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Luomaranta M, Grones C, Choudhary S, Milhinhos A, Kalman TA, Nilsson O, Robinson KM, Street NR, Tuominen H. Systems genetic analysis of lignin biosynthesis in Populus tremula. THE NEW PHYTOLOGIST 2024. [PMID: 39072753 DOI: 10.1111/nph.19993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Accepted: 07/02/2024] [Indexed: 07/30/2024]
Abstract
The genetic control underlying natural variation in lignin content and composition in trees is not fully understood. We performed a systems genetic analysis to uncover the genetic regulation of lignin biosynthesis in a natural 'SwAsp' population of aspen (Populus tremula) trees. We analyzed gene expression by RNA sequencing (RNA-seq) in differentiating xylem tissues, and lignin content and composition using Pyrolysis-GC-MS in mature wood of 268 trees from 99 genotypes. Abundant variation was observed for lignin content and composition, and genome-wide association study identified proteins in the pentose phosphate pathway and arabinogalactan protein glycosylation among the top-ranked genes that are associated with these traits. Variation in gene expression and the associated genetic polymorphism was revealed through the identification of 312 705 local and 292 003 distant expression quantitative trait loci (eQTL). A co-expression network analysis suggested modularization of lignin biosynthesis and novel functions for the lignin-biosynthetic CINNAMYL ALCOHOL DEHYDROGENASE 2 and CAFFEOYL-CoA O-METHYLTRANSFERASE 3. PHENYLALANINE AMMONIA LYASE 3 was co-expressed with HOMEOBOX PROTEIN 5 (HB5), and the role of HB5 in stimulating lignification was demonstrated in transgenic trees. The systems genetic approach allowed linking natural variation in lignin biosynthesis to trees´ responses to external cues such as mechanical stimulus and nutrient availability.
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Affiliation(s)
- Mikko Luomaranta
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 90187, Umeå, Sweden
| | - Carolin Grones
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 90187, Umeå, Sweden
| | - Shruti Choudhary
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, 90183, Umeå, Sweden
| | - Ana Milhinhos
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 90187, Umeå, Sweden
| | - Teitur Ahlgren Kalman
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 90187, Umeå, Sweden
| | - Ove Nilsson
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, 90183, Umeå, Sweden
| | - Kathryn M Robinson
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 90187, Umeå, Sweden
| | - Nathaniel R Street
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 90187, Umeå, Sweden
- SciLifeLab, Umeå University, 90187, Umeå, Sweden
| | - Hannele Tuominen
- Department of Forest Genetics and Plant Physiology, Umeå Plant Science Centre, Swedish University of Agricultural Sciences, 90183, Umeå, Sweden
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2
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Hartfield M, Glémin S. Polygenic selection to a changing optimum under self-fertilisation. PLoS Genet 2024; 20:e1011312. [PMID: 39018328 DOI: 10.1371/journal.pgen.1011312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 07/29/2024] [Accepted: 05/21/2024] [Indexed: 07/19/2024] Open
Abstract
Many traits are polygenic, affected by multiple genetic variants throughout the genome. Selection acting on these traits involves co-ordinated allele-frequency changes at these underlying variants, and this process has been extensively studied in random-mating populations. Yet many species self-fertilise to some degree, which incurs changes to genetic diversity, recombination and genome segregation. These factors cumulatively influence how polygenic selection is realised in nature. Here, we use analytical modelling and stochastic simulations to investigate to what extent self-fertilisation affects polygenic adaptation to a new environment. Our analytical solutions show that while selfing can increase adaptation to an optimum, it incurs linkage disequilibrium that can slow down the initial spread of favoured mutations due to selection interference, and favours the fixation of alleles with opposing trait effects. Simulations show that while selection interference is present, high levels of selfing (at least 90%) aids adaptation to a new optimum, showing a higher long-term fitness. If mutations are pleiotropic then only a few major-effect variants fix along with many neutral hitchhikers, with a transient increase in linkage disequilibrium. These results show potential advantages to self-fertilisation when adapting to a new environment, and how the mating system affects the genetic composition of polygenic selection.
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Affiliation(s)
- Matthew Hartfield
- Institute of Ecology and Evolution, The University of Edinburgh, Edinburgh, United Kingdom
| | - Sylvain Glémin
- Université de Rennes, Centre National de la Recherche Scientifique (CNRS), ECOBIO (Ecosystèmes, Biodiversité, Evolution) - Unité Mixte de Recherche (UMR) 6553, Rennes, France
- Department of Ecology and Evolution, Evolutionary Biology Center, Uppsala University, Uppsala, Sweden
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3
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Hu Z, Chen J, Olatoye MO, Zhang H, Lin Z. Transcriptome-wide expression landscape and starch synthesis pathway co-expression network in sorghum. THE PLANT GENOME 2024; 17:e20448. [PMID: 38602082 DOI: 10.1002/tpg2.20448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2024]
Abstract
The gene expression landscape across different tissues and developmental stages reflects their biological functions and evolutionary patterns. Integrative and comprehensive analyses of all transcriptomic data in an organism are instrumental to obtaining a comprehensive picture of gene expression landscape. Such studies are still very limited in sorghum, which limits the discovery of the genetic basis underlying complex agricultural traits in sorghum. We characterized the genome-wide expression landscape for sorghum using 873 RNA-sequencing (RNA-seq) datasets representing 19 tissues. Our integrative analysis of these RNA-seq data provides the most comprehensive transcriptomic atlas for sorghum, which will be valuable for the sorghum research community for functional characterizations of sorghum genes. Based on the transcriptome atlas, we identified 595 housekeeping genes (HKGs) and 2080 tissue-specific expression genes (TEGs) for the 19 tissues. We identified different gene features between HKGs and TEGs, and we found that HKGs have experienced stronger selective constraints than TEGs. Furthermore, we built a transcriptome-wide co-expression network (TW-CEN) comprising 35 modules with each module enriched in specific Gene Ontology terms. High-connectivity genes in TW-CEN tend to express at high levels while undergoing intensive selective pressure. We also built global and seed-preferential co-expression networks of starch synthesis pathways, which indicated that photosynthesis and microtubule-based movement play important roles in starch synthesis. The global transcriptome atlas of sorghum generated by this study provides an important functional genomics resource for trait discovery and insight into starch synthesis regulation in sorghum.
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Affiliation(s)
- Zhenbin Hu
- Department of Biology, Saint Louis University, Saint Louis, Missouri, USA
| | - Junhao Chen
- Department of Biology, Saint Louis University, Saint Louis, Missouri, USA
| | - Marcus O Olatoye
- USDA-ARS, Forage Seed and Cereal Research Unit, Prosser, Washington, USA
| | - Hengyou Zhang
- State Key Laboratory of Black Soils Conservation and Utilization, Key Laboratory of Soybean Molecular Design and Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin, China
| | - Zhenguo Lin
- Department of Biology, Saint Louis University, Saint Louis, Missouri, USA
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4
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Veltsos P, Kelly JK. The quantitative genetics of gene expression in Mimulus guttatus. PLoS Genet 2024; 20:e1011072. [PMID: 38603726 PMCID: PMC11060551 DOI: 10.1371/journal.pgen.1011072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 04/30/2024] [Accepted: 03/23/2024] [Indexed: 04/13/2024] Open
Abstract
Gene expression can be influenced by genetic variants that are closely linked to the expressed gene (cis eQTLs) and variants in other parts of the genome (trans eQTLs). We created a multiparental mapping population by sampling genotypes from a single natural population of Mimulus guttatus and scored gene expression in the leaves of 1,588 plants. We find that nearly every measured gene exhibits cis regulatory variation (91% have FDR < 0.05). cis eQTLs are usually allelic series with three or more functionally distinct alleles. The cis locus explains about two thirds of the standing genetic variance (on average) but varies among genes and tends to be greatest when there is high indel variation in the upstream regulatory region and high nucleotide diversity in the coding sequence. Despite mapping over 10,000 trans eQTL / affected gene pairs, most of the genetic variance generated by trans acting loci remains unexplained. This implies a large reservoir of trans acting genes with subtle or diffuse effects. Mapped trans eQTLs show lower allelic diversity but much higher genetic dominance than cis eQTLs. Several analyses also indicate that trans eQTLs make a substantial contribution to the genetic correlations in expression among different genes. They may thus be essential determinants of "gene expression modules," which has important implications for the evolution of gene expression and how it is studied by geneticists.
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Affiliation(s)
- Paris Veltsos
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, United States of America
| | - John K. Kelly
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, United States of America
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Campelo dos Santos AL, DeGiorgio M, Assis R. Predicting evolutionary targets and parameters of gene deletion from expression data. BIOINFORMATICS ADVANCES 2024; 4:vbae002. [PMID: 38282974 PMCID: PMC10812876 DOI: 10.1093/bioadv/vbae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 12/08/2023] [Accepted: 01/04/2024] [Indexed: 01/30/2024]
Abstract
Motivation Gene deletion is traditionally thought of as a nonadaptive process that removes functional redundancy from genomes, such that it generally receives less attention than duplication in evolutionary turnover studies. Yet, mounting evidence suggests that deletion may promote adaptation via the "less-is-more" evolutionary hypothesis, as it often targets genes harboring unique sequences, expression profiles, and molecular functions. Hence, predicting the relative prevalence of redundant and unique functions among genes targeted by deletion, as well as the parameters underlying their evolution, can shed light on the role of gene deletion in adaptation. Results Here, we present CLOUDe, a suite of machine learning methods for predicting evolutionary targets of gene deletion events from expression data. Specifically, CLOUDe models expression evolution as an Ornstein-Uhlenbeck process, and uses multi-layer neural network, extreme gradient boosting, random forest, and support vector machine architectures to predict whether deleted genes are "redundant" or "unique", as well as several parameters underlying their evolution. We show that CLOUDe boasts high power and accuracy in differentiating between classes, and high accuracy and precision in estimating evolutionary parameters, with optimal performance achieved by its neural network architecture. Application of CLOUDe to empirical data from Drosophila suggests that deletion primarily targets genes with unique functions, with further analysis showing these functions to be enriched for protein deubiquitination. Thus, CLOUDe represents a key advance in learning about the role of gene deletion in functional evolution and adaptation. Availability and implementation CLOUDe is freely available on GitHub (https://github.com/anddssan/CLOUDe).
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Affiliation(s)
- Andre Luiz Campelo dos Santos
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, United States
| | - Michael DeGiorgio
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, United States
| | - Raquel Assis
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, United States
- Institute for Human Health and Disease Intervention, Florida Atlantic University, Boca Raton, FL 33431, United States
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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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Petak C, Frati L, Brennan RS, Pespeni MH. Whole-Genome Sequencing Reveals That Regulatory and Low Pleiotropy Variants Underlie Local Adaptation to Environmental Variability in Purple Sea Urchins. Am Nat 2023; 202:571-586. [PMID: 37792925 DOI: 10.1086/726013] [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] [Indexed: 10/06/2023]
Abstract
AbstractOrganisms experience environments that vary across both space and time. Such environmental heterogeneity shapes standing genetic variation and may influence species' capacity to adapt to rapid environmental change. However, we know little about the kind of genetic variation that is involved in local adaptation to environmental variability. To address this gap, we sequenced the whole genomes of 140 purple sea urchins (Strongylocentrotus purpuratus) from seven populations that vary in their degree of pH variability. Despite no evidence of global population structure, we found a suite of single-nucleotide polymorphisms (SNPs) tightly correlated with local pH variability (outlier SNPs), which were overrepresented in regions putatively involved in gene regulation (long noncoding RNA and enhancers), supporting the idea that variation in regulatory regions is important for local adaptation to variability. In addition, outliers in genes were found to be (i) enriched for biomineralization and ion homeostasis functions related to low pH response, (ii) less central to the protein-protein interaction network, and (iii) underrepresented among genes highly expressed during early development. Taken together, these results suggest that loci that underlie local adaptation to pH variability in purple sea urchins fall in regions with potentially low pleiotropic effects (based on analyses involving regulatory regions, network centrality, and expression time) involved in low pH response (based on functional enrichment).
