectral library showed degraded performance on external datasets (average R 2 0.159 for camelina, 0.337 for soybean). Models improved significantly when a small portion of external samples (n=20) was added to the library via extra-weighted spiking (average R 2 0.574 for camelina, 0.536 for soybean). The leaf-level spectral library greatly benefits plant physiological and biochemical phenotyping; whereas extra-weight spiking improves model transferability and extends its utility.
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Affiliation(s)
- Nuwan K Wijewardane
- Department of Agricultural and Biological Engineering, Mississippi State University, Starkville, MS, USA
| | - Huichun Zhang
- College of Mechanical and Electrical Engineering, Nanjing Forestry University, China
- Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing, China
| | - Jinliang Yang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - James C Schnable
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Daniel P Schachtman
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Yufeng Ge
- Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE, USA
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13
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Grzybowski MW, Mural RV, Xu G, Turkus J, Yang J, Schnable JC. A common resequencing-based genetic marker data set for global maize diversity. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 113:1109-1121. [PMID: 36705476 DOI: 10.1111/tpj.16123] [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: 10/28/2022] [Revised: 01/20/2023] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
Maize (Zea mays ssp. mays) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole-genome resequencing strategies, identifying millions of segregating single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high-confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering-time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.
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Affiliation(s)
- Marcin W Grzybowski
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Plant Molecular Ecophysiology, Institute of Plant Experimental Biology and Biotechnology, Faculty of Biology, University of Warsaw, Warsaw, Poland
| | - Ravi V Mural
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Gen Xu
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Jonathan Turkus
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Jinliang Yang
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - James C Schnable
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
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14
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Genetic structure and molecular mechanism underlying the stalk lodging traits in maize ( Zea mays L.). Comput Struct Biotechnol J 2022; 21:485-494. [PMID: 36618981 PMCID: PMC9803694 DOI: 10.1016/j.csbj.2022.12.037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 12/03/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
Stalk lodging seriously affects yield and quality of crops, and it can be caused by several factors, such as environments, developmental stages, and internal chemical components of plant stalks. Breeding of stalk lodging-resistant varieties is thus an important task for maize breeders. To better understand the genetic basis underlying stalk lodging resistance, several methods such as quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) have been used to mine potential gene resources. Based on different types of genetic populations and mapping methods, many significant loci associated with stalk lodging resistance have been identified so far. However, few work has been performed to compare and integrate these reported genetic loci. In this study, we first collected hundreds of QTLs and quantitative trait nucleotides (QTNs) related to stalk lodging traits in maize. Then we mapped and integrated the QTLs and QTNs in maize genome to identify overlapped hotspot regions. Based on the genomic confidence intervals harboring these overlapped hotspot regions, we predicted candidate genes related to stalk lodging traits. Meanwhile, we mapped reported genes to these hotspot regions. Finally, we constructed molecular regulatory networks underlying stalk lodging resistance in maize. Collectively, this study provides not only useful genetic loci for deeply exploring molecular mechanisms of stalk lodging resistance traits, but also potential candidate genes and targeted strategies for improving stalk lodging resistance to increase crop yields in future.
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15
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Wu S, Wang J, Zhao Y, Wen W, Zhang Y, Lu X, Wang C, Liu K, Chen B, Guo X, Zhao C. Characterization and genetic dissection of maize ear leaf midrib acquired by 3D digital technology. FRONTIERS IN PLANT SCIENCE 2022; 13:1063056. [PMID: 36531364 PMCID: PMC9754214 DOI: 10.3389/fpls.2022.1063056] [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: 10/06/2022] [Accepted: 11/11/2022] [Indexed: 06/17/2023]
Abstract
The spatial morphological structure of plant leaves is an important index to evaluate crop ideotype. In this study, we characterized the three-dimensional (3D) data of the ear leaf midrib of maize at the grain-filling stage using the 3D digitization technology and obtained the phenotypic values of 15 traits covering four different dimensions of the ear leaf midrib, of which 13 phenotypic traits were firstly proposed for featuring plant leaf spatial structure. Cluster analysis results showed that the 13 traits could be divided into four groups, Group I, -II, -III and -IV. Group I contains HorizontalLength, OutwardGrowthMeasure, LeafAngle and DeviationTip; Group II contains DeviationAngle, MaxCurvature and CurvaturePos; Group III contains LeafLength and ProjectionArea; Group IV contains TipTop, VerticalHeight, UpwardGrowthMeasure, and CurvatureRatio. To investigate the genetic basis of the ear leaf midrib curve, 13 traits with high repeatability were subjected to genome-wide association study (GWAS) analysis. A total of 828 significantly related SNPs were identified and 1365 candidate genes were annotated. Among these, 29 candidate genes with the highest significant and multi-method validation were regarded as the key findings. In addition, pathway enrichment analysis was performed on the candidate genes of traits to explore the potential genetic mechanism of leaf midrib curve phenotype formation. These results not only contribute to further understanding of maize leaf spatial structure traits but also provide new genetic loci for maize leaf spatial structure to improve the plant type of maize varieties.
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Affiliation(s)
- Sheng Wu
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Jinglu Wang
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Yanxin Zhao
- Beijing Key Laboratory of Maize DNA (DeoxyriboNucleic Acid) Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Weiliang Wen
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Ying Zhang
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Xianju Lu
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Chuanyu Wang
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Kai Liu
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Bo Chen
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Xinyu Guo
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
| | - Chunjiang Zhao
- Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing, China
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16
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Lopez-Marnet PL, Guillaume S, Méchin V, Reymond M. A robust and efficient automatic method to segment maize FASGA stained stem cross section images to accurately quantify histological profile. PLANT METHODS 2022; 18:125. [PMID: 36424625 PMCID: PMC9694518 DOI: 10.1186/s13007-022-00957-0] [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: 07/01/2022] [Accepted: 11/11/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Grasses internodes are made of distinct tissues such as vascular bundles, epidermis, rind and pith. The histology of grasses stem was largely revisited recently taking advantage of the development of microscopy combined with the development of computer-automated image analysis workflows. However, the diversity and complexity of the histological profile complicates quantification. Accurate and automated analysis of histological images thus remains challenging. RESULTS Herein, we present a workflow that automatically segments maize internode cross section images into 40 distinct tissues: two tissues in the epidermis, 19 tissues in the rind, 14 tissues in the pith and 5 tissues in the bundles. This level of segmentation is achieved by combining the Hue, Saturation and Value properties of each pixel and the location of each pixel in FASGA stained cross sectiona. This workflow is likewise able to highlight significant and subtle histological genotypic variations between maize internodes. The grain of precision provided by the workflow also makes it possible to demonstrate different levels of sensitivity to digestion by enzymatic cocktails of the tissues in the pith. The precision and strength of the workflow is all the more impressive because it is preserved on cross section images of other grasses such as miscanthus or sorghum. CONCLUSIONS The fidelity of this tool and its capacity to automatically identify variations of a large number of histological profiles among different genotypes pave the way for its use to identify genotypes of interest and to study the underlying genetic bases of variations in histological profiles in maize or other species.
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Affiliation(s)
- P.-L. Lopez-Marnet
- Université Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), 78000 Versailles, France
- Ecole Doctorale Numéro 581 : ABIES, AgroParisTech, Université Paris-Saclay, 19 Av du Maine, 75732 Paris Cedex 15, France
| | - S. Guillaume
- Université Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), 78000 Versailles, France
| | - V. Méchin
- Université Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), 78000 Versailles, France
| | - M. Reymond
- Université Paris-Saclay, INRAE, AgroParisTech, Institut Jean-Pierre Bourgin (IJPB), 78000 Versailles, France
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17
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Varela JI, Miller ND, Infante V, Kaeppler SM, de Leon N, Spalding EP. A novel high-throughput hyperspectral scanner and analytical methods for predicting maize kernel composition and physical traits. Food Chem 2022; 391:133264. [DOI: 10.1016/j.foodchem.2022.133264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 05/16/2022] [Accepted: 05/17/2022] [Indexed: 11/25/2022]
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18
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Zuffo LT, DeLima RO, Lübberstedt T. Combining datasets for maize root seedling traits increases the power of GWAS and genomic prediction accuracies. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:5460-5473. [PMID: 35608947 PMCID: PMC9467658 DOI: 10.1093/jxb/erac236] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 06/06/2022] [Indexed: 05/13/2023]
Abstract
The identification of genomic regions associated with root traits and the genomic prediction of untested genotypes can increase the rate of genetic gain in maize breeding programs targeting roots traits. Here, we combined two maize association panels with different genetic backgrounds to identify single nucleotide polymorphisms (SNPs) associated with root traits, and used a genome-wide association study (GWAS) and to assess the potential of genomic prediction for these traits in maize. For this, we evaluated 377 lines from the Ames panel and 302 from the Backcrossed Germplasm Enhancement of Maize (BGEM) panel in a combined panel of 679 lines. The lines were genotyped with 232 460 SNPs, and four root traits were collected from 14-day-old seedlings. We identified 30 SNPs significantly associated with root traits in the combined panel, whereas only two and six SNPs were detected in the Ames and BGEM panels, respectively. Those 38 SNPs were in linkage disequilibrium with 35 candidate genes. In addition, we found higher prediction accuracy in the combined panel than in the Ames or BGEM panel. We conclude that combining association panels appears to be a useful strategy to identify candidate genes associated with root traits in maize and improve the efficiency of genomic prediction.
