1
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He C, Washburn JD, Schleif N, Hao Y, Kaeppler H, Kaeppler SM, Zhang Z, Yang J, Liu S. Trait association and prediction through integrative k-mer analysis. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024. [PMID: 39259496 DOI: 10.1111/tpj.17012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 08/14/2024] [Accepted: 08/22/2024] [Indexed: 09/13/2024]
Abstract
Genome-wide association study (GWAS) with single nucleotide polymorphisms (SNPs) has been widely used to explore genetic controls of phenotypic traits. Alternatively, GWAS can use counts of substrings of length k from longer sequencing reads, k-mers, as genotyping data. Using maize cob and kernel color traits, we demonstrated that k-mer GWAS can effectively identify associated k-mers. Co-expression analysis of kernel color k-mers and genes directly found k-mers from known causal genes. Analyzing complex traits of kernel oil and leaf angle resulted in k-mers from both known and candidate genes. A gene encoding a MADS transcription factor was functionally validated by showing that ectopic expression of the gene led to less upright leaves. Evolution analysis revealed most k-mers positively correlated with kernel oil were strongly selected against in maize populations, while most k-mers for upright leaf angle were positively selected. In addition, genomic prediction of kernel oil, leaf angle, and flowering time using k-mer data resulted in a similarly high prediction accuracy to the standard SNP-based method. Collectively, we showed k-mer GWAS is a powerful approach for identifying trait-associated genetic elements. Further, our results demonstrated the bridging role of k-mers for data integration and functional gene discovery.
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Affiliation(s)
- Cheng He
- Department of Plant Pathology, Kansas State University, Manhattan, Kansas, 66506, USA
| | - Jacob D Washburn
- Plant Genetics Research Unit, USDA-ARS, Columbia, Missouri, 65211, USA
| | - Nathaniel Schleif
- Department of Agronomy, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Yangfan Hao
- Department of Plant Pathology, Kansas State University, Manhattan, Kansas, 66506, USA
| | - Heidi Kaeppler
- Department of Agronomy, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Shawn M Kaeppler
- Department of Agronomy, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Zhiwu Zhang
- Department of Crop and Soil Sciences, Washington State University, Pullman, Washington, 99164, USA
| | - Jinliang Yang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska, 68583-0915, USA
- Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, Nebraska, 68583, USA
| | - Sanzhen Liu
- Department of Plant Pathology, Kansas State University, Manhattan, Kansas, 66506, USA
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2
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Mishra S, Srivastava AK, Khan AW, Tran LSP, Nguyen HT. The era of panomics-driven gene discovery in plants. TRENDS IN PLANT SCIENCE 2024; 29:995-1005. [PMID: 38658292 DOI: 10.1016/j.tplants.2024.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 03/01/2024] [Accepted: 03/08/2024] [Indexed: 04/26/2024]
Abstract
Panomics is an approach to integrate multiple 'omics' datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.
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Affiliation(s)
- Shefali Mishra
- Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai, Maharashtra 400085, India
| | - Ashish Kumar Srivastava
- Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai, Maharashtra 400085, India; Homi Bhabha National Institute, Mumbai 400094, India.
| | - Aamir W Khan
- Division of Plant Science and Technology and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211, USA
| | - Lam-Son Phan Tran
- Institute of Genomics for Crop Abiotic Stress Tolerance, Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, USA
| | - Henry T Nguyen
- Division of Plant Science and Technology and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211, USA.
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3
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Catlin NS, Agha HI, Platts AE, Munasinghe M, Hirsch CN, Josephs EB. Structural variants contribute to phenotypic variation in maize. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.14.599082. [PMID: 38948717 PMCID: PMC11212879 DOI: 10.1101/2024.06.14.599082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Comprehensively identifying the loci shaping trait variation has been challenging, in part because standard approaches often miss many types of genetic variants. Structural variants, especially transposable elements are likely to affect phenotypic variation but we need better methods in maize for detecting polymorphic structural variants and TEs using short-read sequencing data. Here, we used a whole genome alignment between two maize genotypes to identify polymorphic structural variants and then genotyped a large maize diversity panel for these variants using short-read sequencing data. We characterized variation of SVs within the panel and identified SV polymorphisms that are associated with life history traits and genotype-by-environment interactions. While most of the SVs associated with traits contained TEs, only one of the SV's boundaries clearly matched TE breakpoints indicative of a TE insertion, whereas the other polymorphisms were likely caused by deletions. All of the SVs associated with traits were in linkage disequilibrium with nearby single nucleotide polymorphisms (SNPs), suggesting that this method did not identify variants that would have been missed in a SNP association study.