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8
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Favreau B, Gaal C, Pereira de Lima I, Droc G, Roques S, Sotillo A, Guérard F, Cantonny V, Gakière B, Leclercq J, Lafarge T, de Raissac M. A multi-level approach reveals key physiological and molecular traits in the response of two rice genotypes subjected to water deficit at the reproductive stage. PLANT-ENVIRONMENT INTERACTIONS (HOBOKEN, N.J.) 2023; 4:229-257. [PMID: 37822730 PMCID: PMC10564380 DOI: 10.1002/pei3.10121] [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: 01/20/2023] [Revised: 07/20/2023] [Accepted: 07/31/2023] [Indexed: 10/13/2023]
Abstract
Rice is more vulnerable to drought than maize, wheat, and sorghum because its water requirements remain high throughout the rice life cycle. The effects of drought vary depending on the timing, intensity, and duration of the events, as well as on the rice genotype and developmental stage. It can affect all levels of organization, from genes to the cells, tissues, and/or organs. In this study, a moderate water deficit was applied to two contrasting rice genotypes, IAC 25 and CIRAD 409, during their reproductive stage. Multi-level transcriptomic, metabolomic, physiological, and morphological analyses were performed to investigate the complex traits involved in their response to drought. Weighted gene network correlation analysis was used to identify the specific molecular mechanisms regulated by each genotype, and the correlations between gene networks and phenotypic traits. A holistic analysis of all the data provided a deeper understanding of the specific mechanisms regulated by each genotype, and enabled the identification of gene markers. Under non-limiting water conditions, CIRAD 409 had a denser shoot, but shoot growth was slower despite better photosynthetic performance. Under water deficit, CIRAD 409 was weakly affected regardless of the plant level analyzed. In contrast, IAC 25 had reduced growth and reproductive development. It regulated transcriptomic and metabolic activities at a high level, and activated a complex gene regulatory network involved in growth-limiting processes. By comparing two contrasting genotypes, the present study identified the regulation of some fundamental processes and gene markers, that drive rice development, and influence its response to water deficit, in particular, the importance of the biosynthetic and regulatory pathways for cell wall metabolism. These key processes determine the biological and mechanical properties of the cell wall and thus influence plant development, organ expansion, and turgor maintenance under water deficit. Our results also question the genericity of the antagonism between morphogenesis and organogenesis observed in the two genotypes.
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Affiliation(s)
- Bénédicte Favreau
- CIRAD, UMR AGAP InstitutMontpellierFrance
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroMontpellierFrance
| | - Camille Gaal
- CIRAD, UMR AGAP InstitutMontpellierFrance
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroMontpellierFrance
| | | | - Gaétan Droc
- CIRAD, UMR AGAP InstitutMontpellierFrance
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroMontpellierFrance
| | - Sandrine Roques
- CIRAD, UMR AGAP InstitutMontpellierFrance
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroMontpellierFrance
| | - Armel Sotillo
- CIRAD, UMR AGAP InstitutMontpellierFrance
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroMontpellierFrance
| | - Florence Guérard
- Plateforme Métabolisme‐MétabolomeInstitute of Plant Sciences Paris‐Saclay (IPS2), Université Paris‐Saclay, National Committee of Scientific Research (CNRS), National Institute for Research for Agriculture, Food and Environment (INRAE), Université d'Evry, Université de ParisGif‐sur‐YvetteFrance
| | - Valérie Cantonny
- Plateforme Métabolisme‐MétabolomeInstitute of Plant Sciences Paris‐Saclay (IPS2), Université Paris‐Saclay, National Committee of Scientific Research (CNRS), National Institute for Research for Agriculture, Food and Environment (INRAE), Université d'Evry, Université de ParisGif‐sur‐YvetteFrance
| | - Bertrand Gakière
- Plateforme Métabolisme‐MétabolomeInstitute of Plant Sciences Paris‐Saclay (IPS2), Université Paris‐Saclay, National Committee of Scientific Research (CNRS), National Institute for Research for Agriculture, Food and Environment (INRAE), Université d'Evry, Université de ParisGif‐sur‐YvetteFrance
| | - Julie Leclercq
- CIRAD, UMR AGAP InstitutMontpellierFrance
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroMontpellierFrance
| | - Tanguy Lafarge
- CIRAD, UMR AGAP InstitutMontpellierFrance
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroMontpellierFrance
| | - Marcel de Raissac
- CIRAD, UMR AGAP InstitutMontpellierFrance
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut AgroMontpellierFrance
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Li P, Xiao L, Du Q, Quan M, Song Y, He Y, Huang W, Xie J, Lv C, Wang D, Zhou J, Li L, Liu Q, El‐Kassaby YA, Zhang D. Genomic insights into selection for heterozygous alleles and woody traits in Populus tomentosa. PLANT BIOTECHNOLOGY JOURNAL 2023; 21:2002-2018. [PMID: 37392407 PMCID: PMC10502748 DOI: 10.1111/pbi.14108] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/03/2023] [Accepted: 06/12/2023] [Indexed: 07/03/2023]
Abstract
Heterozygous alleles are widespread in outcrossing and clonally propagated woody plants. The variation in heterozygosity that underlies population adaptive evolution and phenotypic variation, however, remains largely unknown. Here, we describe a de novo chromosome-level genome assembly of Populus tomentosa, an economic and ecologically important native tree in northern China. By resequencing 302 natural accessions, we determined that the South subpopulation (Pop_S) encompasses the ancestral strains of P. tomentosa, while the Northwest subpopulation (Pop_NW) and Northeast subpopulation (Pop_NE) experienced different selection pressures during population evolution, resulting in significant population differentiation and a decrease in the extent of heterozygosity. Analysis of heterozygous selective sweep regions (HSSR) suggested that selection for lower heterozygosity contributed to the local adaptation of P. tomentosa by dwindling gene expression and genetic load in the Pop_NW and Pop_NE subpopulations. Genome-wide association studies (GWAS) revealed that 88 single nucleotide polymorphisms (SNPs) within 63 genes are associated with nine wood composition traits. Among them, the selection for the homozygous AA allele in PtoARF8 is associated with reductions in cellulose and hemicellulose contents by attenuating PtoARF8 expression, and the increase in lignin content is attributable to the selection for decreases in exon heterozygosity in PtoLOX3 during adaptive evolution of natural populations. This study provides novel insights into allelic variations in heterozygosity associated with adaptive evolution of P. tomentosa in response to the local environment and identifies a series of key genes for wood component traits, thereby facilitating genomic-based breeding of important traits in perennial woody plants.
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Affiliation(s)
- Peng Li
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Liang Xiao
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Qingzhang Du
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Mingyang Quan
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Yuepeng Song
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Yuling He
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Weixiong Huang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Jianbo Xie
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Chenfei Lv
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Dan Wang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Jiaxuan Zhou
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Lianzheng Li
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
| | - Qing Liu
- CSIRO Agriculture and Food, Black MountainCanberraAustralian Capital TerritoryAustralia
| | - Yousry A. El‐Kassaby
- Department of Forest and Conservation Sciences, Faculty of Forestry, Forest Sciences CentreUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Deqiang Zhang
- National Engineering Research Center of Tree Breeding and Ecological Restoration, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and TechnologyBeijing Forestry UniversityBeijingChina
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10
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Li Z, Liu X, Wang C, Li Z, Jiang B, Zhang R, Tong L, Qu Y, He S, Chen H, Mao Y, Li Q, Pook T, Wu Y, Zan Y, Zhang H, Li L, Wen K, Chen Y. The pig pangenome provides insights into the roles of coding structural variations in genetic diversity and adaptation. Genome Res 2023; 33:1833-1847. [PMID: 37914227 PMCID: PMC10691484 DOI: 10.1101/gr.277638.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 09/12/2023] [Indexed: 11/03/2023]
Abstract
Structural variations have emerged as an important driving force for genome evolution and phenotypic variation in various organisms, yet their contributions to genetic diversity and adaptation in domesticated animals remain largely unknown. Here we constructed a pangenome based on 250 sequenced individuals from 32 pig breeds in Eurasia and systematically characterized coding sequence presence/absence variations (PAVs) within pigs. We identified 308.3-Mb nonreference sequences and 3438 novel genes absent from the current reference genome. Gene PAV analysis showed that 16.8% of the genes in the pangene catalog undergo PAV. A number of newly identified dispensable genes showed close associations with adaptation. For instance, several novel swine leukocyte antigen (SLA) genes discovered in nonreference sequences potentially participate in immune responses to productive and respiratory syndrome virus (PRRSV) infection. We delineated previously unidentified features of the pig mobilome that contained 490,480 transposable element insertion polymorphisms (TIPs) resulting from recent mobilization of 970 TE families, and investigated their population dynamics along with influences on population differentiation and gene expression. In addition, several candidate adaptive TE insertions were detected to be co-opted into genes responsible for responses to hypoxia, skeletal development, regulation of heart contraction, and neuronal cell development, likely contributing to local adaptation of Tibetan wild boars. These findings enhance our understanding on hidden layers of the genetic diversity in pigs and provide novel insights into the role of SVs in the evolutionary adaptation of mammals.
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Affiliation(s)
- Zhengcao Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China;
| | - Xiaohong Liu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Chen Wang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Zhenyang Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Bo Jiang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Ruifeng Zhang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Lu Tong
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Youping Qu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Sheng He
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Haifan Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Yafei Mao
- Bio-X Institutes, Shanghai Jiao Tong University, 200240 Shanghai, China
| | - Qingnan Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Torsten Pook
- Animal Breeding and Genomics, Wageningen University & Research, Wageningen 6700 AH, The Netherlands
| | - Yu Wu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Yanjun Zan
- Key Laboratory of Tobacco Improvement and Biotechnology, Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao 266000, China
| | - Hui Zhang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Lu Li
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Keying Wen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China
| | - Yaosheng Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, 510006 Guangzhou, China;
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11
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Della Coletta R, Liese SE, Fernandes SB, Mikel MA, Bohn MO, Lipka AE, Hirsch CN. Linking genetic and environmental factors through marker effect networks to understand trait plasticity. Genetics 2023; 224:iyad103. [PMID: 37246567 DOI: 10.1093/genetics/iyad103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 05/19/2023] [Accepted: 05/24/2023] [Indexed: 05/30/2023] Open
Abstract
Understanding how plants adapt to specific environmental changes and identifying genetic markers associated with phenotypic plasticity can help breeders develop plant varieties adapted to a rapidly changing climate. Here, we propose the use of marker effect networks as a novel method to identify markers associated with environmental adaptability. These marker effect networks are built by adapting commonly used software for building gene coexpression networks with marker effects across growth environments as the input data into the networks. To demonstrate the utility of these networks, we built networks from the marker effects of ∼2,000 nonredundant markers from 400 maize hybrids across 9 environments. We demonstrate that networks can be generated using this approach, and that the markers that are covarying are rarely in linkage disequilibrium, thus representing higher biological relevance. Multiple covarying marker modules associated with different weather factors throughout the growing season were identified within the marker effect networks. Finally, a factorial test of analysis parameters demonstrated that marker effect networks are relatively robust to these options, with high overlap in modules associated with the same weather factors across analysis parameters. This novel application of network analysis provides unique insights into phenotypic plasticity and specific environmental factors that modulate the genome.
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Affiliation(s)
- Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Sharon E Liese
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Samuel B Fernandes
- Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR 72701, USA
| | - Mark A Mikel
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Martin O Bohn
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
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12
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Wolf S, Melo D, Garske KM, Pallares LF, Lea AJ, Ayroles JF. Characterizing the landscape of gene expression variance in humans. PLoS Genet 2023; 19:e1010833. [PMID: 37410774 DOI: 10.1371/journal.pgen.1010833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 06/15/2023] [Indexed: 07/08/2023] Open
Abstract
Gene expression variance has been linked to organismal function and fitness but remains a commonly neglected aspect of molecular research. As a result, we lack a comprehensive understanding of the patterns of transcriptional variance across genes, and how this variance is linked to context-specific gene regulation and gene function. Here, we use 57 large publicly available RNA-seq data sets to investigate the landscape of gene expression variance. These studies cover a wide range of tissues and allowed us to assess if there are consistently more or less variable genes across tissues and data sets and what mechanisms drive these patterns. We show that gene expression variance is broadly similar across tissues and studies, indicating that the pattern of transcriptional variance is consistent. We use this similarity to create both global and within-tissue rankings of variation, which we use to show that function, sequence variation, and gene regulatory signatures contribute to gene expression variance. Low-variance genes are associated with fundamental cell processes and have lower levels of genetic polymorphisms, have higher gene-gene connectivity, and tend to be associated with chromatin states associated with transcription. In contrast, high-variance genes are enriched for genes involved in immune response, environmentally responsive genes, immediate early genes, and are associated with higher levels of polymorphisms. These results show that the pattern of transcriptional variance is not noise. Instead, it is a consistent gene trait that seems to be functionally constrained in human populations. Furthermore, this commonly neglected aspect of molecular phenotypic variation harbors important information to understand complex traits and disease.
