1
|
Abley K, Goswami R, Locke JCW. Bet-hedging and variability in plant development: seed germination and beyond. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230048. [PMID: 38432313 PMCID: PMC10909506 DOI: 10.1098/rstb.2023.0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/28/2023] [Indexed: 03/05/2024] Open
Abstract
When future conditions are unpredictable, bet-hedging strategies can be advantageous. This can involve isogenic individuals producing different phenotypes, under the same environmental conditions. Ecological studies provide evidence that variability in seed germination time has been selected for as a bet-hedging strategy. We demonstrate how variability in germination time found in Arabidopsis could function as a bet-hedging strategy in the face of unpredictable lethal stresses. Despite a body of knowledge on how the degree of seed dormancy versus germination is controlled, relatively little is known about how differences between isogenic seeds in a batch are generated. We review proposed mechanisms for generating variability in germination time and the current limitations and new possibilities for testing the model predictions. We then look beyond germination to the role of variability in seedling and adult plant growth and review new technologies for quantification of noisy gene expression dynamics. We discuss evidence for phenotypic variability in plant traits beyond germination being under genetic control and propose that variability in stress response gene expression could function as a bet-hedging strategy. We discuss open questions about how noisy gene expression could lead to between-plant heterogeneity in gene expression and phenotypes. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.
Collapse
Affiliation(s)
- Katie Abley
- The Sainsbury Laboratory, University of Cambridge, Cambridge, Cambridgeshire CB2 1LR, UK
| | - Rituparna Goswami
- The Sainsbury Laboratory, University of Cambridge, Cambridge, Cambridgeshire CB2 1LR, UK
| | - James C. W. Locke
- The Sainsbury Laboratory, University of Cambridge, Cambridge, Cambridgeshire CB2 1LR, UK
| |
Collapse
|
2
|
Zhang X, Bell JT. Detecting genetic effects on phenotype variability to capture gene-by-environment interactions: a systematic method comparison. G3 (BETHESDA, MD.) 2024; 14:jkae022. [PMID: 38289865 PMCID: PMC10989912 DOI: 10.1093/g3journal/jkae022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/16/2024] [Accepted: 01/19/2024] [Indexed: 02/01/2024]
Abstract
Genetically associated phenotypic variability has been widely observed across organisms and traits, including in humans. Both gene-gene and gene-environment interactions can lead to an increase in genetically associated phenotypic variability. Therefore, detecting the underlying genetic variants, or variance Quantitative Trait Loci (vQTLs), can provide novel insights into complex traits. Established approaches to detect vQTLs apply different methodologies from variance-only approaches to mean-variance joint tests, but a comprehensive comparison of these methods is lacking. Here, we review available methods to detect vQTLs in humans, carry out a simulation study to assess their performance under different biological scenarios of gene-environment interactions, and apply the optimal approaches for vQTL identification to gene expression data. Overall, with a minor allele frequency (MAF) of less than 0.2, the squared residual value linear model (SVLM) and the deviation regression model (DRM) are optimal when the data follow normal and non-normal distributions, respectively. In addition, the Brown-Forsythe (BF) test is one of the optimal methods when the MAF is 0.2 or larger, irrespective of phenotype distribution. Additionally, a larger sample size and more balanced sample distribution in different exposure categories increase the power of BF, SVLM, and DRM. Our results highlight vQTL detection methods that perform optimally under realistic simulation settings and show that their relative performance depends on the phenotype distribution, allele frequency, sample size, and the type of exposure in the interaction model underlying the vQTL.
Collapse
Affiliation(s)
- Xiaopu Zhang
- Department of Twin Research and Genetic Epidemiology, King's College London, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, St Thomas’ Hospital, Westminster Bridge Road, London SE1 7EH, UK
| |
Collapse
|
3
|
de Jager N, Shukla V, Koprivova A, Lyčka M, Bilalli L, You Y, Zeier J, Kopriva S, Ristova D. Traits linked to natural variation of sulfur content in Arabidopsis thaliana. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:1036-1050. [PMID: 37831920 PMCID: PMC10837017 DOI: 10.1093/jxb/erad401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 10/12/2023] [Indexed: 10/15/2023]
Abstract
Sulfur (S) is an essential mineral nutrient for plant growth and development; it is important for primary and specialized plant metabolites that are crucial for biotic and abiotic interactions. Foliar S content varies up to 6-fold under a controlled environment, suggesting an adaptive value under certain natural environmental conditions. However, a major quantitative regulator of S content in Arabidopsis thaliana has not been identified yet, pointing to the existence of either additional genetic factors controlling sulfate/S content or of many minor quantitative regulators. Here, we use overlapping information of two separate ionomics studies to select groups of accessions with low, mid, and high foliar S content. We quantify series of metabolites, including anions (sulfate, phosphate, and nitrate), thiols (cysteine and glutathione), and seven glucosinolates, gene expression of 20 genes, sulfate uptake, and three biotic traits. Our results suggest that S content is tightly connected with sulfate uptake, the concentration of sulfate and phosphate anions, and glucosinolate and glutathione synthesis. Additionally, our results indicate that the growth of pathogenic bacteria is enhanced in the A. thaliana accessions containing higher S in their leaves, suggesting a complex regulation between S homeostasis, primary and secondary metabolism, and biotic pressures.