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Affiliation(s)
- Nathan S. Catlin
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
- Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, MI, 48824, USA
- Plant Resilience Institute, Michigan State University, East Lansing, MI, 48824, USA
| | - Husain I. Agha
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
- Plant Resilience Institute, Michigan State University, East Lansing, MI, 48824, USA
| | - Adrian E. Platts
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Manisha Munasinghe
- 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
| | - Emily B. Josephs
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
- Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, MI, 48824, USA
- Plant Resilience Institute, Michigan State University, East Lansing, MI, 48824, USA
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4
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Fang C, Jiang N, Teresi SJ, Platts AE, Agarwal G, Niederhuth C, Edger PP, Jiang J. Dynamics of accessible chromatin regions and subgenome dominance in octoploid strawberry. Nat Commun 2024; 15:2491. [PMID: 38509076 PMCID: PMC10954716 DOI: 10.1038/s41467-024-46861-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 03/12/2024] [Indexed: 03/22/2024] Open
Abstract
Subgenome dominance has been reported in diverse allopolyploid species, where genes from one subgenome are preferentially retained and are more highly expressed than those from other subgenome(s). However, the molecular mechanisms responsible for subgenome dominance remain poorly understood. Here, we develop genome-wide map of accessible chromatin regions (ACRs) in cultivated strawberry (2n = 8x = 56, with A, B, C, D subgenomes). Each ACR is identified as an MNase hypersensitive site (MHS). We discover that the dominant subgenome A contains a greater number of total MHSs and MHS per gene than the submissive B/C/D subgenomes. Subgenome A suffers fewer losses of MHS-related DNA sequences and fewer MHS fragmentations caused by insertions of transposable elements. We also discover that genes and MHSs related to stress response have been preferentially retained in subgenome A. We conclude that preservation of genes and their cognate ACRs, especially those related to stress responses, play a major role in the establishment of subgenome dominance in octoploid strawberry.
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Affiliation(s)
- Chao Fang
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Ning Jiang
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
- Michigan State University AgBioResearch, East Lansing, MI, 48824, USA
- Genetics and Genome Sciences Program, Michigan State University, East Lansing, MI, 48824, USA
| | - Scott J Teresi
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
- Genetics and Genome Sciences Program, Michigan State University, East Lansing, MI, 48824, USA
| | - Adrian E Platts
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA
| | - Gaurav Agarwal
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Chad Niederhuth
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
- Michigan State University AgBioResearch, East Lansing, MI, 48824, USA
| | - Patrick P Edger
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA.
- Michigan State University AgBioResearch, East Lansing, MI, 48824, USA.
- Genetics and Genome Sciences Program, Michigan State University, East Lansing, MI, 48824, USA.
| | - Jiming Jiang
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA.
- Department of Horticulture, Michigan State University, East Lansing, MI, 48824, USA.
- Michigan State University AgBioResearch, East Lansing, MI, 48824, USA.
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5
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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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6
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de Tomás C, Vicient CM. The Genomic Shock Hypothesis: Genetic and Epigenetic Alterations of Transposable Elements after Interspecific Hybridization in Plants. EPIGENOMES 2023; 8:2. [PMID: 38247729 PMCID: PMC10801548 DOI: 10.3390/epigenomes8010002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 12/21/2023] [Accepted: 12/24/2023] [Indexed: 01/23/2024] Open
Abstract
Transposable elements (TEs) are major components of plant genomes with the ability to change their position in the genome or to create new copies of themselves in other positions in the genome. These can cause gene disruption and large-scale genomic alterations, including inversions, deletions, and duplications. Host organisms have evolved a set of mechanisms to suppress TE activity and counter the threat that they pose to genome integrity. These includes the epigenetic silencing of TEs mediated by a process of RNA-directed DNA methylation (RdDM). In most cases, the silencing machinery is very efficient for the vast majority of TEs. However, there are specific circumstances in which TEs can evade such silencing mechanisms, for example, a variety of biotic and abiotic stresses or in vitro culture. Hybridization is also proposed as an inductor of TE proliferation. In fact, the discoverer of the transposons, Barbara McClintock, first hypothesized that interspecific hybridization provides a "genomic shock" that inhibits the TE control mechanisms leading to the mobilization of TEs. However, the studies carried out on this topic have yielded diverse results, showing in some cases a total absence of mobilization or being limited to only some TE families. Here, we review the current knowledge about the impact of interspecific hybridization on TEs in plants and the possible implications of changes in the epigenetic mechanisms.