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Affiliation(s)
- Scott Wolf
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
| | - Diogo Melo
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Kristina M Garske
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
| | - Luisa F Pallares
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
- Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany
| | - Amanda J Lea
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America
- Child and Brain Development, Canadian Institute for Advanced Research, Toronto, Canada
| | - Julien F Ayroles
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
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13
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Roberts M, Josephs EB. Weaker selection on genes with treatment-specific expression consistent with a limit on plasticity evolution in Arabidopsis thaliana. Genetics 2023; 224:iyad074. [PMID: 37094602 PMCID: PMC10484170 DOI: 10.1093/genetics/iyad074] [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: 03/06/2023] [Revised: 03/06/2023] [Accepted: 04/07/2023] [Indexed: 04/26/2023] Open
Abstract
Differential gene expression between environments often underlies phenotypic plasticity. However, environment-specific expression patterns are hypothesized to relax selection on genes, and thus limit plasticity evolution. We collated over 27 terabases of RNA-sequencing data on Arabidopsis thaliana from over 300 peer-reviewed studies and 200 treatment conditions to investigate this hypothesis. Consistent with relaxed selection, genes with more treatment-specific expression have higher levels of nucleotide diversity and divergence at nonsynonymous sites but lack stronger signals of positive selection. This result persisted even after controlling for expression level, gene length, GC content, the tissue specificity of expression, and technical variation between studies. Overall, our investigation supports the existence of a hypothesized trade-off between the environment specificity of a gene's expression and the strength of selection on said gene in A. thaliana. Future studies should leverage multiple genome-scale datasets to tease apart the contributions of many variables in limiting plasticity evolution.
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Affiliation(s)
- Miles Roberts
- Genetics and Genome Sciences Program, Michigan State University, East Lansing, MI 48824, USA
| | - Emily B Josephs
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
- Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, MI 48824, USA
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14
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Piya AA, DeGiorgio M, Assis R. Predicting gene expression divergence between single-copy orthologs in two species. Genome Biol Evol 2023; 15:evad078. [PMID: 37170892 PMCID: PMC10220509 DOI: 10.1093/gbe/evad078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 04/21/2023] [Accepted: 05/02/2023] [Indexed: 05/13/2023] Open
Abstract
Predicting gene expression divergence is integral to understanding the emergence of new biological functions and associated traits. Whereas several sophisticated methods have been developed for this task, their applications are either limited to duplicate genes or require expression data from more than two species. Thus, here we present PiXi, the first machine learning framework for predicting gene expression divergence between single-copy orthologs in two species. PiXi models gene expression evolution as an Ornstein-Uhlenbeck process, and overlays this model with multi-layer neural network, random forest, and support vector machine architectures for making predictions. It outputs the predicted class "conserved" or "diverged" for each pair of orthologs, as well as their predicted expression optima in the two species. We show that PiXi has high power and accuracy in predicting gene expression divergence between single-copy orthologs, as well as high accuracy and precision in estimating their expression optima in the two species, across a wide range of evolutionary scenarios, with the globally best performance achieved by a multi-layer neural network. Moreover, application of our best performing PiXi predictor to empirical gene expression data from single-copy orthologs residing at different loci in two species of Drosophila reveals that approximately 23% underwent expression divergence after positional relocation. Further analysis shows that several of these "diverged" genes are involved in the electron transport chain of the mitochondrial membrane, suggesting that new chromatin environments may impact energy production in Drosophila. Thus, by providing a toolkit for predicting gene expression divergence between single-copy orthologs in two species, PiXi can shed light on the origins of novel phenotypes across diverse biological processes and study systems.
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Affiliation(s)
- Antara Anika Piya
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FloridaUSA
| | - Michael DeGiorgio
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FloridaUSA
| | - Raquel Assis
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FloridaUSA
- Institute for Human Health and Disease Intervention, Florida Atlantic University, Boca Raton, FloridaUSA
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15
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Kuo HC, Yao CT, Liao BY, Weng MP, Dong F, Hsu YC, Hung CM. Weak gene-gene interaction facilitates the evolution of gene expression plasticity. BMC Biol 2023; 21:57. [PMID: 36941675 PMCID: PMC10029303 DOI: 10.1186/s12915-023-01558-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 03/10/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Individual organisms may exhibit phenotypic plasticity when they acclimate to different conditions. Such plastic responses may facilitate or constrain the adaptation of their descendant populations to new environments, complicating their evolutionary trajectories beyond the genetic blueprint. Intriguingly, phenotypic plasticity itself can evolve in terms of its direction and magnitude during adaptation. However, we know little about what determines the evolution of phenotypic plasticity, including gene expression plasticity. Recent laboratory-based studies suggest dominance of reversing gene expression plasticity-plastic responses that move the levels of gene expression away from the new optima. Nevertheless, evidence from natural populations is still limited. RESULTS Here, we studied gene expression plasticity and its evolution in the montane and lowland populations of an elevationally widespread songbird-the Rufous-capped Babbler (Cyanoderma ruficeps)-with reciprocal transplant experiments and transcriptomic analyses; we set common gardens at altitudes close to these populations' native ranges. We confirmed the prevalence of reversing plasticity in genes associated with altitudinal adaptation. Interestingly, we found a positive relationship between magnitude and degree of evolution in gene expression plasticity, which was pertinent to not only adaptation-associated genes but also the whole transcriptomes from multiple tissues. Furthermore, we revealed that genes with weaker expressional interactions with other genes tended to exhibit stronger plasticity and higher degree of plasticity evolution, which explains the positive magnitude-evolution relationship. CONCLUSIONS Our experimental evidence demonstrates that species may initiate their adaptation to new habitats with genes exhibiting strong expression plasticity. We also highlight the role of expression interdependence among genes in regulating the magnitude and evolution of expression plasticity. This study illuminates how the evolution of phenotypic plasticity in gene expression facilitates the adaptation of species to challenging environments in nature.
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Affiliation(s)
- Hao-Chih Kuo
- Biodiversity Research Center, Academia Sinica, Taipei, 11529, Taiwan
| | - Cheng-Te Yao
- Division of Zoology, Endemic Species Research Institute, Nantou, 55244, Taiwan
| | - Ben-Yang Liao
- Institute of Population Health Sciences, National Health Research Institutes, Miaoli, 35053, Taiwan
| | - Meng-Pin Weng
- Institute of Population Health Sciences, National Health Research Institutes, Miaoli, 35053, Taiwan
| | - Feng Dong
- Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China
| | - Yu-Cheng Hsu
- Department of Natural Resources and Environmental Studies, National Dong Hwa University, Hualien, 97401, Taiwan
| | - Chih-Ming Hung
- Biodiversity Research Center, Academia Sinica, Taipei, 11529, Taiwan.
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16
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Detecting signatures of selection on gene expression. Nat Ecol Evol 2022; 6:1035-1045. [PMID: 35551249 DOI: 10.1038/s41559-022-01761-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 04/01/2022] [Indexed: 12/15/2022]
Abstract
A substantial amount of phenotypic diversity results from changes in gene expression levels and patterns. Understanding how the transcriptome evolves is therefore a key priority in identifying mechanisms of adaptive change. However, in contrast to powerful models of sequence evolution, we lack a consensus model of gene expression evolution. Furthermore, recent work has shown that many of the comparative approaches used to study gene expression are subject to biases that can lead to false signatures of selection. Here we first outline the main approaches for describing expression evolution and their inherent biases. Next, we bridge the gap between the fields of phylogenetic comparative methods and transcriptomics to reinforce the main pitfalls of inferring selection on expression patterns and use simulation studies to show that shifts in tissue composition can heavily bias inferences of selection. We close by highlighting the multi-dimensional nature of transcriptional variation and identifying major unanswered questions in disentangling how selection acts on the transcriptome.
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17
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Gaynor SM, Fagny M, Lin X, Platig J, Quackenbush J. Connectivity in eQTL networks dictates reproducibility and genomic properties. CELL REPORTS METHODS 2022; 2:100218. [PMID: 35637906 PMCID: PMC9142682 DOI: 10.1016/j.crmeth.2022.100218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 02/08/2022] [Accepted: 04/25/2022] [Indexed: 01/11/2023]
Abstract
Expression quantitative trait locus (eQTL) analysis associates SNPs with gene expression; these relationships can be represented as a bipartite network with association strength as "edge weights" between SNPs and genes. However, most eQTL networks use binary edge weights based on thresholded FDR estimates: definitions that influence reproducibility and downstream analyses. We constructed twenty-nine tissue-specific eQTL networks using GTEx data and evaluated a comprehensive set of network specifications based on false discovery rates, test statistics, and p values, focusing on the degree centrality-a metric of an SNP or gene node's potential network influence. We found a thresholded Benjamini-Hochberg q value weighted by the Z-statistic balances metric reproducibility and computational efficiency. Our estimated gene degrees positively correlate with gene degrees in gene regulatory networks, demonstrating that these networks are complementary in understanding regulation. Gene degrees also correlate with genetic diversity, and heritability analyses show that highly connected nodes are enriched for tissue-relevant traits.
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Affiliation(s)
- Sheila M. Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Maud Fagny
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, 91190 Gif-sur-Yvette, France
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Statistics, Harvard University, Cambridge, MA 02138, USA
| | - John Platig
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - John Quackenbush
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
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18
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de Miguel M, Rodríguez-Quilón I, Heuertz M, Hurel A, Grivet D, Jaramillo-Correa JP, Vendramin GG, Plomion C, Majada J, Alía R, Eckert AJ, González-Martínez SC. Polygenic adaptation and negative selection across traits, years and environments in a long-lived plant species (Pinus pinaster Ait., Pinaceae). Mol Ecol 2022; 31:2089-2105. [PMID: 35075727 DOI: 10.1111/mec.16367] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 11/30/2021] [Accepted: 01/11/2022] [Indexed: 11/26/2022]
Abstract
A decade of genetic association studies in multiple organisms suggests that most complex traits are polygenic, i.e., they have a genetic architecture determined by numerous loci each with small effect-size. Thus, determining the degree of polygenicity and its variation across traits, environments and time is crucial to understand the genetic basis of phenotypic variation. We applied multilocus approaches to estimate the degree of polygenicity of fitness-related traits in a long-lived plant (Pinus pinaster Ait., maritime pine) and to analyze this variation across environments and years. We evaluated five categories of fitness-related traits (survival, height, phenology, functional, and biotic-stress response traits) in a clonal common-garden network, planted in contrasted environments (over 12,500 trees). Most of the analyzed traits showed evidence of local adaptation based on Qst -Fst comparisons. We further observed a remarkably stable degree of polygenicity, averaging 6% (range of 0-27%), across traits, environments and years. We detected evidence of negative selection, which could explain, at least partially, the high degree of polygenicity. Because polygenic adaptation can occur rapidly, our results suggest that current predictions on the capacity of natural forest tree populations to adapt to new environments should be revised, especially in the current context of climate change.
