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Ahrens CW, Murray K, Mazanec RA, Ferguson S, Jones A, Tissue DT, Byrne M, Borevitz JO, Rymer PD. Genomic determinants, architecture, and constraints in drought-related traits in Corymbia calophylla. BMC Genomics 2024; 25:640. [PMID: 38937661 PMCID: PMC11209971 DOI: 10.1186/s12864-024-10531-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 06/14/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND Drought adaptation is critical to many tree species persisting under climate change, however our knowledge of the genetic basis for trees to adapt to drought is limited. This knowledge gap impedes our fundamental understanding of drought response and application to forest production and conservation. To improve our understanding of the genomic determinants, architecture, and trait constraints, we assembled a reference genome and detected ~ 6.5 M variants in 432 phenotyped individuals for the foundational tree Corymbia calophylla. RESULTS We found 273 genomic variants determining traits with moderate heritability (h2SNP = 0.26-0.64). Significant variants were predominantly in gene regulatory elements distributed among several haplotype blocks across all chromosomes. Furthermore, traits were constrained by frequent epistatic and pleiotropic interactions. CONCLUSIONS Our results on the genetic basis for drought traits in Corymbia calophylla have several implications for the ability to adapt to climate change: (1) drought related traits are controlled by complex genomic architectures with large haplotypes, epistatic, and pleiotropic interactions; (2) the most significant variants determining drought related traits occurred in regulatory regions; and (3) models incorporating epistatic interactions increase trait predictions. Our findings indicate that despite moderate heritability drought traits are likely constrained by complex genomic architecture potentially limiting trees response to climate change.
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Affiliation(s)
- Collin W Ahrens
- Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW, 2753, Australia.
- Cesar Australia, Brunswick, VIC, 3058, Australia.
| | - Kevin Murray
- Research School of Biology, Australian National University, Canberra, ACT, 2600, Australia
| | - Richard A Mazanec
- Biodiversity and Conservation Science, Western Australian Department of Biodiversity, Conservation and Attractions, Kensington, WA, 6151, Australia
| | - Scott Ferguson
- Research School of Biology, Australian National University, Canberra, ACT, 2600, Australia
| | - Ashley Jones
- Research School of Biology, Australian National University, Canberra, ACT, 2600, Australia
| | - David T Tissue
- Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW, 2753, Australia
| | - Margaret Byrne
- Biodiversity and Conservation Science, Western Australian Department of Biodiversity, Conservation and Attractions, Kensington, WA, 6151, Australia
| | - Justin O Borevitz
- Research School of Biology, Australian National University, Canberra, ACT, 2600, Australia
| | - Paul D Rymer
- Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW, 2753, Australia
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2
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Simon SJ, Furches A, Chhetri H, Evans L, Abeyratne CR, Jones P, Wimp G, Macaya-Sanz D, Jacobson D, Tschaplinski TJ, Tuskan GA, DiFazio SP. Genetic underpinnings of arthropod community distributions in Populus trichocarpa. THE NEW PHYTOLOGIST 2024; 242:1307-1323. [PMID: 38488269 DOI: 10.1111/nph.19660] [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: 10/18/2023] [Accepted: 02/21/2024] [Indexed: 04/12/2024]
Abstract
Community genetics seeks to understand the mechanisms by which natural genetic variation in heritable host phenotypes can encompass assemblages of organisms such as bacteria, fungi, and many animals including arthropods. Prior studies that focused on plant genotypes have been unable to identify genes controlling community composition, a necessary step to predict ecosystem structure and function as underlying genes shift within plant populations. We surveyed arthropods within an association population of Populus trichocarpa in three common gardens to discover plant genes that contributed to arthropod community composition. We analyzed our surveys with traditional single-trait genome-wide association analysis (GWAS), multitrait GWAS, and functional networks built from a diverse set of plant phenotypes. Plant genotype was influential in structuring arthropod community composition among several garden sites. Candidate genes important for higher level organization of arthropod communities had broadly applicable functions, such as terpenoid biosynthesis and production of dsRNA binding proteins and protein kinases, which may be capable of targeting multiple arthropod species. We have demonstrated the ability to detect, in an uncontrolled environment, individual genes that are associated with the community assemblage of arthropods on a host plant, further enhancing our understanding of genetic mechanisms that impact ecosystem structure.
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Affiliation(s)
- Sandra J Simon
- Department of Biology, West Virginia University, Morgantown, WV, 26506, USA
| | - Anna Furches
- Biosciences Division and Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
- The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, 37996, USA
| | - Hari Chhetri
- Department of Biology, West Virginia University, Morgantown, WV, 26506, USA
- Computational Systems Biology Group, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Luke Evans
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, 80309, USA
| | | | - Piet Jones
- Biosciences Division and Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
- The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, 37996, USA
| | - Gina Wimp
- Department of Biology, Georgetown University, Washington, DC, 20057, USA
| | - David Macaya-Sanz
- Department of Biology, West Virginia University, Morgantown, WV, 26506, USA
| | - Daniel Jacobson
- Biosciences Division and Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
- The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, 37996, USA
| | - Timothy J Tschaplinski
- Biosciences Division and Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Gerald A Tuskan
- Biosciences Division and Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Stephen P DiFazio
- Department of Biology, West Virginia University, Morgantown, WV, 26506, USA
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3
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Nagle MF, Yuan J, Kaur D, Ma C, Peremyslova E, Jiang Y, Goralogia GS, Magnuson A, Li JY, Muchero W, Fuxin L, Strauss SH. Genome-wide association study and network analysis of in vitro transformation in Populus trichocarpa support key roles of diverse phytohormone pathways and cross talk. THE NEW PHYTOLOGIST 2024. [PMID: 38650352 DOI: 10.1111/nph.19737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 03/06/2024] [Indexed: 04/25/2024]
Abstract
Wide variation in amenability to transformation and regeneration (TR) among many plant species and genotypes presents a challenge to the use of genetic engineering in research and breeding. To help understand the causes of this variation, we performed association mapping and network analysis using a population of 1204 wild trees of Populus trichocarpa (black cottonwood). To enable precise and high-throughput phenotyping of callus and shoot TR, we developed a computer vision system that cross-referenced complementary red, green, and blue (RGB) and fluorescent-hyperspectral images. We performed association mapping using single-marker and combined variant methods, followed by statistical tests for epistasis and integration of published multi-omic datasets to identify likely regulatory hubs. We report 409 candidate genes implicated by associations within 5 kb of coding sequences, and epistasis tests implicated 81 of these candidate genes as regulators of one another. Gene ontology terms related to protein-protein interactions and transcriptional regulation are overrepresented, among others. In addition to auxin and cytokinin pathways long established as critical to TR, our results highlight the importance of stress and wounding pathways. Potential regulatory hubs of signaling within and across these pathways include GROWTH REGULATORY FACTOR 1 (GRF1), PHOSPHATIDYLINOSITOL 4-KINASE β1 (PI-4Kβ1), and OBF-BINDING PROTEIN 1 (OBP1).
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Affiliation(s)
- Michael F Nagle
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Jialin Yuan
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Damanpreet Kaur
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Cathleen Ma
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Ekaterina Peremyslova
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Yuan Jiang
- Statistics Department, Oregon State University, Corvallis, OR, 97331, USA
| | - Greg S Goralogia
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Anna Magnuson
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
| | - Jia Yi Li
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Wellington Muchero
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, 37996, USA
| | - Li Fuxin
- School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, 97331, USA
| | - Steven H Strauss
- Department of Forest Ecosystems & Society, Oregon State University, Corvallis, OR, 97331, USA
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4
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Happs R, Hanes RJ, Bartling AW, Field JL, Harman-Ware AE, Clark RJ, Pendergast TH, Devos KM, Webb EG, Missaoui A, Xu Y, Makaju S, Shrestha V, Mazarei M, Stewart CN, Millwood RJ, Davison BH. Economic and Sustainability Impacts of Yield and Composition Variation in Bioenergy Crops: Switchgrass ( Panicum virgatum L.). ACS SUSTAINABLE CHEMISTRY & ENGINEERING 2024; 12:1897-1910. [PMID: 38333206 PMCID: PMC10848292 DOI: 10.1021/acssuschemeng.3c05770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 12/20/2023] [Accepted: 12/20/2023] [Indexed: 02/10/2024]
Abstract
Economically viable production of biobased products and fuels requires high-yielding, high-quality, sustainable process-advantaged crops, developed using bioengineering or advanced breeding approaches. Understanding which crop phenotypic traits have the largest impact on biofuel economics and sustainability outcomes is important for the targeted feedstock crop development. Here, we evaluated biomass yield and cell-wall composition traits across a large natural variant population of switchgrass (Panicum virgatum L.) grown across three common garden sites. Samples from 331 switchgrass genotypes were collected and analyzed for carbohydrate and lignin components. Considering plant survival and biomass after multiple years of growth, we found that 84 of the genotypes analyzed may be suited for commercial production in the southeastern U.S. These genotypes show a range of growth and compositional traits across the population that are apparently independent of each other. We used these data to conduct techno-economic analyses and life cycle assessments evaluating the performance of each switchgrass genotype under a standard cellulosic ethanol process model with pretreatment, added enzymes, and fermentation. We find that switchgrass yield per area is the largest economic driver of the minimum fuel selling price (MSFP), ethanol yield per hectare, global warming potential (GWP), and cumulative energy demand (CED). At any yield, the carbohydrate content is significant but of secondary importance. Water use follows similar trends but has more variability due to an increased dependence on the biorefinery model. Analyses presented here highlight the primary importance of plant yield and the secondary importance of carbohydrate content when selecting a feedstock that is both economical and sustainable.
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Affiliation(s)
- Renee
M. Happs
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Rebecca J. Hanes
- Strategic
Energy Analysis Center, National Renewable
Energy Laboratory, Golden, Colorado 80401, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Andrew W. Bartling
- Catalytic
Carbon and Transformation Center, National
Renewable Energy Laboratory, Golden, Colorado 80401, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - John L. Field
- Environmental
Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Anne E. Harman-Ware
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, Colorado 80401, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Robin J. Clark
- Environmental
Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Thomas H. Pendergast
- Institute
of Plant Breeding, Genetics and Genomics, University of Georgia, Athens, Georgia 30602, United States
- Department
of Crop and Soil Sciences, University of
Georgia, Athens, Georgia 30602, United States
- Department
of Plant Biology, University of Georgia, Athens, Georgia 30602, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Katrien M. Devos
- Institute
of Plant Breeding, Genetics and Genomics, University of Georgia, Athens, Georgia 30602, United States
- Department
of Crop and Soil Sciences, University of
Georgia, Athens, Georgia 30602, United States
- Department
of Plant Biology, University of Georgia, Athens, Georgia 30602, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Erin G. Webb
- Environmental
Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Ali Missaoui
- Institute
of Plant Breeding, Genetics and Genomics, University of Georgia, Athens, Georgia 30602, United States
- Department
of Crop and Soil Sciences, University of
Georgia, Athens, Georgia 30602, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Yaping Xu
- Department
of Plant Sciences, University of Tennessee
Knoxville, Knoxville, Tennessee 37919, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Shiva Makaju
- Institute
of Plant Breeding, Genetics and Genomics, University of Georgia, Athens, Georgia 30602, United States
- Department
of Crop and Soil Sciences, University of
Georgia, Athens, Georgia 30602, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Vivek Shrestha
- Department
of Plant Sciences, University of Tennessee
Knoxville, Knoxville, Tennessee 37919, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Mitra Mazarei
- Department
of Plant Sciences, University of Tennessee
Knoxville, Knoxville, Tennessee 37919, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Charles Neal Stewart
- Department
of Plant Sciences, University of Tennessee
Knoxville, Knoxville, Tennessee 37919, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Reginald J. Millwood
- Department
of Plant Sciences, University of Tennessee
Knoxville, Knoxville, Tennessee 37919, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
| | - Brian H. Davison
- Biosciences
Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States
- Center
for Bioenergy Innovation, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37830, United States
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5
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Alía R, Climent J, Santos-Del-Blanco L, Gonzalez-Arrojo A, Feito I, Grivet D, Majada J. Adaptive potential of maritime pine under contrasting environments. BMC PLANT BIOLOGY 2024; 24:37. [PMID: 38191282 PMCID: PMC10775667 DOI: 10.1186/s12870-023-04687-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: 04/28/2023] [Accepted: 12/13/2023] [Indexed: 01/10/2024]
Abstract
BACKGROUND Predicting the adaptability of forest tree populations under future climates requires a better knowledge of both the adaptive significance and evolvability of measurable key traits. Phenotypic plasticity, standing genetic variation and degree of phenotypic integration shape the actual and future population genetic structure, but empirical estimations in forest tree species are still extremely scarce. We analysed 11 maritime pine populations covering the distribution range of the species (119 families and 8 trees/family, ca. 1300 trees) in a common garden experiment planted at two sites with contrasting productivity. We used plant height as a surrogate of fitness and measured five traits (mean and plasticity of carbon isotope discrimination, specific leaf area, needle biomass, Phenology growth index) related to four different strategies (acquisitive economics, photosynthetic organ size, growth allocation and avoidance of water stress). RESULTS Estimated values of additive genetic variation would allow adaptation of the populations to future environmental conditions. Overall phenotypic integration and selection gradients were higher at the high productivity site, while phenotypic integration within populations was higher at the low productivity site. Response to selection was related mainly to photosynthetic organ size and drought-avoidance mechanisms rather than to water use efficiency. Phenotypic plasticity of water use efficiency could be maladaptive, resulting from selection for height growth. CONCLUSIONS Contrary to the expectations in a drought tolerant species, our study suggests that variation in traits related to photosynthetic organ size and acquisitive investment of resources drive phenotypic selection across and within maritime pine populations. Both genetic variation and evolvability of key adaptive traits were considerably high, including plasticity of water use efficiency. These characteristics would enable a relatively fast micro-evolution of populations in response to the ongoing climate changes. Moreover, differentiation among populations in the studied traits would increase under the expected more productive future Atlantic conditions.
