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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. Theor Appl Genet 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] [What about the content of this article? (0)] [Affiliation(s)] [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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2
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Della Coletta R, Liese SE, Fernandes SB, Mikel MA, Bohn MO, Lipka AE, Hirsch CN. Linking genetic and environmental factors through marker effect networks to understand trait plasticity. Genetics 2023; 224:iyad103. [PMID: 37246567 DOI: 10.1093/genetics/iyad103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 05/19/2023] [Accepted: 05/24/2023] [Indexed: 05/30/2023] Open
Abstract
Understanding how plants adapt to specific environmental changes and identifying genetic markers associated with phenotypic plasticity can help breeders develop plant varieties adapted to a rapidly changing climate. Here, we propose the use of marker effect networks as a novel method to identify markers associated with environmental adaptability. These marker effect networks are built by adapting commonly used software for building gene coexpression networks with marker effects across growth environments as the input data into the networks. To demonstrate the utility of these networks, we built networks from the marker effects of ∼2,000 nonredundant markers from 400 maize hybrids across 9 environments. We demonstrate that networks can be generated using this approach, and that the markers that are covarying are rarely in linkage disequilibrium, thus representing higher biological relevance. Multiple covarying marker modules associated with different weather factors throughout the growing season were identified within the marker effect networks. Finally, a factorial test of analysis parameters demonstrated that marker effect networks are relatively robust to these options, with high overlap in modules associated with the same weather factors across analysis parameters. This novel application of network analysis provides unique insights into phenotypic plasticity and specific environmental factors that modulate the genome.
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Affiliation(s)
- Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Sharon E Liese
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Samuel B Fernandes
- Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR 72701, 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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3
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Fernandes SB, Casstevens TM, Bradbury PJ, Lipka AE. A multi-trait multi-locus stepwise approach for conducting GWAS on correlated traits. Plant Genome 2022; 15:e20200. [PMID: 35307964 DOI: 10.1002/tpg2.20200] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 02/14/2022] [Indexed: 06/14/2023]
Abstract
The ability to accurately quantify the simultaneous effect of multiple genomic loci on multiple traits is now possible due to current and emerging high-throughput genotyping and phenotyping technologies. To date, most efforts to quantify these genotype-to-phenotype relationships have focused on either multi-trait models that test a single marker at a time or multi-locus models that quantify associations with a single trait. Therefore, the purpose of this study was to compare the performance of a multi-trait, multi-locus stepwise (MSTEP) model selection procedure we developed to (a) a commonly used multi-trait single-locus model and (b) a univariate multi-locus model. We used real marker data in maize (Zea mays L.) and soybean (Glycine max L.) to simulate multiple traits controlled by various combinations of pleiotropic and nonpleiotropic quantitative trait nucleotides (QTNs). In general, we found that both multi-trait models outperformed the univariate multi-locus model, especially when analyzing a trait of low heritability. For traits controlled by either a combination of pleiotropic and nonpleiotropic QTNs or a large number of QTNs (i.e., 50), our MSTEP model often outperformed at least one of the two alternative models. When applied to the analysis of two tocochromanol-related traits in maize grain, MSTEP identified the same peak-associated marker that has been reported in a previous study. We therefore conclude that MSTEP is a useful addition to the suite of statistical models that are commonly used to gain insight into the genetic architecture of agronomically important traits.
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Affiliation(s)
- Samuel B Fernandes
- Dep. of Crop Sciences, Univ. of Illinois Urbana-Champaign, Urbana, IL, USA
| | | | | | - Alexander E Lipka
- Dep. of Crop Sciences, Univ. of Illinois Urbana-Champaign, Urbana, IL, USA
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4
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Murphy MD, Fernandes SB, Morota G, Lipka AE. Assessment of two statistical approaches for variance genome-wide association studies in plants. Heredity (Edinb) 2022; 129:93-102. [PMID: 35538221 PMCID: PMC9338250 DOI: 10.1038/s41437-022-00541-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 11/09/2022] Open
Abstract
Genomic loci that control the variance of agronomically important traits are increasingly important due to the profusion of unpredictable environments arising from climate change. The ability to identify such variance-controlling loci in association studies will be critical for future breeding efforts. Two statistical approaches that have already been used in the variance genome-wide association study (vGWAS) paradigm are the Brown-Forsythe test (BFT) and the double generalized linear model (DGLM). To ensure that these approaches are deployed as effectively as possible, it is critical to study the factors that influence their ability to identify variance-controlling loci. We used genome-wide marker data in maize (Zea mays L.) and Arabidopsis thaliana to simulate traits controlled by epistasis, genotype by environment (GxE) interactions, and variance quantitative trait nucleotides (vQTNs). We then quantified true and false positive detection rates of the BFT and DGLM across all simulated traits. We also conducted a vGWAS using both the BFT and DGLM on plant height in a maize diversity panel. The observed true positive detection rates at the maximum sample size considered (N = 2815) suggest that both of these vGWAS approaches are capable of identifying epistasis and GxE for sufficiently large sample sizes. We also noted that the DGLM decisively outperformed the BFT for simulated traits controlled by vQTNs at sample sizes of N = 500. Although we conclude that there are still certain aspects of vGWAS approaches that need further refinement, this study suggests that the BFT and DGLM are capable of identifying variance-controlling loci in current state-of-the-art plant or agronomic data sets.