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Affiliation(s)
- Marina de Miguel
- INRAE, Univ. Bordeaux, BIOGECO, F-33610, Cestas, France.,EGFV, Univ. Bordeaux, Bordeaux Sciences Agro, INRAE, ISVV, F-33882, Villenave d'Ornon, France
| | - Isabel Rodríguez-Quilón
- Department of Forest Ecology and Genetics, Forest Research Centre, INIA, Carretera de la Coruña km 7.5, 28040, Madrid, Spain
| | | | - Agathe Hurel
- INRAE, Univ. Bordeaux, BIOGECO, F-33610, Cestas, France
| | - Delphine Grivet
- Department of Forest Ecology and Genetics, Forest Research Centre, INIA, Carretera de la Coruña km 7.5, 28040, Madrid, Spain
| | - Juan-Pablo Jaramillo-Correa
- Department of Evolutionary Ecology, Institute of Ecology, Universidad Nacional Autónoma de México, AP 70-275, México City, CDMX 04510, Mexico
| | - Giovanni G Vendramin
- Institute of Biosciences and Bioresources, Division of Florence, National Research Council, 50019, Sesto Fiorentino (FI), Italy
| | | | - Juan Majada
- Sección Forestal, SERIDA, Finca Experimental ''La Mata'', 33820, Grado, Principado de Asturias, Spain
| | - Ricardo Alía
- EGFV, Univ. Bordeaux, Bordeaux Sciences Agro, INRAE, ISVV, F-33882, Villenave d'Ornon, France
| | - Andrew J Eckert
- Department of Biology, Virginia Commonwealth University, Richmond, VA, 23284, USA
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19
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Rennison DJ, Peichel CL. Pleiotropy facilitates parallel adaptation in sticklebacks. Mol Ecol 2022; 31:1476-1486. [PMID: 34997980 PMCID: PMC9306781 DOI: 10.1111/mec.16335] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 10/27/2021] [Accepted: 12/20/2021] [Indexed: 11/27/2022]
Abstract
Highly pleiotropic genes are predicted to be used less often during adaptation, as mutations in these loci are more likely to have negative fitness consequences. Following this logic, we tested whether pleiotropy impacts the probability that a locus will be used repeatedly in adaptation. We used two proxies to estimate pleiotropy: number of phenotypic traits affected by a given genomic region and gene connectivity. We first surveyed 16 independent stream‐lake and three independent benthic‐limnetic ecotype pairs of threespine stickleback to estimate genome‐wide patterns in parallel genomic differentiation. Our analysis revealed parallel divergence across the genome; 30%–37% of outlier regions were shared between at least two independent pairs in either the stream‐lake or benthic‐limnetic comparisons. We then tested whether parallel genomic regions are less pleiotropic than nonparallel regions. Counter to our a priori prediction, parallel genomic regions contained genes with significantly more pleiotropy; that is, influencing a greater number of traits and more highly connected. The increased pleiotropy of parallel regions could not be explained by other genomic factors, as there was no significant difference in mean gene count, mutation or recombination rates between parallel and nonparallel regions. Interestingly, although nonparallel regions contained genes that were less connected and influenced fewer mapped traits on average than parallel regions, they also tended to contain the genes that were predicted to be the most pleiotropic. Taken together, our findings are consistent with the idea that pleiotropy only becomes constraining at high levels and that low or intermediate levels of pleiotropy may be beneficial for adaptation.
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Affiliation(s)
- Diana J Rennison
- Division of Evolutionary Ecology, Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012, Bern, Switzerland
| | - Catherine L Peichel
- Division of Evolutionary Ecology, Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012, Bern, Switzerland
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20
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Brown KE, Kelly JK. Genome-wide association mapping of transcriptome variation in Mimulus guttatus indicates differing patterns of selection on cis- versus trans-acting mutations. Genetics 2022; 220:iyab189. [PMID: 34791192 PMCID: PMC8733635 DOI: 10.1093/genetics/iyab189] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 09/28/2021] [Indexed: 11/14/2022] Open
Abstract
We measured the floral bud transcriptome of 151 fully sequenced lines of Mimulus guttatus from one natural population. Thousands of single nucleotide polymorphisms (SNPs) are implicated as transcription regulators, but there is a striking difference in the allele frequency spectrum of cis-acting and trans-acting mutations. Cis-SNPs have intermediate frequencies (consistent with balancing selection) while trans-SNPs exhibit a rare-alleles model (consistent with purifying selection). This pattern only becomes clear when transcript variation is normalized on a gene-to-gene basis. If a global normalization is applied, as is typically in RNAseq experiments, asymmetric transcript distributions combined with "rarity disequilibrium" produce a superabundance of false positives for trans-acting SNPs. To explore the cause of purifying selection on trans-acting mutations, we identified gene expression modules as sets of coexpressed genes. The extent to which trans-acting mutations influence modules is a strong predictor of allele frequency. Mutations altering expression of genes with high "connectedness" (those that are highly predictive of the representative module expression value) have the lowest allele frequency. The expression modules can also predict whole-plant traits such as flower size. We find that a substantial portion of the genetic (co)variance among traits can be described as an emergent property of genetic effects on expression modules.
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Affiliation(s)
- Keely E Brown
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA
| | - John K Kelly
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA
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21
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Three topological features of regulatory networks control life-essential and specialized subsystems. Sci Rep 2021; 11:24209. [PMID: 34930908 PMCID: PMC8688434 DOI: 10.1038/s41598-021-03625-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 12/07/2021] [Indexed: 11/08/2022] Open
Abstract
Gene regulatory networks (GRNs) play key roles in development, phenotype plasticity, and evolution. Although graph theory has been used to explore GRNs, associations amongst topological features, transcription factors (TFs), and systems essentiality are poorly understood. Here we sought the relationship amongst the main GRN topological features that influence the control of essential and specific subsystems. We found that the Knn, page rank, and degree are the most relevant GRN features: the ones are conserved along the evolution and are also relevant in pluripotent cells. Interestingly, life-essential subsystems are governed mainly by TFs with intermediary Knn and high page rank or degree, whereas specialized subsystems are mainly regulated by TFs with low Knn. Hence, we suggest that the high probability of TFs be toured by a random signal, and the high probability of the signal propagation to target genes ensures the life-essential subsystems' robustness. Gene/genome duplication is the main evolutionary process to rise Knn as the most relevant feature. Herein, we shed light on unexplored topological GRN features to assess how they are related to subsystems and how the duplications shaped the regulatory systems along the evolution. The classification model generated can be found here: https://github.com/ivanrwolf/NoC/ .
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Christie N, Mannapperuma C, Ployet R, van der Merwe K, Mähler N, Delhomme N, Naidoo S, Mizrachi E, Street NR, Myburg AA. qtlXplorer: an online systems genetics browser in the Eucalyptus Genome Integrative Explorer (EucGenIE). BMC Bioinformatics 2021; 22:595. [PMID: 34911434 PMCID: PMC8672637 DOI: 10.1186/s12859-021-04514-9] [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: 09/23/2021] [Accepted: 12/06/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Affordable high-throughput DNA and RNA sequencing technologies are allowing genomic analysis of plant and animal populations and as a result empowering new systems genetics approaches to study complex traits. The availability of intuitive tools to browse and analyze the resulting large-scale genetic and genomic datasets remain a significant challenge. Furthermore, these integrative genomics approaches require innovative methods to dissect the flow and interconnectedness of biological information underlying complex trait variation. The Plant Genome Integrative Explorer (PlantGenIE.org) is a multi-species database and domain that houses online tools for model and woody plant species including Eucalyptus. Since the Eucalyptus Genome Integrative Explorer (EucGenIE) is integrated within PlantGenIE, it shares genome and expression analysis tools previously implemented within the various subdomains (ConGenIE, PopGenIE and AtGenIE). Despite the success in setting up integrative genomics databases, online tools for systems genetics modelling and high-resolution dissection of complex trait variation in plant populations have been lacking. RESULTS We have developed qtlXplorer ( https://eucgenie.org/QTLXplorer ) for visualizing and exploring systems genetics data from genome-wide association studies including quantitative trait loci (QTLs) and expression-based QTL (eQTL) associations. This module allows users to, for example, find co-located QTLs and eQTLs using an interactive version of Circos, or explore underlying genes using JBrowse. It provides users with a means to build systems genetics models and generate hypotheses from large-scale population genomics data. We also substantially upgraded the EucGenIE resource and show how it enables users to combine genomics and systems genetics approaches to discover candidate genes involved in biotic stress responses and wood formation by focusing on two multigene families, laccases and peroxidases. CONCLUSIONS qtlXplorer adds a new dimension, population genomics, to the EucGenIE and PlantGenIE environment. The resource will be of interest to researchers and molecular breeders working in Eucalyptus and other woody plant species. It provides an example of how systems genetics data can be integrated with functional genetics data to provide biological insight and formulate hypotheses. Importantly, integration within PlantGenIE enables novel comparative genomics analyses to be performed from population-scale data.
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Affiliation(s)
- Nanette Christie
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Private bag X20, Pretoria, 0028, South Africa.
| | - Chanaka Mannapperuma
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 907 81, Umeå, Sweden
| | - Raphael Ployet
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Private bag X20, Pretoria, 0028, South Africa
| | - Karen van der Merwe
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Private bag X20, Pretoria, 0028, South Africa
| | - Niklas Mähler
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 907 81, Umeå, Sweden
| | - Nicolas Delhomme
- Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, 901 83, Umeå, Sweden
| | - Sanushka Naidoo
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Private bag X20, Pretoria, 0028, South Africa
| | - Eshchar Mizrachi
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Private bag X20, Pretoria, 0028, South Africa
| | - Nathaniel R Street
- Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, 907 81, Umeå, Sweden.
| | - Alexander A Myburg
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Private bag X20, Pretoria, 0028, South Africa
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23
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Brænne I, Onengut-Gumuscu S, Chen R, Manichaikul AW, Rich SS, Chen WM, Farber CR. Dynamic changes in immune gene co-expression networks predict development of type 1 diabetes. Sci Rep 2021; 11:22651. [PMID: 34811390 PMCID: PMC8609030 DOI: 10.1038/s41598-021-01840-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 11/01/2021] [Indexed: 01/13/2023] Open
Abstract
Significant progress has been made in elucidating genetic risk factors influencing Type 1 diabetes (T1D); however, features other than genetic variants that initiate and/or accelerate islet autoimmunity that lead to the development of clinical T1D remain largely unknown. We hypothesized that genetic and environmental risk factors can both contribute to T1D through dynamic alterations of molecular interactions in physiologic networks. To test this hypothesis, we utilized longitudinal blood transcriptomic profiles in The Environmental Determinants of Diabetes in the Young (TEDDY) study to generate gene co-expression networks. In network modules that contain immune response genes associated with T1D, we observed highly dynamic differences in module connectivity in the 600 days (~ 2 years) preceding clinical diagnosis of T1D. Our results suggest that gene co-expression is highly plastic and that connectivity differences in T1D-associated immune system genes influence the timing and development of clinical disease.
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Affiliation(s)
- Ingrid Brænne
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
| | - Ruoxi Chen
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
| | - Ani W Manichaikul
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA
| | - Charles R Farber
- Center for Public Health Genomics, University of Virginia, P.O. Box 800717, Charlottesville, VA, 22908, USA.
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA.
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA.
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24
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Abstract
Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS in the model plant species Arabidopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, whereas others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be extremely sensitive to sampling and population structure.
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Affiliation(s)
| | - Stephan Reinert
- Center for Computational and Theoretical Biology, University of Würzburg, Würzburg, Germany
| | - Magnus Nordborg
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
| | - Arthur Korte
- Center for Computational and Theoretical Biology, University of Würzburg, Würzburg, Germany
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25
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Guillaume B, Jérôme T, Philippe L, Eduardo C, François-Joseph L, Eric B. Aging at evolutionary crossroads: longitudinal gene co-expression network analyses of proximal and ultimate causes of aging in bats. Mol Biol Evol 2021; 39:6400255. [PMID: 34662394 PMCID: PMC8763092 DOI: 10.1093/molbev/msab302] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
How, when, and why do organisms, their tissues, and their cells age remain challenging issues, although researchers have identified multiple mechanistic causes of aging, and three major evolutionary theories have been developed to unravel the ultimate causes of organismal aging. A central hypothesis of these theories is that the strength of natural selection decreases with age. However, empirical evidence on when, why, and how organisms age is phylogenetically limited, especially in natural populations. Here, we developed generic comparisons of gene co-expression networks that quantify and dissect the heterogeneity of gene co-expression in conspecific individuals from different age-classes to provide topological evidence about some mechanical and fundamental causes of organismal aging. We applied this approach to investigate the complexity of some proximal and ultimate causes of aging phenotypes in a natural population of the greater mouse-eared bat Myotis myotis, a remarkably long-lived species given its body size and metabolic rate, with available longitudinal blood transcriptomes. M. myotis gene co-expression networks become increasingly fragmented with age, suggesting an erosion of the strength of natural selection and a general dysregulation of gene co-expression in aging bats. However, selective pressures remain sufficiently strong to allow successive emergence of homogeneous age-specific gene co-expression patterns, for at least 7 years. Thus, older individuals from long-lived species appear to sit at an evolutionary crossroad: as they age, they experience both a decrease in the strength of natural selection and a targeted selection for very specific biological processes, further inviting to refine a central hypothesis in evolutionary aging theories.