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Affiliation(s)
- Ricardo Alía
- Instituto de Ciencias Forestales, ICIFOR-INIA, CSIC, Madrid, 28040, Spain.
| | - Jose Climent
- Instituto de Ciencias Forestales, ICIFOR-INIA, CSIC, Madrid, 28040, Spain
| | | | | | | | - Delphine Grivet
- Instituto de Ciencias Forestales, ICIFOR-INIA, CSIC, Madrid, 28040, Spain
| | - Juan Majada
- Forest and Wood Technology Research Centre (CETEMAS), Carbayin, 33936, Spain
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6
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Ullah A, Lin YJ, Zhang H, Yu XZ. Identification of the Key Genes Involved in Proline-Mediated Modification of Cell Wall Components in Rice Seedlings under Trivalent Chromium Exposure. TOXICS 2023; 12:4. [PMID: 38276717 PMCID: PMC10818556 DOI: 10.3390/toxics12010004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/15/2023] [Accepted: 12/18/2023] [Indexed: 01/27/2024]
Abstract
Chromium (Cr) toxicity exerts a detrimental effect on various physiological, biochemical, and molecular attributes of plants including the structure and functions of cell walls. On the other hand, the exogenous application of proline (Pro) is a beneficial strategy to overcome Cr toxicity. Therefore, it is a novel strategy to find the key genes associated with cell wall composition in rice under trivalent Cr with/without Pro application. A total of 203 genes were activated in the four cell wall biosynthesis pathways under chromium stress, namely cellulose (60), hemicellulose (57), lignin (35), and pectin (51). Based on the expression abundance of microarrays, the number of differentially expressed genes, and the expression level of genes, the lignin pathway was a crucial pathway in response to Cr treatments, followed by the cellulose pathway. Through the estimation of gene expression variation factors between 'Cr' and 'Cr+Pro' treatments, OsUGP1, OsBGLU24, OsBGLU29, OsBGLU33, OsBMY1, and OsBMY2 in the cellulose pathway; OsXTH9, OsXTH10, OsXTH16, OsGAUT3, OsGAUT19, OsGAUT28, OsXTH1, OsGAUT12, and OsGAUT21 in the hemicellulose pathway; OsPAL3, OsPAL3, OsPOX1, and OsPRX77 in the lignin pathway; and OsPME25, OsPGL27, OsPME26, OsPGL9, and OsPLL12 in the pectin pathway are the key genes involved in cell wall modification during Cr exposure with exogenous Pro application. The Pro-mediated activation of these genes could be crucial players in modifying the cell wall structure and composition of rice plants under Cr stress, which needs to be further clarified.
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Affiliation(s)
| | | | | | - Xiao-Zhang Yu
- College of Environmental Science & Engineering, Guilin University of Technology, Guilin 541004, China; (A.U.); (Y.-J.L.); (H.Z.)
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7
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Riehl JFL, Cole CT, Morrow CJ, Barker HL, Bernhardsson C, Rubert‐Nason K, Ingvarsson PK, Lindroth RL. Genomic and transcriptomic analyses reveal polygenic architecture for ecologically important traits in aspen ( Populus tremuloides Michx.). Ecol Evol 2023; 13:e10541. [PMID: 37780087 PMCID: PMC10534199 DOI: 10.1002/ece3.10541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/30/2023] [Accepted: 09/04/2023] [Indexed: 10/03/2023] Open
Abstract
Intraspecific genetic variation in foundation species such as aspen (Populus tremuloides Michx.) shapes their impact on forest structure and function. Identifying genes underlying ecologically important traits is key to understanding that impact. Previous studies, using single-locus genome-wide association (GWA) analyses to identify candidate genes, have identified fewer genes than anticipated for highly heritable quantitative traits. Mounting evidence suggests that polygenic control of quantitative traits is largely responsible for this "missing heritability" phenomenon. Our research characterized the genetic architecture of 30 ecologically important traits using a common garden of aspen through genomic and transcriptomic analyses. A multilocus association model revealed that most traits displayed a highly polygenic architecture, with most variation explained by loci with small effects (likely below the detection levels of single-locus GWA methods). Consistent with a polygenic architecture, our single-locus GWA analyses found only 38 significant SNPs in 22 genes across 15 traits. Next, we used differential expression analysis on a subset of aspen genets with divergent concentrations of salicinoid phenolic glycosides (key defense traits). This complementary method to traditional GWA discovered 1243 differentially expressed genes for a polygenic trait. Soft clustering analysis revealed three gene clusters (241 candidate genes) involved in secondary metabolite biosynthesis and regulation. Our work reveals that ecologically important traits governing higher-order community- and ecosystem-level attributes of a foundation forest tree species have complex underlying genetic structures and will require methods beyond traditional GWA analyses to unravel.
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Affiliation(s)
| | | | - Clay J. Morrow
- Department of Forest and Wildlife EcologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Hilary L. Barker
- Department of EntomologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Present address:
Office of Student SuccessWisconsin Technical College SystemMadisonWisconsinUSA
| | - Carolina Bernhardsson
- Department of Ecology and Environmental ScienceUmeå UniversityUmeåSweden
- Present address:
Department of Organismal Biology, Center for Evolutionary BiologyUppsala UniversityUppsalaSweden
| | - Kennedy Rubert‐Nason
- Department of EntomologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Present address:
Division of Natural SciencesUniversity of Maine at Fort KentFort KentMaineUSA
| | - Pär K. Ingvarsson
- Department of Plant BiologySwedish University of Agricultural Sciences, Uppsala BioCenterUppsalaSweden
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8
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Li C, Huang W, Han X, Zhao G, Zhang W, He W, Nie B, Chen X, Zhang T, Bai W, Zhang X, He J, Zhao C, Fernie AR, Tschaplinski TJ, Yang X, Yan S, Wang L. Diel dynamics of multi-omics in elkhorn fern provide new insights into weak CAM photosynthesis. PLANT COMMUNICATIONS 2023; 4:100594. [PMID: 36960529 PMCID: PMC10504562 DOI: 10.1016/j.xplc.2023.100594] [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: 10/27/2022] [Revised: 02/19/2023] [Accepted: 03/20/2023] [Indexed: 05/29/2023]
Abstract
Crassulacean acid metabolism (CAM) has high water-use efficiency (WUE) and is widely recognized to have evolved from C3 photosynthesis. Different plant lineages have convergently evolved CAM, but the molecular mechanism that underlies C3-to-CAM evolution remains to be clarified. Platycerium bifurcatum (elkhorn fern) provides an opportunity to study the molecular changes underlying the transition from C3 to CAM photosynthesis because both modes of photosynthesis occur in this species, with sporotrophophyll leaves (SLs) and cover leaves (CLs) performing C3 and weak CAM photosynthesis, respectively. Here, we report that the physiological and biochemical attributes of CAM in weak CAM-performing CLs differed from those in strong CAM species. We investigated the diel dynamics of the metabolome, proteome, and transcriptome in these dimorphic leaves within the same genetic background and under identical environmental conditions. We found that multi-omic diel dynamics in P. bifurcatum exhibit both tissue and diel effects. Our analysis revealed temporal rewiring of biochemistry relevant to the energy-producing pathway (TCA cycle), CAM pathway, and stomatal movement in CLs compared with SLs. We also confirmed that PHOSPHOENOLPYRUVATE CARBOXYLASE KINASE (PPCK) exhibits convergence in gene expression among highly divergent CAM lineages. Gene regulatory network analysis identified candidate transcription factors regulating the CAM pathway and stomatal movement. Taken together, our results provide new insights into weak CAM photosynthesis and new avenues for CAM bioengineering.
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Affiliation(s)
- Cheng Li
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Wenjie Huang
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Xiaoxu Han
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Guohua Zhao
- Key Laboratory of Southern Subtropical Plant Diversity, Fairy Lake Botanical Garden, Shenzhen & Chinese Academy of Science, Shenzhen, China
| | - Wenyang Zhang
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Weijun He
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Bao Nie
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xufeng Chen
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Taijie Zhang
- Institute of Plant Protection, Guangdong Academy of Agricultural Sciences, Key Laboratory of Green Prevention and Control on Fruits and Vegetables in South China, Ministry of Agriculture and Rural Affairs, Guangdong Provincial Key Laboratory of High Technology for Plant Protection, Guangzhou, China
| | - Wenhui Bai
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xiaopeng Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Jingjing He
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Cheng Zhao
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, Am Muhlenberg 1, 14476 Potsdam-Golm, Germany
| | - Timothy J Tschaplinski
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA; The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Xiaohan Yang
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA; The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
| | - Shijuan Yan
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, China.
| | - Li Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China; Kunpeng Institute of Modern Agriculture at Foshan, Chinese Academy of Agricultural Sciences, Foshan, China.
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9
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Yang M, Zinkgraf M, Fitzgerald-Cook C, Harrison BR, Putzier A, Promislow DEL, Wang AM. Using Drosophila to identify naturally occurring genetic modifiers of amyloid beta 42- and tau-induced toxicity. G3 (BETHESDA, MD.) 2023; 13:jkad132. [PMID: 37311212 PMCID: PMC10468303 DOI: 10.1093/g3journal/jkad132] [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: 04/11/2023] [Revised: 04/15/2023] [Accepted: 05/15/2023] [Indexed: 06/15/2023]
Abstract
Alzheimer's disease is characterized by 2 pathological proteins, amyloid beta 42 and tau. The majority of Alzheimer's disease cases in the population are sporadic and late-onset Alzheimer's disease, which exhibits high levels of heritability. While several genetic risk factors for late-onset Alzheimer's disease have been identified and replicated in independent studies, including the ApoE ε4 allele, the great majority of the heritability of late-onset Alzheimer's disease remains unexplained, likely due to the aggregate effects of a very large number of genes with small effect size, as well as to biases in sample collection and statistical approaches. Here, we present an unbiased forward genetic screen in Drosophila looking for naturally occurring modifiers of amyloid beta 42- and tau-induced ommatidial degeneration. Our results identify 14 significant SNPs, which map to 12 potential genes in 8 unique genomic regions. Our hits that are significant after genome-wide correction identify genes involved in neuronal development, signal transduction, and organismal development. Looking more broadly at suggestive hits (P < 10-5), we see significant enrichment in genes associated with neurogenesis, development, and growth as well as significant enrichment in genes whose orthologs have been identified as significantly or suggestively associated with Alzheimer's disease in human GWAS studies. These latter genes include ones whose orthologs are in close proximity to regions in the human genome that are associated with Alzheimer's disease, but where a causal gene has not been identified. Together, our results illustrate the potential for complementary and convergent evidence provided through multitrait GWAS in Drosophila to supplement and inform human studies, helping to identify the remaining heritability and novel modifiers of complex diseases.
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Affiliation(s)
- Ming Yang
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Matthew Zinkgraf
- Department of Biology, Western Washington University, Bellingham, WA 98225, USA
| | - Cecilia Fitzgerald-Cook
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Benjamin R Harrison
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Alexandra Putzier
- Department of Biology, Western Washington University, Bellingham, WA 98225, USA
| | - Daniel E L Promislow
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA
- Department of Biology, University of Washington, Seattle, WA 98195, USA
| | - Adrienne M Wang
- Department of Biology, Western Washington University, Bellingham, WA 98225, USA
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10
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Song B, Ning W, Wei D, Jiang M, Zhu K, Wang X, Edwards D, Odeny DA, Cheng S. Plant genome resequencing and population genomics: Current status and future prospects. MOLECULAR PLANT 2023; 16:1252-1268. [PMID: 37501370 DOI: 10.1016/j.molp.2023.07.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 05/30/2023] [Accepted: 07/25/2023] [Indexed: 07/29/2023]
Abstract
Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.
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Affiliation(s)
- Bo Song
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Weidong Ning
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; Huazhong Agricultural University, College of Informatics, Hubei Key Laboratory of Agricultural Bioinformatics, Wuhan, Hubei, China
| | - Di Wei
- Biotechnology Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 53007, China
| | - Mengyun Jiang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Kun Zhu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Xingwei Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Damaris A Odeny
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) - Eastern and Southern Africa, Nairobi, Kenya
| | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.
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11
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Nagle MF, Yuan J, Kaur D, Ma C, Peremyslova E, Jiang Y, Zahl B, Niño de Rivera A, Muchero W, Fuxin L, Strauss SH. GWAS identifies candidate genes controlling adventitious rooting in Populus trichocarpa. HORTICULTURE RESEARCH 2023; 10:uhad125. [PMID: 37560019 PMCID: PMC10407606 DOI: 10.1093/hr/uhad125] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 06/05/2023] [Indexed: 08/11/2023]
Abstract
Adventitious rooting (AR) is critical to the propagation, breeding, and genetic engineering of trees. The capacity for plants to undergo this process is highly heritable and of a polygenic nature; however, the basis of its genetic variation is largely uncharacterized. To identify genetic regulators of AR, we performed a genome-wide association study (GWAS) using 1148 genotypes of Populus trichocarpa. GWASs are often limited by the abilities of researchers to collect precise phenotype data on a high-throughput scale; to help overcome this limitation, we developed a computer vision system to measure an array of traits related to adventitious root development in poplar, including temporal measures of lateral and basal root length and area. GWAS was performed using multiple methods and significance thresholds to handle non-normal phenotype statistics and to gain statistical power. These analyses yielded a total of 277 unique associations, suggesting that genes that control rooting include regulators of hormone signaling, cell division and structure, reactive oxygen species signaling, and other processes with known roles in root development. Numerous genes with uncharacterized functions and/or cryptic roles were also identified. These candidates provide targets for functional analysis, including physiological and epistatic analyses, to better characterize the complex polygenic regulation of AR.
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Affiliation(s)
- Michael F Nagle
- Department of Forest Ecosystems and Society, Oregon State University, 3180 SW Jefferson Way, Corvallis, OR, 97331, United States
| | - Jialin Yuan
- Department of Electrical Engineering and Computer Science, Oregon State University, 110 SW Park Terrace, Corvallis, OR, 97331, United States
| | - Damanpreet Kaur
- Department of Electrical Engineering and Computer Science, Oregon State University, 110 SW Park Terrace, Corvallis, OR, 97331, United States
| | - Cathleen Ma
- Department of Forest Ecosystems and Society, Oregon State University, 3180 SW Jefferson Way, Corvallis, OR, 97331, United States
| | - Ekaterina Peremyslova
- Department of Forest Ecosystems and Society, Oregon State University, 3180 SW Jefferson Way, Corvallis, OR, 97331, United States
| | - Yuan Jiang
- Statistics Department, Oregon State University, 103 SW Memorial Place, Corvallis, OR, 97331, United States
| | - Bahiya Zahl
- Department of Forest Ecosystems and Society, Oregon State University, 3180 SW Jefferson Way, Corvallis, OR, 97331, United States
| | - Alexa Niño de Rivera
- Department of Forest Ecosystems and Society, Oregon State University, 3180 SW Jefferson Way, Corvallis, OR, 97331, United States
| | - Wellington Muchero
- Biosciences Division, Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN, 37830, United States
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN, 37830, United States
- Bredesen Center for Interdisciplinary Research, University of Tennessee, 821 Volunteer Blvd., Knoxville, TN, 37996, United States
| | - Li Fuxin
- Department of Electrical Engineering and Computer Science, Oregon State University, 110 SW Park Terrace, Corvallis, OR, 97331, United States
| | - Steven H Strauss
- Department of Forest Ecosystems and Society, Oregon State University, 3180 SW Jefferson Way, Corvallis, OR, 97331, United States
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12
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Lagergren J, Pavicic M, Chhetri HB, York LM, Hyatt D, Kainer D, Rutter EM, Flores K, Bailey-Bale J, Klein M, Taylor G, Jacobson D, Streich J. Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0072. [PMID: 37519935 PMCID: PMC10380552 DOI: 10.34133/plantphenomics.0072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 06/27/2023] [Indexed: 08/01/2023]
Abstract
Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.