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Affiliation(s)
- Matthew D Murphy
- Department of Crop Sciences, University of Illinois Urbana-Champaign, 1102 S Goodwin Ave, Urbana, IL, 61801, USA
| | - Samuel B Fernandes
- Department of Crop Sciences, University of Illinois Urbana-Champaign, 1102 S Goodwin Ave, Urbana, IL, 61801, USA
| | - Gota Morota
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, 175 West Campus Drive, Blacksburg, VA, 24061, USA
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois Urbana-Champaign, 1102 S Goodwin Ave, Urbana, IL, 61801, USA.
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5
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Pignon CP, Fernandes SB, Valluru R, Bandillo N, Lozano R, Buckler E, Gore MA, Long SP, Brown PJ, Leakey ADB. Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes. Plant Physiol 2021; 187:2544-2562. [PMID: 34618072 PMCID: PMC8644692 DOI: 10.1093/plphys/kiab395] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 07/26/2021] [Indexed: 05/07/2023]
Abstract
Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.
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Affiliation(s)
- Charles P Pignon
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Samuel B Fernandes
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Ravi Valluru
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
- Lincoln Institute for Agri-Food Technology, University of Lincoln, Lincoln LN1 3QE, UK
| | - Nonoy Bandillo
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota 58105, USA
| | - Roberto Lozano
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, USA
| | - Edward Buckler
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, USA
- United States Department of Agriculture, Agricultural Research Service (USDA-ARS) R.W. Holley Center for Agriculture and Health, Ithaca, New York 14853, USA
| | - Michael A Gore
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, USA
| | - Stephen P Long
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Lancaster Environment Centre, University of Lancaster, Lancaster LA1 1YX, UK
| | - Patrick J Brown
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Andrew D B Leakey
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
- Author for communication:
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6
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Ferguson JN, Fernandes SB, Monier B, Miller ND, Allen D, Dmitrieva A, Schmuker P, Lozano R, Valluru R, Buckler ES, Gore MA, Brown PJ, Spalding EP, Leakey ADB. Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions. Plant Physiol 2021; 187:1481-1500. [PMID: 34618065 PMCID: PMC9040483 DOI: 10.1093/plphys/kiab346] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 06/29/2021] [Indexed: 05/04/2023]
Abstract
Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.
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Affiliation(s)
- John N Ferguson
- Institute for Genomic Biology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Samuel B Fernandes
- Institute for Genomic Biology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Brandon Monier
- Institute for Genomic Diversity, Cornell University, Ithaca, New
York 14853, USA
| | - Nathan D Miller
- Department of Botany, University of Wisconsin, Madison, Wisconsin
53706, USA
| | - Dylan Allen
- Institute for Genomic Biology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Anna Dmitrieva
- Institute for Genomic Biology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Peter Schmuker
- Institute for Genomic Biology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Roberto Lozano
- Plant Breeding and Genetics Section, School of Integrative Plant Science,
Cornell University, Ithaca, New York 14853, USA
| | - Ravi Valluru
- Institute for Genomic Diversity, Cornell University, Ithaca, New
York 14853, USA
- Present address: Lincoln Institute for Agri-Food Technology,
University of Lincoln, Lincoln LN2 2LG, UK
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, New
York 14853, USA
- Plant Breeding and Genetics Section, School of Integrative Plant Science,
Cornell University, Ithaca, New York 14853, USA
| | - Michael A Gore
- Plant Breeding and Genetics Section, School of Integrative Plant Science,
Cornell University, Ithaca, New York 14853, USA
| | - Patrick J Brown
- Institute for Genomic Biology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
- Present address: Section of Agricultural Plant Biology,
Department of Plant Sciences, University of California Davis, California 95616,
USA
| | - Edgar P Spalding
- Department of Botany, University of Wisconsin, Madison, Wisconsin
53706, USA
| | - Andrew D B Leakey
- Institute for Genomic Biology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
- Department of Crop Sciences, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
- Department of Plant Biology, University of Illinois at
Urbana-Champaign, Urbana, Illinois 61901, USA
- Author for communication: ,
Present address: Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA,
UK
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7
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Xie J, Fernandes SB, Mayfield-Jones D, Erice G, Choi M, E Lipka A, Leakey ADB. Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping. Plant Physiol 2021; 187:1462-1480. [PMID: 34618057 PMCID: PMC8566313 DOI: 10.1093/plphys/kiab299] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 05/26/2021] [Indexed: 05/03/2023]
Abstract
Stomata are adjustable pores on leaf surfaces that regulate the tradeoff of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping epidermal cell traits have limited discoveries about the genetic basis of stomatal patterning. A high-throughput epidermal cell phenotyping pipeline is presented here and used for quantitative trait loci (QTL) mapping in field-grown maize (Zea mays). The locations and sizes of stomatal complexes and pavement cells on images acquired by an optical topometer from mature leaves were automatically determined. Computer estimated stomatal complex density (SCD; R2 = 0.97) and stomatal complex area (SCA; R2 = 0.71) were strongly correlated with human measurements. Leaf gas exchange traits were genetically correlated with the dimensions and proportions of stomatal complexes (rg = 0.39-0.71) but did not correlate with SCD. Heritability of epidermal traits was moderate to high (h2 = 0.42-0.82) across two field seasons. Thirty-six QTL were consistently identified for a given trait in both years. Twenty-four clusters of overlapping QTL for multiple traits were identified, with univariate versus multivariate single marker analysis providing evidence consistent with pleiotropy in multiple cases. Putative orthologs of genes known to regulate stomatal patterning in Arabidopsis (Arabidopsis thaliana) were located within some, but not all, of these regions. This study demonstrates how discovery of the genetic basis for stomatal patterning can be accelerated in maize, a C4 model species where these processes are poorly understood.