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Affiliation(s)
- Leandro Tonello Zuffo
- Corteva Agriscience, Rio Verde, GO, Brazil
- Department of Agronomy, Universidade Federal de Viçosa, Viçosa, MG, Brazil
- Department of Agronomy, Iowa State University, Ames, IA, USA
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19
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Mural RV, Sun G, Grzybowski M, Tross MC, Jin H, Smith C, Newton L, Andorf CM, Woodhouse MR, Thompson AM, Sigmon B, Schnable JC. Association mapping across a multitude of traits collected in diverse environments in maize. Gigascience 2022; 11:6673780. [PMID: 35997208 PMCID: PMC9396454 DOI: 10.1093/gigascience/giac080] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 05/25/2022] [Indexed: 11/14/2022] Open
Abstract
Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data-18M markers-from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.
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Affiliation(s)
- Ravi V Mural
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.,Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Guangchao Sun
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.,Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Marcin Grzybowski
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.,Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Michael C Tross
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.,Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Hongyu Jin
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.,Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Christine Smith
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Linsey Newton
- Department of Plant Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Carson M Andorf
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, IA 50010, USA.,Department of Computer Science, Iowa State University, Ames, IA 50011, USA
| | | | - Addie M Thompson
- Department of Plant Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Brandi Sigmon
- Department of Plant Pathology, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - James C Schnable
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.,Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
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20
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Wang J, Wang C, Lu X, Zhang Y, Zhao Y, Wen W, Song W, Guo X. Dissecting the Genetic Structure of Maize Leaf Sheaths at Seedling Stage by Image-Based High-Throughput Phenotypic Acquisition and Characterization. FRONTIERS IN PLANT SCIENCE 2022; 13:826875. [PMID: 35837446 PMCID: PMC9274118 DOI: 10.3389/fpls.2022.826875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/17/2022] [Indexed: 06/15/2023]
Abstract
The rapid development of high-throughput phenotypic detection techniques makes it possible to obtain a large number of crop phenotypic information quickly, efficiently, and accurately. Among them, image-based phenotypic acquisition method has been widely used in crop phenotypic identification and characteristic research due to its characteristics of automation, non-invasive, non-destructive and high throughput. In this study, we proposed a method to define and analyze the traits related to leaf sheaths including morphology-related, color-related and biomass-related traits at V6 stage. Next, we analyzed the phenotypic variation of leaf sheaths of 418 maize inbred lines based on 87 leaf sheath-related phenotypic traits. In order to further analyze the mechanism of leaf sheath phenotype formation, 25 key traits (2 biomass-related, 19 morphology-related and 4 color-related traits) with heritability greater than 0.3 were analyzed by genome-wide association studies (GWAS). And 1816 candidate genes of 17 whole plant leaf sheath traits and 1,297 candidate genes of 8 sixth leaf sheath traits were obtained, respectively. Among them, 46 genes with clear functional descriptions were annotated by single nucleotide polymorphism (SNPs) that both Top1 and multi-method validated. Functional enrichment analysis results showed that candidate genes of leaf sheath traits were enriched into multiple pathways related to cellular component assembly and organization, cell proliferation and epidermal cell differentiation, and response to hunger, nutrition and extracellular stimulation. The results presented here are helpful to further understand phenotypic traits of maize leaf sheath and provide a reference for revealing the genetic mechanism of maize leaf sheath phenotype formation.
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Affiliation(s)
- Jinglu Wang
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Chuanyu Wang
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Xianju Lu
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Ying Zhang
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Yanxin Zhao
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Weiliang Wen
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Wei Song
- Key Laboratory of Crop Genetics and Breeding of Hebei Province, Institute of Cereal and Oil Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Xinyu Guo
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
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21
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Rodriguez J, Gomez-Cano L, Grotewold E, de Leon N. Normalizing and Correcting Variable and Complex LC-MS Metabolomic Data with the R Package pseudoDrift. Metabolites 2022; 12:435. [PMID: 35629939 PMCID: PMC9144304 DOI: 10.3390/metabo12050435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/09/2022] [Accepted: 05/10/2022] [Indexed: 01/27/2023] Open
Abstract
In biological research domains, liquid chromatography-mass spectroscopy (LC-MS) has prevailed as the preferred technique for generating high quality metabolomic data. However, even with advanced instrumentation and established data acquisition protocols, technical errors are still routinely encountered and can pose a significant challenge to unveiling biologically relevant information. In large-scale studies, signal drift and batch effects are how technical errors are most commonly manifested. We developed pseudoDrift, an R package with capabilities for data simulation and outlier detection, and a new training and testing approach that is implemented to capture and to optionally correct for technical errors in LC-MS metabolomic data. Using data simulation, we demonstrate here that our approach performs equally as well as existing methods and offers increased flexibility to the researcher. As part of our study, we generated a targeted LC-MS dataset that profiled 33 phenolic compounds from seedling stem tissue in 602 genetically diverse non-transgenic maize inbred lines. This dataset provides a unique opportunity to investigate the dynamics of specialized metabolism in plants.
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Affiliation(s)
- Jonas Rodriguez
- Department of Agronomy, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Lina Gomez-Cano
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA; (L.G.-C.); (E.G.)
| | - Erich Grotewold
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA; (L.G.-C.); (E.G.)
| | - Natalia de Leon
- Department of Agronomy, University of Wisconsin-Madison, Madison, WI 53706, USA;
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22
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Deciphering Pleiotropic Signatures of Regulatory SNPs in Zea mays L. Using Multi-Omics Data and Machine Learning Algorithms. Int J Mol Sci 2022; 23:ijms23095121. [PMID: 35563516 PMCID: PMC9100765 DOI: 10.3390/ijms23095121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/28/2022] [Accepted: 05/02/2022] [Indexed: 01/25/2023] Open
Abstract
Maize is one of the most widely grown cereals in the world. However, to address the challenges in maize breeding arising from climatic anomalies, there is a need for developing novel strategies to harness the power of multi-omics technologies. In this regard, pleiotropy is an important genetic phenomenon that can be utilized to simultaneously enhance multiple agronomic phenotypes in maize. In addition to pleiotropy, another aspect is the consideration of the regulatory SNPs (rSNPs) that are likely to have causal effects in phenotypic development. By incorporating both aspects in our study, we performed a systematic analysis based on multi-omics data to reveal the novel pleiotropic signatures of rSNPs in a global maize population. For this purpose, we first applied Random Forests and then Markov clustering algorithms to decipher the pleiotropic signatures of rSNPs, based on which hierarchical network models are constructed to elucidate the complex interplay among transcription factors, rSNPs, and phenotypes. The results obtained in our study could help to understand the genetic programs orchestrating multiple phenotypes and thus could provide novel breeding targets for the simultaneous improvement of several agronomic traits.
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23
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Variability in changes of acrylamide precursors during nixtamalization for masa production. Lebensm Wiss Technol 2022. [DOI: 10.1016/j.lwt.2022.113400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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24
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Liu H, Wang H, Shao C, Han Y, He Y, Yin Z. Genetic Architecture of Maize Stalk Diameter and Rind Penetrometer Resistance in a Recombinant Inbred Line Population. Genes (Basel) 2022; 13:genes13040579. [PMID: 35456384 PMCID: PMC9032882 DOI: 10.3390/genes13040579] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/20/2022] [Accepted: 03/23/2022] [Indexed: 02/05/2023] Open
Abstract
Stalk lodging presents a major constraint on maize (Zea mays L.) quantity and quality and hampers mechanized grain harvesting. Stalk diameter (SD) and rind penetrometer resistance (RPR) are crucial indicators of stalk lodging. To dissect the genetic architecture of these indicators, we constructed a recombinant inbred line (RIL) population derived from a cross between maize inbred lines LDC-1 and YS501 to identify quantitative trait loci (QTLs) controlling SD and RPR. Corresponding phenotypes of basal second, third, and fourth internodes in four environments were determined. By integrating QTL mapping results based on individual environments and best linear unbiased prediction (BLUP) values, we identified 12, 12, and 13 QTLs associated with SD and 17, 14, and 17 associated with RPR. Each QTL accounted for 3.83–21.72% of phenotypic variation. For SD-related QTLs, 30 of 37 were enriched in 12 QTL clusters; similarly, RPR-related QTLs had 38 of 48 enriched in 12 QTL clusters. The stable QTL qSD9-2 for SD on chromosome 9 was validated and delimited within a physical region of 9.97 Mb. Confidence intervals of RPR-related QTLs contained 169 genes involved in lignin and polysaccharide biosynthesis, with 12 of these less than 500 kb from the peak of the corresponding QTL. Our results deepen our understanding of the genetic mechanism of maize stalk strength and provide a basis for breeding lodging resistance.
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Affiliation(s)
- Huanhuan Liu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genetics and Physiology, Agricultural College of Yangzhou University, Yangzhou 225009, China; (H.L.); (H.W.); (C.S.); (Y.H.); (Y.H.)
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China
| | - Huan Wang
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genetics and Physiology, Agricultural College of Yangzhou University, Yangzhou 225009, China; (H.L.); (H.W.); (C.S.); (Y.H.); (Y.H.)
| | - Cong Shao
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genetics and Physiology, Agricultural College of Yangzhou University, Yangzhou 225009, China; (H.L.); (H.W.); (C.S.); (Y.H.); (Y.H.)
| | - Youle Han
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genetics and Physiology, Agricultural College of Yangzhou University, Yangzhou 225009, China; (H.L.); (H.W.); (C.S.); (Y.H.); (Y.H.)
| | - Yonghui He
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genetics and Physiology, Agricultural College of Yangzhou University, Yangzhou 225009, China; (H.L.); (H.W.); (C.S.); (Y.H.); (Y.H.)
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China
| | - Zhitong Yin
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genetics and Physiology, Agricultural College of Yangzhou University, Yangzhou 225009, China; (H.L.); (H.W.); (C.S.); (Y.H.); (Y.H.)