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Affiliation(s)
- John Lagergren
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Mirko Pavicic
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Hari B Chhetri
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Larry M York
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Doug Hyatt
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - David Kainer
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Erica M Rutter
- Department of Applied Mathematics, University of California, Merced, CA, USA
| | - Kevin Flores
- Department of Mathematics, North Carolina State University, Raleigh, NC, USA
| | - Jack Bailey-Bale
- Department of Plant Sciences, University of California, Davis, CA, USA
| | - Marie Klein
- Department of Plant Sciences, University of California, Davis, CA, USA
| | - Gail Taylor
- Department of Plant Sciences, University of California, Davis, CA, USA
| | - Daniel Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Jared Streich
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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13
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Saint-Vincent PMB, Furches A, Galanie S, Teixeira Prates E, Aldridge JL, Labbe A, Zhao N, Martin MZ, Ranjan P, Jones P, Kainer D, Kalluri UC, Chen JG, Muchero W, Jacobson DA, Tschaplinski TJ. Validation of a metabolite-GWAS network for Populus trichocarpa family 1 UDP-glycosyltransferases. FRONTIERS IN PLANT SCIENCE 2023; 14:1210146. [PMID: 37546246 PMCID: PMC10402742 DOI: 10.3389/fpls.2023.1210146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 06/05/2023] [Indexed: 08/08/2023]
Abstract
Metabolite genome-wide association studies (mGWASs) are increasingly used to discover the genetic basis of target phenotypes in plants such as Populus trichocarpa, a biofuel feedstock and model woody plant species. Despite their growing importance in plant genetics and metabolomics, few mGWASs are experimentally validated. Here, we present a functional genomics workflow for validating mGWAS-predicted enzyme-substrate relationships. We focus on uridine diphosphate-glycosyltransferases (UGTs), a large family of enzymes that catalyze sugar transfer to a variety of plant secondary metabolites involved in defense, signaling, and lignification. Glycosylation influences physiological roles, localization within cells and tissues, and metabolic fates of these metabolites. UGTs have substantially expanded in P. trichocarpa, presenting a challenge for large-scale characterization. Using a high-throughput assay, we produced substrate acceptance profiles for 40 previously uncharacterized candidate enzymes. Assays confirmed 10 of 13 leaf mGWAS associations, and a focused metabolite screen demonstrated varying levels of substrate specificity among UGTs. A substrate binding model case study of UGT-23 rationalized observed enzyme activities and mGWAS associations, including glycosylation of trichocarpinene to produce trichocarpin, a major higher-order salicylate in P. trichocarpa. We identified UGTs putatively involved in lignan, flavonoid, salicylate, and phytohormone metabolism, with potential implications for cell wall biosynthesis, nitrogen uptake, and biotic and abiotic stress response that determine sustainable biomass crop production. Our results provide new support for in silico analyses and evidence-based guidance for in vivo functional characterization.
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Affiliation(s)
- Patricia M. B. Saint-Vincent
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Anna Furches
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, United States
| | - Stephanie Galanie
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
- Protein Engineering, Merck & Co., Inc., Rahway, NJ, United States
| | - Erica Teixeira Prates
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Jessa L. Aldridge
- Department of Biomedical Sciences, Quillen College of Medicine, East Tennessee State University, Johnson City, TN, United States
| | - Audrey Labbe
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Nan Zhao
- School of Electrical Engineering, Southeast University, Nanjing, China
| | - Madhavi Z. Martin
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Priya Ranjan
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Piet Jones
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, United States
| | - David Kainer
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Udaya C. Kalluri
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, United States
| | - Jin-Gui Chen
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, United States
| | - Wellington Muchero
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, United States
| | - Daniel A. Jacobson
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, United States
| | - Timothy J. Tschaplinski
- Center for Bioenergy Innovation, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
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14
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Zhou X, Xiang X, Zhang M, Cao D, Du C, Zhang L, Hu J. Combining GS-assisted GWAS and transcriptome analysis to mine candidate genes for nitrogen utilization efficiency in Populus cathayana. BMC PLANT BIOLOGY 2023; 23:182. [PMID: 37020197 PMCID: PMC10074878 DOI: 10.1186/s12870-023-04202-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 03/29/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Forest trees such as poplar, shrub willow, et al. are essential natural resources for sustainable and renewable energy production, and their wood can reduce dependence on fossil fuels and reduce environmental pollution. However, the productivity of forest trees is often limited by the availability of nitrogen (N), improving nitrogen use efficiency (NUE) is an important way to address it. Currently, NUE genetic resources are scarce in forest tree research, and more genetic resources are urgently needed. RESULTS Here, we performed genome-wide association studies (GWAS) using the mixed linear model (MLM) to identify genetic loci regulating growth traits in Populus cathayana at two N levels, and attempted to enhance the signal strength of single nucleotide polymorphism (SNP) detection by performing genome selection (GS) assistance GWAS. The results of the two GWAS analyses identified 55 and 40 SNPs that were respectively associated with plant height (PH) and ground diameter (GD), and 92 and 69 candidate genes, including 30 overlapping genes. The prediction accuracy of the GS model (rrBLUP) for phenotype exceeds 0.9. Transcriptome analysis of 13 genotypes under two N levels showed that genes related to carbon and N metabolism, amino acid metabolism, energy metabolism, and signal transduction were differentially expressed in the xylem of P. cathayana under N treatment. Furthermore, we observed strong regional patterns in gene expression levels of P. cathayana, with significant differences between different regions. Among them, P. cathayana in Longquan region exhibited the highest response to N. Finally, through weighted gene co-expression network analysis (WGCNA), we identified a module closely related to the N metabolic process and eight hub genes. CONCLUSIONS Integrating the GWAS, RNA-seq and WGCNA data, we ultimately identified four key regulatory genes (PtrNAC123, PtrNAC025, Potri.002G233100, and Potri.006G236200) involved in the wood formation process, and they may affect P. cathayana growth and wood formation by regulating nitrogen metabolism. This study will provide strong evidence for N regulation mechanisms, and reliable genetic resources for growth and NUE genetic improvement in poplar.
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Affiliation(s)
- Xinglu Zhou
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Xiaodong Xiang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Min Zhang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Demei Cao
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Changjian Du
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Lei Zhang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China.
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, Jiangsu, China.
| | - Jianjun Hu
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China.
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, Jiangsu, China.
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15
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Liu P, Bu C, Chen P, El-Kassaby YA, Zhang D, Song Y. Enhanced genome-wide association reveals the role of YABBY11-NGATHA-LIKE1 in leaf serration development of Populus. PLANT PHYSIOLOGY 2023; 191:1702-1718. [PMID: 36535002 PMCID: PMC10022644 DOI: 10.1093/plphys/kiac585] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 11/17/2022] [Indexed: 06/17/2023]
Abstract
Leaf margins are complex plant morphological features that contribute to leaf shape diversity, which affects plant structure, yield, and adaptation. Although several leaf margin regulators have been identified to date, the genetic basis of their natural variation has not been fully elucidated. In this study, we profiled two distinct leaf morphology types (serrated and smooth) using the persistent homology mathematical framework (PHMF) in two poplar species (Populus tomentosa and Populus simonii, respectively). A combined genome-wide association study (GWAS) and expression quantitative trait nucleotide (eQTN) mapping were applied to create a leaf morphology control module using data from P. tomentosa and P. simonii populations. Natural variation in leaf margins was associated with YABBY11 (YAB11) transcript abundance in poplar. In P. tomentosa, PtoYAB11 carries a premature stop codon (PtoYAB11PSC), resulting in the loss of its positive regulation of NGATHA-LIKE1 (PtoNGAL-1) and RIBULOSE BISPHOSPHATE CARBOXYLASE LARGE SUBUNIT (PtoRBCL). Overexpression of PtoYAB11PSC promoted serrated leaf margins, enlarged leaves, enhanced photosynthesis, and increased biomass. Overexpression of PsiYAB11 in P. tomentosa promoted smooth leaf margins, higher stomatal density, and greater light damage repair ability. In poplar, YAB11-NGAL1 is sensitive to environmental conditions, acts as a positive regulator of leaf margin serration, and may also link environmental signaling to leaf morphological plasticity.
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Affiliation(s)
- Peng Liu
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
| | - Chenhao Bu
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
| | - Panfei Chen
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
| | - Yousry A El-Kassaby
- Department of Forest and Conservation Sciences, Faculty of Forestry, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Deqiang Zhang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
| | - Yuepeng Song
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing 100083, P.R. China
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16
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Responses to Drought Stress in Poplar: What Do We Know and What Can We Learn? Life (Basel) 2023; 13:life13020533. [PMID: 36836891 PMCID: PMC9962866 DOI: 10.3390/life13020533] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 02/09/2023] [Accepted: 02/11/2023] [Indexed: 02/17/2023] Open
Abstract
Poplar (Populus spp.) is a high-value crop for wood and biomass production and a model organism for tree physiology and genomics. The early release, in 2006, of the complete genome sequence of P. trichocarpa was followed by a wealth of studies that significantly enriched our knowledge of complex pathways inherent to woody plants, such as lignin biosynthesis and secondary cell wall deposition. Recently, in the attempt to cope with the challenges posed by ongoing climate change, fundamental studies and breeding programs with poplar have gradually shifted their focus to address the responses to abiotic stresses, particularly drought. Taking advantage from a set of modern genomic and phenotyping tools, these studies are now shedding light on important processes, including embolism formation (the entry and expansion of air bubbles in the xylem) and repair, the impact of drought stress on biomass yield and quality, and the long-term effects of drought events. In this review, we summarize the status of the research on the molecular bases of the responses to drought in poplar. We highlight how this knowledge can be exploited to select more tolerant genotypes and how it can be translated to other tree species to improve our understanding of forest dynamics under rapidly changing environmental conditions.
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17
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Zhou J, Xiao L, Huang R, Song F, Li L, Li P, Fang Y, Lu W, Lv C, Quan M, Zhang D, Du Q. Local diversity of drought resistance and resilience in Populus tomentosa correlates with the variation of DNA methylation. PLANT, CELL & ENVIRONMENT 2023; 46:479-497. [PMID: 36385613 DOI: 10.1111/pce.14490] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/25/2022] [Accepted: 11/10/2022] [Indexed: 06/16/2023]
Abstract
Little information is known about DNA methylation variation in shaping environment-specific drought resistance and resilience for tree adaptation. In this study, we leveraged RNA sequencing and whole-genome bisulfite sequencing data to dissect the distinction of epigenetic regulation under drought stress and rewater condition of Populus tomentosa accessions from three geographical regions. We demonstrated low resistance and high resilience for accessions from South. Non-CG methylation levels in promoter regions of Southern accessions were lower than accessions from higher latitudes and negatively regulated gene expression. CHH context methylation was more sensitive to drought stress, and the geographical-specific differentially methylated regions were scarcely changed by environmental fluctuation. We identified 60 conserved hub genes within the co-expression networks that correlate with photosynthetic and stomatal morphological traits. Epigenome-wide association studies and genome-wide association studies of these 60 hub genes revealed the interdependency between genetic and epigenetic variation in GATA9 and LECRK-VIII.2, which was associated with stomatal morphology and chlorophyll content. The natural epigenetic variation in GATA9 was also faithfully transmitted to progenies in two family-based F1 populations. This study indicates a functional relationship of DNA methylation diversity with drought resistance and resilience which offers new insights into plants' local adaptation to a stressful environment.
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Affiliation(s)
- Jiaxuan Zhou
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Liang Xiao
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Rui Huang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Fangyuan Song
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Lianzheng Li
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Peng Li
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Yuanyuan Fang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Wenjie Lu
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Chenfei Lv
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Mingyang Quan
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Deqiang Zhang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Qingzhang Du
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
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18
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Harfouche AL, Nakhle F, Harfouche AH, Sardella OG, Dart E, Jacobson D. A primer on artificial intelligence in plant digital phenomics: embarking on the data to insights journey. TRENDS IN PLANT SCIENCE 2023; 28:154-184. [PMID: 36167648 DOI: 10.1016/j.tplants.2022.08.021] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 08/22/2022] [Accepted: 08/25/2022] [Indexed: 06/16/2023]
Abstract
Artificial intelligence (AI) has emerged as a fundamental component of global agricultural research that is poised to impact on many aspects of plant science. In digital phenomics, AI is capable of learning intricate structure and patterns in large datasets. We provide a perspective and primer on AI applications to phenome research. We propose a novel human-centric explainable AI (X-AI) system architecture consisting of data architecture, technology infrastructure, and AI architecture design. We clarify the difference between post hoc models and 'interpretable by design' models. We include guidance for effectively using an interpretable by design model in phenomic analysis. We also provide directions to sources of tools and resources for making data analytics increasingly accessible. This primer is accompanied by an interactive online tutorial.