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Affiliation(s)
- Bernard Guillaume
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, 75005, France
| | - Teulière Jérôme
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, 75005, France
| | - Lopez Philippe
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, 75005, France
| | - Corel Eduardo
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, 75005, France
| | - Lapointe François-Joseph
- Département de sciences biologiques, Complexe des sciences, 1375 avenue Thérèse-Lavoie-Roux, Université de Montréal, Montréal, Québec), H2V 0B3, Canada (
| | - Bapteste Eric
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Sorbonne Université, CNRS, Museum National d'Histoire Naturelle, EPHE, Université des Antilles, Paris, 75005, France
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26
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Miculan M, Nelissen H, Ben Hassen M, Marroni F, Inzé D, Pè ME, Dell’Acqua M. A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays). THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2021; 107:1056-1071. [PMID: 34087008 PMCID: PMC8519057 DOI: 10.1111/tpj.15364] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 05/31/2021] [Indexed: 05/13/2023]
Abstract
The characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript-trait correlations. Then, leaf traits were associated with SNPs in a genome-wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript-trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co-expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize.
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Affiliation(s)
- Mara Miculan
- Institute of Life SciencesScuola Superiore Sant’AnnaPisa56127Italy
| | - Hilde Nelissen
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhent9052Belgium
- Center for Plant Systems Biology, VIBGhent9052Belgium
| | - Manel Ben Hassen
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhent9052Belgium
- Center for Plant Systems Biology, VIBGhent9052Belgium
| | - Fabio Marroni
- IGA Technology ServicesUdine33100Italy
- Department of Agricultural, FoodAT, Environmental and Animal Sciences (DI4A)University of UdineUdine33100Italy
| | - Dirk Inzé
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhent9052Belgium
- Center for Plant Systems Biology, VIBGhent9052Belgium
| | - Mario Enrico Pè
- Institute of Life SciencesScuola Superiore Sant’AnnaPisa56127Italy
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27
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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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28
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Blanc J, Kremling KAG, Buckler E, Josephs EB. Local adaptation contributes to gene expression divergence in maize. G3-GENES GENOMES GENETICS 2021; 11:6114460. [PMID: 33604670 PMCID: PMC8022924 DOI: 10.1093/g3journal/jkab004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 12/20/2020] [Indexed: 11/14/2022]
Abstract
Gene expression links genotypes to phenotypes, so identifying genes whose expression is shaped by selection will be important for understanding the traits and processes underlying local adaptation. However, detecting local adaptation for gene expression will require distinguishing between divergence due to selection and divergence due to genetic drift. Here, we adapt a QST−FST framework to detect local adaptation for transcriptome-wide gene expression levels in a population of diverse maize genotypes. We compare the number and types of selected genes across a wide range of maize populations and tissues, as well as selection on cold-response genes, drought-response genes, and coexpression clusters. We identify a number of genes whose expression levels are consistent with local adaptation and show that genes involved in stress response show enrichment for selection. Due to its history of intense selective breeding and domestication, maize evolution has long been of interest to researchers, and our study provides insight into the genes and processes important for in local adaptation of maize.
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Affiliation(s)
- Jennifer Blanc
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Karl A G Kremling
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA.,Inari Agriculture, Cambridge, MA 02139, USA
| | - Edward Buckler
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA.,Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA.,United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY 14853, USA
| | - Emily B Josephs
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA.,Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, MI 48824, USA
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29
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DeGiorgio M, Assis R. Learning Retention Mechanisms and Evolutionary Parameters of Duplicate Genes from Their Expression Data. Mol Biol Evol 2021; 38:1209-1224. [PMID: 33045078 PMCID: PMC7947822 DOI: 10.1093/molbev/msaa267] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Learning about the roles that duplicate genes play in the origins of novel phenotypes requires an understanding of how their functions evolve. A previous method for achieving this goal, CDROM, employs gene expression distances as proxies for functional divergence and then classifies the evolutionary mechanisms retaining duplicate genes from comparisons of these distances in a decision tree framework. However, CDROM does not account for stochastic shifts in gene expression or leverage advances in contemporary statistical learning for performing classification, nor is it capable of predicting the parameters driving duplicate gene evolution. Thus, here we develop CLOUD, a multi-layer neural network built on a model of gene expression evolution that can both classify duplicate gene retention mechanisms and predict their underlying evolutionary parameters. We show that not only is the CLOUD classifier substantially more powerful and accurate than CDROM, but that it also yields accurate parameter predictions, enabling a better understanding of the specific forces driving the evolution and long-term retention of duplicate genes. Further, application of the CLOUD classifier and predictor to empirical data from Drosophila recapitulates many previous findings about gene duplication in this lineage, showing that new functions often emerge rapidly and asymmetrically in younger duplicate gene copies, and that functional divergence is driven by strong natural selection. Hence, CLOUD represents a major advancement in classifying retention mechanisms and predicting evolutionary parameters of duplicate genes, thereby highlighting the utility of incorporating sophisticated statistical learning techniques to address long-standing questions about evolution after gene duplication.
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Affiliation(s)
- Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431.,Institute for Human Health and Disease Intervention, Florida Atlantic University, Boca Raton, FL 33431
| | - Raquel Assis
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431.,Institute for Human Health and Disease Intervention, Florida Atlantic University, Boca Raton, FL 33431
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30
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Sudhakar P, Verstockt B, Cremer J, Verstockt S, Sabino J, Ferrante M, Vermeire S. Understanding the Molecular Drivers of Disease Heterogeneity in Crohn's Disease Using Multi-omic Data Integration and Network Analysis. Inflamm Bowel Dis 2021; 27:870-886. [PMID: 33313682 PMCID: PMC8128416 DOI: 10.1093/ibd/izaa281] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Indexed: 12/12/2022]
Abstract
Crohn's disease (CD), a form of inflammatory bowel disease (IBD), is characterized by heterogeneity along multiple clinical axes, which in turn impacts disease progression and treatment modalities. Using advanced data integration approaches and systems biology tools, we studied the contribution of CD susceptibility variants and gene expression in distinct peripheral immune cell subsets (CD14+ monocytes and CD4+ T cells) to relevant clinical traits. Our analyses revealed that most clinical traits capturing CD heterogeneity could be associated with CD14+ and CD4+ gene expression rather than disease susceptibility variants. By disentangling the sources of variation, we identified molecular features that could potentially be driving the heterogeneity of various clinical traits of CD patients. Further downstream analyses identified contextual hub proteins such as genes encoding barrier functions, antimicrobial peptides, chemokines, and their receptors, which are either targeted by drugs used in CD or other inflammatory diseases or are relevant to the biological functions implicated in disease pathology. These hubs could be used as cell type-specific targets to treat specific subtypes of CD patients in a more individualized approach based on the underlying biology driving their disease subtypes. Our study highlights the importance of data integration and systems approaches to investigate complex and heterogeneous diseases such as IBD.
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Affiliation(s)
- Padhmanand Sudhakar
- Department of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID)
| | - Bram Verstockt
- Department of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID)
- University Hospitals Leuven, Department of Gastroenterology and Hepatology
| | - Jonathan Cremer
- Department of Microbiology and Immunology, Laboratory of Clinical Immunology, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Sare Verstockt
- Department of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID)
| | - João Sabino
- Department of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID)
- University Hospitals Leuven, Department of Gastroenterology and Hepatology
| | - Marc Ferrante
- Department of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID)
- University Hospitals Leuven, Department of Gastroenterology and Hepatology
| | - Séverine Vermeire
- Department of Chronic Diseases, Metabolism and Ageing, Translational Research Center for Gastrointestinal Disorders (TARGID)
- University Hospitals Leuven, Department of Gastroenterology and Hepatology
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31
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Zhu J, Lu Q, Li B, Li H, Wu C, Li C, Jin H. Potential of the cell-free blood-based biomarker uroplakin 2 RNA to detect recurrence after surgical resection of lung adenocarcinoma. Oncol Lett 2021; 22:520. [PMID: 34025787 PMCID: PMC8130048 DOI: 10.3892/ol.2021.12781] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 10/26/2020] [Indexed: 12/17/2022] Open
Abstract
Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, and ~30% of patients with LUAD develop cancer recurrence after surgery. The present study aimed to identify and validate biomarkers that may be used to monitor recurrence following LUAD surgery. Data from patients with LUAD were downloaded from The Cancer Genome Atlas database and postoperative recurrence samples were selected. Subsequently, weighted gene co-expression network analysis (WGCNA) was subsequently performed to identify key co-expression gene modules. Additionally, enrichment analysis of the key gene modules was performed using the Database for Annotation, Visualization and Integrated Discovery. Furthermore, survival analysis was performed on the most notable biomarker, uroplakin 2 (UPK2), which was downloaded from the Oncomine database, and its effect on prognosis was assessed. WGCNA identified 39 gene modules, of which one was most associated with recurrence. Among them, UPK2, kelch domain containing 3, galanin receptor 2 and tyrosinase-related protein 1 served a central role in the co-expression network and were significantly associated with the survival of patients. A total of 132 blood samples were collected from patients with LUAD with free UPK2 in the plasma. The expression levels of UPK2 relative to GADPH were 0.1623 and 0.2763 in non-relapsed and relapsed patients, respectively. Receiver operating characteristic curve analysis was used to detect free UPK2 mRNA in the blood in order to monitor postoperative recurrence, resulting in an area under the curve of 0.767 and a 95% CI of 0.675-0.858. Patients with high free UPK2 mRNA expression had unfavorable survival outcomes compared with those with low UPK2 expression. Therefore, free UPK2 mRNA expression in the plasma may have the potential to act as an indicator of postoperative recurrence in patients with early stage LUAD.
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Affiliation(s)
- Ji Zhu
- Department of Thoracic Surgery, First Affiliated Hospital of The Second Military Medical University, Shanghai 200433, P.R. China
| | - Qijue Lu
- Department of Thoracic Surgery, First Affiliated Hospital of The Second Military Medical University, Shanghai 200433, P.R. China
| | - Bin Li
- Department of Thoracic Surgery, Section of Esophageal Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, P.R. China
| | - Huafei Li
- School of Life Sciences, Shanghai University, Shanghai 200444, P.R. China
| | - Cong Wu
- Department of Laboratory Diagnosis, First Affiliated Hospital of The Second Military Medical University, Shanghai 200433, P.R. China
| | - Chunguang Li
- Department of Thoracic Surgery, First Affiliated Hospital of The Second Military Medical University, Shanghai 200433, P.R. China
| | - Hai Jin
- Department of Thoracic Surgery, First Affiliated Hospital of The Second Military Medical University, Shanghai 200433, P.R. China
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Lu M, Feau N, Vidakovic DO, Ukrainetz N, Wong B, Aitken SN, Hamelin RC, Yeaman S. Comparative Gene Expression Analysis Reveals Mechanism of Pinus contorta Response to the Fungal Pathogen Dothistroma septosporum. MOLECULAR PLANT-MICROBE INTERACTIONS : MPMI 2021; 34:397-409. [PMID: 33258711 DOI: 10.1094/mpmi-10-20-0282-r] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Many conifers have distributions that span wide ranges in both biotic and abiotic conditions, but the basis of response to biotic stress has received much less attention than response to abiotic stress. In this study, we investigated the gene expression response of lodgepole pine (Pinus contorta) to attack by the fungal pathogen Dothistroma septosporum, which causes Dothistroma needle blight, a disease that has caused severe climate-related outbreaks in northwestern British Columbia. We inoculated tolerant and susceptible pines with two D. septosporum isolates and analyzed the differentially expressed genes (DEGs), differential exon usage, and coexpressed gene modules using RNA-sequencing data. We found a rapid and strong transcriptomic response in tolerant lodgepole pine samples inoculated with one D. septosporum isolate, and a late and weak response in susceptible samples inoculated with another isolate. We mapped 43 of the DEG- or gene module-identified genes to the reference plant-pathogen interaction pathway deposited in the Kyoto Encyclopedia of Genes and Genomes database. These genes are present in PAMP-triggered and effector-triggered immunity pathways. Genes comprising pathways and gene modules had signatures of strong selective constraint, while the highly expressed genes in tolerant samples appear to have been favored by selection to counterattack the pathogen. We identified candidate resistance genes that may respond to D. septosporum effectors. Taken together, our results show that gene expression response to D. septosporum infection in lodgepole pine varies both among tree genotypes and pathogen strains and involves both known candidate genes and a number of genes with previously unknown functions.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
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Affiliation(s)
- Mengmeng Lu
- Department of Biological Sciences, University of Calgary, 507 Campus Drive NW, Calgary, Canada
| | - Nicolas Feau
- Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, Canada
| | - Dragana Obreht Vidakovic
- Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, Canada
| | - Nicholas Ukrainetz
- Forest Improvement and Research Management Branch, Ministry of Forests, Lands and Natural Resource Operations & Rural Development, 18793-32nd Ave., Surrey, Canada
| | - Barbara Wong
- Institut de Biologie Intégrative et des Systèmes, Université Laval, Pavillon Charles-Eugène-Marchand 1030, avenue de la Médecine, Québec, Canada
| | - Sally N Aitken
- Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, Canada
| | - Richard C Hamelin
- Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, Canada
- Institut de Biologie Intégrative et des Systèmes, Université Laval, Pavillon Charles-Eugène-Marchand 1030, avenue de la Médecine, Québec, Canada
| | - Sam Yeaman
- Department of Biological Sciences, University of Calgary, 507 Campus Drive NW, Calgary, Canada
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Wu J, Xia X, Hu Y, Fang X, Orsulic S. Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis. Front Genet 2021; 12:580190. [PMID: 33613630 PMCID: PMC7887323 DOI: 10.3389/fgene.2021.580190] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 01/04/2021] [Indexed: 12/19/2022] Open
Abstract
Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to identify gene modules highly correlated with clinical features of infertility in endometriosis. Additionally, the protein–protein interaction network analysis was used to identify the potential 20 hub messenger RNAs (mRNAs) while the network topological analysis was used to identify nine candidate long non-coding RNAs (lncRNAs). Functional annotations of clinically significant modules and lncRNAs revealed that hub genes might be involved in infertility in endometriosis by regulating G protein-coupled receptor signaling (GPCR) activity. Gene Set Enrichment Analysis showed that the phospholipase C-activating GPCR signaling pathway is correlated with infertility in patients with endometriosis. Taken together, our analysis has identified 29 hub genes which might lead to infertility in endometriosis through the regulation of the GPCR network.