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China
- Correspondence:
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25
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Ana LM, Rogelio S, Xose Carlos S, Rosa Ana M. Cell Wall Composition Impacts Structural Characteristics of the Stems and Thereby the Biomass Yield. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:3136-3141. [PMID: 35232018 PMCID: PMC8931758 DOI: 10.1021/acs.jafc.1c06986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 02/16/2022] [Accepted: 02/18/2022] [Indexed: 06/14/2023]
Abstract
Maize stalks support leaves and reproductive structures and functionally support water and nutrient transport; besides, their anatomical and biochemical characteristics have been described as a plant defense against stress, also impacting economically important applications. In this study, we evaluated agronomical and stem description traits in a subset of maize inbred lines that showed variability for cell wall composition in the internodes. Overall, a great proportion of lignin subunit G and a low concentration of p-coumaric acid and lignin subunit S are beneficial for greater rind puncture resistance and taller plants, with a greater biomass yield. Also, the greater the proportions of subunit H, the longer the internode. Finally, the lower the total hemicellulose content, the greater the rind puncture resistance. Our results confirmed the effect of the cell wall on agronomic and stalk traits, which would be useful in applied breeding programs focused on biomass yield improvement.
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Affiliation(s)
- López-Malvar Ana
- Facultad
de Biología, Departamento de Biología Vegetal y Ciencias
del Suelo, Universidade de Vigo, As Lagoas Marcosende, 36310 Vigo, Spain
| | - Santiago Rogelio
- Facultad
de Biología, Departamento de Biología Vegetal y Ciencias
del Suelo, Universidade de Vigo, As Lagoas Marcosende, 36310 Vigo, Spain
- Agrobiología
Ambiental, Calidad de Suelos y Plantas (UVIGO), Unidad Asociada a la MBG (CSIC), 36310 Vigo, Spain
- Misión
Biológica de Galicia (CSIC), Pazo
de Salcedo, Carballeira 8, 36143 Pontevedra, Spain
| | - Souto Xose Carlos
- Departamente
Ingeniería Recursos Naturales Y Medio Ambiente, E.E. Forestales, Universidade de Vigo, 36005 Pontevedra, Spain
| | - Malvar Rosa Ana
- Agrobiología
Ambiental, Calidad de Suelos y Plantas (UVIGO), Unidad Asociada a la MBG (CSIC), 36310 Vigo, Spain
- Misión
Biológica de Galicia (CSIC), Pazo
de Salcedo, Carballeira 8, 36143 Pontevedra, Spain
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26
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Sun G, Mural RV, Turkus JD, Schnable JC. Quantitative Resistance Loci to Southern Rust Mapped in a Temperate Maize Diversity Panel. PHYTOPATHOLOGY 2022; 112:579-587. [PMID: 34282952 DOI: 10.1094/phyto-04-21-0160-r] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Southern rust is a severe foliar disease of maize (Zea mays) resulting from infection with the obligate biotrophic fungus Puccinia polysora. This disease reduces photosynthetic productivity, which in turn reduces yields, with the greatest yield losses (up to 50%) associated with earlier onset infections. P. polysora urediniospores overwinter only in tropical and subtropical regions but cause outbreaks when environmental conditions favor initial infection. Increased temperatures and humidity during the growing season combined with an increased frequency of moderate winters are likely to increase the frequency of severe southern rust outbreaks in the U.S. Corn Belt. In summer 2020, a severe outbreak of southern rust was observed in eastern Nebraska, United States. We scored a replicated maize association panel planted in Lincoln, NE for disease severity and found that disease incidence and severity showed significant variation among maize genotypes. Genome-wide association studies identified four loci associated with significant quantitative variation in disease severity. These loci were associated with candidate genes with plausible links to quantitative disease resistance. A transcriptome-wide association study identified additional genes associated with disease severity. Together, these results indicate that substantial diversity in resistance to southern rust exists among current temperate-adapted maize germplasm, including several candidate loci that may explain the observed variation in resistance to southern rust.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
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Affiliation(s)
- Guangchao Sun
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, NE 68588
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588
| | - Ravi V Mural
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, NE 68588
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588
| | - Jonathan D Turkus
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, NE 68588
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588
| | - James C Schnable
- Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, NE 68588
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68588
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588
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27
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Schneider HM, Lor VSN, Hanlon MT, Perkins A, Kaeppler SM, Borkar AN, Bhosale R, Zhang X, Rodriguez J, Bucksch A, Bennett MJ, Brown KM, Lynch JP. Root angle in maize influences nitrogen capture and is regulated by calcineurin B-like protein (CBL)-interacting serine/threonine-protein kinase 15 (ZmCIPK15). PLANT, CELL & ENVIRONMENT 2022; 45:837-853. [PMID: 34169548 PMCID: PMC9544310 DOI: 10.1111/pce.14135] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 06/05/2021] [Accepted: 06/16/2021] [Indexed: 05/06/2023]
Abstract
Crops with reduced nutrient and water requirements are urgently needed in global agriculture. Root growth angle plays an important role in nutrient and water acquisition. A maize diversity panel of 481 genotypes was screened for variation in root angle employing a high-throughput field phenotyping platform. Genome-wide association mapping identified several single nucleotide polymorphisms (SNPs) associated with root angle, including one located in the root expressed CBL-interacting serine/threonine-protein kinase 15 (ZmCIPK15) gene (LOC100285495). Reverse genetic studies validated the functional importance of ZmCIPK15, causing a approximately 10° change in root angle in specific nodal positions. A steeper root growth angle improved nitrogen capture in silico and in the field. OpenSimRoot simulations predicted at 40 days of growth that this change in angle would improve nitrogen uptake by 11% and plant biomass by 4% in low nitrogen conditions. In field studies under suboptimal N availability, the cipk15 mutant with steeper growth angles had 18% greater shoot biomass and 29% greater shoot nitrogen accumulation compared to the wild type after 70 days of growth. We propose that a steeper root growth angle modulated by ZmCIPK15 will facilitate efforts to develop new crop varieties with optimal root architecture for improved performance under edaphic stress.
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Affiliation(s)
- Hannah M. Schneider
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | - Vai Sa Nee Lor
- Department of AgronomyUniversity of WisconsinMadisonWisconsinUSA
| | - Meredith T. Hanlon
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | - Alden Perkins
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | | | - Aditi N. Borkar
- School of Veterinary Medicine and ScienceUniversity of NottinghamSutton BoningtonUK
| | - Rahul Bhosale
- Future Food Beacon of Excellence and School of BiosciencesUniversity of NottinghamNottinghamUK
| | - Xia Zhang
- Department of AgronomyUniversity of WisconsinMadisonWisconsinUSA
| | - Jonas Rodriguez
- Department of AgronomyUniversity of WisconsinMadisonWisconsinUSA
| | - Alexander Bucksch
- Department of Plant BiologyUniversity of GeorgiaAthensGeorgiaUSA
- Warnell School of Forestry and Natural ResourcesUniversity of GeorgiaAthensGeorgiaUSA
- Institute of BioinformaticsUniversity of GeorgiaAthensGeorgiaUSA
| | - Malcolm J. Bennett
- Future Food Beacon of Excellence and School of BiosciencesUniversity of NottinghamNottinghamUK
| | - Kathleen M. Brown
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
| | - Jonathan P. Lynch
- Department of Plant ScienceThe Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA
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28
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Renk JS, Gilbert AM, Hattery TJ, O'Connor CH, Monnahan PJ, Anderson N, Waters AJ, Eickholt DP, Flint-Garcia SA, Yandeau-Nelson MD, Hirsch CN. Genetic control of kernel compositional variation in a maize diversity panel. THE PLANT GENOME 2021; 14:e20115. [PMID: 34197039 DOI: 10.1002/tpg2.20115] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 05/07/2021] [Indexed: 06/13/2023]
Abstract
Maize (Zea mays L.) is a multi-purpose row crop grown worldwide, which, over time, has often been bred for increased yield at the detriment of lower composition grain quality. Some knowledge of the genetic factors that affect quality traits has been discovered through the study of classical maize mutants; however, much of the underlying genetic control of these traits and the interaction between these traits remains unknown. To better understand variation that exists for grain compositional traits in maize, we evaluated 501 diverse temperate maize inbred lines in five unique environments and predicted 16 compositional traits (e.g., carbohydrates, protein, and starch) based on the output of near-infrared (NIR) spectroscopy. Phenotypic analysis found substantial variation for compositional traits and the majority of variation was explained by genetic and environmental factors. Correlations and trade-offs among traits in different maize types (e.g., dent, sweetcorn, and popcorn) were explored, and significant differences and meaningful correlations were detected. In total, 22.9-71.0% of the phenotypic variation across these traits could be explained using 2,386,666 single nucleotide polymorphism (SNP) markers generated from whole-genome resequencing data. A genome-wide association study (GWAS) was conducted using these same markers and found 72 statistically significant SNPs for 11 compositional traits. This study provides valuable insights in the phenotypic variation and genetic control underlying compositional traits that can be used in breeding programs for improving maize grain quality.