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Affiliation(s)
- Antoine L Harfouche
- Department for Innovation in Biological, Agro-Food, and Forest Systems, University of Tuscia, Viterbo, VT 01100, Italy.
| | - Farid Nakhle
- Department for Innovation in Biological, Agro-Food, and Forest Systems, University of Tuscia, Viterbo, VT 01100, Italy
| | - Antoine H Harfouche
- Unité de Formation et de Recherche en Sciences Économiques, Gestion, Mathématiques, et Informatique, Université Paris Nanterre, 92001 Nanterre, France
| | - Orlando G Sardella
- Department for Innovation in Biological, Agro-Food, and Forest Systems, University of Tuscia, Viterbo, VT 01100, Italy
| | - Eli Dart
- Energy Sciences Network (ESnet), Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Daniel Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
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19
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Abeyratne CR, Macaya-Sanz D, Zhou R, Barry KW, Daum C, Haiby K, Lipzen A, Stanton B, Yoshinaga Y, Zane M, Tuskan GA, DiFazio SP. High-resolution mapping reveals hotspots and sex-biased recombination in Populus trichocarpa. G3 (BETHESDA, MD.) 2023; 13:jkac269. [PMID: 36250890 PMCID: PMC9836356 DOI: 10.1093/g3journal/jkac269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 09/28/2022] [Indexed: 12/14/2022]
Abstract
Fine-scale meiotic recombination is fundamental to the outcome of natural and artificial selection. Here, dense genetic mapping and haplotype reconstruction were used to estimate recombination for a full factorial Populus trichocarpa cross of 7 males and 7 females. Genomes of the resulting 49 full-sib families (N = 829 offspring) were resequenced, and high-fidelity biallelic SNP/INDELs and pedigree information were used to ascertain allelic phase and impute progeny genotypes to recover gametic haplotypes. The 14 parental genetic maps contained 1,820 SNP/INDELs on average that covered 376.7 Mb of physical length across 19 chromosomes. Comparison of parental and progeny haplotypes allowed fine-scale demarcation of cross-over regions, where 38,846 cross-over events in 1,658 gametes were observed. Cross-over events were positively associated with gene density and negatively associated with GC content and long-terminal repeats. One of the most striking findings was higher rates of cross-overs in males in 8 out of 19 chromosomes. Regions with elevated male cross-over rates had lower gene density and GC content than windows showing no sex bias. High-resolution analysis identified 67 candidate cross-over hotspots spread throughout the genome. DNA sequence motifs enriched in these regions showed striking similarity to those of maize, Arabidopsis, and wheat. These findings, and recombination estimates, will be useful for ongoing efforts to accelerate domestication of this and other biomass feedstocks, as well as future studies investigating broader questions related to evolutionary history, perennial development, phenology, wood formation, vegetative propagation, and dioecy that cannot be studied using annual plant model systems.
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Affiliation(s)
| | - David Macaya-Sanz
- Department of Forest Ecology & Genetics, CIFOR-INIA, CSIC, Madrid 28040, Spain
| | - Ran Zhou
- Warnell School of Forestry and Natural Resources, Department of Genetics, and Department of Plant Biology, University of Georgia, Athens, GA 30602, USA
| | - Kerrie W Barry
- Department of Energy Joint Genome Institute, Berkeley, CA 94720, USA
| | - Christopher Daum
- Department of Energy Joint Genome Institute, Berkeley, CA 94720, USA
| | | | - Anna Lipzen
- Department of Energy Joint Genome Institute, Berkeley, CA 94720, USA
| | | | - Yuko Yoshinaga
- Department of Energy Joint Genome Institute, Berkeley, CA 94720, USA
| | - Matthew Zane
- Department of Energy Joint Genome Institute, Berkeley, CA 94720, USA
| | - Gerald A Tuskan
- Biosciences Division, Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
| | - Stephen P DiFazio
- Department of Biology, West Virginia University, Morgantown, WV 26506, USA
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20
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Li L, Jin Z, Huang R, Zhou J, Song F, Yao L, Li P, Lu W, Xiao L, Quan M, Zhang D, Du Q. Leaf physiology variations are modulated by natural variations that underlie stomatal morphology in Populus. PLANT, CELL & ENVIRONMENT 2023; 46:150-170. [PMID: 36285358 DOI: 10.1111/pce.14471] [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: 02/23/2022] [Revised: 05/26/2022] [Accepted: 05/28/2022] [Indexed: 06/16/2023]
Abstract
Stomata are essential for photosynthesis and abiotic stress tolerance. Here, we used multiomics approaches to dissect the genetic architecture and adaptive mechanisms that underlie stomatal morphology in Populus tomentosa juvenile natural population (303 accessions). We detected 46 candidate genes and 15 epistatic gene-pairs, associated with 5 stomatal morphologies and 18 leaf development and photosynthesis traits, through genome-wide association studies. Expression quantitative trait locus mapping revealed that stomata-associated gene loci were significantly associated with the expression of leaf-related genes; selective sweep analysis uncovered significant differentiation in the allele frequencies of genes that underlie stomatal variations. An allelic regulatory network operating under drought stress and adequate precipitation conditions, with three key regulators (DUF538, TRA2 and AbFH2) and eight interacting genes, was identified that might regulate leaf physiology via modulation of stomatal shape and density. Validation of candidate gene variations in drought-tolerant and F1 hybrid populations of P. tomentosa showed that the DUF538, TRA2 and AbFH2 loci cause functional stabilisation of spatiotemporal regulatory, whose favourable alleles can be faithfully transmitted to offspring. This study provides insights concerning leaf physiology and stress tolerance via the regulation of stomatal determination in perennial plants.
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Affiliation(s)
- Lianzheng Li
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Zhuoying Jin
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Rui Huang
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Jiaxuan Zhou
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Fangyuan Song
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Liangchen Yao
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Peng Li
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Wenjie Lu
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Liang Xiao
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Mingyang Quan
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Deqiang Zhang
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
| | - Qingzhang Du
- National Engineering Research Center of Tree breeding and Ecological restoration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
- The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P.R. China
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21
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Cappa EP, Chen C, Klutsch JG, Sebastian-Azcona J, Ratcliffe B, Wei X, Da Ros L, Ullah A, Liu Y, Benowicz A, Sadoway S, Mansfield SD, Erbilgin N, Thomas BR, El-Kassaby YA. Multiple-trait analyses improved the accuracy of genomic prediction and the power of genome-wide association of productivity and climate change-adaptive traits in lodgepole pine. BMC Genomics 2022; 23:536. [PMID: 35870886 PMCID: PMC9308220 DOI: 10.1186/s12864-022-08747-7] [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: 02/03/2022] [Accepted: 07/08/2022] [Indexed: 11/10/2022] Open
Abstract
Background Genomic prediction (GP) and genome-wide association (GWA) analyses are currently being employed to accelerate breeding cycles and to identify alleles or genomic regions of complex traits in forest trees species. Here, 1490 interior lodgepole pine (Pinus contorta Dougl. ex. Loud. var. latifolia Engelm) trees from four open-pollinated progeny trials were genotyped with 25,099 SNPs, and phenotyped for 15 growth, wood quality, pest resistance, drought tolerance, and defense chemical (monoterpenes) traits. The main objectives of this study were to: (1) identify genetic markers associated with these traits and determine their genetic architecture, and to compare the marker detected by single- (ST) and multiple-trait (MT) GWA models; (2) evaluate and compare the accuracy and control of bias of the genomic predictions for these traits underlying different ST and MT parametric and non-parametric GP methods. GWA, ST and MT analyses were compared using a linear transformation of genomic breeding values from the respective genomic best linear unbiased prediction (GBLUP) model. GP, ST and MT parametric and non-parametric (Reproducing Kernel Hilbert Spaces, RKHS) models were compared in terms of prediction accuracy (PA) and control of bias. Results MT-GWA analyses identified more significant associations than ST. Some SNPs showed potential pleiotropic effects. Averaging across traits, PA from the studied ST-GP models did not differ significantly from each other, with generally a slight superiority of the RKHS method. MT-GP models showed significantly higher PA (and lower bias) than the ST models, being generally the PA (bias) of the RKHS approach significantly higher (lower) than the GBLUP. Conclusions The power of GWA and the accuracy of GP were improved when MT models were used in this lodgepole pine population. Given the number of GP and GWA models fitted and the traits assessed across four progeny trials, this work has produced the most comprehensive empirical genomic study across any lodgepole pine population to date. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08747-7.
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22
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Reinert S. Quantitative genetics of pleiotropy and its potential for plant sciences. JOURNAL OF PLANT PHYSIOLOGY 2022; 276:153784. [PMID: 35944292 DOI: 10.1016/j.jplph.2022.153784] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/14/2022] [Accepted: 07/18/2022] [Indexed: 06/15/2023]
Affiliation(s)
- Stephan Reinert
- Friedrich-Alexander-University Erlangen-Nürnberg, Department of Biology, Division of Biochemistry, Biocomputing Lab, Staudtstraße 5, 91058, Erlangen, Germany.
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23
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Snyder KA, Robinson SA, Schmidt S, Hultine KR. Stable isotope approaches and opportunities for improving plant conservation. CONSERVATION PHYSIOLOGY 2022; 10:coac056. [PMID: 35966756 PMCID: PMC9367551 DOI: 10.1093/conphys/coac056] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 04/15/2021] [Accepted: 08/01/2022] [Indexed: 06/01/2023]
Abstract
Successful conservation of threatened species and ecosystems in a rapidly changing world requires scientifically sound decision-making tools that are readily accessible to conservation practitioners. Physiological applications that examine how plants and animals interact with their environment are now widely used when planning, implementing and monitoring conservation. Among these tools, stable-isotope physiology is a potentially powerful, yet under-utilized cornerstone of current and future conservation efforts of threatened and endangered plants. We review the underlying concepts and theory of stable-isotope physiology and describe how stable-isotope applications can support plant conservation. We focus on stable isotopes of carbon, hydrogen, oxygen and nitrogen to address plant ecophysiological responses to changing environmental conditions across temporal scales from hours to centuries. We review examples from a broad range of plant taxa, life forms and habitats and provide specific examples where stable-isotope analysis can directly improve conservation, in part by helping identify resilient, locally adapted genotypes or populations. Our review aims to provide a guide for practitioners to easily access and evaluate the information that can be derived from stable-isotope signatures, their limitations and how stable isotopes can improve conservation efforts.
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Affiliation(s)
- Keirith A Snyder
- Corresponding author: USDA Agricultural Research Service, Great Basin Rangelands Research Unit, Reno,
920 Valley Road, NV 89512, USA.
| | - Sharon A Robinson
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, New South Wales 2522, Australia
- Securing Antarctica’s Environmental Future, University of Wollongong, Wollongong, New South Wales 2522, Australia
| | - Susanne Schmidt
- School of Agriculture and Food Sciences, The University of Queensland, Building 62, Brisbane Queensland 4075, Australia
| | - Kevin R Hultine
- Department of Research, Conservation and Collections, Desert Botanical Garden, 1201 Galvin Parkway, Phoenix, AZ 85008, USA
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24
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Chen ZQ, Zan Y, Zhou L, Karlsson B, Tuominen H, García-Gil MR, Wu HX. Genetic architecture behind developmental and seasonal control of tree growth and wood properties in Norway spruce. FRONTIERS IN PLANT SCIENCE 2022; 13:927673. [PMID: 36017254 PMCID: PMC9396349 DOI: 10.3389/fpls.2022.927673] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 07/12/2022] [Indexed: 06/01/2023]
Abstract
Genetic control of tree growth and wood formation varies depending on the age of the tree and the time of the year. Single-locus, multi-locus, and multi-trait genome-wide association studies (GWAS) were conducted on 34 growth and wood property traits in 1,303 Norway spruce individuals using exome capture to cover ~130K single-nucleotide polymorphisms (SNPs). GWAS identified associations to the different wood traits in a total of 85 gene models, and several of these were validated in a progenitor population. A multi-locus GWAS model identified more SNPs associated with the studied traits than single-locus or multivariate models. Changes in tree age and annual season influenced the genetic architecture of growth and wood properties in unique ways, manifested by non-overlapping SNP loci. In addition to completely novel candidate genes, SNPs were located in genes previously associated with wood formation, such as cellulose synthases and a NAC transcription factor, but that have not been earlier linked to seasonal or age-dependent regulation of wood properties. Interestingly, SNPs associated with the width of the year rings were identified in homologs of Arabidopsis thaliana BARELY ANY MERISTEM 1 and rice BIG GRAIN 1, which have been previously shown to control cell division and biomass production. The results provide tools for future Norway spruce breeding and functional studies.
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Affiliation(s)
- Zhi-Qiang Chen
- Department Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Yanjun Zan
- Department Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Linghua Zhou
- Department Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, Umeå, Sweden
| | | | - Hannele Tuominen
- Department Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Maria Rosario García-Gil
- Department Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Harry X. Wu
- Department Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, Umeå, Sweden
- The Commonwealth Scientific and Industrial Research Organisation (CSIRO) National Collection Research Australia, Black Mountain Laboratory, Canberra, ACT, Australia
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25
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Hillary VE, Ceasar SA. Prime editing in plants and mammalian cells: Mechanism, achievements, limitations, and future prospects. Bioessays 2022; 44:e2200032. [PMID: 35750651 DOI: 10.1002/bies.202200032] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 06/13/2022] [Accepted: 06/14/2022] [Indexed: 01/06/2023]
Abstract
Clustered, regularly interspaced, short palindromic repeat (CRISPR)/CRISPR-associated protein (CRISPR/Cas) system has revolutionized genetic research in the life sciences. Four classes of CRISPR/Cas-derived genome editing agents, such as nuclease, base editor, recombinase, and prime editor have been introduced for engineering the genomes of diverse organisms. The recently introduced prime editing system offers precise editing without many off-target effects than traditional CRISPR-based systems. Many researchers have successfully applied this gene-editing toolbox in diverse systems for various genome-editing applications. This review presents the mechanism of prime editing and summarizes the details of the prime editing system applied in plants and mammalian cells for precise genome editing. We also discuss the advantages, limitations, and potential future applications of prime editing in these systems. This review enables the researcher to gain knowledge on prime editing tools and their potential applications in plants and mammalian cells.
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Affiliation(s)
- V Edwin Hillary
- Department of Biosciences, Rajagiri College of Social Sciences, Cochin, Kerala, India
| | - S Antony Ceasar
- Department of Biosciences, Rajagiri College of Social Sciences, Cochin, Kerala, India
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Zhang M, Lu N, Jiang L, Liu B, Fei Y, Ma W, Shi C, Wang J. Multiple dynamic models reveal the genetic architecture for growth in height of Catalpa bungei in the field. TREE PHYSIOLOGY 2022; 42:1239-1255. [PMID: 34940852 DOI: 10.1093/treephys/tpab171] [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: 06/28/2021] [Accepted: 12/19/2021] [Indexed: 06/14/2023]
Abstract
Growth in height (GH) is a critical determinant for tree survival and development in forests and can be depicted using logistic growth curves. Our understanding of the genetic mechanism underlying dynamic GH, however, is limited, particularly under field conditions. We applied two mapping models (Funmap and FVTmap) to find quantitative trait loci responsible for dynamic GH and two epistatic models (2HiGWAS and 1HiGWAS) to detect epistasis in Catalpa bungei grown in the field. We identified 13 co-located quantitative trait loci influencing the growth curve by Funmap and three heterochronic parameters (the timing of the inflection point, maximum acceleration and maximum deceleration) by FVTmap. The combined use of FVTmap and Funmap reduced the number of candidate genes by >70%. We detected 76 significant epistatic interactions, amongst which a key gene, COMT14, co-located by three models (but not 1HiGWAS) interacted with three other genes, implying that a novel network of protein interaction centered on COMT14 may control the dynamic GH of C. bungei. These findings provide new insights into the genetic mechanisms underlying the dynamic growth in tree height in natural environments and emphasize the necessity of incorporating multiple dynamic models for screening more reliable candidate genes.
