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Meng QL, Qiang CG, Li JL, Geng MF, Ren NN, Cai Z, Wang MX, Jiao ZH, Zhang FM, Song XJ, Ge S. Genetic architecture of ecological divergence between Oryza rufipogon and Oryza nivara. Mol Ecol 2024; 33:e17268. [PMID: 38230514 DOI: 10.1111/mec.17268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 01/04/2024] [Accepted: 01/08/2024] [Indexed: 01/18/2024]
Abstract
Ecological divergence due to habitat difference plays a prominent role in the formation of new species, but the genetic architecture during ecological speciation and the mechanism underlying phenotypic divergence remain less understood. Two wild ancestors of rice (Oryza rufipogon and Oryza nivara) are a progenitor-derivative species pair with ecological divergence and provide a unique system for studying ecological adaptation/speciation. Here, we constructed a high-resolution linkage map and conducted a quantitative trait locus (QTL) analysis of 19 phenotypic traits using an F2 population generated from a cross between the two Oryza species. We identified 113 QTLs associated with interspecific divergence of 16 quantitative traits, with effect sizes ranging from 1.61% to 34.1% in terms of the percentage of variation explained (PVE). The distribution of effect sizes of QTLs followed a negative exponential, suggesting that a few genes of large effect and many genes of small effect were responsible for the phenotypic divergence. We observed 18 clusters of QTLs (QTL hotspots) on 11 chromosomes, significantly more than that expected by chance, demonstrating the importance of coinheritance of loci/genes in ecological adaptation/speciation. Analysis of effect direction and v-test statistics revealed that interspecific differentiation of most traits was driven by divergent natural selection, supporting the argument that ecological adaptation/speciation would proceed rapidly under coordinated selection on multiple traits. Our findings provide new insights into the understanding of genetic architecture of ecological adaptation and speciation in plants and help effective manipulation of specific genes or gene cluster in rice breeding.
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Affiliation(s)
- Qing-Lin Meng
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Cheng-Gen Qiang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ji-Long Li
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Mu-Fan Geng
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ning-Ning Ren
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Zhe Cai
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Mei-Xia Wang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zi-Hui Jiao
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fu-Min Zhang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xian-Jun Song
- Key Laboratory of Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Song Ge
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
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2
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Jakobson CM, Aguilar-Rodríguez J, Jarosz DF. Hsp90 shapes adaptation by controlling the fitness consequences of regulatory variation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.30.564848. [PMID: 37961536 PMCID: PMC10634948 DOI: 10.1101/2023.10.30.564848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The essential stress-responsive chaperone Hsp90 impacts development and adaptation from microbes to humans. Yet despite evidence of its role in evolution, pathogenesis, and oncogenic transformation, the molecular mechanisms by which Hsp90 alters the consequences of mutations remain vigorously debated. Here we exploit the power of nucleotide-resolution genetic mapping in Saccharomyces cerevisiae to uncover more than 1,000 natural variant-to-phenotype associations governed by this molecular chaperone. Strikingly, Hsp90 more frequently modified the phenotypic effects of cis-regulatory variation than variants that altered protein sequence. Moreover, these interactions made the largest contribution to Hsp90-dependent heredity. Nearly all interacting variants-both regulatory and protein-coding-fell within clients of Hsp90 or targets of its direct binding partners. Hsp90 activity affected mutations in evolutionarily young genes, segmental deletions, and heterozygotes, highlighting its influence on variation central to evolutionary novelty. Reconciling the diverse epistatic effects of this chaperone, synthetic transcriptional regulation and reconstructions of natural alleles by genome editing revealed a central role for Hsp90 in regulating the fundamental relationship between activity and phenotype. Our findings establish that non-coding variation is a core driver of Hsp90's influence on heredity, offering a mechanistic explanation for the chaperone's strong effects on evolution and development across species.
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Affiliation(s)
- Christopher M. Jakobson
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- These authors contributed equally
| | - José Aguilar-Rodríguez
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- These authors contributed equally
| | - Daniel F. Jarosz
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
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3
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Wang X, Li J, Han L, Liang C, Li J, Shang X, Miao X, Luo Z, Zhu W, Li Z, Li T, Qi Y, Li H, Lu X, Li L. QTG-Miner aids rapid dissection of the genetic base of tassel branch number in maize. Nat Commun 2023; 14:5232. [PMID: 37633966 PMCID: PMC10460418 DOI: 10.1038/s41467-023-41022-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 08/21/2023] [Indexed: 08/28/2023] Open
Abstract
Genetic dissection of agronomic traits is important for crop improvement and global food security. Phenotypic variation of tassel branch number (TBN), a major breeding target, is controlled by many quantitative trait loci (QTLs). The lack of large-scale QTL cloning methodology constrains the systematic dissection of TBN, which hinders modern maize breeding. Here, we devise QTG-Miner, a multi-omics data-based technique for large-scale and rapid cloning of quantitative trait genes (QTGs) in maize. Using QTG-Miner, we clone and verify seven genes underlying seven TBN QTLs. Compared to conventional methods, QTG-Miner performs well for both major- and minor-effect TBN QTLs. Selection analysis indicates that a substantial number of genes and network modules have been subjected to selection during maize improvement. Selection signatures are significantly enriched in multiple biological pathways between female heterotic groups and male heterotic groups. In summary, QTG-Miner provides a large-scale approach for rapid cloning of QTGs in crops and dissects the genetic base of TBN for further maize breeding.