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Affiliation(s)
- Jonathan S Renk
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Amanda M Gilbert
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Travis J Hattery
- Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA, 50011, 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
| | - Patrick J Monnahan
- 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
| | | | | | | | - Sherry A Flint-Garcia
- United States Department of Agriculture, Agricultural Research Service, Columbia, MO, 65211, USA
| | - Marna D Yandeau-Nelson
- Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA, 50011, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
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29
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Bornowski N, Michel KJ, Hamilton JP, Ou S, Seetharam AS, Jenkins J, Grimwood J, Plott C, Shu S, Talag J, Kennedy M, Hundley H, Singan VR, Barry K, Daum C, Yoshinaga Y, Schmutz J, Hirsch CN, Hufford MB, de Leon N, Kaeppler SM, Buell CR. Genomic variation within the maize stiff-stalk heterotic germplasm pool. THE PLANT GENOME 2021; 14:e20114. [PMID: 34275202 DOI: 10.1002/tpg2.20114] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 05/06/2021] [Indexed: 05/28/2023]
Abstract
The stiff-stalk heterotic group in Maize (Zea mays L.) is an important source of inbreds used in U.S. commercial hybrid production. Founder inbreds B14, B37, B73, and, to a lesser extent, B84, are found in the pedigrees of a majority of commercial seed parent inbred lines. We created high-quality genome assemblies of B84 and four expired Plant Variety Protection (ex-PVP) lines LH145 representing B14, NKH8431 of mixed descent, PHB47 representing B37, and PHJ40, which is a Pioneer Hi-Bred International (PHI) early stiff-stalk type. Sequence was generated using long-read sequencing achieving highly contiguous assemblies of 2.13-2.18 Gbp with N50 scaffold lengths >200 Mbp. Inbred-specific gene annotations were generated using a core five-tissue gene expression atlas, whereas transposable element (TE) annotation was conducted using de novo and homology-directed methodologies. Compared with the reference inbred B73, synteny analyses revealed extensive collinearity across the five stiff-stalk genomes, although unique components of the maize pangenome were detected. Comparison of this set of stiff-stalk inbreds with the original Iowa Stiff Stalk Synthetic breeding population revealed that these inbreds represent only a proportion of variation in the original stiff-stalk pool and there are highly conserved haplotypes in released public and ex-Plant Variety Protection inbreds. Despite the reduction in variation from the original stiff-stalk population, substantial genetic and genomic variation was identified supporting the potential for continued breeding success in this pool. The assemblies described here represent stiff-stalk inbreds that have historical and commercial relevance and provide further insight into the emerging maize pangenome.
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Affiliation(s)
- Nolan Bornowski
- Dep. of Plant Biology, Michigan State Univ., 612 Wilson Road, East Lansing, MI, 48824, USA
| | - Kathryn J Michel
- Dep. of Agronomy, Univ. of Wisconsin - Madison, 1575 Linden Drive, Madison, WI, 53706, USA
| | - John P Hamilton
- Dep. of Plant Biology, Michigan State Univ., 612 Wilson Road, East Lansing, MI, 48824, USA
| | - Shujun Ou
- Dep. of Ecology, Evolution, and Organismal Biology, Iowa State Univ., 2200 Osborn Drive, Ames, IA, 50011, USA
| | - Arun S Seetharam
- Dep. of Ecology, Evolution, and Organismal Biology, Iowa State Univ., 2200 Osborn Drive, Ames, IA, 50011, USA
| | - Jerry Jenkins
- HudsonAlpha Institute for Biotechnology, 601 Genome Way Northwest, Huntsville, AL, 35806, USA
| | - Jane Grimwood
- HudsonAlpha Institute for Biotechnology, 601 Genome Way Northwest, Huntsville, AL, 35806, USA
| | - Chris Plott
- HudsonAlpha Institute for Biotechnology, 601 Genome Way Northwest, Huntsville, AL, 35806, USA
| | - Shengqiang Shu
- U.S. Dep. of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Jayson Talag
- Arizona Genomics Institute, School of Plant Sciences, Univ. of Arizona, 1657 E Helen Street, Tucson, AZ, 85721, USA
| | - Megan Kennedy
- U.S. Dep. of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Hope Hundley
- U.S. Dep. of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Vasanth R Singan
- U.S. Dep. of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Kerrie Barry
- U.S. Dep. of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Chris Daum
- U.S. Dep. of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Yuko Yoshinaga
- U.S. Dep. of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Jeremy Schmutz
- HudsonAlpha Institute for Biotechnology, 601 Genome Way Northwest, Huntsville, AL, 35806, USA
- U.S. Dep. of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA
| | - Candice N Hirsch
- Dep. of Agronomy and Plant Genetics, Univ. of Minnesota, 1991 Upper Buford Circle, Saint Paul, MN, 55108, USA
| | - Matthew B Hufford
- Dep. of Ecology, Evolution, and Organismal Biology, Iowa State Univ., 2200 Osborn Drive, Ames, IA, 50011, USA
| | - Natalia de Leon
- Dep. of Agronomy, Univ. of Wisconsin - Madison, 1575 Linden Drive, Madison, WI, 53706, USA
- Dep. of Energy, Great Lakes Bioenergy Research Center, Univ. of Wisconsin - Madison, 1575 Linden Drive, Madison, WI, 53706, USA
| | - Shawn M Kaeppler
- Dep. of Agronomy, Univ. of Wisconsin - Madison, 1575 Linden Drive, Madison, WI, 53706, USA
- Dep. of Energy, Great Lakes Bioenergy Research Center, Univ. of Wisconsin - Madison, 1575 Linden Drive, Madison, WI, 53706, USA
- Wisconsin Crop Innovation Center, Univ. of Wisconsin - Madison, 8520 University Green, Middleton, WI, 53562, USA
| | - C Robin Buell
- Dep. of Plant Biology, Michigan State Univ., 612 Wilson Road, East Lansing, MI, 48824, USA
- Dep. of Energy, Great Lakes Bioenergy Research Center, Michigan State Univ., 612 Wilson Road, East Lansing, MI, 48824, USA
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Volk GM, Byrne PF, Coyne CJ, Flint-Garcia S, Reeves PA, Richards C. Integrating Genomic and Phenomic Approaches to Support Plant Genetic Resources Conservation and Use. PLANTS (BASEL, SWITZERLAND) 2021; 10:2260. [PMID: 34834625 PMCID: PMC8619436 DOI: 10.3390/plants10112260] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 10/20/2021] [Accepted: 10/20/2021] [Indexed: 05/17/2023]
Abstract
Plant genebanks provide genetic resources for breeding and research programs worldwide. These programs benefit from having access to high-quality, standardized phenotypic and genotypic data. Technological advances have made it possible to collect phenomic and genomic data for genebank collections, which, with the appropriate analytical tools, can directly inform breeding programs. We discuss the importance of considering genebank accession homogeneity and heterogeneity in data collection and documentation. Citing specific examples, we describe how well-documented genomic and phenomic data have met or could meet the needs of plant genetic resource managers and users. We explore future opportunities that may emerge from improved documentation and data integration among plant genetic resource information systems.
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Affiliation(s)
- Gayle M. Volk
- United States Department of Agriculture, Agricultural Research Service, National Laboratory for Genetic Resources Preservation, Fort Collins, CO 80521, USA; (P.A.R.); (C.R.)
| | - Patrick F. Byrne
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523, USA;
| | - Clarice J. Coyne
- United States Department of Agriculture, Agricultural Research Service, Western Regional Plant Introduction Station, Pullman, WA 99164, USA;
| | - Sherry Flint-Garcia
- Plant Genetics Research Unit, United States Department of Agriculture, Agricultural Research Service, Columbia, MO 65211, USA;
| | - Patrick A. Reeves
- United States Department of Agriculture, Agricultural Research Service, National Laboratory for Genetic Resources Preservation, Fort Collins, CO 80521, USA; (P.A.R.); (C.R.)
| | - Chris Richards
- United States Department of Agriculture, Agricultural Research Service, National Laboratory for Genetic Resources Preservation, Fort Collins, CO 80521, USA; (P.A.R.); (C.R.)
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Qiu Y, O’Connor CH, Della Coletta R, Renk JS, Monnahan PJ, Noshay JM, Liang Z, Gilbert A, Anderson SN, McGaugh SE, Springer NM, Hirsch CN. Whole-genome variation of transposable element insertions in a maize diversity panel. G3 (BETHESDA, MD.) 2021; 11:jkab238. [PMID: 34568911 PMCID: PMC8473971 DOI: 10.1093/g3journal/jkab238] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 06/29/2021] [Indexed: 01/09/2023]
Abstract
Intact transposable elements (TEs) account for 65% of the maize genome and can impact gene function and regulation. Although TEs comprise the majority of the maize genome and affect important phenotypes, genome-wide patterns of TE polymorphisms in maize have only been studied in a handful of maize genotypes, due to the challenging nature of assessing highly repetitive sequences. We implemented a method to use short-read sequencing data from 509 diverse inbred lines to classify the presence/absence of 445,418 nonredundant TEs that were previously annotated in four genome assemblies including B73, Mo17, PH207, and W22. Different orders of TEs (i.e., LTRs, Helitrons, and TIRs) had different frequency distributions within the population. LTRs with lower LTR similarity were generally more frequent in the population than LTRs with higher LTR similarity, though high-frequency insertions with very high LTR similarity were observed. LTR similarity and frequency estimates of nested elements and the outer elements in which they insert revealed that most nesting events occurred very near the timing of the outer element insertion. TEs within genes were at higher frequency than those that were outside of genes and this is particularly true for those not inserted into introns. Many TE insertional polymorphisms observed in this population were tagged by SNP markers. However, there were also 19.9% of the TE polymorphisms that were not well tagged by SNPs (R2 < 0.5) that potentially represent information that has not been well captured in previous SNP-based marker-trait association studies. This study provides a population scale genome-wide assessment of TE variation in maize and provides valuable insight on variation in TEs in maize and factors that contribute to this variation.