Collapse
Affiliation(s)
- Nicholas de Jager
- Institute for Plant Sciences, Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, D-50674 Cologne, Germany
| | - Varsa Shukla
- Institute for Plant Sciences, Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, D-50674 Cologne, Germany
| | - Anna Koprivova
- Institute for Plant Sciences, Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, D-50674 Cologne, Germany
| | - Martin Lyčka
- Mendel Centre for Plant Genomics and Proteomics, Central European Institute of Technology (CEITEC), Masaryk University, 625 00 Brno, Czech Republic
- National Centre for Biomolecular Research, Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
| | - Lorina Bilalli
- Institute for Plant Sciences, Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, D-50674 Cologne, Germany
| | - Yanrong You
- Institute for Molecular Ecophysiology of Plants, Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich Heine University, Universitätsstraße 1, D-40225 Düsseldorf, Germany
| | - Jürgen Zeier
- Institute for Molecular Ecophysiology of Plants, Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich Heine University, Universitätsstraße 1, D-40225 Düsseldorf, Germany
| | - Stanislav Kopriva
- Institute for Plant Sciences, Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, D-50674 Cologne, Germany
| | - Daniela Ristova
- Institute for Plant Sciences, Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne, D-50674 Cologne, Germany
| |
Collapse
|
4
|
Alexandre CM, Bubb KL, Schultz KM, Lempe J, Cuperus JT, Queitsch C. LTP2 hypomorphs show genotype-by-environment interaction in early seedling traits in Arabidopsis thaliana. THE NEW PHYTOLOGIST 2024; 241:253-266. [PMID: 37865885 PMCID: PMC10843042 DOI: 10.1111/nph.19334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 09/26/2023] [Indexed: 10/23/2023]
Abstract
Isogenic individuals can display seemingly stochastic phenotypic differences, limiting the accuracy of genotype-to-phenotype predictions. The extent of this phenotypic variation depends in part on genetic background, raising questions about the genes involved in controlling stochastic phenotypic variation. Focusing on early seedling traits in Arabidopsis thaliana, we found that hypomorphs of the cuticle-related gene LIPID TRANSFER PROTEIN 2 (LTP2) greatly increased variation in seedling phenotypes, including hypocotyl length, gravitropism and cuticle permeability. Many ltp2 hypocotyls were significantly shorter than wild-type hypocotyls while others resembled the wild-type. Differences in epidermal properties and gene expression between ltp2 seedlings with long and short hypocotyls suggest a loss of cuticle integrity as the primary determinant of the observed phenotypic variation. We identified environmental conditions that reveal or mask the increased variation in ltp2 hypomorphs and found that increased expression of its closest paralog LTP1 is necessary for ltp2 phenotypes. Our results illustrate how decreased expression of a single gene can generate starkly increased phenotypic variation in isogenic individuals in response to an environmental challenge.
Collapse
Affiliation(s)
| | - Kerry L Bubb
- Department of Genome Sciences, University of Washington, Seattle WA 98195, USA
| | - Karla M Schultz
- Department of Genome Sciences, University of Washington, Seattle WA 98195, USA
| | - Janne Lempe
- Julius Kühn Institute (JKI) - Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Fruit Crops, Dresden, Germany 1099
| | - Josh T Cuperus
- Department of Genome Sciences, University of Washington, Seattle WA 98195, USA
| | - Christine Queitsch
- Department of Genome Sciences, University of Washington, Seattle WA 98195, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA 98195, USA
| |
Collapse
|
5
|
Alexandre CM, Bubb KL, Schultz KM, Lempe J, Cuperus JT, Queitsch C. LTP2 hypomorphs show genotype-by-environment interaction in early seedling traits in Arabidopsis thaliana. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.11.540469. [PMID: 37214854 PMCID: PMC10197655 DOI: 10.1101/2023.05.11.540469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Isogenic individuals can display seemingly stochastic phenotypic differences, limiting the accuracy of genotype-to-phenotype predictions. The extent of this phenotypic variation depends in part on genetic background, raising questions about the genes involved in controlling stochastic phenotypic variation. Focusing on early seedling traits in Arabidopsis thaliana, we found that hypomorphs of the cuticle-related gene LTP2 greatly increased variation in seedling phenotypes, including hypocotyl length, gravitropism and cuticle permeability. Many ltp2 hypocotyls were significantly shorter than wild-type hypocotyls while others resembled the wild type. Differences in epidermal properties and gene expression between ltp2 seedlings with long and short hypocotyls suggest a loss of cuticle integrity as the primary determinant of the observed phenotypic variation. We identified environmental conditions that reveal or mask the increased variation in ltp2 hypomorphs, and found that increased expression of its closest paralog LTP1 is necessary for ltp2 phenotypes. Our results illustrate how decreased expression of a single gene can generate starkly increased phenotypic variation in isogenic individuals in response to an environmental challenge.