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Affiliation(s)
- Miaomiao Zhang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Nan Lu
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Libo Jiang
- School of Life Sciences and Medicine, Shandong University of Technology, Zibo 255049, China
| | - Bingyang Liu
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Yue Fei
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Wenjun Ma
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Chaozhong Shi
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Junhui Wang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
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Tan B, Ingvarsson PK. Integrating genome-wide association mapping of additive and dominance genetic effects to improve genomic prediction accuracy in Eucalyptus. THE PLANT GENOME 2022; 15:e20208. [PMID: 35441826 DOI: 10.1002/tpg2.20208] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 03/16/2022] [Indexed: 06/14/2023]
Abstract
Genome-wide association studies (GWAS) is a powerful and widely used approach to decipher the genetic control of complex traits. Still, a significant challenge for dissecting quantitative traits in forest trees is statistical power. This study uses a population consisting of 1,123 samples derived from two successive generations of crosses between Eucalyptus grandis (W. Hill) and E. urophylla (S.T. Blake). All samples have been phenotyped for growth and wood property traits and genotyped using the EuChip60K chip, yielding 37,832 informative single nucleotide polymorphisms (SNPs). We use multi-locus GWAS models to assess additive and dominance effects to identify markers associated with growth and wood property traits in the eucalypt hybrids. Additive and dominance association models identified 78 and 82 significant SNPs across all traits, respectively, which captured between 39 and 86% of the genomic-based heritability. We also used SNPs identified from the GWAS and SNPs using less stringent significance thresholds to evaluate predictive abilities in a genomic selection framework. Genomic selection models based on the top 1% SNPs captured a substantially greater proportion of the genetic variance of traits compared with when we used all SNPs for model training. The prediction ability of estimated breeding values improved significantly for all traits when using either the top 1% SNPs or SNPs identified using a relaxed p value threshold (p < 10-3 ). This study also highlights the added value of incorporating dominance effects for identifying genomic regions controlling growth traits in trees. Moreover, integrating GWAS results into genomic selection method provides enhanced power relative to discrete associations for identifying genomic variation potentially valuable for forest tree breeding.
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Affiliation(s)
- Biyue Tan
- Umeå Plant Science Centre, Dep. of Ecology and Environmental Science, Umeå Univ., Umeå, SE-90187, Sweden
- Stora Enso AB, Nacka, SE-131 04, Sweden
| | - Pär K Ingvarsson
- Linnean Centre for Plant Biology, Dep. of Plant Biology, Uppsala BioCenter, Swedish Univ. of Agricultural Sciences, Uppsala, SE-750 07, Sweden
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Yuan J, Kaur D, Zhou Z, Nagle M, Kiddle NG, Doshi NA, Behnoudfar A, Peremyslova E, Ma C, Strauss SH, Li F. Robust High-Throughput Phenotyping with Deep Segmentation Enabled by a Web-Based Annotator. PLANT PHENOMICS 2022; 2022:9893639. [PMID: 36059601 PMCID: PMC9394117 DOI: 10.34133/2022/9893639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 03/17/2022] [Indexed: 11/24/2022]
Abstract
The abilities of plant biologists and breeders to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation, and particularly to collect this data at a high-throughput scale with low cost. Although deep learning methods have demonstrated unprecedented potential to automate plant phenotyping, these methods commonly rely on large training sets that can be time-consuming to generate. Intelligent algorithms have therefore been proposed to enhance the productivity of these annotations and reduce human efforts. We propose a high-throughput phenotyping system which features a Graphical User Interface (GUI) and a novel interactive segmentation algorithm: Semantic-Guided Interactive Object Segmentation (SGIOS). By providing a user-friendly interface and intelligent assistance with annotation, this system offers potential to streamline and accelerate the generation of training sets, reducing the effort required by the user. Our evaluation shows that our proposed SGIOS model requires fewer user inputs compared to the state-of-art models for interactive segmentation. As a case study of the use of the GUI applied for genetic discovery in plants, we present an example of results from a preliminary genome-wide association study (GWAS) of in planta regeneration in Populus trichocarpa (poplar). We further demonstrate that the inclusion of a semantic prior map with SGIOS can accelerate the training process for future GWAS, using a sample of a dataset extracted from a poplar GWAS of in vitro regeneration. The capabilities of our phenotyping system surpass those of unassisted humans to rapidly and precisely phenotype our traits of interest. The scalability of this system enables large-scale phenomic screens that would otherwise be time-prohibitive, thereby providing increased power for GWAS, mutant screens, and other studies relying on large sample sizes to characterize the genetic basis of trait variation. Our user-friendly system can be used by researchers lacking a computational background, thus helping to democratize the use of deep segmentation as a tool for plant phenotyping.
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Affiliation(s)
| | | | - Zheng Zhou
- Oregon State University, Corvallis, OR, USA
| | | | | | | | | | | | | | | | - Fuxin Li
- Oregon State University, Corvallis, OR, USA
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Improving lodgepole pine genomic evaluation using spatial correlation structure and SNP selection with single-step GBLUP. Heredity (Edinb) 2022; 128:209-224. [PMID: 35181761 PMCID: PMC8986842 DOI: 10.1038/s41437-022-00508-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 01/27/2022] [Accepted: 01/28/2022] [Indexed: 01/20/2023] Open
Abstract
Modeling environmental spatial heterogeneity can improve the efficiency of forest tree genomic evaluation. Furthermore, genotyping costs can be lowered by reducing the number of markers needed. We investigated the impact on variance components, breeding value accuracy, and bias of two phenotypic data adjustments (experimental design and autoregressive spatial models), and a relationship matrix calculated from a subset of markers selected for their ability to infer ancestry. Using a multiple-trait multiple-site single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) approach, four scenarios (2 phenotype adjustments × 2 marker sets) were applied to diameter at breast height (DBH), height (HT), and resistance to western gall rust (WGR) in four open-pollinated progeny trials of lodgepole pine, with 1490 (out of 11,188) trees genotyped with 25,099 SNPs. As a control, we fitted the conventional ABLUP model using pedigree information. The highest heritability estimates were achieved for the ABLUP followed closely by the ssGBLUP with the full marker set and using the spatial phenotype adjustments. The highest predictive ability was obtained by using a reduced marker subset (8000 SNPs) when either the spatial (DBH: 0.429, and WGR: 0.513) or design (HT: 0.467) phenotype corrections were used. No significant difference was detected in prediction bias among the six fitted models, and all values were close to 1 (0.918-1.014). Results demonstrated that selecting informative markers, such as those capturing ancestry, can improve the predictive ability. The use of spatial correlation structure increased traits' heritability and reduced prediction bias, while increases in predictive ability were trait-dependent.
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Harman-Ware AE, Happs RM, Macaya-Sanz D, Doeppke C, Muchero W, DiFazio SP. Abundance of Major Cell Wall Components in Natural Variants and Pedigrees of Populus trichocarpa. FRONTIERS IN PLANT SCIENCE 2022; 13:757810. [PMID: 35185975 PMCID: PMC8850957 DOI: 10.3389/fpls.2022.757810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 01/04/2022] [Indexed: 06/14/2023]
Abstract
The rapid analysis of biopolymers including lignin and sugars in lignocellulosic biomass cell walls is essential for the analysis of the large sample populations needed for identifying heritable genetic variation in biomass feedstocks for biofuels and bioproducts. In this study, we reported the analysis of cell wall lignin content, syringyl/guaiacyl (S/G) ratio, as well as glucose and xylose content by high-throughput pyrolysis-molecular beam mass spectrometry (py-MBMS) for >3,600 samples derived from hundreds of accessions of Populus trichocarpa from natural populations, as well as pedigrees constructed from 14 parents (7 × 7). Partial Least Squares (PLS) regression models were built from the samples of known sugar composition previously determined by hydrolysis followed by nuclear magnetic resonance (NMR) analysis. Key spectral features positively correlated with glucose content consisted of m/z 126, 98, and 69, among others, deriving from pyrolyzates such as hydroxymethylfurfural, maltol, and other sugar-derived species. Xylose content positively correlated primarily with many lignin-derived ions and to a lesser degree with m/z 114, deriving from a lactone produced from xylose pyrolysis. Models were capable of predicting glucose and xylose contents with an average error of less than 4%, and accuracy was significantly improved over previously used methods. The differences in the models constructed from the two sample sets varied in training sample number, but the genetic and compositional uniformity of the pedigree set could be a potential driver in the slightly better performance of that model in comparison with the natural variants. Broad-sense heritability of glucose and xylose composition using these data was 0.32 and 0.34, respectively. In summary, we have demonstrated the use of a single high-throughput method to predict sugar and lignin composition in thousands of poplar samples to estimate the heritability and phenotypic plasticity of traits necessary to develop optimized feedstocks for bioenergy applications.
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Affiliation(s)
- Anne E. Harman-Ware
- Renewable Resources and Enabling Sciences Center, Center for Bioenergy Innovation, National Renewable Energy Laboratory, Golden, CO, United States
| | - Renee M. Happs
- Renewable Resources and Enabling Sciences Center, Center for Bioenergy Innovation, National Renewable Energy Laboratory, Golden, CO, United States
| | - David Macaya-Sanz
- Department of Forest Ecology and Genetics, INIA-CIFOR, Madrid, Spain
- Department of Biology, West Virginia University, Morgantown, WV, United States
| | - Crissa Doeppke
- Renewable Resources and Enabling Sciences Center, Center for Bioenergy Innovation, National Renewable Energy Laboratory, Golden, CO, United States
| | - Wellington Muchero
- Biosciences Division, Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Stephen P. DiFazio
- Department of Biology, West Virginia University, Morgantown, WV, United States
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31
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Cavedon M, vonHoldt B, Hebblewhite M, Hegel T, Heppenheimer E, Hervieux D, Mariani S, Schwantje H, Steenweg R, Theoret J, Watters M, Musiani M. Genomic legacy of migration in endangered caribou. PLoS Genet 2022; 18:e1009974. [PMID: 35143486 PMCID: PMC8830729 DOI: 10.1371/journal.pgen.1009974] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 12/01/2021] [Indexed: 11/18/2022] Open
Abstract
Wide-ranging animals, including migratory species, are significantly threatened by the effects of habitat fragmentation and habitat loss. In the case of terrestrial mammals, this results in nearly a quarter of species being at risk of extinction. Caribou are one such example of a wide-ranging, migratory, terrestrial, and endangered mammal. In populations of caribou, the proportion of individuals considered as "migrants" can vary dramatically. There is therefore a possibility that, under the condition that migratory behavior is genetically determined, those individuals or populations that are migratory will be further impacted by humans, and this impact could result in the permanent loss of the migratory trait in some populations. However, genetic determination of migration has not previously been studied in an endangered terrestrial mammal. We examined migratory behavior of 139 GPS-collared endangered caribou in western North America and carried out genomic scans for the same individuals. Here we determine a genetic subdivision of caribou into a Northern and a Southern genetic cluster. We also detect >50 SNPs associated with migratory behavior, which are in genes with hypothesized roles in determining migration in other organisms. Furthermore, we determine that propensity to migrate depends upon the proportion of ancestry in individual caribou, and thus on the evolutionary history of its migratory and sedentary subspecies. If, as we report, migratory behavior is influenced by genes, caribou could be further impacted by the loss of the migratory trait in some isolated populations already at low numbers. Our results indicating an ancestral genetic component also suggest that the migratory trait and their associated genetic mutations could not be easily re-established when lost in a population.
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Affiliation(s)
- Maria Cavedon
- Faculty of Environmental Design, University of Calgary, Calgary, Alberta, Canada
| | - Bridgett vonHoldt
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Mark Hebblewhite
- Wildlife Biology Program, Department of Ecosystem and Conservation Sciences, College of Forestry and Conservation, University of Montana, Missoula, Montana, United States of America
| | - Troy Hegel
- Yukon Department of Environment, Whitehorse, Yukon, Canada
| | - Elizabeth Heppenheimer
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Dave Hervieux
- Fish and Wildlife Stewardship Branch, Alberta Environment and Parks, Grande Prairie, Alberta, Canada
| | - Stefano Mariani
- School of Natural Sciences and Psychology, Liverpool John Moores University, Liverpool, United Kingdom
| | - Helen Schwantje
- Wildlife and Habitat Branch, Ministry of Forests, Lands, Natural Resource Operations and Rural Development, Government of British Columbia, Nanaimo, British Columbia, Canada
| | - Robin Steenweg
- Pacific Region, Canadian Wildlife Service, Environment and Climate Change Canada, Delta, British Columbia, Canada
| | - Jessica Theoret
- Faculty of Environmental Design, University of Calgary, Calgary, Alberta, Canada
| | - Megan Watters
- Land and Resource Specialist, Fort St. John, British Columbia, Canada
| | - Marco Musiani
- Department of Biological Sciences, Faculty of Science and Veterinary Medicine (Joint Appointment), University of Calgary, Calgary, Alberta, Canada
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Zhou S, Ding R, Zhuang Z, Zeng H, Wen S, Ruan D, Wu J, Qiu Y, Zheng E, Cai G, Yang J, Wu Z, Yang M. Genome-Wide Association Analysis Reveals Genetic Loci and Candidate Genes for Chest, Abdominal, and Waist Circumferences in Two Duroc Pig Populations. Front Vet Sci 2022; 8:807003. [PMID: 35224076 PMCID: PMC8865076 DOI: 10.3389/fvets.2021.807003] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 12/15/2021] [Indexed: 12/16/2022] Open
Abstract
Chest circumference (CC), abdominal circumference (AC), and waist circumference (WC) are regarded as important indicators for improving economic traits because they can reflect the growth and physiological status in pigs. However, the genetic architecture of CC, AC, and WC is still elusive. Here, we performed single-trait and multi-trait genome-wide association studies (GWASs) for CC, AC, and WC in 2,206 American origin Duroc (AOD) and 2,082 Canadian origin Duroc (COD) pigs. As a result, one novel quantitative trait locus (QTL) on Sus scrofa chromosome (SSC) one was associated with CC and AC in COD pigs, which spans 6.92 Mb (from 170.06 to 176.98 Mb). Moreover, multi-trait GWAS identified 21 significant SNPs associated with the three conformation traits, indicating the multi-trait GWAS is a powerful statistical approach that uncovers pleiotropic locus. Finally, the three candidate genes (ITGA11, TLE3, and GALC) were selected that may play a role in the conformation traits. Further bioinformatics analysis indicated that the candidate genes for the three conformation traits mainly participated in sphingolipid metabolism and lysosome pathways. For all we know, this study was the first GWAS for WC in pigs. In general, our findings further reveal the genetic architecture of CC, AC, and WC, which may offer a useful reference for improving the conformation traits in pigs.