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Affiliation(s)
- Jingni Wu
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital, Central South University, Changsha, China.,Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Xiaomeng Xia
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ye Hu
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Xiaoling Fang
- Department of Obstetrics and Gynecology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Sandra Orsulic
- Department of Obstetrics and Gynecology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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Mortezaei Z, Khosravi A. New potential anticancer drug-like compounds for squamous cell lung cancer using transcriptome network analysis. INFORMATICS IN MEDICINE UNLOCKED 2021. [DOI: 10.1016/j.imu.2021.100599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Zinkgraf M, Zhao ST, Canning C, Gerttula S, Lu MZ, Filkov V, Groover A. Evolutionary network genomics of wood formation in a phylogenetic survey of angiosperm forest trees. THE NEW PHYTOLOGIST 2020; 228:1811-1823. [PMID: 32696464 DOI: 10.1111/nph.16819] [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: 05/20/2020] [Accepted: 07/06/2020] [Indexed: 06/11/2023]
Abstract
Wood formation was present in early angiosperms, but has been highly modified through evolution to generate the anatomical diversity seen in extant angiosperm lineages. In this project, we modeled changes in gene coexpression relationships associated with the evolution of wood formation in a phylogenetic survey of 13 angiosperm tree species. Gravitropic stimulation was used as an experimental treatment to alter wood formation and also perturb gene expression. Gene transcript abundances were determined using RNA sequencing of developing wood tissues from upright trees, and from the top (tension wood) and bottom (opposite wood) tissues of gravistimulated trees. A network-based approach was employed to align gene coexpression networks across species based on orthologous relationships. A large-scale, multilayer network was modeled that identified both lineage-specific gene coexpression modules and modules conserved across multiple species. Functional annotation and analysis of modules identified specific regulatory processes associated with conserved modules, including regulation of hormones, protein phosphorylation, meristem development and epigenetic processes. Our results provide novel insights into the evolution and development of wood formation, and demonstrate the ability to identify biological processes and genes important for the evolution of a foundational trait in nonmodel, undomesticated forest trees.
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Affiliation(s)
- Matthew Zinkgraf
- USDA Forest Service, Pacific Southwest Research Station, Davis, CA, 95618, USA
- College of Science and Engineering, Western Washington University, Bellingham, WA, 98225-9063, USA
| | - Shu-Tang Zhao
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Courtney Canning
- USDA Forest Service, Pacific Southwest Research Station, Davis, CA, 95618, USA
| | - Suzanne Gerttula
- USDA Forest Service, Pacific Southwest Research Station, Davis, CA, 95618, USA
| | - Meng-Zhu Lu
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China
| | - Vladimir Filkov
- Computer Science, University of California Davis, Davis, CA, 95618, USA
| | - Andrew Groover
- USDA Forest Service, Pacific Southwest Research Station, Davis, CA, 95618, USA
- Department of Plant Biology, University of California Davis, Davis, CA, 95616, USA
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36
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Mähler N, Schiffthaler B, Robinson KM, Terebieniec BK, Vučak M, Mannapperuma C, Bailey MES, Jansson S, Hvidsten TR, Street NR. Leaf shape in Populus tremula is a complex, omnigenic trait. Ecol Evol 2020; 10:11922-11940. [PMID: 33209260 PMCID: PMC7663049 DOI: 10.1002/ece3.6691] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 06/26/2020] [Accepted: 07/08/2020] [Indexed: 01/10/2023] Open
Abstract
Leaf shape is a defining feature of how we recognize and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing genome-wide association study (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we generated RNA-Seq data that we used to perform gene co-expression network analyses from a developmental series, which is publicly available within the PlantGenIE resource. We additionally used existing gene expression measurements across the population to analyze GWAS candidate genes in the context of a population-wide co-expression network and to identify genes that were differentially expressed between groups of individuals with contrasting leaf shapes. These data were integrated with expression GWAS (eQTL) results to define a set of candidate genes associated with leaf shape variation. Our results identified no clear adaptive link to leaf shape variation and indicate that leaf shape traits are genetically complex, likely determined by numerous small-effect variations in gene expression. Genes associated with shape variation were peripheral within the population-wide co-expression network, were not highly connected within the leaf development co-expression network, and exhibited signatures of relaxed selection. As such, our results are consistent with the omnigenic model.
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Affiliation(s)
- Niklas Mähler
- Department of Plant PhysiologyUmeå Plant Science CentreUmeå UniversityUmeåSweden
| | - Bastian Schiffthaler
- Department of Plant PhysiologyUmeå Plant Science CentreUmeå UniversityUmeåSweden
| | - Kathryn M. Robinson
- Department of Plant PhysiologyUmeå Plant Science CentreUmeå UniversityUmeåSweden
| | | | - Matej Vučak
- School of Life SciencesCollege of Medical, Veterinary and Life SciencesUniversity of GlasgowGlasgowScotland
| | - Chanaka Mannapperuma
- Department of Plant PhysiologyUmeå Plant Science CentreUmeå UniversityUmeåSweden
| | - Mark E. S. Bailey
- School of Life SciencesCollege of Medical, Veterinary and Life SciencesUniversity of GlasgowGlasgowScotland
| | - Stefan Jansson
- Department of Plant PhysiologyUmeå Plant Science CentreUmeå UniversityUmeåSweden
| | - Torgeir R. Hvidsten
- Faculty of Chemistry, Biotechnology and Food ScienceNorwegian University of Life SciencesÅsNorway
| | - Nathaniel R. Street
- Department of Plant PhysiologyUmeå Plant Science CentreUmeå UniversityUmeåSweden
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Fair BJ, Blake LE, Sarkar A, Pavlovic BJ, Cuevas C, Gilad Y. Gene expression variability in human and chimpanzee populations share common determinants. eLife 2020; 9:59929. [PMID: 33084571 PMCID: PMC7644215 DOI: 10.7554/elife.59929] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 10/20/2020] [Indexed: 12/20/2022] Open
Abstract
Inter-individual variation in gene expression has been shown to be heritable and is often associated with differences in disease susceptibility between individuals. Many studies focused on mapping associations between genetic and gene regulatory variation, yet much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative analysis of gene expression variability and expression quantitative trait loci (eQTLs) in humans and chimpanzees, using gene expression data from primary heart samples. We found that expression variability in both species is often determined by non-genetic sources, such as cell-type heterogeneity. However, we also provide evidence that inter-individual variation in gene regulation can be genetically controlled, and that the degree of such variability is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of orthologous genes associated with eQTLs in both species. We conclude that gene expression variability in humans and chimpanzees often evolves under similar evolutionary pressures.
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Affiliation(s)
| | - Lauren E Blake
- Department of Human Genetics, University of Chicago, Chicago, United States
| | - Abhishek Sarkar
- Department of Human Genetics, University of Chicago, Chicago, United States
| | - Bryan J Pavlovic
- Department of Neurology, University of California, San Francisco (UCSF), San Francisco, United States
| | - Claudia Cuevas
- Department of Human Genetics, University of Chicago, Chicago, United States
| | - Yoav Gilad
- Department of Medicine, University of Chicago, Chicago, United States.,Department of Human Genetics, University of Chicago, Chicago, United States
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A systems genetics approach reveals environment-dependent associations between SNPs, protein coexpression, and drought-related traits in maize. Genome Res 2020; 30:1593-1604. [PMID: 33060172 PMCID: PMC7605251 DOI: 10.1101/gr.255224.119] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 09/24/2020] [Indexed: 12/21/2022]
Abstract
The effect of drought on maize yield is of particular concern in the context of climate change and human population growth. However, the complexity of drought-response mechanisms makes the design of new drought-tolerant varieties a difficult task that would greatly benefit from a better understanding of the genotype–phenotype relationship. To provide novel insight into this relationship, we applied a systems genetics approach integrating high-throughput phenotypic, proteomic, and genomic data acquired from 254 maize hybrids grown under two watering conditions. Using association genetics and protein coexpression analysis, we detected more than 22,000 pQTLs across the two conditions and confidently identified 15 loci with potential pleiotropic effects on the proteome. We showed that even mild water deficit induced a profound remodeling of the proteome, which affected the structure of the protein coexpression network, and a reprogramming of the genetic control of the abundance of many proteins, including those involved in stress response. Colocalizations between pQTLs and QTLs for ecophysiological traits, found mostly in the water deficit condition, indicated that this reprogramming may also affect the phenotypic level. Finally, we identified several candidate genes that are potentially responsible for both the coexpression of stress response proteins and the variations of ecophysiological traits under water deficit. Taken together, our findings provide novel insights into the molecular mechanisms of drought tolerance and suggest some pathways for further research and breeding.
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39
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Satokangas I, Martin SH, Helanterä H, Saramäki J, Kulmuni J. Multi-locus interactions and the build-up of reproductive isolation. Philos Trans R Soc Lond B Biol Sci 2020; 375:20190543. [PMID: 32654649 PMCID: PMC7423273 DOI: 10.1098/rstb.2019.0543] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/26/2020] [Indexed: 12/15/2022] Open
Abstract
All genes interact with other genes, and their additive effects and epistatic interactions affect an organism's phenotype and fitness. Recent theoretical and empirical work has advanced our understanding of the role of multi-locus interactions in speciation. However, relating different models to one another and to empirical observations is challenging. This review focuses on multi-locus interactions that lead to reproductive isolation (RI) through reduced hybrid fitness. We first review theoretical approaches and show how recent work incorporating a mechanistic understanding of multi-locus interactions recapitulates earlier models, but also makes novel predictions concerning the build-up of RI. These include high variance in the build-up rate of RI among taxa, the emergence of strong incompatibilities producing localized barriers to introgression, and an effect of population size on the build-up of RI. We then review recent experimental approaches to detect multi-locus interactions underlying RI using genomic data. We argue that future studies would benefit from overlapping methods like ancestry disequilibrium scans, genome scans of differentiation and analyses of hybrid gene expression. Finally, we highlight a need for further overlap between theoretical and empirical work, and approaches that predict what kind of patterns multi-locus interactions resulting in incompatibilities will leave in genome-wide polymorphism data. This article is part of the theme issue 'Towards the completion of speciation: the evolution of reproductive isolation beyond the first barriers'.