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Affiliation(s)
- Jiayang Xie
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Samuel B Fernandes
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Center for Digital Agriculture, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Dustin Mayfield-Jones
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Center for Digital Agriculture, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Gorka Erice
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Min Choi
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Center for Digital Agriculture, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Andrew D B Leakey
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Center for Digital Agriculture, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Author for communication: , cor2">Present address: Agrotecnologías Naturales S.L., 43762 Tarragona, Spain
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8
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Ferguson JN, Fernandes SB, Monier B, Miller ND, Allen D, Dmitrieva A, Schmuker P, Lozano R, Valluru R, Buckler ES, Gore MA, Brown PJ, Spalding EP, Leakey ADB. Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions. Plant Physiol 2021; 187:1481-1500. [PMID: 34618065 DOI: 10.1093/plphys/kiab34] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 06/29/2021] [Indexed: 05/27/2023]
Abstract
Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.
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Affiliation(s)
- John N Ferguson
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Samuel B Fernandes
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Brandon Monier
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
| | - Nathan D Miller
- Department of Botany, University of Wisconsin, Madison, Wisconsin 53706, USA
| | - Dylan Allen
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Anna Dmitrieva
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Peter Schmuker
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Roberto Lozano
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, USA
| | - Ravi Valluru
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
| | - Edward S Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, USA
| | - Michael A Gore
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, USA
| | - Patrick J Brown
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
| | - Edgar P Spalding
- Department of Botany, University of Wisconsin, Madison, Wisconsin 53706, USA
| | - Andrew D B Leakey
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
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Fernandes SB, Frigotto KG, Garcia GSB, Valviesse VRA. ALTERAÇÕES HEMATOLÓGICAS BENIGNAS EM PACIENTES INFECTADOS PELO HIV ACOMPANHADOS NO HOSPITAL UNIVERSITÁRIO GAFRÉE GUINLE. Hematol Transfus Cell Ther 2021. [DOI: 10.1016/j.htct.2021.10.071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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10
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Jaikumar NS, Stutz SS, Fernandes SB, Leakey ADB, Bernacchi CJ, Brown PJ, Long SP. Can improved canopy light transmission ameliorate loss of photosynthetic efficiency in the shade? An investigation of natural variation in Sorghum bicolor. J Exp Bot 2021; 72:4965-4980. [PMID: 33914063 PMCID: PMC8219039 DOI: 10.1093/jxb/erab176] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Accepted: 04/28/2021] [Indexed: 05/29/2023]
Abstract
Previous studies have found that maximum quantum yield of CO2 assimilation (Φ CO2,max,app) declines in lower canopies of maize and miscanthus, a maladaptive response to self-shading. These observations were limited to single genotypes, leaving it unclear whether the maladaptive shade response is a general property of this C4 grass tribe, the Andropogoneae. We explored the generality of this maladaptation by testing the hypothesis that erect leaf forms (erectophiles), which allow more light into the lower canopy, suffer less of a decline in photosynthetic efficiency than drooping leaf (planophile) forms. On average, Φ CO2,max,app declined 27% in lower canopy leaves across 35 accessions, but the decline was over twice as great in planophiles than in erectophiles. The loss of photosynthetic efficiency involved a decoupling between electron transport and assimilation. This was not associated with increased bundle sheath leakage, based on 13C measurements. In both planophiles and erectophiles, shaded leaves had greater leaf absorptivity and lower activities of key C4 enzymes than sun leaves. The erectophile form is considered more productive because it allows a more effective distribution of light through the canopy to support photosynthesis. We show that in sorghum, it provides a second benefit, maintenance of higher Φ CO2,max,app to support efficient use of that light resource.