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Affiliation(s)
- Yinjie Qiu
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, 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
| | - Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Jonathan S Renk
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Patrick J Monnahan
- 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
| | - Jaclyn M Noshay
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, MN 55108, USA
| | - Zhikai Liang
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, MN 55108, USA
| | - Amanda Gilbert
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Sarah N Anderson
- Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA 50011, USA
| | - Suzanne E McGaugh
- Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, MN 55108, USA
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, MN 55108, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
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Noshay JM, Marand AP, Anderson SN, Zhou P, Mejia Guerra MK, Lu Z, O'Connor CH, Crisp PA, Hirsch CN, Schmitz RJ, Springer NM. Assessing the regulatory potential of transposable elements using chromatin accessibility profiles of maize transposons. Genetics 2021; 217:1-13. [PMID: 33683350 DOI: 10.1093/genetics/iyaa003] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 11/02/2020] [Indexed: 11/14/2022] Open
Abstract
Transposable elements (TEs) have the potential to create regulatory variation both through the disruption of existing DNA regulatory elements and through the creation of novel DNA regulatory elements. In a species with a large genome, such as maize, many TEs interspersed with genes create opportunities for significant allelic variation due to TE presence/absence polymorphisms among individuals. We used information on putative regulatory elements in combination with knowledge about TE polymorphisms in maize to identify TE insertions that interrupt existing accessible chromatin regions (ACRs) in B73 as well as examples of polymorphic TEs that contain ACRs among four inbred lines of maize including B73, Mo17, W22, and PH207. The TE insertions in three other assembled maize genomes (Mo17, W22, or PH207) that interrupt ACRs that are present in the B73 genome can trigger changes to the chromatin, suggesting the potential for both genetic and epigenetic influences of these insertions. Nearly 20% of the ACRs located over 2 kb from the nearest gene are located within an annotated TE. These are regions of unmethylated DNA that show evidence for functional importance similar to ACRs that are not present within TEs. Using a large panel of maize genotypes, we tested if there is an association between the presence of TE insertions that interrupt, or carry, an ACR and the expression of nearby genes. While most TE polymorphisms are not associated with expression for nearby genes, the TEs that carry ACRs exhibit enrichment for being associated with higher expression of nearby genes, suggesting that these TEs may contribute novel regulatory elements. These analyses highlight the potential for a subset of TEs to rewire transcriptional responses in eukaryotic genomes.
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Affiliation(s)
- Jaclyn M Noshay
- Department of Plant and Microbial Biology, University of Minnesota, 140 Gortner Laboratory, 1479 Gortner Avenue, St. Paul, MN 55108, USA
| | - Alexandre P Marand
- Department of Genetics, University of Georgia, 120 W Green St, Athens, GA 30602, USA
| | - Sarah N Anderson
- Department of Genetics, Development, and Cell Biology, Iowa State University, 2437 Pammel Dr, Ames, IA 50011, USA
| | - Peng Zhou
- Department of Plant and Microbial Biology, University of Minnesota, 140 Gortner Laboratory, 1479 Gortner Avenue, St. Paul, MN 55108, USA
| | | | - Zefu Lu
- Department of Genetics, University of Georgia, 120 W Green St, Athens, GA 30602, USA
| | - Christine H O'Connor
- Department of Agronomy and Plant Genetics, University of Minnesota, 1994 Upper Buford Circle, 411 Borlaug Hall, St. Paul, MN 55108, USA
| | - Peter A Crisp
- School of Agriculture and Food Sciences, The University of Queensland, Harley Teakle Building, Keyhold Rd, St Lucia QLD 4067, Australia
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, 1994 Upper Buford Circle, 411 Borlaug Hall, St. Paul, MN 55108, USA
| | - Robert J Schmitz
- Department of Genetics, University of Georgia, 120 W Green St, Athens, GA 30602, USA
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, 140 Gortner Laboratory, 1479 Gortner Avenue, St. Paul, MN 55108, USA
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Berhe M, Dossa K, You J, Mboup PA, Diallo IN, Diouf D, Zhang X, Wang L. Genome-wide association study and its applications in the non-model crop Sesamum indicum. BMC PLANT BIOLOGY 2021; 21:283. [PMID: 34157965 PMCID: PMC8218510 DOI: 10.1186/s12870-021-03046-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Accepted: 05/17/2021] [Indexed: 05/05/2023]
Abstract
BACKGROUND Sesame is a rare example of non-model and minor crop for which numerous genetic loci and candidate genes underlying features of interest have been disclosed at relatively high resolution. These progresses have been achieved thanks to the applications of the genome-wide association study (GWAS) approach. GWAS has benefited from the availability of high-quality genomes, re-sequencing data from thousands of genotypes, extensive transcriptome sequencing, development of haplotype map and web-based functional databases in sesame. RESULTS In this paper, we reviewed the GWAS methods, the underlying statistical models and the applications for genetic discovery of important traits in sesame. A novel online database SiGeDiD ( http://sigedid.ucad.sn/ ) has been developed to provide access to all genetic and genomic discoveries through GWAS in sesame. We also tested for the first time, applications of various new GWAS multi-locus models in sesame. CONCLUSIONS Collectively, this work portrays steps and provides guidelines for efficient GWAS implementation in sesame, a non-model crop.
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Affiliation(s)
- Muez Berhe
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, and Rural Affairs, No.2 Xudong 2nd Road, Wuhan, 430062, China
- Humera Agricultural Research Center of Tigray Agricultural Research Institute, Humera, Tigray, Ethiopia
| | - Komivi Dossa
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, and Rural Affairs, No.2 Xudong 2nd Road, Wuhan, 430062, China.
- Laboratoire Campus de Biotechnologies Végétales, Département de Biologie Végétale, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, BP 5005 Dakar-Fann, 10700, Dakar, Senegal.
- Laboratory of Genetics, Horticulture and Seed Sciences, Faculty of Agronomic Sciences, University of Abomey-Calavi, 01 BP 526, Cotonou, Republic of Benin.
| | - Jun You
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, and Rural Affairs, No.2 Xudong 2nd Road, Wuhan, 430062, China
| | - Pape Adama Mboup
- Département de Mathématiques et Informatique, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, BP 5005 Dakar-Fann, 10700, Dakar, Senegal
| | - Idrissa Navel Diallo
- Laboratoire Campus de Biotechnologies Végétales, Département de Biologie Végétale, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, BP 5005 Dakar-Fann, 10700, Dakar, Senegal
- Département de Mathématiques et Informatique, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, BP 5005 Dakar-Fann, 10700, Dakar, Senegal
| | - Diaga Diouf
- Laboratoire Campus de Biotechnologies Végétales, Département de Biologie Végétale, Faculté des Sciences et Techniques, Université Cheikh Anta Diop, BP 5005 Dakar-Fann, 10700, Dakar, Senegal
| | - Xiurong Zhang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, and Rural Affairs, No.2 Xudong 2nd Road, Wuhan, 430062, China
| | - Linhai Wang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, and Rural Affairs, No.2 Xudong 2nd Road, Wuhan, 430062, China.
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Shikha K, Shahi JP, Vinayan MT, Zaidi PH, Singh AK, Sinha B. Genome-wide association mapping in maize: status and prospects. 3 Biotech 2021; 11:244. [PMID: 33968587 PMCID: PMC8085158 DOI: 10.1007/s13205-021-02799-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 04/19/2021] [Indexed: 12/11/2022] Open
Abstract
Genome-wide association study (GWAS) provides a robust and potent tool to retrieve complex phenotypic traits back to their underlying genetics. Maize is an excellent crop for performing GWAS due to diverse genetic variability, rapid decay of linkage disequilibrium, availability of distinct sub-populations and abundant SNP information. The application of GWAS in maize has resulted in successful identification of thousands of genomic regions associated with many abiotic and biotic stresses. Many agronomic and quality traits of maize are severely affected by such stresses and, significantly affecting its growth and productivity. To improve productivity of maize crop in countries like India which contribute only 2% to the world's total production in 2019-2020, it is essential to understand genetic complexity of underlying traits. Various DNA markers and trait associations have been revealed using conventional linkage mapping methods. However, it has achieved limited success in improving polygenic complex traits due to lower resolution of trait mapping. The present review explores the prospects of GWAS in improving yield, quality and stress tolerance in maize besides, strengths and challenges of using GWAS for molecular breeding and genomic selection. The information gathered will facilitate elucidation of genetic mechanisms of complex traits and improve efficiency of marker-assisted selection in maize breeding. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s13205-021-02799-4.
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Affiliation(s)
- Kumari Shikha
- Department of Genetics and Plant Breeding, Institute of Agriculltural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India
| | - J. P. Shahi
- Department of Genetics and Plant Breeding, Institute of Agriculltural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India
| | - M. T. Vinayan
- International Maize and Wheat Improvement Centre (CIMMYT)-Asia, ICRISAT Campus, Patancheru, Hyderabad, Telangana India
| | - P. H. Zaidi
- International Maize and Wheat Improvement Centre (CIMMYT)-Asia, ICRISAT Campus, Patancheru, Hyderabad, Telangana India
| | - A. K. Singh
- Department of Genetics and Plant Breeding, Institute of Agriculltural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India
| | - B. Sinha
- Department of Genetics and Plant Breeding, Institute of Agriculltural Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh India
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El Hage F, Virlouvet L, Lopez-Marnet PL, Griveau Y, Jacquemot MP, Coursol S, Méchin V, Reymond M. Responses of Maize Internode to Water Deficit Are Different at the Biochemical and Histological Levels. FRONTIERS IN PLANT SCIENCE 2021; 12:628960. [PMID: 33719300 PMCID: PMC7952650 DOI: 10.3389/fpls.2021.628960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 01/22/2021] [Indexed: 06/12/2023]
Abstract
Maize feeding value is strongly linked to plant digestibility. Cell wall composition and structure can partly explain cell wall digestibility variations, and we recently showed that tissue lignification and lignin spatial distribution also contribute to cell wall digestibility variations. Although the genetic determinism of digestibility and cell wall composition has been studied for more than 20 years, little is available concerning that of tissue lignification. Moreover, maize yield is negatively impacted by water deficit, and we newly highlighted the impact of water deficit on cell wall digestibility and composition together with tissue lignification. Consequently, the aim of this study was to explore the genetic mechanisms of lignin distribution in link with cell wall composition and digestibility under contrasted water regimes. Maize internodes from a recombinant inbred line (RIL) population grown in field trials with contrasting irrigation scenarios were biochemically and histologically quantified. Results obtained showed that biochemical and histological traits have different response thresholds to water deficit. Histological profiles were therefore only modified under pronounced water deficit, while most of the biochemical traits responded whatever the strength of the water deficit. Three main clusters of quantitative trait locus (QTL) for histological traits were detected. Interestingly, overlap between the biochemical and histological clusters is rare, and one noted especially colocalizations between histological QTL/clusters and QTL for p-coumaric acid content. These findings reinforce the suspected role of tissue p-coumaroylation for both the agronomic properties of plants as well as their digestibility.