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Affiliation(s)
- Shenping Zhou
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, China
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Haiyu Zeng
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Shuxian Wen
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
- *Correspondence: Zhenfang Wu
| | - Ming Yang
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, China
- Ming Yang
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Bowen MT, George O, Muskiewicz DE, Hall FS. FACTORS CONTRIBUTING TO THE ESCALATION OF ALCOHOL CONSUMPTION. Neurosci Biobehav Rev 2022; 132:730-756. [PMID: 34839930 PMCID: PMC8892842 DOI: 10.1016/j.neubiorev.2021.11.017] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 11/05/2021] [Accepted: 11/12/2021] [Indexed: 01/03/2023]
Abstract
Understanding factors that contribute to the escalation of alcohol consumption is key to understanding how an individual transitions from non/social drinking to AUD and to providing better treatment. In this review, we discuss how the way ethanol is consumed as well as individual and environmental factors contribute to the escalation of ethanol consumption from intermittent low levels to consistently high levels. Moreover, we discuss how these factors are modelled in animals. It is clear a vast array of complex, interacting factors influence changes in alcohol consumption. Some of these factors act early in the acquisition of ethanol consumption and initial escalation, while others contribute to escalation of ethanol consumption at a later stage and are involved in the development of alcohol dependence. There is considerable need for more studies examining escalation associated with the formation of dependence and other hallmark features of AUD, especially studies examining mechanisms, as it is of considerable relevance to understanding and treating AUD.
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Affiliation(s)
- Michael T. Bowen
- The University of Sydney, Brain and Mind Centre, Sydney, NSW, 2050, Australia,The University of Sydney, Faculty of Science, School of Psychology, Sydney, NSW, 2006, Australia,Corresponding Author: Michael T. Bowen, Brain and Mind Centre, The University of Sydney, 94 Mallett Street, Camperdown, Sydney, NSW, 2050, Australia,
| | - Olivier George
- Department of Psychology, University of California, San Diego, School of Medicine, La Jolla, CA, 92093, USA
| | - Dawn E. Muskiewicz
- Department of Pharmacology & Experimental Therapeutics, College of Pharmacology and Pharmacological Science, University of Toledo, OH, USA
| | - F. Scott Hall
- Department of Pharmacology & Experimental Therapeutics, College of Pharmacology and Pharmacological Science, University of Toledo, OH, USA
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Zhang M, Lu N, Zhu T, Yang G, Qu G, Shi C, Fei Y, Liu B, Ma W, Wang J. A Bivariate Mapping Model Identifies Major Covariation QTLs for Biomass Allocation Between Leaf and Stem Growth of Catalpa bungei. Front Genet 2021; 12:758209. [PMID: 34868235 PMCID: PMC8637733 DOI: 10.3389/fgene.2021.758209] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 10/21/2021] [Indexed: 11/13/2022] Open
Abstract
Biomass allocation plays a critical role in plant morphological formation and phenotypic plasticity, which greatly impact plant adaptability and competitiveness. While empirical studies on plant biomass allocation have focused on molecular biology and ecology approaches, detailed insight into the genetic basis of biomass allocation between leaf and stem growth is still lacking. Herein, we constructed a bivariate mapping model to identify covariation QTLs governing carbon (C) allocation between the leaves and stem as well as the covariation of traits within and between organs in a full-sib mapping population of C. bungei. A total of 123 covQTLs were detected for 23 trait pairs, including six leaf traits (leaf length, width, area, perimeter, length/width ratio and petiole length) and five stem traits (height, diameter at breast height, wood density, stemwood volume and stemwood biomass). The candidate genes were further identified in tissue-specific gene expression data, which provided insights into the genetic architecture underlying C allocation for traits or organs. The key QTLs related to growth and biomass allocation, which included UVH1, CLPT2, GAD/SPL, COG1 and MTERF4, were characterised and verified via gene function annotation and expression profiling. The integration of a bivariate Quantitative trait locus mapping model and gene expression profiling will enable the elucidation of genetic architecture underlying biomass allocation and covariation growth, in turn providing a theoretical basis for forest molecular marker-assisted breeding with specific C allocation strategies for adaptation to heterogeneous environments.
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Affiliation(s)
- Miaomiao Zhang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Nan Lu
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Tianqing Zhu
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Guijuan Yang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Guanzheng Qu
- State Key Laboratory of Tree Genetics and Breeding, Northeast Forestry University, Harbin, China
| | - Chaozhong Shi
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Yue Fei
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Bingyang Liu
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Wenjun Ma
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
| | - Junhui Wang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China
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35
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Yang W, Yao D, Wu H, Zhao W, Chen Y, Tong C. Multivariate genome-wide association study of leaf shape in a Populus deltoides and P. simonii F1 pedigree. PLoS One 2021; 16:e0259278. [PMID: 34710178 PMCID: PMC8553126 DOI: 10.1371/journal.pone.0259278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 10/16/2021] [Indexed: 11/19/2022] Open
Abstract
Leaf morphology exhibits tremendous diversity between and within species, and is likely related to adaptation to environmental factors. Most poplar species are of great economic and ecological values and their leaf morphology can be a good predictor for wood productivity and environment adaptation. It is important to understand the genetic mechanism behind variation in leaf shape. Although some initial efforts have been made to identify quantitative trait loci (QTLs) for poplar leaf traits, more effort needs to be expended to unravel the polygenic architecture of the complex traits of leaf shape. Here, we performed a genome-wide association analysis (GWAS) of poplar leaf shape traits in a randomized complete block design with clones from F1 hybrids of Populus deltoides and Populus simonii. A total of 35 SNPs were identified as significantly associated with the multiple traits of a moderate number of regular polar radii between the leaf centroid and its edge points, which could represent the leaf shape, based on a multivariate linear mixed model. In contrast, the univariate linear mixed model was applied as single leaf traits for GWAS, leading to genomic inflation; thus, no significant SNPs were detected for leaf length, measures of leaf width, leaf area, or the ratio of leaf length to leaf width under genomic control. Investigation of the candidate genes showed that most flanking regions of the significant leaf shape-associated SNPs harbored genes that were related to leaf growth and development and to the regulation of leaf morphology. The combined use of the traditional experimental design and the multivariate linear mixed model could greatly improve the power in GWAS because the multiple trait data from a large number of individuals with replicates of clones were incorporated into the statistical model. The results of this study will enhance the understanding of the genetic mechanism of leaf shape variation in Populus. In addition, a moderate number of regular leaf polar radii can largely represent the leaf shape and can be used for GWAS of such a complicated trait in Populus, instead of the higher-dimensional regular radius data that were previously considered to well represent leaf shape.
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Affiliation(s)
- Wenguo Yang
- Co-Innovation Center for Sustainable Forestry in South China, College of Forestry, Nanjing Forestry University, Nanjing, Jiangsu Province, China
- School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing, Jiangsu Province, China
| | - Dan Yao
- Co-Innovation Center for Sustainable Forestry in South China, College of Forestry, Nanjing Forestry University, Nanjing, Jiangsu Province, China
| | - Hainan Wu
- Co-Innovation Center for Sustainable Forestry in South China, College of Forestry, Nanjing Forestry University, Nanjing, Jiangsu Province, China
| | - Wei Zhao
- Co-Innovation Center for Sustainable Forestry in South China, College of Forestry, Nanjing Forestry University, Nanjing, Jiangsu Province, China
| | - Yuhua Chen
- Co-Innovation Center for Sustainable Forestry in South China, College of Forestry, Nanjing Forestry University, Nanjing, Jiangsu Province, China
| | - Chunfa Tong
- Co-Innovation Center for Sustainable Forestry in South China, College of Forestry, Nanjing Forestry University, Nanjing, Jiangsu Province, China
- * E-mail:
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36
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Guo H, Ayalew H, Seethepalli A, Dhakal K, Griffiths M, Ma X, York LM. Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture. THE NEW PHYTOLOGIST 2021; 232:98-112. [PMID: 33683730 PMCID: PMC8518983 DOI: 10.1111/nph.17329] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 02/26/2021] [Indexed: 05/05/2023]
Abstract
The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO2 flux and the open-source software RhizoVision Explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems.
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Affiliation(s)
- Haichao Guo
- Noble Research Institute LLC2510 Sam Noble ParkwayArdmoreOK73401USA
| | - Habtamu Ayalew
- Noble Research Institute LLC2510 Sam Noble ParkwayArdmoreOK73401USA
| | | | - Kundan Dhakal
- Noble Research Institute LLC2510 Sam Noble ParkwayArdmoreOK73401USA
| | - Marcus Griffiths
- Noble Research Institute LLC2510 Sam Noble ParkwayArdmoreOK73401USA
| | - Xue‐Feng Ma
- Noble Research Institute LLC2510 Sam Noble ParkwayArdmoreOK73401USA
| | - Larry M. York
- Noble Research Institute LLC2510 Sam Noble ParkwayArdmoreOK73401USA
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Guo H, Ayalew H, Seethepalli A, Dhakal K, Griffiths M, Ma XF, York LM. Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture. THE NEW PHYTOLOGIST 2021. [PMID: 33683730 DOI: 10.1101/2020.11.12.380238] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO2 flux and the open-source software RhizoVision Explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems.
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Affiliation(s)
- Haichao Guo
- Noble Research Institute LLC, 2510 Sam Noble Parkway, Ardmore, OK, 73401, USA
| | - Habtamu Ayalew
- Noble Research Institute LLC, 2510 Sam Noble Parkway, Ardmore, OK, 73401, USA
| | - Anand Seethepalli
- Noble Research Institute LLC, 2510 Sam Noble Parkway, Ardmore, OK, 73401, USA
| | - Kundan Dhakal
- Noble Research Institute LLC, 2510 Sam Noble Parkway, Ardmore, OK, 73401, USA
| | - Marcus Griffiths
- Noble Research Institute LLC, 2510 Sam Noble Parkway, Ardmore, OK, 73401, USA
| | - Xue-Feng Ma
- Noble Research Institute LLC, 2510 Sam Noble Parkway, Ardmore, OK, 73401, USA
| | - Larry M York
- Noble Research Institute LLC, 2510 Sam Noble Parkway, Ardmore, OK, 73401, USA
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38
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Guo X, He C, Cheng F, Zhong Y, Cheng X, Tao X. Dissection of Allelic Variation Underlying Floral and Fruit Traits in Flare Tree Peony ( Paeonia rockii) Using Association Mapping. Front Genet 2021; 12:664814. [PMID: 34456963 PMCID: PMC8385368 DOI: 10.3389/fgene.2021.664814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 06/29/2021] [Indexed: 11/13/2022] Open
Abstract
Allelic variation in floral quantitative traits, including the elements of flowers and fruits, is caused by extremely complex regulatory processes. In the genetic improvement of flare tree peony (Paeonia rockii), a unique ornamental and edible oil woody species in the genus Paeonia, a better understanding of the genetic composition of these complex traits related to flowers and fruits is needed. Therefore, we investigated the genetic diversity and population structure of 160 P. rockii accessions and conducted single-marker association analysis for 19 quantitative flower and fruit traits using 81 EST-SSR markers. The results showed that the population had a high phenotypic diversity (coefficients of variation, 11.87-110.64%) and a high level of genetic diversity (mean number of alleles, N A = 6.09). These accessions were divided into three subgroups by STRUCTURE analysis and a neighbor-joining tree. Furthermore, we also found a low level of linkage disequilibrium between these EST-SSRs and, by single-marker association analysis, identified 134 significant associations, including four flower traits with 11 EST-SSRs and 10 fruit traits with 32 EST-SSRs. Finally, based on the sequence alignment of the associated markers, P280, PS2, PS12, PS27, PS118, PS131, and PS145 may be considered potential loci to increase the yield of flare tree peony. These results laid the foundation for further analysis of the genetic structure of some key traits in P. rockii and had an obvious potential application value in marker-assisted selection breeding.