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Affiliation(s)
- Nikhil S Jaikumar
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Samantha S Stutz
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Samuel B Fernandes
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Andrew D B Leakey
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Carl J Bernacchi
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- USDA ARS Global Change and Photosynthesis Research Unit, Urbana, IL 61801, USA
| | - Patrick J Brown
- Department of Plant Sciences, University of California at Davis, Davis, CA 95616, USA
| | - Stephen P Long
- Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Lancaster Environment Centre, University of Lancaster, Lancaster LA1 4YQ, UK
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11
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Fernandes SB, Zhang KS, Jamann TM, Lipka AE. How Well Can Multivariate and Univariate GWAS Distinguish Between True and Spurious Pleiotropy? Front Genet 2021; 11:602526. [PMID: 33584799 PMCID: PMC7873880 DOI: 10.3389/fgene.2020.602526] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 12/11/2020] [Indexed: 11/13/2022] Open
Abstract
Quantification of the simultaneous contributions of loci to multiple traits, a phenomenon called pleiotropy, is facilitated by the increased availability of high-throughput genotypic and phenotypic data. To understand the prevalence and nature of pleiotropy, the ability of multivariate and univariate genome-wide association study (GWAS) models to distinguish between pleiotropic and non-pleiotropic loci in linkage disequilibrium (LD) first needs to be evaluated. Therefore, we used publicly available maize and soybean genotypic data to simulate multiple pairs of traits that were either (i) controlled by quantitative trait nucleotides (QTNs) on separate chromosomes, (ii) controlled by QTNs in various degrees of LD with each other, or (iii) controlled by a single pleiotropic QTN. We showed that multivariate GWAS could not distinguish between QTNs in LD and a single pleiotropic QTN. In contrast, a unique QTN detection rate pattern was observed for univariate GWAS whenever the simulated QTNs were in high LD or pleiotropic. Collectively, these results suggest that multivariate and univariate GWAS should both be used to infer whether or not causal mutations underlying peak GWAS associations are pleiotropic. Therefore, we recommend that future studies use a combination of multivariate and univariate GWAS models, as both models could be useful for identifying and narrowing down candidate loci with potential pleiotropic effects for downstream biological experiments.
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Affiliation(s)
- Samuel B. Fernandes
- Department of Crop Science, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | | | | | - Alexander E. Lipka
- Department of Crop Science, University of Illinois at Urbana-Champaign, Urbana, IL, United States
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12
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Lozano R, Gazave E, Dos Santos JPR, Stetter MG, Valluru R, Bandillo N, Fernandes SB, Brown PJ, Shakoor N, Mockler TC, Cooper EA, Taylor Perkins M, Buckler ES, Ross-Ibarra J, Gore MA. Comparative evolutionary genetics of deleterious load in sorghum and maize. Nat Plants 2021; 7:17-24. [PMID: 33452486 DOI: 10.1038/s41477-020-00834-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 12/09/2020] [Indexed: 06/12/2023]
Abstract
Sorghum and maize share a close evolutionary history that can be explored through comparative genomics1,2. To perform a large-scale comparison of the genomic variation between these two species, we analysed ~13 million variants identified from whole-genome resequencing of 499 sorghum lines together with 25 million variants previously identified in 1,218 maize lines. Deleterious mutations in both species were prevalent in pericentromeric regions, enriched in non-syntenic genes and present at low allele frequencies. A comparison of deleterious burden between sorghum and maize revealed that sorghum, in contrast to maize, departed from the domestication-cost hypothesis that predicts a higher deleterious burden among domesticates compared with wild lines. Additionally, sorghum and maize population genetic summary statistics were used to predict a gene deleterious index with an accuracy greater than 0.5. This research represents a key step towards understanding the evolutionary dynamics of deleterious variants in sorghum and provides a comparative genomics framework to start prioritizing these variants for removal through genome editing and breeding.
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Affiliation(s)
- Roberto Lozano
- Plant Breeding and Genetics, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Elodie Gazave
- Plant Breeding and Genetics, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
- Institute of Biotechnology, Cornell University, Ithaca, NY, USA
| | - Jhonathan P R Dos Santos
- Plant Breeding and Genetics, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil
| | - Markus G Stetter
- Botanical Institute, Biozentrum, University of Cologne, Cologne, Germany
| | - Ravi Valluru
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA
- University of Lincoln, Lincoln, UK
| | - Nonoy Bandillo
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA
- Department of Plant Sciences, North Dakota State University, Fargo, ND, USA
| | - Samuel B Fernandes
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Patrick J Brown
- Department of Plant Sciences, University of California Davis, Davis, CA, USA
| | - Nadia Shakoor
- Donald Danforth Plant Science Center, St. Louis, MO, USA
| | - Todd C Mockler
- Donald Danforth Plant Science Center, St. Louis, MO, USA
| | - Elizabeth A Cooper
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - M Taylor Perkins
- Department of Evolution and Ecology, University of California Davis, Davis, CA, USA
| | - Edward S Buckler
- Plant Breeding and Genetics, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
- Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA
- United States Department of Agriculture, Agricultural Research Service (USDA-ARS) R. W. Holley Center for Agriculture and Health, Ithaca, NY, USA
| | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology, University of California Davis, Davis, CA, USA.