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Affiliation(s)
- Fadi El Hage
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
- Ecole Doctorale n° 567: Science du Végétal: Du gène à l’écosystème, Université Paris-Saclay, Orsay, France
| | - Laetitia Virlouvet
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Paul-Louis Lopez-Marnet
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
- Ecole Doctorale n° 581: ABIES, Paris, France
| | - Yves Griveau
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Marie-Pierre Jacquemot
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Sylvie Coursol
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Valérie Méchin
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Matthieu Reymond
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
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Genome wide association study and genomic prediction for stover quality traits in tropical maize (Zea mays L.). Sci Rep 2021; 11:686. [PMID: 33436870 PMCID: PMC7804097 DOI: 10.1038/s41598-020-80118-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 12/15/2020] [Indexed: 11/09/2022] Open
Abstract
Maize is rapidly replacing traditionally cultivated dual purpose crops of South Asia, primarily due to the better economic remuneration. This has created an impetus for improving maize for both grain productivity and stover traits. Molecular techniques can largely assist breeders in determining approaches for effectively integrating stover trait improvement in their existing breeding pipeline. In the current study we identified a suite of potential genomic regions associated to the two major stover quality traits-in-vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) through genome wide association study. However, considering the fact that the loci identified for these complex traits all had smaller effects and accounted only a small portion of phenotypic variation, the effectiveness of following a genomic selection approach for these traits was evaluated. The testing set consists of breeding lines recently developed within the program and the training set consists of a panel of lines from the working germplasm comprising the founder lines of the newly developed breeding lines and also an unrelated diversity set. The prediction accuracy as determined by the Pearson's correlation coefficient between observed and predicted values of these breeding lines were high even at lower marker density (200 random SNPs), when the training and testing set were related. However, the accuracies were dismal, when there was no relationship between the training and the testing set.
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Li Z, Zhou P, Della Coletta R, Zhang T, Brohammer AB, H O'Connor C, Vaillancourt B, Lipzen A, Daum C, Barry K, de Leon N, Hirsch CD, Buell CR, Kaeppler SM, Springer NM, Hirsch CN. Single-parent expression drives dynamic gene expression complementation in maize hybrids. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 105:93-107. [PMID: 33098691 DOI: 10.1111/tpj.15042] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 09/27/2020] [Accepted: 10/02/2020] [Indexed: 06/11/2023]
Abstract
Single-parent expression (SPE) is defined as gene expression in only one of the two parents. SPE can arise from differential expression between parental alleles, termed non-presence/absence (non-PAV) SPE, or from the physical absence of a gene in one parent, termed PAV SPE. We used transcriptome data of diverse Zea mays (maize) inbreds and hybrids, including 401 samples from five different tissues, to test for differences between these types of SPE genes. Although commonly observed, SPE is highly genotype and tissue specific. A positive correlation was observed between the genetic distance of the two inbred parents and the number of SPE genes identified. Regulatory analysis showed that PAV SPE and non-PAV SPE genes are mainly regulated by cis effects, with a small fraction under trans regulation. Polymorphic transposable element insertions in promoter sequences contributed to the high level of cis regulation for PAV SPE and non-PAV SPE genes. PAV SPE genes were more frequently expressed in hybrids than non-PAV SPE genes. The expression of parentally silent alleles in hybrids of non-PAV SPE genes was relatively rare but occurred in most hybrids. Non-PAV SPE genes with expression of the silent allele in hybrids are more likely to exhibit above high parent expression level than hybrids that do not express the silent allele, leading to non-additive expression. This study provides a comprehensive understanding of the nature of non-PAV SPE and PAV SPE genes and their roles in gene expression complementation in maize hybrids.
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Affiliation(s)
- Zhi Li
- Department of Agronomy and Plant Genetics, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Peng Zhou
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Tifu Zhang
- Jiangsu Provincial Key Laboratory of Agrobiology, Institute of Germplasm Resources and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Alex B Brohammer
- Department of Agronomy and Plant Genetics, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Christine H O'Connor
- Department of Agronomy and Plant Genetics, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Brieanne Vaillancourt
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Anna Lipzen
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Chris Daum
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Kerrie Barry
- Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Natalia de Leon
- Department of Agronomy, University of Wisconsin, Madison, WI, 53706, USA
| | - Cory D Hirsch
- Department of Plant Pathology, University of Minnesota, Saint Paul, MN, 55108, USA
| | - C Robin Buell
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Shawn M Kaeppler
- Department of Agronomy, University of Wisconsin, Madison, WI, 53706, USA
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, Saint Paul, MN, 55108, USA
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38
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Sant’Ana GC, Espolador FG, Granato ÍSC, Mendonça LF, Fritsche-Neto R, Borém A. Population structure analysis and identification of genomic regions under selection associated with low-nitrogen tolerance in tropical maize lines. PLoS One 2020; 15:e0239900. [PMID: 32991596 PMCID: PMC7523979 DOI: 10.1371/journal.pone.0239900] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/15/2020] [Indexed: 11/18/2022] Open
Abstract
Increasing low nitrogen (N) tolerance in maize is an important goal for food security and agricultural sustainability. In order to analyze the population structure of tropical maize lines and identify genomic regions associated with low-N tolerance, a set of 64 inbred lines were evaluated under low-N and optimal-N conditions. The low-N Agronomic Efficiency index (LNAE) of each line was calculated. The maize lines were genotyped using 417,112 SNPs markers. The grouping based on the LNAE values classified the lines into two phenotypic groups, the first comprised by genotypes with high LNAE (named H_LNAE group), while the second one comprised genotypes with low LNAE (named L_LNAE group). The H_LNAE and L_LNAE groups had LNAE mean values of 3,304 and 1,644, respectively. The population structure analysis revealed a weak relationship between genetic and phenotypic diversity. Pairs of lines were identified, having at the same time high LNAE and high genetic distance from each other. A set of 29 SNPs markers exhibited a significant difference in allelic frequencies (Fst > 0.2) between H_LNAE and L_LNAE groups. The Pearson's correlation between LNAE and the favorable alleles in this set of SNPs was 0.69. These SNPs could be useful for marker-assisted selection for low-N tolerance in maize breeding programs. The results of this study could help maize breeders identify accessions to be used in the development of low-N tolerant cultivars.
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Affiliation(s)
| | - Fernando Garcia Espolador
- Department of Genetics, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Piracicaba, São Paulo, Brazil
| | | | - Leandro Freitas Mendonça
- Department of Genetics, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Piracicaba, São Paulo, Brazil
| | - Roberto Fritsche-Neto
- Department of Genetics, “Luiz de Queiroz” College of Agriculture, University of São Paulo, Piracicaba, São Paulo, Brazil
- * E-mail:
| | - Aluízio Borém
- Department of Agronomy, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
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39
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Klein SP, Schneider HM, Perkins AC, Brown KM, Lynch JP. Multiple Integrated Root Phenotypes Are Associated with Improved Drought Tolerance. PLANT PHYSIOLOGY 2020; 183:1011-1025. [PMID: 32332090 PMCID: PMC7333687 DOI: 10.1104/pp.20.00211] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 04/02/2020] [Indexed: 05/18/2023]
Abstract
To test the hypothesis that multiple integrated root phenotypes would co-optimize drought tolerance, we phenotyped the root anatomy and architecture of 400 mature maize (Zea mays) genotypes under well-watered and water-stressed conditions in the field. We found substantial variation in all 23 root phenes measured. A phenotypic bulked segregant analysis revealed that bulks representing the best and worst performers in the field displayed distinct root phenotypes. In contrast to the worst bulk, the root phenotype of the best bulk under drought consisted of greater cortical aerenchyma formation, more numerous and narrower metaxylem vessels, and thicker nodal roots. Partition-against-medians clustering revealed several clusters of unique root phenotypes related to plant performance under water stress. Clusters associated with improved drought tolerance consisted of phene states that likely enable greater soil exploration by reallocating internal resources to greater root construction (increased aerenchyma content, larger cortical cells, fewer cortical cell files), restrict uptake of water to conserve soil moisture (reduced hydraulic conductance, narrow metaxylem vessels), and improve penetrability of hard, dry soils (thick roots with a larger proportion of stele, and smaller distal cortical cells). We propose that the most drought-tolerant-integrated phenotypes merit consideration as breeding ideotypes.