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Affiliation(s)
| | - Carlos M. Vicient
- Centre for Research in Agricultural Genomics, CRAG (CSIC-IRTA-UAB-UB), Campus UAB, Cerdanyola del Vallès, 08193 Barcelona, Spain
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7
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Munasinghe M, Read A, Stitzer MC, Song B, Menard CC, Ma KY, Brandvain Y, Hirsch CN, Springer N. Combined analysis of transposable elements and structural variation in maize genomes reveals genome contraction outpaces expansion. PLoS Genet 2023; 19:e1011086. [PMID: 38134220 PMCID: PMC10773942 DOI: 10.1371/journal.pgen.1011086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 01/08/2024] [Accepted: 11/28/2023] [Indexed: 12/24/2023] Open
Abstract
Structural differences between genomes are a major source of genetic variation that contributes to phenotypic differences. Transposable elements, mobile genetic sequences capable of increasing their copy number and propagating themselves within genomes, can generate structural variation. However, their repetitive nature makes it difficult to characterize fine-scale differences in their presence at specific positions, limiting our understanding of their impact on genome variation. Domesticated maize is a particularly good system for exploring the impact of transposable element proliferation as over 70% of the genome is annotated as transposable elements. High-quality transposable element annotations were recently generated for de novo genome assemblies of 26 diverse inbred maize lines. We generated base-pair resolved pairwise alignments between the B73 maize reference genome and the remaining 25 inbred maize line assemblies. From this data, we classified transposable elements as either shared or polymorphic in a given pairwise comparison. Our analysis uncovered substantial structural variation between lines, representing both simple and complex connections between TEs and structural variants. Putative insertions in SNP depleted regions, which represent recently diverged identity by state blocks, suggest some TE families may still be active. However, our analysis reveals that within these recently diverged genomic regions, deletions of transposable elements likely account for more structural variation events and base pairs than insertions. These deletions are often large structural variants containing multiple transposable elements. Combined, our results highlight how transposable elements contribute to structural variation and demonstrate that deletion events are a major contributor to genomic differences.
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Affiliation(s)
- Manisha Munasinghe
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Andrew Read
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota, United States of America
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Michelle C. Stitzer
- Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, United States of America
| | - Baoxing Song
- Peking University Institute of Advanced Agricultural Sciences, Weifang, China
| | - Claire C. Menard
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Kristy Yubo Ma
- Department of Mathematics, Statistics, and Computer Science, Macalester College, St. Paul, Minnesota, United States of America
| | - Yaniv Brandvain
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota, United States of America
- Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Candice N. Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Nathan Springer
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota, United States of America
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8
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Della Coletta R, Fernandes SB, Monnahan PJ, Mikel MA, Bohn MO, Lipka AE, Hirsch CN. Importance of genetic architecture in marker selection decisions for genomic prediction. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:220. [PMID: 37819415 DOI: 10.1007/s00122-023-04469-w] [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: 02/28/2023] [Accepted: 09/25/2023] [Indexed: 10/13/2023]
Abstract
KEY MESSAGE We demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on the genetic architecture of the trait. Breeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy, but it is highly dependent on the genetic architecture of the trait and the relative gain in accuracy is minimal. When SVs are the only causative variant type, 70% of the time SV predictors outperform SNP predictors. However, the improvement in accuracy in these instances is only 1.5% on average. Further simulations with predictors in varying degrees of LD with causative variants of different types (e.g., SNPs, SVs, SNPs and SVs) showed that prediction accuracy increased as linkage disequilibrium between causative variants and predictors increased regardless of the marker type. This study demonstrates that knowing the genetic architecture of a trait in deciding what markers to use in large-scale genomic prediction modeling in a breeding program is more important than what types of markers to use.