- Center for Population Biology and Genome Center, University of California Davis, Davis, CA, USA.
| | - Michael A Gore
- Plant Breeding and Genetics, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA.
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13
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Abstract
BACKGROUND Advances in genotyping and phenotyping techniques have enabled the acquisition of a great amount of data. Consequently, there is an interest in multivariate statistical analyses that identify genomic regions likely to contain causal mutations affecting multiple traits (i.e., pleiotropy). As the demand for multivariate analyses increases, it is imperative that optimal tools are available to assess their performance. To facilitate the testing and validation of these multivariate approaches, we developed simplePHENOTYPES, an R/CRAN package that simulates pleiotropy, partial pleiotropy, and spurious pleiotropy in a wide range of genetic architectures, including additive, dominance and epistatic models. RESULTS We illustrate simplePHENOTYPES' ability to simulate thousands of phenotypes in less than one minute. We then provide two vignettes illustrating how to simulate sets of correlated traits in simplePHENOTYPES. Finally, we demonstrate the use of results from simplePHENOTYPES in a standard GWAS software, as well as the equivalence of simulated phenotypes from simplePHENOTYPES and other packages with similar capabilities. CONCLUSIONS simplePHENOTYPES is a R/CRAN package that makes it possible to simulate multiple traits controlled by loci with varying degrees of pleiotropy. Its ability to interface with both commonly-used marker data formats and downstream quantitative genetics software and packages should facilitate a rigorous assessment of both existing and emerging statistical GWAS and GS approaches. simplePHENOTYPES is also available at https://github.com/samuelbfernandes/simplePHENOTYPES .
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Affiliation(s)
- Samuel B Fernandes
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, 61801, USA
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, 61801, USA.
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Adhikari P, Goodrich E, Fernandes SB, Lipka AE, Tranel P, Brown P, Jamann TM. Genetic variation associated with PPO-inhibiting herbicide tolerance in sorghum. PLoS One 2020; 15:e0233254. [PMID: 33052910 PMCID: PMC7556536 DOI: 10.1371/journal.pone.0233254] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 08/26/2020] [Indexed: 11/29/2022] Open
Abstract
Herbicide application is crucial for weed management in most crop production systems, but for sorghum herbicide options are limited. Sorghum is sensitive to residual protoporphyrinogen oxidase (PPO)-inhibiting herbicides, such as fomesafen, and a long re-entry period is required before sorghum can be planted after its application. Improving sorghum for tolerance to such residual herbicides would allow for increased sorghum production and the expansion of herbicide options for growers. In this study, we observed sorghum tolerance to residual fomesafen. To investigate the underlying tolerance mechanism a genome-wide association mapping study was conducted using field-collected sorghum biomass panel (SBP) data, and a greenhouse assay was developed to confirm the field phenotypes. A total of 26 significant SNPs (FDR<0.05), spanning a 215.3 kb region on chromosome 3, were detected. The ten most significant SNPs included two in genic regions (Sobic.003G136800, and Sobic.003G136900) and eight SNPs in the intergenic region encompassing the genes Sobic.003G136700, Sobic.003G136800, Sobic.003G137000, Sobic.003G136900, and Sobic.003G137100. The gene Sobic.003G137100 (PPXI), which encodes the PPO1 enzyme, one of the targets of PPO-inhibiting herbicides, was located 12kb downstream of the significant SNP S03_13152838. We found that PPXI is highly conserved in sorghum and expression does not significantly differ between tolerant and sensitive sorghum lines. Our results suggest that PPXI most likely does not underlie the observed herbicide tolerance. Instead, the mechanism underlying herbicide tolerance in the SBP is likely metabolism-based resistance, possibly regulated by the action of multiple genes. Further research is necessary to confirm candidate genes and their functions.