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Affiliation(s)
- Xi Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Juan Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Linqian Han
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Chengyong Liang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Jiaxin Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Xiaoyang Shang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Xinxin Miao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Zi Luo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Wanchao Zhu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Zhao Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Tianhuan Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Yongwen Qi
- College of Agriculture and Biology, Zhongkai University of Agriculture and Engineering, Guangzhou, 510325, Guangdong, China
| | - Huihui Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 100081, Beijing, China
| | - Xiaoduo Lu
- Institute of Molecular Breeding for Maize, Qilu Normal University, Jinan, 250200, China
| | - Lin Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
- Hubei Hongshan Laboratory, Wuhan, 430070, China.
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4
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Fausett SR, Sandjak A, Billard B, Braendle C. Higher-order epistasis shapes natural variation in germ stem cell niche activity. Nat Commun 2023; 14:2824. [PMID: 37198172 DOI: 10.1038/s41467-023-38527-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 05/05/2023] [Indexed: 05/19/2023] Open
Abstract
To study how natural allelic variation explains quantitative developmental system variation, we characterized natural differences in germ stem cell niche activity, measured as progenitor zone (PZ) size, between two Caenorhabditis elegans isolates. Linkage mapping yielded candidate loci on chromosomes II and V, and we found that the isolate with a smaller PZ size harbours a 148 bp promoter deletion in the Notch ligand, lag-2/Delta, a central signal promoting germ stem cell fate. As predicted, introducing this deletion into the isolate with a large PZ resulted in a smaller PZ size. Unexpectedly, restoring the deleted ancestral sequence in the isolate with a smaller PZ did not increase-but instead further reduced-PZ size. These seemingly contradictory phenotypic effects are explained by epistatic interactions between the lag-2/Delta promoter, the chromosome II locus, and additional background loci. These results provide first insights into the quantitative genetic architecture regulating an animal stem cell system.
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Affiliation(s)
- Sarah R Fausett
- Université Côte d'Azur, CNRS, Inserm, IBV, Nice, France.
- Department of Biology and Marine Biology, University of North Carolina Wilmington, Wilmington, NC, USA.
| | - Asma Sandjak
- Université Côte d'Azur, CNRS, Inserm, IBV, Nice, France
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5
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McGale E, Sanders IR. Integrating plant and fungal quantitative genetics to improve the ecological and agricultural applications of mycorrhizal symbioses. Curr Opin Microbiol 2022; 70:102205. [PMID: 36201974 DOI: 10.1016/j.mib.2022.102205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 08/12/2022] [Accepted: 08/18/2022] [Indexed: 01/25/2023]
Abstract
Finding and targeting genes that quantitatively contribute to agricultural and ecological processes progresses food production and conservation efforts. Typically, quantitative genetic approaches link variants in a single organism's genome with a trait of interest. Recently, genome-to-genome mapping has found genome variants interacting between species to produce the result of a multiorganism (including multikingdom) interaction. These were plant and bacterial pathogen genome interactions; plant-fungal coquantitative genetics have not yet been applied. Plant-mycorrhizae symbioses exist across most biomes, for a majority of land plants, including crop plants, and manipulate many traits from single organisms to ecosystems for which knowing the genetic basis would be useful. The availability of Rhizophagus irregularis mycorrhizal isolates, with genomic information, makes dual-genome methods with beneficial mutualists accessible and imminent.
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Affiliation(s)
- Erica McGale
- Department of Ecology and Evolution, Biophore Building, University of Lausanne, 1015 Lausanne, Switzerland
| | - Ian R Sanders
- Department of Ecology and Evolution, Biophore Building, University of Lausanne, 1015 Lausanne, Switzerland.
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6
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Wu S, Chen D, Snyder MP. Network biology bridges the gaps between quantitative genetics and multi-omics to map complex diseases. Curr Opin Chem Biol 2021; 66:102101. [PMID: 34861483 DOI: 10.1016/j.cbpa.2021.102101] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/17/2021] [Accepted: 10/27/2021] [Indexed: 12/27/2022]
Abstract
With advances in high-throughput sequencing technologies, quantitative genetics approaches have provided insights into genetic basis of many complex diseases. Emerging in-depth multi-omics profiling technologies have created exciting opportunities for systematically investigating intricate interaction networks with different layers of biological molecules underlying disease etiology. Herein, we summarized two main categories of biological networks: evidence-based and statistically inferred. These different types of molecular networks complement each other at both bulk and single-cell levels. We also review three main strategies to incorporate quantitative genetics results with multi-omics data by network analysis: (a) network propagation, (b) functional module-based methods, (c) comparative/dynamic networks. These strategies not only aid in elucidating molecular mechanisms of complex diseases but can guide the search for therapeutic targets.