Collapse
Affiliation(s)
| | - Kerry L Bubb
- Department of Genome Sciences, University of Washington, Seattle WA 98195, USA
| | - Karla M Schultz
- Department of Genome Sciences, University of Washington, Seattle WA 98195, USA
| | - Janne Lempe
- Julius Kühn Institute (JKI) - Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Fruit Crops, Dresden, Germany
| | - Josh T Cuperus
- Department of Genome Sciences, University of Washington, Seattle WA 98195, USA
| | - Christine Queitsch
- Department of Genome Sciences, University of Washington, Seattle WA 98195, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA 98195, USA
| |
Collapse
|
6
|
Alseekh S, Karakas E, Zhu F, Wijesingha Ahchige M, Fernie AR. Plant biochemical genetics in the multiomics era. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:4293-4307. [PMID: 37170864 PMCID: PMC10433942 DOI: 10.1093/jxb/erad177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 05/09/2023] [Indexed: 05/13/2023]
Abstract
Our understanding of plant biology has been revolutionized by modern genetics and biochemistry. However, biochemical genetics can be traced back to the foundation of Mendelian genetics; indeed, one of Mendel's milestone discoveries of seven characteristics of pea plants later came to be ascribed to a mutation in a starch branching enzyme. Here, we review both current and historical strategies for the elucidation of plant metabolic pathways and the genes that encode their component enzymes and regulators. We use this historical review to discuss a range of classical genetic phenomena including epistasis, canalization, and heterosis as viewed through the lens of contemporary high-throughput data obtained via the array of approaches currently adopted in multiomics studies.
Collapse
Affiliation(s)
- Saleh Alseekh
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
- Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria
| | - Esra Karakas
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Feng Zhu
- National R&D Center for Citrus Preservation, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, 430070 Wuhan, China
| | | | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
- Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria
| |
Collapse
|
7
|
Steward KF, Refai M, Dyer WE, Copié V, Lachowiec J, Bothner B. Acute stress reduces population-level metabolic and proteomic variation. BMC Bioinformatics 2023; 24:87. [PMID: 36882728 PMCID: PMC9993721 DOI: 10.1186/s12859-023-05185-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 02/14/2023] [Indexed: 03/09/2023] Open
Abstract
BACKGROUND Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. RESULTS We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. CONCLUSIONS RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.
Collapse
Affiliation(s)
- Katherine F Steward
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT, 59717, USA
| | - Mohammed Refai
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT, 59717, USA
| | - William E Dyer
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT, 59717, USA.,Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, USA
| | - Valérie Copié
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT, 59717, USA.,Thermal Biology Institute, Montana State University, Bozeman, USA
| | - Jennifer Lachowiec
- Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, USA
| | - Brian Bothner
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT, 59717, USA. .,Thermal Biology Institute, Montana State University, Bozeman, USA.