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Affiliation(s)
- Pragya Adhikari
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
| | - Emma Goodrich
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
| | - Samuel B. Fernandes
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
| | - Alexander E. Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
| | - Patrick Tranel
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
| | - Patrick Brown
- Department of Plant Sciences, University of California Davis, Davis, CA, United States of America
| | - Tiffany M. Jamann
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
- * E-mail:
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15
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Rice BR, Fernandes SB, Lipka AE. CorrigendumMulti-Trait Genome-Wide Association Studies Reveal Loci Associated with Maize Inflorescence and Leaf Architecture. Plant Cell Physiol 2020; 61:1530. [PMID: 32812044 DOI: 10.1093/pcp/pcaa078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
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16
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Rice BR, Fernandes SB, Lipka AE. Multi-Trait Genome-Wide Association Studies Reveal Loci Associated with Maize Inflorescence and Leaf Architecture. Plant Cell Physiol 2020; 61:1427-1437. [PMID: 32186727 DOI: 10.1093/pcp/pcaa039] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 03/17/2020] [Indexed: 05/23/2023]
Abstract
Maize inflorescence is a complex phenotype that involves the physical and developmental interplay of multiple traits. Given the evidence that genes could pleiotropically contribute to several of these traits, we used publicly available maize data to assess the ability of multivariate genome-wide association study (GWAS) approaches to identify pleiotropic quantitative trait loci (pQTL). Our analysis of 23 publicly available inflorescence and leaf-related traits in a diversity panel of n = 281 maize lines genotyped with 376,336 markers revealed that the two multivariate GWAS approaches we tested were capable of identifying pQTL in genomic regions coinciding with similar associations found in previous studies. We then conducted a parallel simulation study on the same individuals, where it was shown that multivariate GWAS approaches yielded a higher true-positive quantitative trait nucleotide (QTN) detection rate than comparable univariate approaches for all evaluated simulation settings except for when the correlated simulated traits had a heritability of 0.9. We therefore conclude that the implementation of state-of-the-art multivariate GWAS approaches is a useful tool for dissecting pleiotropy and their more widespread implementation could facilitate the discovery of genes and other biological mechanisms underlying maize inflorescence.
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Affiliation(s)
- Brian R Rice
- Department of Crop Sciences, University of Illinois, Urbana, IL, USA
| | | | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois, Urbana, IL, USA
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17
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Zhang X, Fernandes SB, Kaiser C, Adhikari P, Brown PJ, Mideros SX, Jamann TM. Conserved defense responses between maize and sorghum to Exserohilum turcicum. BMC Plant Biol 2020; 20:67. [PMID: 32041528 PMCID: PMC7011368 DOI: 10.1186/s12870-020-2275-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 02/03/2020] [Indexed: 05/10/2023]
Abstract
BACKGROUND Exserohilum turcicum is an important pathogen of both sorghum and maize, causing sorghum leaf blight and northern corn leaf blight. Because the same pathogen can infect and cause major losses for two of the most important grain crops, it is an ideal pathosystem to study plant-pathogen evolution and investigate shared resistance mechanisms between the two plant species. To identify sorghum genes involved in the E. turcicum response, we conducted a genome-wide association study (GWAS). RESULTS Using the sorghum conversion panel evaluated across three environments, we identified a total of 216 significant markers. Based on physical linkage with the significant markers, we detected a total of 113 unique candidate genes, some with known roles in plant defense. Also, we compared maize genes known to play a role in resistance to E. turcicum with the association mapping results and found evidence of genes conferring resistance in both crops, providing evidence of shared resistance between maize and sorghum. CONCLUSIONS Using a genetics approach, we identified shared genetic regions conferring resistance to E. turcicum in both maize and sorghum. We identified several promising candidate genes for resistance to leaf blight in sorghum, including genes related to R-gene mediated resistance. We present significant advancements in the understanding of host resistance to E. turcicum, which is crucial to reduce losses due to this important pathogen.
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Affiliation(s)
- Xiaoyue Zhang
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Samuel B Fernandes
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Christopher Kaiser
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Pragya Adhikari
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Patrick J Brown
- Department of Plant Sciences, University of California, Davis, CA, 95616, USA
| | - Santiago X Mideros
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Tiffany M Jamann
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
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18
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Dos Santos JPR, Fernandes SB, McCoy S, Lozano R, Brown PJ, Leakey ADB, Buckler ES, Garcia AAF, Gore MA. Novel Bayesian Networks for Genomic Prediction of Developmental Traits in Biomass Sorghum. G3 (Bethesda) 2020; 10:769-781. [PMID: 31852730 PMCID: PMC7003104 DOI: 10.1534/g3.119.400759] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Accepted: 12/15/2019] [Indexed: 11/23/2022]
Abstract
The ability to connect genetic information between traits over time allow Bayesian networks to offer a powerful probabilistic framework to construct genomic prediction models. In this study, we phenotyped a diversity panel of 869 biomass sorghum (Sorghum bicolor (L.) Moench) lines, which had been genotyped with 100,435 SNP markers, for plant height (PH) with biweekly measurements from 30 to 120 days after planting (DAP) and for end-of-season dry biomass yield (DBY) in four environments. We evaluated five genomic prediction models: Bayesian network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait GBLUP (MTr-GBLUP), and multi-time GBLUP (MTi-GBLUP) models. In fivefold cross-validation, prediction accuracies ranged from 0.46 (PBN) to 0.49 (MTr-GBLUP) for DBY and from 0.47 (DBN, DAP120) to 0.75 (MTi-GBLUP, DAP60) for PH. Forward-chaining cross-validation further improved prediction accuracies of the DBN, MTi-GBLUP and MTr-GBLUP models for PH (training slice: 30-45 DAP) by 36.4-52.4% relative to the BN and PBN models. Coincidence indices (target: biomass, secondary: PH) and a coincidence index based on lines (PH time series) showed that the ranking of lines by PH changed minimally after 45 DAP. These results suggest a two-level indirect selection method for PH at harvest (first-level target trait) and DBY (second-level target trait) could be conducted earlier in the season based on ranking of lines by PH at 45 DAP (secondary trait). With the advance of high-throughput phenotyping technologies, our proposed two-level indirect selection framework could be valuable for enhancing genetic gain per unit of time when selecting on developmental traits.