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Affiliation(s)
- Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Samuel B Fernandes
- Department of Crop, Soil and Environmental Sciences at University of Arkansas, Fayetteville, AR, 72701, USA
| | - Patrick J Monnahan
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Mark A Mikel
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Martin O Bohn
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
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9
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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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10
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Liang Z, Myers ZA, Petrella D, Engelhorn J, Hartwig T, Springer NM. Mapping responsive genomic elements to heat stress in a maize diversity panel. Genome Biol 2022; 23:234. [PMID: 36345007 PMCID: PMC9639295 DOI: 10.1186/s13059-022-02807-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 10/29/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Many plant species exhibit genetic variation for coping with environmental stress. However, there are still limited approaches to effectively uncover the genomic region that regulates distinct responsive patterns of the gene across multiple varieties within the same species under abiotic stress. RESULTS By analyzing the transcriptomes of more than 100 maize inbreds, we reveal many cis- and trans-acting eQTLs that influence the expression response to heat stress. The cis-acting eQTLs in response to heat stress are identified in genes with differential responses to heat stress between genotypes as well as genes that are only expressed under heat stress. The cis-acting variants for heat stress-responsive expression likely result from distinct promoter activities, and the differential heat responses of the alleles are confirmed for selected genes using transient expression assays. Global footprinting of transcription factor binding is performed in control and heat stress conditions to document regions with heat-enriched transcription factor binding occupancies. CONCLUSIONS Footprints enriched near proximal regions of characterized heat-responsive genes in a large association panel can be utilized for prioritizing functional genomic regions that regulate genotype-specific responses under heat stress.
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Affiliation(s)
- Zhikai Liang
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN, 55108, USA.
| | - Zachary A Myers
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Dominic Petrella
- Department of Horticulture, University of Minnesota, Saint Paul, MN, 55108, USA
- Present address: Agricultural Technical Institute, The Ohio State University, Wooster, OH, 44691, USA
| | - Julia Engelhorn
- Max Planck Institute for Plant Breeding Research, 50829, Cologne, Germany
- Heinrich-Heine University, 40225, Dusseldorf, Germany
| | - Thomas Hartwig
- Max Planck Institute for Plant Breeding Research, 50829, Cologne, Germany
- Heinrich-Heine University, 40225, Dusseldorf, Germany
| | - Nathan M Springer
- Department of Plant and Microbial Biology, University of Minnesota, Saint Paul, MN, 55108, USA.
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11
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Genetic Analysis and Fine Mapping of ZmGHT1 Conferring Glufosinate Herbicide Tolerance in Maize (Zea mays L.). Int J Mol Sci 2022; 23:ijms231911481. [PMID: 36232781 PMCID: PMC9570099 DOI: 10.3390/ijms231911481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 09/15/2022] [Accepted: 09/26/2022] [Indexed: 11/17/2022] Open
Abstract
Weed interference in the crop field is one of the major biotic stresses causing dramatic crop yield losses, and the development of herbicide-resistant crops is critical for weed control in the application of herbicide technologies. To identify herbicide-resistant germplasms, we screened 854 maize inbreed lines and 25,620 seedlings by spraying them with 1 g/L glufosinate. One plant (L336R), possibly derived from a natural variation of line L336, was identified to have the potential for glufosinate tolerance. Genetic analysis validated that the glufosinate tolerance of L336R is conferred by a single locus, which was tentatively designated as ZmGHT1. By constructing a bi-parental population derived from L336R, and a glufosinate sensitive line L312, ZmGHT1 was mapped between molecular markers M9 and M10. Interestingly, genomic comparation between the two sequenced reference genomes showed that large scale structural variations (SVs) occurred within the mapped region, resulting in 2.16 Mb in the inbreed line B73, and 11.5 kb in CML277, respectively. During the fine mapping process, we did not detect any additional recombinant, even by using more than 9500 F2 and F3 plants, suspecting that SVs should also have occurred between L336R and L312 in this region, which inhibited recombination. By evaluating the expression of the genes within the mapped interval and using functional annotation, we predict that the gene Zm00001eb361930, encoding an aminotransferase, is the most likely causative gene. After glufosinate treatment, lower levels of ammonia content and a higher activity of glutamine synthetase (GS) in L336R were detected compared with those of L336 and L312, suggesting that the target gene may participate in ammonia elimination involving GS activity. Collectively, our study can provide a material resource for maize herbicide resistant breeding, with the potential to reveal a new mechanism for herbicide resistance.
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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:giac080. [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] [MESH Headings] [Grants] [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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