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Affiliation(s)
- Xin Guo
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China.,Peony International Institute, School of Landscape Architecture, Beijing Forestry University, Beijing, China.,Beijing Key Laboratory of Ornamental Plants Germplasm Innovation & Molecular Breeding, Beijing Forestry University, Beijing, China.,Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Beijing Forestry University, Beijing, China.,National Engineering Research Center for Floriculture, Beijing Forestry University, Beijing, China
| | - Chunyan He
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China.,Peony International Institute, School of Landscape Architecture, Beijing Forestry University, Beijing, China.,Beijing Key Laboratory of Ornamental Plants Germplasm Innovation & Molecular Breeding, Beijing Forestry University, Beijing, China.,Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Beijing Forestry University, Beijing, China.,National Engineering Research Center for Floriculture, Beijing Forestry University, Beijing, China
| | - Fangyun Cheng
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China.,Peony International Institute, School of Landscape Architecture, Beijing Forestry University, Beijing, China.,Beijing Key Laboratory of Ornamental Plants Germplasm Innovation & Molecular Breeding, Beijing Forestry University, Beijing, China.,Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Beijing Forestry University, Beijing, China.,National Engineering Research Center for Floriculture, Beijing Forestry University, Beijing, China
| | - Yuan Zhong
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China.,Peony International Institute, School of Landscape Architecture, Beijing Forestry University, Beijing, China.,Beijing Key Laboratory of Ornamental Plants Germplasm Innovation & Molecular Breeding, Beijing Forestry University, Beijing, China.,Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, Beijing Forestry University, Beijing, China.,National Engineering Research Center for Floriculture, Beijing Forestry University, Beijing, China
| | - Xinyun Cheng
- Beijing Guose Peony Technology Co. Ltd., Beijing, China
| | - Xiwen Tao
- Beijing Guose Peony Technology Co. Ltd., Beijing, China
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Quan M, Liu X, Du Q, Xiao L, Lu W, Fang Y, Li P, Ji L, Zhang D. Genome-wide association studies reveal the coordinated regulatory networks underlying photosynthesis and wood formation in Populus. JOURNAL OF EXPERIMENTAL BOTANY 2021; 72:5372-5389. [PMID: 33733665 DOI: 10.1093/jxb/erab122] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 03/16/2021] [Indexed: 06/12/2023]
Abstract
Photosynthesis and wood formation underlie the ability of trees to provide renewable resources and perform ecological functions; however, the genetic basis and regulatory pathways coordinating these two linked processes remain unclear. Here, we used a systems genetics strategy, integrating genome-wide association studies, transcriptomic analyses, and transgenic experiments, to investigate the genetic architecture of photosynthesis and wood properties among 435 unrelated individuals of Populus tomentosa, and unravel the coordinated regulatory networks resulting in two trait categories. We detected 222 significant single-nucleotide polymorphisms, annotated to 177 candidate genes, for 10 traits of photosynthesis and wood properties. Epistasis uncovered 74 epistatic interactions for phenotypes. Strikingly, we deciphered the coordinated regulation patterns of pleiotropic genes underlying phenotypic variations for two trait categories. Furthermore, expression quantitative trait nucleotide mapping and coexpression analysis were integrated to unravel the potential transcriptional regulatory networks of candidate genes coordinating photosynthesis and wood properties. Finally, heterologous expression of two pleiotropic genes, PtoMYB62 and PtoMYB80, in Arabidopsis thaliana demonstrated that they control regulatory networks balancing photosynthesis and stem secondary cell wall components, respectively. Our study provides insights into the regulatory mechanisms coordinating photosynthesis and wood formation in poplar, and should facilitate genetic breeding in trees via molecular design.
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Affiliation(s)
- Mingyang Quan
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, P. R. China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Xin Liu
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Qingzhang Du
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, P. R. China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Liang Xiao
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Wenjie Lu
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Yuanyuan Fang
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Peng Li
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Li Ji
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, P. R. China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Deqiang Zhang
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, P. R. China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
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40
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Capador-Barreto HD, Bernhardsson C, Milesi P, Vos I, Lundén K, Wu HX, Karlsson B, Ingvarsson PK, Stenlid J, Elfstrand M. Killing two enemies with one stone? Genomics of resistance to two sympatric pathogens in Norway spruce. Mol Ecol 2021; 30:4433-4447. [PMID: 34218489 DOI: 10.1111/mec.16058] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 06/22/2021] [Accepted: 06/29/2021] [Indexed: 12/31/2022]
Abstract
Trees must cope with the attack of multiple pathogens, often simultaneously during their long lifespan. Ironically, the genetic and molecular mechanisms controlling this process are poorly understood. The objective of this study was to compare the genetic component of resistance in Norway spruce to Heterobasidion annosum s.s. and its sympatric congener Heterobasidion parviporum. Heterobasidion root- and stem-rot is a major disease of Norway spruce caused by members of the Heterobasidion annosum species complex. Resistance to both pathogens was measured using artificial inoculations in half-sib families of Norway spruce trees originating from central to northern Europe. The genetic component of resistance was analysed using 63,760 genome-wide exome-capture sequenced SNPs and multitrait genome-wide associations. No correlation was found for resistance to the two pathogens; however, associations were found between genomic variants and resistance traits with synergic or antagonist pleiotropic effects to both pathogens. Additionally, a latitudinal cline in resistance in the bark to H. annosum s.s. was found; trees from southern latitudes, with a later bud-set and thicker stem diameter, allowed longer lesions, but this was not the case for H. parviporum. In summary, this study detects genomic variants with pleiotropic effects which explain multiple disease resistance from a genic level and could be useful for selection of resistant trees to both pathogens. Furthermore, it highlights the need for additional research to understand the evolution of resistance traits to multiple pathogens in trees.
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Affiliation(s)
- Hernán D Capador-Barreto
- Uppsala Biocentre, Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Carolina Bernhardsson
- Uppsala Biocentre, Department of Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Pascal Milesi
- Department of Ecology and Genetics, Evolutionary Biology Centre, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Ingrid Vos
- Forestry Research Institute of Sweden (Skogforsk), Ekebo, Sweden
| | - Karl Lundén
- Uppsala Biocentre, Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Harry X Wu
- Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Umeå, Sweden
| | - Bo Karlsson
- Forestry Research Institute of Sweden (Skogforsk), Ekebo, Sweden
| | - Pär K Ingvarsson
- Uppsala Biocentre, Department of Plant Biology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Jan Stenlid
- Uppsala Biocentre, Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Malin Elfstrand
- Uppsala Biocentre, Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, Sweden
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Chen ZQ, Zan Y, Milesi P, Zhou L, Chen J, Li L, Cui B, Niu S, Westin J, Karlsson B, García-Gil MR, Lascoux M, Wu HX. Leveraging breeding programs and genomic data in Norway spruce (Picea abies L. Karst) for GWAS analysis. Genome Biol 2021; 22:179. [PMID: 34120648 PMCID: PMC8201819 DOI: 10.1186/s13059-021-02392-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 05/26/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) identify loci underlying the variation of complex traits. One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. We combine spatial and factor-analytics analyses to standardize the heterogeneous data from 120 field experiments of 483,424 progenies of Norway spruce to implement the largest reported GWAS for trees using 134 605 SNPs from exome sequencing of 5056 parental trees. RESULTS We identify 55 novel quantitative trait loci (QTLs) that are associated with phenotypic variation. The largest number of QTLs is associated with the budburst stage, followed by diameter at breast height, wood quality, and frost damage. Two QTLs with the largest effect have a pleiotropic effect for budburst stage, frost damage, and diameter and are associated with MAP3K genes. Genotype data called from exome capture, recently developed SNP array and gene expression data indirectly support this discovery. CONCLUSION Several important QTLs associated with growth and frost damage have been verified in several southern and northern progeny plantations, indicating that these loci can be used in QTL-assisted genomic selection. Our study also demonstrates that existing heterogeneous phenotypic data from breeding programs, collected over several decades, is an important source for GWAS and that such integration into GWAS should be a major area of inquiry in the future.
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Affiliation(s)
- Zhi-Qiang Chen
- Umeå Plant Science Centre, Department Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-90183, Umeå, Sweden
| | - Yanjun Zan
- Umeå Plant Science Centre, Department Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-90183, Umeå, Sweden
| | - Pascal Milesi
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre and SciLifeLab, Uppsala University, Uppsala, Sweden
| | - Linghua Zhou
- Umeå Plant Science Centre, Department Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-90183, Umeå, Sweden
| | - Jun Chen
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre and SciLifeLab, Uppsala University, Uppsala, Sweden
- College of Life Sciences, Zhejiang University, Zhejiang, 310058, Hangzhou, China
| | - Lili Li
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre and SciLifeLab, Uppsala University, Uppsala, Sweden
| | - BinBin Cui
- College of Biochemistry and Environmental Engineering, Baoding University, Baoding, 071000, Hebei, China
| | - Shihui Niu
- Beijing Advanced Innovation Centre for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
| | - Johan Westin
- Skogforsk, Box 3, SE-91821, Sävar, Sweden
- Unit for Field-Based Forest Research, Swedish University of Agricultural Sciences, SE-90183, Umeå, Sweden
| | - Bo Karlsson
- Skogforsk, Ekebo, 2250, SE-26890, Svalöv, Sweden
| | - Maria Rosario García-Gil
- Umeå Plant Science Centre, Department Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-90183, Umeå, Sweden
| | - Martin Lascoux
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre and SciLifeLab, Uppsala University, Uppsala, Sweden
| | - Harry X Wu
- Umeå Plant Science Centre, Department Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-90183, Umeå, Sweden.
- Beijing Advanced Innovation Centre for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China.
- CSIRO National Collection Research Australia, Black Mountain Laboratory, Canberra, ACT, 2601, Australia.
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42
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Zhao Y, Liu X, Wang M, Bi Q, Cui Y, Wang L. Transcriptome and physiological analyses provide insights into the leaf epicuticular wax accumulation mechanism in yellowhorn. HORTICULTURE RESEARCH 2021; 8:134. [PMID: 34059653 PMCID: PMC8167135 DOI: 10.1038/s41438-021-00564-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 03/03/2021] [Accepted: 03/14/2021] [Indexed: 06/02/2023]
Abstract
Plantations and production of yellowhorn, one of the most important woody oil and urban greening trees widely cultivated in northern China, have gradually become limited by drought stress. The epicuticular wax layer plays a key role in the protection of yellowhorn trees from drought and other stresses. However, there is no research on the mechanism of wax loading in yellowhorn trees. In this study, we investigated the anatomical and physiological characteristics of leaves from different germplasm resources and different parts of the same tree and compared their cuticle properties. In addition, the different expression patterns of genes involved in wax accumulation were analyzed, and a coexpression network was built based on transcriptome sequencing data. Morphological and physiological comparisons found that the sun leaves from the outer part of the crown had thicker epicuticular wax, which altered the permeability and improved the drought resistance of leaves, than did shade leaves. Based on transcriptome data, a total of 3008 and 1324 differentially expressed genes (DEGs) were identified between the sun leaves and shade leaves in glossy- and non-glossy-type germplasm resources, respectively. We identified 138 DEGs involved in wax biosynthesis and transport, including structural genes (such as LACS8, ECH1, and ns-LTP) and transcription factors (such as MYB, WRKY, and bHLH transcription factor family proteins). The coexpression network showed a strong correlation between these DEGs. The differences in gene expression patterns between G- and NG-type germplasm resources under different light conditions were very clear. These results not only provide a theoretical basis for screening and developing drought-resistant yellowhorn germplasm resources but also provide a data platform to reveal the wax accumulation process of yellowhorn leaves.
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Affiliation(s)
- Yang Zhao
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, 100091, Beijing, China
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, 100101, Beijing, China
- University of Chinese Academy of Sciences, 100039, Beijing, China
| | - Xiaojuan Liu
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, 100091, Beijing, China
| | - Mengke Wang
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, 100091, Beijing, China
| | - Quanxin Bi
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, 100091, Beijing, China
| | - Yifan Cui
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, 100091, Beijing, China
| | - Libing Wang
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, 100091, Beijing, China.
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Mushtaq M, Ahmad Dar A, Skalicky M, Tyagi A, Bhagat N, Basu U, Bhat BA, Zaid A, Ali S, Dar TUH, Rai GK, Wani SH, Habib-Ur-Rahman M, Hejnak V, Vachova P, Brestic M, Çığ A, Çığ F, Erman M, EL Sabagh A. CRISPR-Based Genome Editing Tools: Insights into Technological Breakthroughs and Future Challenges. Genes (Basel) 2021; 12:797. [PMID: 34073848 PMCID: PMC8225059 DOI: 10.3390/genes12060797] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 05/17/2021] [Accepted: 05/18/2021] [Indexed: 12/11/2022] Open
Abstract
Genome-editing (GE) is having a tremendous influence around the globe in the life science community. Among its versatile uses, the desired modifications of genes, and more importantly the transgene (DNA)-free approach to develop genetically modified organism (GMO), are of special interest. The recent and rapid developments in genome-editing technology have given rise to hopes to achieve global food security in a sustainable manner. We here discuss recent developments in CRISPR-based genome-editing tools for crop improvement concerning adaptation, opportunities, and challenges. Some of the notable advances highlighted here include the development of transgene (DNA)-free genome plants, the availability of compatible nucleases, and the development of safe and effective CRISPR delivery vehicles for plant genome editing, multi-gene targeting and complex genome editing, base editing and prime editing to achieve more complex genetic engineering. Additionally, new avenues that facilitate fine-tuning plant gene regulation have also been addressed. In spite of the tremendous potential of CRISPR and other gene editing tools, major challenges remain. Some of the challenges are related to the practical advances required for the efficient delivery of CRISPR reagents and for precision genome editing, while others come from government policies and public acceptance. This review will therefore be helpful to gain insights into technological advances, its applications, and future challenges for crop improvement.
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Affiliation(s)
- Muntazir Mushtaq
- School of Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu 180009, India; (M.M.); (A.A.D.)
| | - Aejaz Ahmad Dar
- School of Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu 180009, India; (M.M.); (A.A.D.)
| | - Milan Skalicky
- Department of Botany and Plant Physiology, Faculty of Agrobiology, Food, and Natural Resources, Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague, Czech Republic; (M.S.); (V.H.); (P.V.); (M.B.)
| | - Anshika Tyagi
- ICAR-National Institute for Plant Biotechnology, New Delhi 110012, India;
| | - Nancy Bhagat
- School of Biotechnology, University of Jammu, Jammu 180006, India;
| | - Umer Basu
- Division of Plant Pathology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu 180009, India;
| | | | - Abbu Zaid
- Plant Physiology and Biochemistry Section, Department of Botany Aligarh Muslim University, Aigarh 202002, India;
| | - Sajad Ali
- Centre of Research for Development, University of Kashmir, Srinagar 190006, India;
| | | | - Gyanendra Kumar Rai
- School of Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu 180009, India; (M.M.); (A.A.D.)
| | - Shabir Hussain Wani
- Mountain Research Centre for Field Crops, Khudwani, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Jammu 192101, India
| | - Muhammad Habib-Ur-Rahman
- Department of Crop Science, Institute of Crop Science and Resource Conservation (INRES), University Bonn, 53115 Bonn, Germany;
| | - Vaclav Hejnak
- Department of Botany and Plant Physiology, Faculty of Agrobiology, Food, and Natural Resources, Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague, Czech Republic; (M.S.); (V.H.); (P.V.); (M.B.)
| | - Pavla Vachova
- Department of Botany and Plant Physiology, Faculty of Agrobiology, Food, and Natural Resources, Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague, Czech Republic; (M.S.); (V.H.); (P.V.); (M.B.)
| | - Marian Brestic
- Department of Botany and Plant Physiology, Faculty of Agrobiology, Food, and Natural Resources, Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague, Czech Republic; (M.S.); (V.H.); (P.V.); (M.B.)