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Affiliation(s)
- Stephanie P Klein
- Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania 16802
| | - Hannah M Schneider
- Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania 16802
| | - Alden C Perkins
- Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania 16802
| | - Kathleen M Brown
- Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania 16802
| | - Jonathan P Lynch
- Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania 16802
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Liu N, Cheng F. Association mapping for yield traits in Paeonia rockii based on SSR markers within transcription factors of comparative transcriptome. BMC PLANT BIOLOGY 2020; 20:245. [PMID: 32487017 PMCID: PMC7265254 DOI: 10.1186/s12870-020-02449-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Accepted: 05/18/2020] [Indexed: 05/30/2023]
Abstract
BACKGROUND Allelic variation underlying the quantitative traits in plants is caused by the extremely complex regulation process. Tree peony originated in China is a peculiar ornamental, medicinal and oil woody plant. Paeonia rockii, one of tree peony species, is a precious emerging woody oil crop. However, in this valuable plant, the study of functional loci associated with yield traits has rarely been identified. Therefore, to explore the genetic architecture of 24 yield quantitative traits, the association mapping was first reported in 420 unrelated cultivated P. rockii individuals based on the next-generation sequencing (NGS) and single-molecule long-read sequencing (SMLRS). RESULTS The developed 58 pairs of polymorphic expressed sequence tag-simple sequence repeat (EST-SSR) markers from 959 candidate transcription factors (TFs) associated with yield were used for genotyping the 420 P. rockii accessions. We observed a high level of genetic diversity (polymorphic information content, PIC = 0.514) and low linkage disequilibrium (LD) between EST-SSRs. Moreover, four subpopulations in the association population were revealed by STRUCTURE analyses. Further, single-marker association analysis identified 141 significant associations, involving 17 quantitative traits and 41 EST-SSRs. These loci were mainly from AP2, TCP, MYB, HSF, bHLH, GATA, and B3 gene families and showed a small proportion of the phenotypic variance (3.79 to 37.45%). CONCLUSIONS Our results summarize a valuable collection of functional loci associated with yield traits in P. rockii, and provide a precious resource that reveals allelic variation underlying quantitative traits in Paeonia and other woody oil crops.
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Affiliation(s)
- Na Liu
- Peony International Institute, Beijing Advanced Innovation Center of Tree Breeding by Molecular Design, Beijing Key Laboratory of Ornamental Plants Germplasm Innovation & Molecular Breeding, National Engineering Research Center for Floriculture, Beijing Laboratory of Urban and Rural Ecological Environment, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, School of Landscape Architecture, Beijing Forestry University, Beijing, 100083, China
| | - Fangyun Cheng
- Peony International Institute, Beijing Advanced Innovation Center of Tree Breeding by Molecular Design, Beijing Key Laboratory of Ornamental Plants Germplasm Innovation & Molecular Breeding, National Engineering Research Center for Floriculture, Beijing Laboratory of Urban and Rural Ecological Environment, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, School of Landscape Architecture, Beijing Forestry University, Beijing, 100083, China.
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Schneider HM, Klein SP, Hanlon MT, Nord EA, Kaeppler S, Brown KM, Warry A, Bhosale R, Lynch JP. Genetic control of root architectural plasticity in maize. JOURNAL OF EXPERIMENTAL BOTANY 2020; 71:3185-3197. [PMID: 32080722 PMCID: PMC7260711 DOI: 10.1093/jxb/eraa084] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 02/20/2020] [Indexed: 05/05/2023]
Abstract
Root phenotypes regulate soil resource acquisition; however, their genetic control and phenotypic plasticity are poorly understood. We hypothesized that the responses of root architectural phenes to water deficit (stress plasticity) and different environments (environmental plasticity) are under genetic control and that these loci are distinct. Root architectural phenes were phenotyped in the field using a large maize association panel with and without water deficit stress for three seasons in Arizona and without water deficit stress for four seasons in South Africa. All root phenes were plastic and varied in their plastic response. We identified candidate genes associated with stress and environmental plasticity and candidate genes associated with phenes in well-watered conditions in South Africa and in well-watered and water-stress conditions in Arizona. Few candidate genes for plasticity overlapped with those for phenes expressed under each condition. Our results suggest that phenotypic plasticity is highly quantitative, and plasticity loci are distinct from loci that control phene expression in stress and non-stress, which poses a challenge for breeding programs. To make these loci more accessible to the wider research community, we developed a public online resource that will allow for further experimental validation towards understanding the genetic control underlying phenotypic plasticity.
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Affiliation(s)
- Hannah M Schneider
- Department of Plant Science, The Pennsylvania State University, University Park, PA, USA
| | - Stephanie P Klein
- Department of Plant Science, The Pennsylvania State University, University Park, PA, USA
| | - Meredith T Hanlon
- Department of Plant Science, The Pennsylvania State University, University Park, PA, USA
| | - Eric A Nord
- Department of Plant Science, The Pennsylvania State University, University Park, PA, USA
| | - Shawn Kaeppler
- Department of Agronomy, University of Wisconsin, Madison, WI, USA
| | - Kathleen M Brown
- Department of Plant Science, The Pennsylvania State University, University Park, PA, USA
| | - Andrew Warry
- Advanced Data Analysis Centre, University of Nottingham, Nottingham, UK
| | - Rahul Bhosale
- Plant and Crop Sciences, School of Biosciences, University of Nottingham, Sutton Bonington, UK
| | - Jonathan P Lynch
- Department of Plant Science, The Pennsylvania State University, University Park, PA, USA
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Thabet SG, Moursi YS, Karam MA, Börner A, Alqudah AM. Natural Variation Uncovers Candidate Genes for Barley Spikelet Number and Grain Yield under Drought Stress. Genes (Basel) 2020; 11:genes11050533. [PMID: 32403266 PMCID: PMC7290517 DOI: 10.3390/genes11050533] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Revised: 04/29/2020] [Accepted: 05/05/2020] [Indexed: 01/01/2023] Open
Abstract
Drought stress can occur at any growth stage and can affect crop productivity, which can result in large yield losses all over the world. In this respect, understanding the genetic architecture of agronomic traits under drought stress is essential for increasing crop yield potential and harvest. Barley is considered the most abiotic stress-tolerant cereal, particularly with respect to drought. In the present study, worldwide spring barley accessions were exposed to drought stress beginning from the early reproductive stage with 35% field capacity under field conditions. Drought stress had significantly reduced the agronomic and yield-related traits such as spike length, awn length, spikelet per spike, grains per spike and thousand kernel weight. To unravel the genetic factors underlying drought tolerance at the early reproductive stage, genome-wide association scan (GWAS) was performed using 121 spring barley accessions and a 9K single nucleotide polymorphisms (SNPs) chip. A total number of 101 significant SNPs, distributed over all seven barley chromosomes, were found to be highly associated with the studied traits, of which five genomic regions were associated with candidate genes at chromosomes 2 and 3. On chromosome 2H, the region between 6469300693-647258342 bp includes two candidate drought-specific genes (HORVU2Hr1G091030 and HORVU2Hr1G091170), which are highly associated with spikelet and final grain number per spike under drought stress conditions. Interestingly, the gene expression profile shows that the candidate genes were highly expressed in spikelet, grain, spike and leaf organs, demonstrating their pivotal role in drought tolerance. To the best of our knowledge, we reported the first detailed study that used GWAS with bioinformatic analyses to define the causative alleles and putative candidate genes underlying grain yield-related traits under field drought conditions in diverse barley germplasm. The identified alleles and candidate genes represent valuable resources for future functional characterization towards the enhancement of barley cultivars for drought tolerance.
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Affiliation(s)
- Samar G. Thabet
- Department of Botany, Faculty of Science, University of Fayoum, Fayoum 63514, Egypt; (S.G.T.); (Y.S.M.); (M.A.K.)
| | - Yasser S. Moursi
- Department of Botany, Faculty of Science, University of Fayoum, Fayoum 63514, Egypt; (S.G.T.); (Y.S.M.); (M.A.K.)
| | - Mohamed A. Karam
- Department of Botany, Faculty of Science, University of Fayoum, Fayoum 63514, Egypt; (S.G.T.); (Y.S.M.); (M.A.K.)
| | - Andreas Börner
- Research Group Resources Genetics and Reproduction, Department Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research, 06466 Seeland OT Gatersleben, Germany;
| | - Ahmad M. Alqudah
- Research Group Resources Genetics and Reproduction, Department Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research, 06466 Seeland OT Gatersleben, Germany;
- Correspondence: or
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Zhou P, Li Z, Magnusson E, Gomez Cano F, Crisp PA, Noshay JM, Grotewold E, Hirsch CN, Briggs SP, Springer NM. Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions. THE PLANT CELL 2020; 32:1377-1396. [PMID: 32184350 PMCID: PMC7203921 DOI: 10.1105/tpc.20.00080] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 03/06/2020] [Accepted: 03/16/2020] [Indexed: 05/22/2023]
Abstract
The regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent maps of potential transcriptional regulation. Here, we analyzed a large number of publically available maize (Zea mays) transcriptome data sets including >6000 RNA sequencing samples to generate 45 coexpression-based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, and tissue-and-genotype samples). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes. By examining the power of our coexpression-based GRNs to accurately predict covarying TF-target relationships in natural variation data sets, we found that presence/absence changes rather than quantitative changes in TF gene expression are more likely associated with changes in target gene expression. Integrating information from our TF-target predictions and previous expression quantitative trait loci (eQTL) mapping results provided support for 68 TFs underlying 74 previously identified trans-eQTL hotspots spanning a variety of metabolic pathways. This study highlights the utility of developing multiple GRNs within a species to detect putative regulators of important plant pathways and provides potential targets for breeding or biotechnological applications.