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Affiliation(s)
- Jhonathan P R Dos Santos
- Plant Breeding and Genetics Section, School of Integrative Plant Science
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP, Brazil
| | | | | | - Roberto Lozano
- Plant Breeding and Genetics Section, School of Integrative Plant Science
| | - Patrick J Brown
- Section of Agricultural Plant Biology, Department of Plant Sciences, University of California Davis, 95616, and
| | - Andrew D B Leakey
- Department of Crop Science
- Institute for Genomic Biology
- Department of Plant Biology, University of Illinois at Urbana Champaign, 61801
| | - Edward S Buckler
- Plant Breeding and Genetics Section, School of Integrative Plant Science
- United States Department of Agriculture, Agricultural Research Service, R. W. Holley Center, Ithaca, New York 14853
- Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853
| | - Antonio A F Garcia
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP, Brazil,
| | - Michael A Gore
- Plant Breeding and Genetics Section, School of Integrative Plant Science,
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19
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Fernandes SB, Dias KOG, Ferreira DF, Brown PJ. Efficiency of multi-trait, indirect, and trait-assisted genomic selection for improvement of biomass sorghum. Theor Appl Genet 2018; 131:747-755. [PMID: 29218378 PMCID: PMC5814553 DOI: 10.1007/s00122-017-3033-y] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 12/01/2017] [Indexed: 05/18/2023]
Abstract
We compare genomic selection methods that use correlated traits to help predict biomass yield in sorghum, and find that trait-assisted genomic selection performs best. Genomic selection (GS) is usually performed on a single trait, but correlated traits can also help predict a focal trait through indirect or multi-trait GS. In this study, we use a pre-breeding population of biomass sorghum to compare strategies that use correlated traits to improve prediction of biomass yield, the focal trait. Correlated traits include moisture, plant height measured at monthly intervals between planting and harvest, and the area under the growth progress curve. In addition to single- and multi-trait direct and indirect GS, we test a new strategy called trait-assisted GS, in which correlated traits are used along with marker data in the validation population to predict a focal trait. Single-trait GS for biomass yield had a prediction accuracy of 0.40. Indirect GS performed best using area under the growth progress curve to predict biomass yield, with a prediction accuracy of 0.37, and did not differ from indirect multi-trait GS that also used moisture information. Multi-trait GS and single-trait GS yielded similar results, indicating that correlated traits did not improve prediction of biomass yield in a standard GS scenario. However, trait-assisted GS increased prediction accuracy by up to [Formula: see text] when using plant height in both the training and validation populations to help predict yield in the validation population. Coincidence between selected genotypes in phenotypic and genomic selection was also highest in trait-assisted GS. Overall, these results suggest that trait-assisted GS can be an efficient strategy when correlated traits are obtained earlier or more inexpensively than a focal trait.
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Affiliation(s)
- Samuel B Fernandes
- Department of Crop Sciences, University of Illinois, 1206 W Gregory Drive, IL, Urbana, 61801, USA.
| | - Kaio O G Dias
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, PO Box 83, Piracicaba, SP, 13400-970, Brazil
| | - Daniel F Ferreira
- Departamento de Estatística, Universidade Federal de Lavras, 3037, Lavras, MG, 37200-000, Brazil
| | - Patrick J Brown
- Department of Crop Sciences, University of Illinois, 1206 W Gregory Drive, IL, Urbana, 61801, USA
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20
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Fernandes SB, Abreu AFB, Ramalho MAP. Genotype x environment interaction and its implication in identification of common bean populations with high calcium content. Genet Mol Res 2016; 15:gmr8053. [PMID: 27420963 DOI: 10.4238/gmr.15028053] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The common bean is a food with high mineral content. Of the various types of beans cultivated in Brazil, carioca type beans are the most consumed. The aim of this study was to identify promising common bean populations with an emphasis toward the selection of carioca type bean lines with high calcium content. We also aimed to verify whether and how the crop season and the genotype (parental line and hybrid populations) x crop season interaction affect calcium content. A group of 3 lines of good agronomic characteristics were crossed with a group of 4 lines with high calcium content in a 3 x 4 partial diallel design. Great variability was identified among both the parental lines and the hybrid populations derived from the diallel crosses among the parental lines. We found significant interactions between crop season and both parental line and hybrid population. In the diallel analysis, only the general combining ability was significant, explaining 89.4% of the sum of squares. The RP-1, CNF05, and Safira lines exhibited the greatest calcium contents and a positive GCA. RP-1 is a line that presents high calcium content, in addition to having carioca type beans and an upright plant with high yield. To further increase the calcium content of the RP-1 line, we suggest crossing it with the CNF05 and Safira lines. Although there was a hybrid population x crop season interaction, it was possible to identify populations that performed best in terms of calcium content in both crop seasons.