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Affiliation(s)
- Si Wu
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Dijun Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
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7
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Hansen TF, Pélabon C. Evolvability: A Quantitative-Genetics Perspective. ANNUAL REVIEW OF ECOLOGY, EVOLUTION, AND SYSTEMATICS 2021. [DOI: 10.1146/annurev-ecolsys-011121-021241] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The concept of evolvability emerged in the early 1990s and soon became fashionable as a label for different streams of research in evolutionary biology. In evolutionary quantitative genetics, evolvability is defined as the ability of a population to respond to directional selection. This differs from other fields by treating evolvability as a property of populations rather than organisms or lineages and in being focused on quantification and short-term prediction rather than on macroevolution. While the term evolvability is new to quantitative genetics, many of the associated ideas and research questions have been with the field from its inception as biometry. Recent research on evolvability is more than a relabeling of old questions, however. New operational measures of evolvability have opened possibilities for understanding adaptation to rapid environmental change, assessing genetic constraints, and linking micro- and macroevolution.
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Affiliation(s)
- Thomas F. Hansen
- Department of Biosciences, University of Oslo, 0316 Oslo, Norway
| | - Christophe Pélabon
- Center for Biodiversity Dynamics, Department of Biology, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
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8
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Zhang J, Zhang D, Fan Y, Li C, Xu P, Li W, Sun Q, Huang X, Zhang C, Wu L, Yang H, Wang S, Su X, Li X, Song Y, Wu ME, Lian X, Li Y. The identification of grain size genes by RapMap reveals directional selection during rice domestication. Nat Commun 2021; 12:5673. [PMID: 34584089 PMCID: PMC8478914 DOI: 10.1038/s41467-021-25961-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Accepted: 09/10/2021] [Indexed: 11/09/2022] Open
Abstract
Cloning quantitative trait locus (QTL) is time consuming and laborious, which hinders the understanding of natural variation and genetic diversity. Here, we introduce RapMap, a method for rapid multi-QTL mapping by employing F2 gradient populations (F2GPs) constructed by minor-phenotypic-difference accessions. The co-segregation standard of the single-locus genetic models ensures simultaneous integration of a three-in-one framework in RapMap i.e. detecting a real QTL, confirming its effect, and obtaining its near-isogenic line-like line (NIL-LL). We demonstrate the feasibility of RapMap by cloning eight rice grain-size genes using 15 F2GPs in three years. These genes explain a total of 75% of grain shape variation. Allele frequency analysis of these genes using a large germplasm collection reveals directional selection of the slender and long grains in indica rice domestication. In addition, major grain-size genes have been strongly selected during rice domestication. We think application of RapMap in crops will accelerate gene discovery and genomic breeding.
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Affiliation(s)
- Juncheng Zhang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Dejian Zhang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Yawei Fan
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Cuicui Li
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Pengkun Xu
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Wei Li
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Qi Sun
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xiaodong Huang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Chunyu Zhang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Linyue Wu
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Huaizhou Yang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Shiyu Wang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xiaomin Su
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xingxing Li
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Yingying Song
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Meng-En Wu
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
| | - Yibo Li
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China.
- Hubei Hongshan Laboratory, Wuhan, China.
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9
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Wang X, Aguirre L, Rodríguez-Leal D, Hendelman A, Benoit M, Lippman ZB. Dissecting cis-regulatory control of quantitative trait variation in a plant stem cell circuit. NATURE PLANTS 2021; 7:419-427. [PMID: 33846596 DOI: 10.1038/s41477-021-00898-x] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 03/10/2021] [Indexed: 05/22/2023]
Abstract
Cis-regulatory mutations underlie important crop domestication and improvement traits1,2. However, limited allelic diversity has hindered functional dissection of the large number of cis-regulatory elements and their potential interactions, thereby precluding a deeper understanding of how cis-regulatory variation impacts traits quantitatively. Here, we engineered over 60 promoter alleles in two tomato fruit size genes3,4 to characterize cis-regulatory sequences and study their functional relationships. We found that targeted mutations in conserved promoter sequences of SlCLV3, a repressor of stem cell proliferation5,6, have a weak impact on fruit locule number. Pairwise combinations of these mutations mildly enhance this phenotype, revealing additive and synergistic relationships between conserved regions and further suggesting even higher-order cis-regulatory interactions within the SlCLV3 promoter. In contrast, SlWUS, a positive regulator of stem cell proliferation repressed by SlCLV3 (refs. 5,6), is more tolerant to promoter perturbations. Our results show that complex interplay among cis-regulatory variants can shape quantitative variation, and suggest that empirical dissections of this hidden complexity can guide promoter engineering to predictably modify crop traits.
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Affiliation(s)
- Xingang Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Lyndsey Aguirre
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Daniel Rodríguez-Leal
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Inari Agriculture, Cambridge, MA, USA
| | - Anat Hendelman
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Matthias Benoit
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Zachary B Lippman
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
- Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
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