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Affiliation(s)
- Peng Zhou
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota 55108
| | - Zhi Li
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108
| | - Erika Magnusson
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota 55108
| | - Fabio Gomez Cano
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824
| | - Peter A Crisp
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota 55108
| | - Jaclyn M Noshay
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota 55108
| | - Erich Grotewold
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108
| | - Steven P Briggs
- Division of Biological Sciences, University of California, San Diego, La Jolla, California 92093
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota 55108
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Schneider HM, Klein SP, Hanlon MT, Kaeppler S, Brown KM, Lynch JP. Genetic control of root anatomical plasticity in maize. THE PLANT GENOME 2020; 13:e20003. [PMID: 33016634 DOI: 10.1002/tpg2.20003] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 11/01/2019] [Indexed: 05/06/2023]
Abstract
Root anatomical phenes have important roles in soil resource capture and plant performance; however, their phenotypic plasticity and genetic architecture is poorly understood. We hypothesized that (a) the responses of root anatomical phenes to water deficit (stress plasticity) and different environmental conditions (environmental plasticity) are genetically controlled and (b) stress and environmental plasticity are associated with different genetic loci than those controlling the expression of phenes under water-stress and well-watered conditions. Root anatomy was phenotyped in a large maize (Zea mays L.) association panel in the field with and without water deficit stress in Arizona and without water deficit stress in South Africa. Anatomical phenes displayed stress and environmental plasticity; many phenotypic responses to water deficit were adaptive, and the magnitude of response varied by genotype. We identified 57 candidate genes associated with stress and environmental plasticity and 64 candidate genes associated with phenes under well-watered and water-stress conditions in Arizona and under well-watered conditions in South Africa. Four candidate genes co-localized between plasticity groups or for phenes expressed under each condition. The genetic architecture of phenotypic plasticity is highly quantitative, and many distinct genes control plasticity in response to water deficit and different environments, which poses a challenge for breeding programs.
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Affiliation(s)
- Hannah M Schneider
- Dep. of Plant Science, Pennsylvania State Univ., University Park, PA, 16802, USA
| | - Stephanie P Klein
- Dep. of Plant Science, Pennsylvania State Univ., University Park, PA, 16802, USA
| | - Meredith T Hanlon
- Dep. of Plant Science, Pennsylvania State Univ., University Park, PA, 16802, USA
| | - Shawn Kaeppler
- Dep. of Agronomy, Univ. of Wisconsin, Madison, WI, 53706, USA
| | - Kathleen M Brown
- Dep. of Plant Science, Pennsylvania State Univ., University Park, PA, 16802, USA
| | - Jonathan P Lynch
- Dep. of Plant Science, Pennsylvania State Univ., University Park, PA, 16802, USA
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Yang W, Feng H, Zhang X, Zhang J, Doonan JH, Batchelor WD, Xiong L, Yan J. Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives. MOLECULAR PLANT 2020; 13:187-214. [PMID: 31981735 DOI: 10.1016/j.molp.2020.01.008] [Citation(s) in RCA: 232] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 01/06/2020] [Accepted: 01/10/2020] [Indexed: 05/18/2023]
Abstract
Since whole-genome sequencing of many crops has been achieved, crop functional genomics studies have stepped into the big-data and high-throughput era. However, acquisition of large-scale phenotypic data has become one of the major bottlenecks hindering crop breeding and functional genomics studies. Nevertheless, recent technological advances provide us potential solutions to relieve this bottleneck and to explore advanced methods for large-scale phenotyping data acquisition and processing in the coming years. In this article, we review the major progress on high-throughput phenotyping in controlled environments and field conditions as well as its use for post-harvest yield and quality assessment in the past decades. We then discuss the latest multi-omics research combining high-throughput phenotyping with genetic studies. Finally, we propose some conceptual challenges and provide our perspectives on how to bridge the phenotype-genotype gap. It is no doubt that accurate high-throughput phenotyping will accelerate plant genetic improvements and promote the next green revolution in crop breeding.
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Affiliation(s)
- Wanneng Yang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, P.R. China.
| | - Hui Feng
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - Xuehai Zhang
- National Key Laboratory of Wheat and Maize Crops Science/College of Agronomy, Henan Agricultural University, Zhengzhou 450002, P.R. China
| | - Jian Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - John H Doonan
- The National Plant Phenomics Centre, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
| | | | - Lizhong Xiong
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, P.R. China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, P.R. China
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Kim KH, Kim JY, Lim WJ, Jeong S, Lee HY, Cho Y, Moon JK, Kim N. Genome-wide association and epistatic interactions of flowering time in soybean cultivar. PLoS One 2020; 15:e0228114. [PMID: 31968016 PMCID: PMC6975553 DOI: 10.1371/journal.pone.0228114] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 01/07/2020] [Indexed: 12/02/2022] Open
Abstract
Genome-wide association studies (GWAS) have enabled the discovery of candidate markers that play significant roles in various complex traits in plants. Recently, with increased interest in the search for candidate markers, studies on epistatic interactions between single nucleotide polymorphism (SNP) markers have also increased, thus enabling the identification of more candidate markers along with GWAS on single-variant-additive-effect. Here, we focused on the identification of candidate markers associated with flowering time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom® SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flowering time. A total of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flowering time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flowering time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flowering pathways. Although further biological validation is needed, our results provide additional information on the existing flowering time markers and present another option to marker-assisted breeding programs for regulating flowering time of soybean.
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Affiliation(s)
- Kyoung Hyoun Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Jae-Yoon Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Won-Jun Lim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Seongmun Jeong
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
| | - Ho-Yeon Lee
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Youngbum Cho
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Jung-Kyung Moon
- National Institute of Agricultural Sciences, Rural Development Administration, Jeonju, Republic of Korea
| | - Namshin Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
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Characterization of natural genetic variation identifies multiple genes involved in salt tolerance in maize. Funct Integr Genomics 2019; 20:261-275. [PMID: 31522293 DOI: 10.1007/s10142-019-00707-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 08/02/2019] [Accepted: 08/08/2019] [Indexed: 01/03/2023]
Abstract
Progressive decline in irrigation water is forcing farmers to use brackish water which increases soil salinity and exposes the crop plants to salinity. Maize, one of the most important crops, is sensitive to salinity. Salt tolerance is a complex trait controlled by a number of physiological and biochemical processes. Scant information is available on the genetic architecture of salt tolerance in maize. We evaluated 399 inbred lines for six early vigor shoot and root traits upon exposure of 18-day seedlings to salinity (ECiw = 16 dS m-1) stress. Contrasting response of shoot and root growth to salinity indicated a meticulous reprogramming of resource partitioning by the plants to cope with the stress. The genomic analysis identified 57 single nucleotide polymorphisms (SNP) associated with early vigor traits. Candidate genes systematically associated with each SNP include both previously known and novel genes. Important candidates include a late embryogenesis protein, a divalent ion symporter, a proton extrusion protein, an RNA-binding protein, a casein kinase 1, and an AP2/EREBP transcription factor. The late embryogenesis protein is associated with both shoot and root length, indicating a coordinated change in resource allocation upon salt stress. Identification of a casein kinase 1 indicates an important role for Ser/Thr kinases in salt tolerance. Validation of eight candidates based on expression in a salt-tolerant and a salt-sensitive inbred line supported their role in salt tolerance. The candidate genes identified in this investigation provide a foundation for dissecting genetic and molecular regulation of salt tolerance in maize and related grasses.
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Zhou P, Hirsch CN, Briggs SP, Springer NM. Dynamic Patterns of Gene Expression Additivity and Regulatory Variation throughout Maize Development. MOLECULAR PLANT 2019; 12:410-425. [PMID: 30593858 DOI: 10.1016/j.molp.2018.12.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 12/14/2018] [Accepted: 12/18/2018] [Indexed: 05/26/2023]
Abstract
Gene expression variation is a key component underlying phenotypic variation and heterosis. Transcriptome profiling was performed on 23 different tissues or developmental stages of two maize inbreds, B73 and Mo17, as well as their F1 hybrid. The obtained large-scale datasets provided opportunities to monitor the developmental dynamics of differential expression, additivity for gene expression, and regulatory variation. The transcriptome can be divided into ∼30 000 genes that are expressed in at least one tissue of one inbred and an additional ∼10 000 ″silent" genes that are not expressed in any tissue of any genotype, 90% of which are non-syntenic relative to other grasses. Many (∼74%) of the expressed genes exhibit differential expression in at least one tissue. However, the majority of genes with differential expression do not exhibit consistent differential expression in different tissues. These genes often exhibit tissue-specific differential expression with equivalent expression in other tissues, and in many cases they switch the directionality of differential expression in different tissues. This suggests widespread variation for tissue-specific regulation of gene expression between the two maize inbreds B73 and Mo17. Nearly 5000 genes are expressed in only one parent in at least one tissue (single parent expression) and 97% of these genes are expressed at mid-parent levels or higher in the hybrid, providing extensive opportunities for hybrid complementation in heterosis. In general, additive expression patterns are much more common than non-additive patterns, and this trend is more pronounced for genes with strong differential expression or single parent expression. There is relatively little evidence for non-additive expression patterns that are maintained in multiple tissues. The analysis of allele-specific expression allowed classification of cis- and trans-regulatory variation. Genes with cis-regulatory variation often exhibit additive expression and tend to have more consistent regulatory variation throughout development. In contrast, genes with trans-regulatory variation are enriched for non-additive patterns and often show tissue-specific differential expression. Taken together, this study provides a deeper understanding of regulatory variation and the degree of additive gene expression throughout maize development. The dynamic nature of differential expression, additivity, and regulatory variation imply abundant variability for tissue-specific regulatory mechanisms and suggest that connections between transcriptome and phenome will require expression data from multiple tissues.
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Affiliation(s)
- Peng Zhou
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN 55108, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, Saint Paul, MN 55108, USA
| | - Steven P Briggs
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN 55108, USA.
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