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Affiliation(s)
- I. Satokangas
- Organismal & Evolutionary Biology Research Programme, University of Helsinki, Viikinkaari 1, PO Box 65, 00014 Helsinki, Finland
| | - S. H. Martin
- Institute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Edinburgh EH9 3FL, UK
| | - H. Helanterä
- Ecology and Genetics research unit, University of Oulu, PO Box 3000, 90014 Oulu, Finland
| | - J. Saramäki
- Department of Computer Science, Aalto University, PO Box 11000, 00076 Aalto, Espoo, Finland
| | - J. Kulmuni
- Organismal & Evolutionary Biology Research Programme, University of Helsinki, Viikinkaari 1, PO Box 65, 00014 Helsinki, Finland
- Tvärminne Zoological Station, University of Helsinki, J. A. Palménin tie 260, 10900 Hanko, Finland
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Balmant KM, Noble JD, C Alves F, Dervinis C, Conde D, Schmidt HW, Vazquez AI, Barbazuk WB, Campos GDL, Resende MFR, Kirst M. Xylem systems genetics analysis reveals a key regulator of lignin biosynthesis in Populus deltoides. Genome Res 2020; 30:1131-1143. [PMID: 32817237 PMCID: PMC7462072 DOI: 10.1101/gr.261438.120] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 07/13/2020] [Indexed: 02/01/2023]
Abstract
Despite the growing resources and tools for high-throughput characterization and analysis of genomic information, the discovery of the genetic elements that regulate complex traits remains a challenge. Systems genetics is an emerging field that aims to understand the flow of biological information that underlies complex traits from genotype to phenotype. In this study, we used a systems genetics approach to identify and evaluate regulators of the lignin biosynthesis pathway in Populus deltoides by combining genome, transcriptome, and phenotype data from a population of 268 unrelated individuals of P. deltoides The discovery of lignin regulators began with the quantitative genetic analysis of the xylem transcriptome and resulted in the detection of 6706 and 4628 significant local- and distant-eQTL associations, respectively. Among the locally regulated genes, we identified the R2R3-MYB transcription factor MYB125 (Potri.003G114100) as a putative trans-regulator of the majority of genes in the lignin biosynthesis pathway. The expression of MYB125 in a diverse population positively correlated with lignin content. Furthermore, overexpression of MYB125 in transgenic poplar resulted in increased lignin content, as well as altered expression of genes in the lignin biosynthesis pathway. Altogether, our findings indicate that MYB125 is involved in the control of a transcriptional coexpression network of lignin biosynthesis genes during secondary cell wall formation in P. deltoides.
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Affiliation(s)
- Kelly M Balmant
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32611, USA
| | - Jerald D Noble
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, Florida 32611, USA
| | - Filipe C Alves
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan 48824, USA
| | - Christopher Dervinis
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32611, USA
| | - Daniel Conde
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32611, USA
| | - Henry W Schmidt
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32611, USA
| | - Ana I Vazquez
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan 48824, USA
| | - William B Barbazuk
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, Florida 32611, USA
- Department of Biology, University of Florida, Gainesville, Florida 32611, USA
- Genetics Institute, University of Florida, Gainesville, Florida 32611, USA
| | - Gustavo de Los Campos
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan 48824, USA
- Statistics Department, Michigan State University, East Lansing, Michigan 48824, USA
| | - Marcio F R Resende
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, Florida 32611, USA
- Horticulture Sciences Department, University of Florida, Gainesville, Florida 32611, USA
| | - Matias Kirst
- School of Forest Resources and Conservation, University of Florida, Gainesville, Florida 32611, USA
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, Florida 32611, USA
- Genetics Institute, University of Florida, Gainesville, Florida 32611, USA
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Joshi SR, Jagtap S, Basu B, Deobagkar DD, Ghosh P. Construction, analysis and validation of co-expression network to understand stress adaptation in Deinococcus radiodurans R1. PLoS One 2020; 15:e0234721. [PMID: 32579573 PMCID: PMC7314050 DOI: 10.1371/journal.pone.0234721] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 06/02/2020] [Indexed: 01/12/2023] Open
Abstract
Systems biology based approaches have been effectively utilized to mine high throughput data. In the current study, we have performed system-level analysis for Deinococcus radiodurans R1 by constructing a gene co-expression network based on several microarray datasets available in the public domain. This condition-independent network was constructed by Weighted Gene Co-expression Network Analysis (WGCNA) with 61 microarray samples from 9 different experimental conditions. We identified 13 co-expressed modules, of which, 11 showed functional enrichments of one or more pathway/s or biological process. Comparative analysis of differentially expressed genes and proteins from radiation and desiccation stress studies with our co-expressed modules revealed the association of cyan with radiation response. Interestingly, two modules viz darkgreen and tan was associated with radiation as well as desiccation stress responses. The functional analysis of these modules showed enrichment of pathways important for adaptation of radiation or desiccation stress. To decipher the regulatory roles of these stress responsive modules, we identified transcription factors (TFs) and then calculated a Biweight mid correlation between modules hub gene and the identified TFs. We obtained 7 TFs for radiation and desiccation responsive modules. The expressions of 3 TFs were validated in response to gamma radiation using qRT-PCR. Along with the TFs, selected close neighbor genes of two important TFs, viz., DR_0997 (CRP) and DR_2287 (AsnC family transcriptional regulator) in the darkgreen module were also validated. In our network, among 13 hub genes associated with 13 modules, the functionality of 5 hub genes which are annotated as hypothetical proteins (hypothetical hub genes) in D. radiodurans genome has been revealed. Overall the study provided a better insight of pathways and regulators associated with relevant DNA damaging stress response in D. radiodurans.
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Affiliation(s)
- Suraj R. Joshi
- Bioinformatics Centre, Savitribai Phule Pune University, Pune, India
- Molecular Biology Research Laboratory, Department of Zoology, Savitribai Phule Pune University, Pune, India
- Molecular Biology Division, Bhabha Atomic Research Centre, Mumbai, India
| | - Surabhi Jagtap
- Bioinformatics Centre, Savitribai Phule Pune University, Pune, India
| | - Bhakti Basu
- Molecular Biology Division, Bhabha Atomic Research Centre, Mumbai, India
| | - Deepti D. Deobagkar
- Molecular Biology Research Laboratory, Department of Zoology, Savitribai Phule Pune University, Pune, India
| | - Payel Ghosh
- Bioinformatics Centre, Savitribai Phule Pune University, Pune, India
- * E-mail: ,
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42
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Identification of therapeutic targets from genetic association studies using hierarchical component analysis. BioData Min 2020; 13:6. [PMID: 32565911 PMCID: PMC7301559 DOI: 10.1186/s13040-020-00216-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 05/29/2020] [Indexed: 01/08/2023] Open
Abstract
Background Mapping disease-associated genetic variants to complex disease pathophysiology is a major challenge in translating findings from genome-wide association studies into novel therapeutic opportunities. The difficulty lies in our limited understanding of how phenotypic traits arise from non-coding genetic variants in highly organized biological systems with heterogeneous gene expression across cells and tissues. Results We present a novel strategy, called GWAS component analysis, for transferring disease associations from single-nucleotide polymorphisms to co-expression modules by stacking models trained using reference genome and tissue-specific gene expression data. Application of this method to genome-wide association studies of blood cell counts confirmed that it could detect gene sets enriched in expected cell types. In addition, coupling of our method with Bayesian networks enables GWAS components to be used to discover drug targets. Conclusions We tested genome-wide associations of four disease phenotypes, including age-related macular degeneration, Crohn’s disease, ulcerative colitis and rheumatoid arthritis, and demonstrated the proposed method could select more functional genes than S-PrediXcan, the previous single-step model for predicting gene-level associations from SNP-level associations.
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Chateigner A, Lesage-Descauses MC, Rogier O, Jorge V, Leplé JC, Brunaud V, Roux CPL, Soubigou-Taconnat L, Martin-Magniette ML, Sanchez L, Segura V. Gene expression predictions and networks in natural populations supports the omnigenic theory. BMC Genomics 2020; 21:416. [PMID: 32571208 PMCID: PMC7310122 DOI: 10.1186/s12864-020-06809-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 06/08/2020] [Indexed: 02/03/2023] Open
Abstract
Background Recent literature on the differential role of genes within networks distinguishes core from peripheral genes. If previous works have shown contrasting features between them, whether such categorization matters for phenotype prediction remains to be studied. Results We measured 17 phenotypic traits for 241 cloned genotypes from a Populus nigra collection, covering growth, phenology, chemical and physical properties. We also sequenced RNA for each genotype and built co-expression networks to define core and peripheral genes. We found that cores were more differentiated between populations than peripherals while being less variable, suggesting that they have been constrained through potentially divergent selection. We also showed that while cores were overrepresented in a subset of genes statistically selected for their capacity to predict the phenotypes (by Boruta algorithm), they did not systematically predict better than peripherals or even random genes. Conclusion Our work is the first attempt to assess the importance of co-expression network connectivity in phenotype prediction. While highly connected core genes appear to be important, they do not bear enough information to systematically predict better quantitative traits than other gene sets.
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Affiliation(s)
| | | | | | | | | | - Véronique Brunaud
- Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Sud, Université d'Evry, Université Paris-Saclay, Gif sur Yvette, France.,Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Diderot, Sorbonne Paris-Cité, Gif sur Yvette, France
| | - Christine Paysant-Le Roux
- Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Sud, Université d'Evry, Université Paris-Saclay, Gif sur Yvette, France.,Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Diderot, Sorbonne Paris-Cité, Gif sur Yvette, France
| | - Ludivine Soubigou-Taconnat
- Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Sud, Université d'Evry, Université Paris-Saclay, Gif sur Yvette, France.,Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Diderot, Sorbonne Paris-Cité, Gif sur Yvette, France
| | - Marie-Laure Martin-Magniette
- Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Sud, Université d'Evry, Université Paris-Saclay, Gif sur Yvette, France.,Institute of Plant Sciences Paris-Saclay (IPS2), CNRS, INRAE, Université Paris-Diderot, Sorbonne Paris-Cité, Gif sur Yvette, France.,MIA-Paris, AgroParisTech, INRAE, Paris, France
| | | | - Vincent Segura
- BioForA, INRAE, ONF, Orléans, France. .,AGAP, Université Montpellier, CIRAD, INRAE, Montpellier SupAgro, Montpellier, France.
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44
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Noble JD, Balmant KM, Dervinis C, de los Campos G, Resende MFR, Kirst M, Barbazuk WB. The Genetic Regulation of Alternative Splicing in Populus deltoides. FRONTIERS IN PLANT SCIENCE 2020; 11:590. [PMID: 32582229 PMCID: PMC7291814 DOI: 10.3389/fpls.2020.00590] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 04/20/2020] [Indexed: 06/11/2023]
Abstract
Alternative splicing (AS) is a mechanism of regulation of the proteome via enabling the production of multiple mRNAs from a single gene. To date, the dynamics of AS and its effects on the protein sequences of individuals in a large and genetically unrelated population of trees have not been investigated. Here we describe the diversity of AS events within a previously genotyped population of 268 individuals of Populus deltoides and their putative downstream functional effects. Using a robust bioinformatics pipeline, the AS events and resulting transcript isoforms were discovered and quantified for each individual in the population. Analysis of the AS revealed that, as expected, most AS isoforms are conserved. However, we also identified a substantial collection of new, unannotated splice junctions and transcript isoforms. Heritability estimates for the expression of transcript isoforms showed that approximately half of the isoforms are heritable. The genetic regulators of these AS isoforms and splice junction usage were then identified using a genome-wide association analysis. The expression of AS isoforms was predominately cis regulated while splice junction usage was generally regulated in trans. Additionally, we identified 696 genes encoding alternatively spliced isoforms that changed putative protein domains relative to the longest protein coding isoform of the gene, and 859 genes exhibiting this same phenomenon relative to the most highly expressed isoform. Finally, we found that 748 genes gained or lost micro-RNA binding sites relative to the longest protein coding isoform of a given gene, while 940 gained or lost micro-RNA binding sites relative to the most highly expressed isoform. These results indicate that a significant fraction of AS events are genetically regulated and that this isoform usage can result in protein domain architecture changes.