- Department of Plant Physiology, Slovak University of Agriculture, Nitra, Tr. A. Hlinku 2, 949 01 Nitra, Slovakia
| | - Arzu Çığ
- Department of Horticulture, Faculty of Agriculture, Siirt University, Siirt 56100, Turkey;
| | - Fatih Çığ
- Department of Field Crops, Faculty of Agriculture, Siirt University, Siirt 56100, Turkey; (F.Ç.); (M.E.)
| | - Murat Erman
- Department of Field Crops, Faculty of Agriculture, Siirt University, Siirt 56100, Turkey; (F.Ç.); (M.E.)
| | - Ayman EL Sabagh
- Department of Field Crops, Faculty of Agriculture, Siirt University, Siirt 56100, Turkey; (F.Ç.); (M.E.)
- Department of Agronomy, Faculty of Agriculture, Kafrelsheikh University, Kafrelsheikh 33516, Egypt
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Yan W, Wang B, Chan E, Mitchell-Olds T. Genetic architecture and adaptation of flowering time among environments. THE NEW PHYTOLOGIST 2021; 230:1214-1227. [PMID: 33484593 PMCID: PMC8193995 DOI: 10.1111/nph.17229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 01/07/2021] [Indexed: 05/17/2023]
Abstract
The genetic basis of flowering time changes across environments, and pleiotropy may limit adaptive evolution of populations in response to local conditions. However, little information is known about how genetic architecture changes among environments. We used genome-wide association studies (GWAS) in Boechera stricta (Graham) Al-Shehbaz, a relative of Arabidopsis, to examine flowering variation among environments and associations with climate conditions in home environments. Also, we used molecular population genetics to search for evidence of historical natural selection. GWAS found 47 significant quantitative trait loci (QTLs) that influence flowering time in one or more environments, control plastic changes in phenology between experiments, or show associations with climate in sites of origin. Genetic architecture of flowering varied substantially among environments. We found that some pairs of QTLs showed similar patterns of pleiotropy across environments. A large-effect QTL showed molecular signatures of adaptive evolution and is associated with climate in home environments. The derived allele at this locus causes later flowering and predominates in sites with greater water availability. This work shows that GWAS of climate associations and ecologically important traits across diverse environments can be combined with molecular signatures of natural selection to elucidate ecological genetics of adaptive evolution.
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Affiliation(s)
- Wenjie Yan
- College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
- Department of Biology, Duke University, Box 90338, Durham, NC 27708, USA
| | - Baosheng Wang
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
- Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Guangzhou, 510650 China
| | - Emily Chan
- Department of Biology, Duke University, Box 90338, Durham, NC 27708, USA
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Quan M, Liu X, Xiao L, Chen P, Song F, Lu W, Song Y, Zhang D. Transcriptome analysis and association mapping reveal the genetic regulatory network response to cadmium stress in Populus tomentosa. JOURNAL OF EXPERIMENTAL BOTANY 2021; 72:576-591. [PMID: 32937662 DOI: 10.1093/jxb/eraa434] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Accepted: 09/12/2020] [Indexed: 06/11/2023]
Abstract
Long non-coding RNAs (lncRNAs) play essential roles in plant abiotic stress responses, but the response of lncRNA-mediated genetic networks to cadmium (Cd) treatment remain elusive in trees, the promising candidates for phytoremediation of Cd contamination. We identified 172 Cd-responsive lncRNAs and 295 differentially expressed target genes in the leaves of Cd-treated Populus tomentosa. Functional annotation revealed that these lncRNAs were involved in various processes, including photosynthesis, hormone regulation, and phenylalanine metabolism. Association studies identified 78 significant associations, representing 14 Cd-responsive lncRNAs and 28 target genes for photosynthetic and leaf physiological traits. Epistasis uncovered 83 pairwise interactions among these traits, revealing Cd-responsive lncRNA-mediated genetic networks for photosynthesis and leaf physiology in P. tomentosa. We focused on the roles of two Cd-responsive lncRNA-gene pairs, MSTRG.22608.1-PtoMYB73 and MSTRG.5634.1-PtoMYB27, in Cd tolerance of Populus, and detected insertions/deletions within lncRNAs as polymorphisms driving target gene expression. Genotype analysis of lncRNAs and heterologous overexpression of PtoMYB73 and PtoMYB27 in Arabidopsis indicated their effects on enhancing Cd tolerance, photosynthetic rate, and leaf growth, and the potential interaction mechanisms of PtoMYB73 with abiotic stresses. Our study identifies the genetic basis for the response of Populus to Cd treatment, facilitating genetic improvement of Cd tolerance in trees.
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Affiliation(s)
- Mingyang Quan
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Xin Liu
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Liang Xiao
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Panfei Chen
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Fangyuan Song
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Wenjie Lu
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Yuepeng Song
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Deqiang Zhang
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
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46
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Hessenauer P, Feau N, Gill U, Schwessinger B, Brar GS, Hamelin RC. Evolution and Adaptation of Forest and Crop Pathogens in the Anthropocene. PHYTOPATHOLOGY 2021; 111:49-67. [PMID: 33200962 DOI: 10.1094/phyto-08-20-0358-fi] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Anthropocene marks the era when human activity is making a significant impact on earth, its ecological and biogeographical systems. The domestication and intensification of agricultural and forest production systems have had a large impact on plant and tree health. Some pathogens benefitted from these human activities and have evolved and adapted in response to the expansion of crop and forest systems, resulting in global outbreaks. Global pathogen genomics data including population genomics and high-quality reference assemblies are crucial for understanding the evolution and adaptation of pathogens. Crops and forest trees have remarkably different characteristics, such as reproductive time and the level of domestication. They also have different production systems for disease management with more intensive management in crops than forest trees. By comparing and contrasting results from pathogen population genomic studies done on widely different agricultural and forest production systems, we can improve our understanding of pathogen evolution and adaptation to different selection pressures. We find that in spite of these differences, similar processes such as hybridization, host jumps, selection, specialization, and clonal expansion are shaping the pathogen populations in both crops and forest trees. We propose some solutions to reduce these impacts and lower the probability of global pathogen outbreaks so that we can envision better management strategies to sustain global food production as well as ecosystem services.
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Affiliation(s)
- Pauline Hessenauer
- Faculty of Forestry, Geography and Geomatics, Laval University, Quebec City, QC, G1V 0A6 Canada
| | - Nicolas Feau
- Faculty of Forestry, The University of British Columbia, Vancouver, BC, V6T 1Z4 Canada
| | - Upinder Gill
- College of Agriculture, Food Systems, and Natural Resources, North Dakota State University, Fargo, ND 58102, U.S.A
| | - Benjamin Schwessinger
- Research School of Biology, Australian National University, Acton, ACT 2601 Australia
| | - Gurcharn S Brar
- Faculty of Land and Food Systems, The University of British Columbia, Vancouver, BC, V6T 1Z4 Canada
| | - Richard C Hamelin
- Faculty of Forestry, Geography and Geomatics, Laval University, Quebec City, QC, G1V 0A6 Canada
- Faculty of Forestry, The University of British Columbia, Vancouver, BC, V6T 1Z4 Canada
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47
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Singh NK, Dutta A, Puccetti G, Croll D. Tackling microbial threats in agriculture with integrative imaging and computational approaches. Comput Struct Biotechnol J 2020; 19:372-383. [PMID: 33489007 PMCID: PMC7787954 DOI: 10.1016/j.csbj.2020.12.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 12/08/2020] [Accepted: 12/13/2020] [Indexed: 11/29/2022] Open
Abstract
Pathogens and pests are one of the major threats to agricultural productivity worldwide. For decades, targeted resistance breeding was used to create crop cultivars that resist pathogens and environmental stress while retaining yields. The often decade-long process of crossing, selection, and field trials to create a new cultivar is challenged by the rapid rise of pathogens overcoming resistance. Similarly, antimicrobial compounds can rapidly lose efficacy due to resistance evolution. Here, we review three major areas where computational, imaging and experimental approaches are revolutionizing the management of pathogen damage on crops. Recognizing and scoring plant diseases have dramatically improved through high-throughput imaging techniques applicable both under well-controlled greenhouse conditions and directly in the field. However, computer vision of complex disease phenotypes will require significant improvements. In parallel, experimental setups similar to high-throughput drug discovery screens make it possible to screen thousands of pathogen strains for variation in resistance and other relevant phenotypic traits. Confocal microscopy and fluorescence can capture rich phenotypic information across pathogen genotypes. Through genome-wide association mapping approaches, phenotypic data helps to unravel the genetic architecture of stress- and virulence-related traits accelerating resistance breeding. Finally, joint, large-scale screenings of trait variation in crops and pathogens can yield fundamental insights into how pathogens face trade-offs in the adaptation to resistant crop varieties. We discuss how future implementations of such innovative approaches in breeding and pathogen screening can lead to more durable disease control.
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Affiliation(s)
- Nikhil Kumar Singh
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, CH-2000 Neuchâtel, Switzerland
| | - Anik Dutta
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, CH-2000 Neuchâtel, Switzerland
- Plant Pathology, Institute of Integrative Biology, ETH Zurich, CH-8092 Zurich, Switzerland
| | - Guido Puccetti
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, CH-2000 Neuchâtel, Switzerland
- Syngenta Crop Protection AG, CH-4332 Stein, Switzerland
| | - Daniel Croll
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, CH-2000 Neuchâtel, Switzerland
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Qu M, Essemine J, Xu J, Ablat G, Perveen S, Wang H, Chen K, Zhao Y, Chen G, Chu C, Zhu X. Alterations in stomatal response to fluctuating light increase biomass and yield of rice under drought conditions. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 104:1334-1347. [PMID: 33015858 DOI: 10.1111/tpj.15004] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 09/23/2020] [Indexed: 05/07/2023]
Abstract
The acceleration of stomatal closure upon high to low light transition could improve plant water use efficiency and drought tolerance. Herein, using genome-wide association study, we showed that the genetic variation in OsNHX1 was strongly associated with the changes in τcl , the time constant of stomatal closure, in 206 rice accessions. OsNHX1 overexpression in rice resulted in a decrease in τcl , and an increase in biomass, grain yield under drought. Conversely, OsNHX1 knockout by CRISPR/CAS9 shows opposite trends for these traits. We further found three haplotypes spanning the OsNHX1 promoter and CDS regions. Two among them, HapII and HapIII, were found to be associated with a high and low τcl , respectively. A near-isogenic line (NIL, S464) was developed through replacing the genomic region harboring HapII (~10 kb) from MH63 (recipient) rice cultivar by the same sized genomic region containing Hap III from 02428 (donor). Compared with MH63, S464 shows a reduction by 35% in τcl and an increase by 40% in the grain yield under drought. However, under normal conditions, S464 maintains closely similar grain yield as MH63. The global distribution of the two OsNHX1 haplotypes is associated with the local precipitation. Taken together, the natural variation in OsNHX1 could be utilized to manipulate the stomatal dynamics for an improved rice drought tolerance.
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Affiliation(s)
- Mingnan Qu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 200032, China
| | - Jemaa Essemine
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 200032, China
| | - Jianlong Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Guljannat Ablat
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 200032, China
- School of Life Sciences, Henan University, Kaifeng, 475004, China
| | - Shahnaz Perveen
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 200032, China
| | - Hongru Wang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Kai Chen
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yang Zhao
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 200032, China
| | - Genyun Chen
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 200032, China
- Laboratory of Photosynthesis and Environmental Biology, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200032, China
| | - Chengcai Chu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinguang Zhu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai, 200032, China
- Laboratory of Photosynthesis and Environmental Biology, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200032, China
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Sarkar D, Maranas CD. SNPeffect: identifying functional roles of SNPs using metabolic networks. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 103:512-531. [PMID: 32167625 PMCID: PMC9328443 DOI: 10.1111/tpj.14746] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 02/20/2020] [Indexed: 05/04/2023]
Abstract
Genetic sources of phenotypic variation have been a focus of plant studies aimed at improving agricultural yield and understanding adaptive processes. Genome-wide association studies identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. Here, we propose a complementary analysis (SNPeffect) that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect is used to explain differential growth rate and metabolite accumulation in A. thaliana and P. trichocarpa accessions as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicate that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition.
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Affiliation(s)
- Debolina Sarkar
- Department of Chemical EngineeringPennsylvania State UniversityUniversity ParkPAUSA
| | - Costas D. Maranas
- Department of Chemical EngineeringPennsylvania State UniversityUniversity ParkPAUSA
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Hassan MM, Yuan G, Chen JG, Tuskan GA, Yang X. Prime Editing Technology and Its Prospects for Future Applications in Plant Biology Research. BIODESIGN RESEARCH 2020; 2020:9350905. [PMID: 37849904 PMCID: PMC10530660 DOI: 10.34133/2020/9350905] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 05/19/2020] [Indexed: 10/19/2023] Open
Abstract
Many applications in plant biology requires editing genomes accurately including correcting point mutations, incorporation of single-nucleotide polymorphisms (SNPs), and introduction of multinucleotide insertion/deletions (indels) into a predetermined position in the genome. These types of modifications are possible using existing genome-editing technologies such as the CRISPR-Cas systems, which require induction of double-stranded breaks in the target DNA site and the supply of a donor DNA molecule that contains the desired edit sequence. However, low frequency of homologous recombination in plants and difficulty of delivering the donor DNA molecules make this process extremely inefficient. Another kind of technology known as base editing can perform precise editing; however, only certain types of modifications can be obtained, e.g., C/G-to-T/A and A/T-to-G/C. Recently, a new type of genome-editing technology, referred to as "prime editing," has been developed, which can achieve various types of editing such as any base-to-base conversion, including both transitions (C→T, G→A, A→G, and T→C) and transversion mutations (C→A, C→G, G→C, G→T, A→C, A→T, T→A, and T→G), as well as small indels without the requirement for inducing double-stranded break in the DNA. Because prime editing has wide flexibility to achieve different types of edits in the genome, it holds a great potential for developing superior crops for various purposes, such as increasing yield, providing resistance to various abiotic and biotic stresses, and improving quality of plant product. In this review, we describe the prime editing technology and discuss its limitations and potential applications in plant biology research.
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Affiliation(s)
- Md. Mahmudul Hassan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Department of Genetics and Plant Breeding, Patuakhali Science and Technology University, Dumki, Patuakhali 8602, Bangladesh
| | - Guoliang Yuan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Jin-Gui Chen
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Gerald A. Tuskan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Xiaohan Yang
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge TN 37831, USA
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
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