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Affiliation(s)
- S B Fernandes
- Departamento de Biologia, Universidade Federal de Lavras, Lavras, MG, Brasil
| | | | - M A P Ramalho
- Departamento de Biologia, Universidade Federal de Lavras, Lavras, MG, Brasil
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Abstract
The aim of this study was to undertake the theoretical derivations of non-parametric methods, which use linear regressions based on rank order, for stability analyses. These methods were extension different parametric methods used for stability analyses and the result was compared with a standard non-parametric method. Intensive computational methods (e.g., bootstrap and permutation) were applied, and data from the plant-breeding program of the Biology Department of UFLA (Minas Gerais, Brazil) were used to illustrate and compare the tests. The non-parametric stability methods were effective for the evaluation of phenotypic stability. In the presence of variance heterogeneity, the non-parametric methods exhibited greater power of discrimination when determining the phenotypic stability of genotypes.
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Affiliation(s)
- D F Ferreira
- Departamento de Ciências Exatas, Universidade Federal de Lavras, Lavras, MG, Brasil
| | - S B Fernandes
- Departamento de Biologia, Universidade Federal de Lavras, Lavras, MG, Brasil
| | - A T Bruzi
- Departamento de Agricultura, Universidade Federal de Lavras, Lavras, MG, Brasil
| | - M A P Ramalho
- Departamento de Biologia, Universidade Federal de Lavras, Lavras, MG, Brasil
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Motta FC, Siqueira MM, Lugon AK, Straliotto SM, Fernandes SB, Krawczuk MM. The reappearance of Victoria lineage influenza B virus in Brazil, antigenic and molecular analysis. J Clin Virol 2006; 36:208-14. [PMID: 16713335 DOI: 10.1016/j.jcv.2006.03.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2005] [Revised: 03/16/2006] [Accepted: 03/21/2006] [Indexed: 11/18/2022]
Abstract
BACKGROUND In contrast to influenza A, minor influenza B viruses can co-circulate with the dominant strain during an epidemic allowing the re-emergence of old strains and reassortment between those different strains. The 2001-2002 influenza season in the northern hemisphere was distinguished by the re-emergence of the Victoria-lineage viruses, which replaced the Yamagata-lineage, after being restricted to East Asia throughout the 1990s. OBJECTIVES To describe the antigenic and genetic characteristics of influenza B viruses detected in South and South East Brazil and determine their lineages. STUDY DESIGN Influenza samples collected during epidemics between 1999 and 2002 were analyzed by indirect immunofluorescence assay (IFA). Positive results were confirmed through multiplex PCR and isolation in cell culture. Isolated viruses were antigenically characterized by hemagglutination inhibition. Fourteen hemagglutinin (HA) gene sequences obtained in this work were used for phylogenetic analysis. RESULTS Brazilian isolates from 2002 were associated with the Victoria-lineage, diverging from the vaccine used throughout that influenza season in Brazil. CONCLUSIONS These results indicate the reappearance of Sichuan/7/97-like samples in South and South East Brazilian Regions simultaneously. They indicate the need for neuraminidase gene evaluation and demonstrate the importance of influenza laboratory surveillance to establish which strains should be included in the influenza vaccine.
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Affiliation(s)
- F C Motta
- Laboratório de Vírus Respiratórios e do Sarampo, Depto. de Virologia, Instituto Oswaldo Cruz, FIOCRUZ, 21045-900, Rio de Janeiro, RJ, Brasil.
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Abstract
Cellophane paper has been used as a dressing for split-thickness skin graft donor sites in 251 patients between October 1985 and December 1989. Twelve donor sites in 10 patients were observed in detail to assess the usefulness of this material. The results of the study are presented and the merits and disadvantages of this dressing material have been discussed. In the opinion of the authors the cellophane paper dressing was found to be most satisfactory. It is also cheaper than the newly available dressing materials for the skin donor area.
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Affiliation(s)
- A M Vartak
- Burns Research Unit, Bai Jerbai Wadia Hospital for Children, Parel, Bombay, India
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