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Affiliation(s)
- Jerald D. Noble
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, FL, United States
| | - Kelly M. Balmant
- School of Forest Resources and Conservation, University of Florida, Gainesville, FL, United States
| | - Christopher Dervinis
- School of Forest Resources and Conservation, University of Florida, Gainesville, FL, United States
| | - Gustavo de los Campos
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, United States
- Department of Statistics and Probability, Michigan State University, East Lansing, MI, United States
| | - Márcio F. R. Resende
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, FL, United States
- Department of Horticultural Science, University of Florida, Gainesville, FL, United States
| | - Matias Kirst
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, FL, United States
- School of Forest Resources and Conservation, University of Florida, Gainesville, FL, United States
- Genetics Institute, University of Florida, Gainesville, FL, United States
| | - William Brad Barbazuk
- Plant Molecular and Cellular Biology Graduate Program, University of Florida, Gainesville, FL, United States
- Genetics Institute, University of Florida, Gainesville, FL, United States
- Department of Biology, University of Florida, Gainesville, FL, United States
- Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, United States
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45
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Josephs EB, Lee YW, Wood CW, Schoen DJ, Wright SI, Stinchcombe JR. The Evolutionary Forces Shaping Cis- and Trans-Regulation of Gene Expression within a Population of Outcrossing Plants. Mol Biol Evol 2020; 37:2386-2393. [DOI: 10.1093/molbev/msaa102] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Abstract
Understanding the persistence of genetic variation within populations has long been a goal of evolutionary biology. One promising route toward achieving this goal is using population genetic approaches to describe how selection acts on the loci associated with trait variation. Gene expression provides a model trait for addressing the challenge of the maintenance of variation because it can be measured genome-wide without information about how gene expression affects traits. Previous work has shown that loci affecting the expression of nearby genes (local or cis-eQTLs) are under negative selection, but we lack a clear understanding of the selective forces acting on variants that affect the expression of genes in trans. Here, we identify loci that affect gene expression in trans using genomic and transcriptomic data from one population of the obligately outcrossing plant, Capsella grandiflora. The allele frequencies of trans-eQTLs are consistent with stronger negative selection acting on trans-eQTLs than cis-eQTLs, and stronger negative selection acting on trans-eQTLs associated with the expression of multiple genes. However, despite this general pattern, we still observe the presence of a trans-eQTL at intermediate frequency that affects the expression of a large number of genes in the same coexpression module. Overall, our work highlights the different selective pressures shaping variation in cis- and trans-regulation.
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Affiliation(s)
- Emily B Josephs
- Department of Plant Biology, Michigan State University, East Lansing, MI
| | | | - Corlett W Wood
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA
| | - Daniel J Schoen
- Department of Biology, McGill University, Montreal, QC, Canada
| | - Stephen I Wright
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
| | - John R Stinchcombe
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
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46
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Roberts WR, Roalson EH. Co-expression clustering across flower development identifies modules for diverse floral forms in Achimenes (Gesneriaceae). PeerJ 2020; 8:e8778. [PMID: 32201652 PMCID: PMC7071821 DOI: 10.7717/peerj.8778] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 02/21/2020] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Genetic pathways involved with flower color and shape are thought to play an important role in the development of flowers associated with different pollination syndromes, such as those associated with bee, butterfly, or hummingbird pollination. Because pollination syndromes are complex traits that are orchestrated by multiple genes and pathways, the gene regulatory networks have not been explored. Gene co-expression networks provide a systems level approach to identify important contributors to floral diversification. METHODS RNA-sequencing was used to assay gene expression across two stages of flower development (an early bud and an intermediate stage) in 10 species of Achimenes (Gesneriaceae). Two stage-specific co-expression networks were created from 9,503 orthologs and analyzed to identify module hubs and the network periphery. Module association with bee, butterfly, and hummingbird pollination syndromes was tested using phylogenetic mixed models. The relationship between network connectivity and evolutionary rates (d N/d S) was tested using linear models. RESULTS Networks contained 65 and 62 modules that were largely preserved between developmental stages and contained few stage-specific modules. Over a third of the modules in both networks were associated with flower color, shape, and pollination syndrome. Within these modules, several hub nodes were identified that related to the production of anthocyanin and carotenoid pigments and the development of flower shape. Evolutionary rates were decreased in highly connected genes and elevated in peripheral genes. DISCUSSION This study aids in the understanding of the genetic architecture and network properties underlying the development of floral form and provides valuable candidate modules and genes for future studies.
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Affiliation(s)
- Wade R. Roberts
- School of Biological Sciences, Washington State University, Pullman, WA, USA
- Biological Sciences, University of Arkansas, Fayetteville, AR, USA
| | - Eric H. Roalson
- School of Biological Sciences, Washington State University, Pullman, WA, USA
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47
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Friedman DA, York RA, Hilliard AT, Gordon DM. Gene expression variation in the brains of harvester ant foragers is associated with collective behavior. Commun Biol 2020; 3:100. [PMID: 32139795 PMCID: PMC7057964 DOI: 10.1038/s42003-020-0813-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 02/10/2020] [Indexed: 01/10/2023] Open
Abstract
Natural selection on collective behavior acts on variation among colonies in behavior that is associated with reproductive success. In the red harvester ant (Pogonomyrmex barbatus), variation among colonies in the collective regulation of foraging in response to humidity is associated with colony reproductive success. We used RNA-seq to examine gene expression in the brains of foragers in a natural setting. We find that colonies differ in the expression of neurophysiologically-relevant genes in forager brains, and a fraction of these gene expression differences are associated with two colony traits: sensitivity of foraging activity to humidity, and forager brain dopamine to serotonin ratio. Loci that were correlated with colony behavioral differences were enriched in neurotransmitter receptor signaling & metabolic functions, tended to be more central to coexpression networks, and are evolving under higher protein-coding sequence constraint. Natural selection may shape colony foraging behavior through variation in gene expression.
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Affiliation(s)
| | | | | | - Deborah M Gordon
- Stanford University, Department of Biology, Stanford, CA, 94305, USA.
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48
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Hämälä T, Gorton AJ, Moeller DA, Tiffin P. Pleiotropy facilitates local adaptation to distant optima in common ragweed (Ambrosia artemisiifolia). PLoS Genet 2020; 16:e1008707. [PMID: 32210431 PMCID: PMC7135370 DOI: 10.1371/journal.pgen.1008707] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 04/06/2020] [Accepted: 03/05/2020] [Indexed: 12/23/2022] Open
Abstract
Pleiotropy, the control of multiple phenotypes by a single locus, is expected to slow the rate of adaptation by increasing the chance that beneficial alleles also have deleterious effects. However, a prediction arising from classical theory of quantitative trait evolution states that pleiotropic alleles may have a selective advantage when phenotypes are distant from their selective optima. We examine the role of pleiotropy in regulating adaptive differentiation among populations of common ragweed (Ambrosia artemisiifolia); a species that has recently expanded its North American range due to human-mediated habitat change. We employ a phenotype-free approach by using connectivity in gene networks as a proxy for pleiotropy. First, we identify loci bearing footprints of local adaptation, and then use genotype-expression mapping and co-expression networks to infer the connectivity of the genes. Our results indicate that the putatively adaptive loci are highly pleiotropic, as they are more likely than expected to affect the expression of other genes, and they reside in central positions within the gene networks. We propose that the conditionally advantageous alleles at these loci avoid the cost of pleiotropy by having large phenotypic effects that are beneficial when populations are far from their selective optima. We further use evolutionary simulations to show that these patterns are in agreement with a model where populations face novel selective pressures, as expected during a range expansion. Overall, our results suggest that highly connected genes may be targets of positive selection during environmental change, even though they likely experience strong purifying selection in stable selective environments.
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Affiliation(s)
- Tuomas Hämälä
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Amanda J. Gorton
- Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, United States of America
| | - David A. Moeller
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Peter Tiffin
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, Minnesota, United States of America
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49
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Hämälä T, Guiltinan MJ, Marden JH, Maximova SN, dePamphilis CW, Tiffin P. Gene Expression Modularity Reveals Footprints of Polygenic Adaptation in Theobroma cacao. Mol Biol Evol 2020; 37:110-123. [PMID: 31501906 DOI: 10.1093/molbev/msz206] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Separating footprints of adaptation from demography is challenging. When selection has acted on a single locus with major effect, this issue can be alleviated through signatures left by selective sweeps. However, as adaptation is often driven by small allele frequency shifts at many loci, studies focusing on single genes are able to identify only a small portion of genomic variants responsible for adaptation. In face of this challenge, we utilize coexpression information to search for signals of polygenetic adaptation in Theobroma cacao, a tropical tree species that is the source of chocolate. Using transcriptomics and a weighted correlation network analysis, we group genes with similar expression patterns into functional modules. We then ask whether modules enriched for specific biological processes exhibit cumulative effects of differential selection in the form of high FST and dXY between populations. Indeed, modules putatively involved in protein modification, flowering, and water transport show signs of polygenic adaptation even though individual genes that are members of those groups do not bear strong signatures of selection. Modeling of demography, background selection, and the effects of genomic features reveal that these patterns are unlikely to arise by chance. We also find that specific modules are enriched for signals of strong or relaxed purifying selection, with one module bearing signs of adaptive differentiation and an excess of deleterious mutations. Our results provide insight into polygenic adaptation and contribute to understanding of population structure, demographic history, and genome evolution in T. cacao.
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Affiliation(s)
- Tuomas Hämälä
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, MN
| | - Mark J Guiltinan
- Department of Plant Sciences, The Pennsylvania State University, University Park, PA.,Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA
| | - James H Marden
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA.,Department of Biology, The Pennsylvania State University, University Park, PA
| | - Siela N Maximova
- Department of Plant Sciences, The Pennsylvania State University, University Park, PA.,Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA
| | - Claude W dePamphilis
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA.,Department of Biology, The Pennsylvania State University, University Park, PA
| | - Peter Tiffin
- Department of Plant and Microbial Biology, University of Minnesota, St. Paul, MN
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50
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Foria S, Copetti D, Eisenmann B, Magris G, Vidotto M, Scalabrin S, Testolin R, Cipriani G, Wiedemann-Merdinoglu S, Bogs J, Di Gaspero G, Morgante M. Gene duplication and transposition of mobile elements drive evolution of the Rpv3 resistance locus in grapevine. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 99:895-909. [PMID: 31571285 DOI: 10.1111/tpj.14370] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 02/19/2019] [Accepted: 03/19/2019] [Indexed: 05/17/2023]
Abstract
A wild grape haplotype (Rpv3-1) confers resistance to Plasmopara viticola. We mapped the causal factor for resistance to an interval containing a TIR-NB-LRR (TNL) gene pair that originated 1.6-2.6 million years ago by a tandem segmental duplication. Transient coexpression of the TNL pair in Vitis vinifera leaves activated pathogen-induced necrosis and reduced sporulation compared with control leaves. Even though transcripts of the TNL pair from the wild haplotype appear to be partially subject to nonsense-mediated mRNA decay, mature mRNA levels in a homozygous resistant genotype were individually higher than the mRNA trace levels observed for the orthologous single-copy TNL in sensitive genotypes. Allelic expression imbalance in a resistant heterozygote confirmed that cis-acting regulatory variation promotes expression in the wild haplotype. The movement of transposable elements had a major impact on the generation of haplotype diversity, altering the DNA context around similar TNL coding sequences and the GC-content in their proximal 5'-intergenic regions. The wild and domesticated haplotypes also diverged in conserved single-copy intergenic DNA, but the highest divergence was observed in intraspecific and not in interspecific comparisons. In this case, introgression breeding did not transgress the genetic boundaries of the domesticated species, because haplotypes present in modern varieties sometimes predate speciation events between wild and cultivated species.
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Affiliation(s)
- Serena Foria
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
| | - Dario Copetti
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
- Istituto di Genomica Applicata, via Jacopo Linussio 51, 33100, Udine, Italy
- Institute of Agricultural Sciences, ETH Zürich, Universitätstrasse 2, 8092, Zürich, Switzerland
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, 8057, Zürich, Switzerland
| | - Birgit Eisenmann
- State Education and Research Center of Viticulture, Horticulture and Rural Development, Breitenweg 71, 67435, Neustadt an der Weinstraße, Germany
- Centre for Organismal Studies Heidelberg, University of Heidelberg, 69120, Heidelberg, Germany
| | - Gabriele Magris
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
- Istituto di Genomica Applicata, via Jacopo Linussio 51, 33100, Udine, Italy
| | - Michele Vidotto
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
| | - Simone Scalabrin
- Istituto di Genomica Applicata, via Jacopo Linussio 51, 33100, Udine, Italy
| | - Raffaele Testolin
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
| | - Guido Cipriani
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
| | | | - Jochen Bogs
- State Education and Research Center of Viticulture, Horticulture and Rural Development, Breitenweg 71, 67435, Neustadt an der Weinstraße, Germany
- Technische Hochschule Bingen, 55411, Bingen am Rhein, Germany
| | | | - Michele Morgante
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, via delle scienze 208, 33100, Udine, Italy
- Istituto di Genomica Applicata, via Jacopo Linussio 51, 33100, Udine, Italy
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