| |
Collapse
|
8
|
Baek EJ, Jung HU, Chung JY, Jung HI, Kwon SY, Lim JE, Kim HK, Kang JO, Oh B. The effect of heteroscedasticity on the prediction efficiency of genome-wide polygenic score for body mass index. Front Genet 2022; 13:1025568. [PMID: 36419825 PMCID: PMC9676478 DOI: 10.3389/fgene.2022.1025568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 10/25/2022] [Indexed: 11/09/2022] Open
Abstract
Globally, more than 1.9 billion adults are overweight. Thus, obesity is a serious public health issue. Moreover, obesity is a major risk factor for diabetes mellitus, coronary heart disease, and cardiovascular disease. Recently, GWAS examining obesity and body mass index (BMI) have increasingly unveiled many aspects of the genetic architecture of obesity and BMI. Information on genome-wide genetic variants has been used to estimate the genome-wide polygenic score (GPS) for a personalized prediction of obesity. However, the prediction power of GPS is affected by various factors, including the unequal variance in the distribution of a phenotype, known as heteroscedasticity. Here, we calculated a GPS for BMI using LDpred2, which was based on the BMI GWAS summary statistics from a European meta-analysis. Then, we tested the GPS in 354,761 European samples from the UK Biobank and found an effective prediction power of the GPS on BMI. To study a change in the variance of BMI, we investigated the heteroscedasticity of BMI across the GPS via graphical and statistical methods. We also studied the homoscedastic samples for BMI compared to the heteroscedastic sample, randomly selecting samples with various standard deviations of BMI residuals. Further, we examined the effect of the genetic interaction of GPS with environment (GPS×E) on the heteroscedasticity of BMI. We observed the changing variance (i.e., heteroscedasticity) of BMI along the GPS. The heteroscedasticity of BMI was confirmed by both the Breusch-Pagan test and the Score test. Compared to the heteroscedastic sample, the homoscedastic samples from small standard deviation of BMI residuals showed a decreased heteroscedasticity and an improved prediction accuracy, suggesting a quantitatively negative correlation between the phenotypic heteroscedasticity and the prediction accuracy of GPS. To further test the effects of the GPS×E on heteroscedasticity, first we tested the genetic interactions of the GPS with 21 environments and found 8 significant GPS×E interactions on BMI. However, the heteroscedasticity of BMI was not ameliorated after adjusting for the GPS×E interactions. Taken together, our findings suggest that the heteroscedasticity of BMI exists along the GPS and is not affected by the GPS×E interaction.
Collapse
Affiliation(s)
- Eun Ju Baek
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, South Korea
| | - Hae-Un Jung
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, South Korea
| | - Ju Yeon Chung
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, South Korea
| | - Hye In Jung
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, South Korea
| | - Shin Young Kwon
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, South Korea
| | - Ji Eun Lim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, South Korea
| | - Han Kyul Kim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, South Korea
| | - Ji-One Kang
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, South Korea
- *Correspondence: Ji-One Kang, ; Bermseok Oh,
| | - Bermseok Oh
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, South Korea
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, South Korea
- *Correspondence: Ji-One Kang, ; Bermseok Oh,
| |
Collapse
|
9
|
Turnbull LB, Button-Simons KA, Agbayani N, Ferdig MT. Sources of transcription variation in Plasmodium falciparum. J Genet Genomics 2022; 49:965-974. [PMID: 35395422 DOI: 10.1016/j.jgg.2022.03.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 03/21/2022] [Accepted: 03/22/2022] [Indexed: 12/20/2022]
Abstract
Variation in transcript abundance can contribute to both short-term environmental response and long-term evolutionary adaptation. Most studies are designed to assess differences in mean transcription levels and do not consider other potentially important and confounding sources of transcriptional variation. Detailed quantification of variation sources will improve our ability to detect and identify the mechanisms that contribute to genome-wide transcription changes that underpin adaptive responses. To quantify innate levels of expression variation, we measured mRNA levels for more than 5000 genes in the malaria parasite, Plasmodium falciparum, among clones derived from two parasite strains across biologically and experimentally replicated batches. Using a mixed effects model, we partitioned the total variation among four sources - between strain, within strain, environmental batch effects, and stochastic noise. We found 646 genes with significant variation attributable to at least one of these sources. These genes were categorized by their predominant variation source and further examined using gene ontology enrichment analysis to associate function with each source of variation. Genes with environmental batch effect and within strain transcript variation may contribute to phenotypic plasticity, while genes with between strain variation may contribute to adaptive responses and processes that lead to parasite strain-specific survival under varied conditions.
Collapse
Affiliation(s)
- Lindsey B Turnbull
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Katrina A Button-Simons
- Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Nestor Agbayani
- Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA; Rush School of Medicine, Chicago, IL, 60612, USA
| | - Michael T Ferdig
- Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, 46556, USA.
| |
Collapse
|
10
|
Sell-Kubiak E, Knol EF, Lopes M. Evaluation of the phenotypic and genomic background of variability based on litter size of Large White pigs. Genet Sel Evol 2022; 54:1. [PMID: 34979897 PMCID: PMC8722267 DOI: 10.1186/s12711-021-00692-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 12/15/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The genetic background of trait variability has captured the interest of ecologists and animal breeders because the genes that control it could be involved in buffering various environmental effects. Phenotypic variability of a given trait can be assessed by studying the heterogeneity of the residual variance, and the quantitative trait loci (QTL) that are involved in the control of this variability are described as variance QTL (vQTL). This study focuses on litter size (total number born, TNB) and its variability in a Large White pig population. The variability of TNB was evaluated either using a simple method, i.e. analysis of the log-transformed variance of residuals (LnVar), or the more complex double hierarchical generalized linear model (DHGLM). We also performed a single-SNP (single nucleotide polymorphism) genome-wide association study (GWAS). To our knowledge, this is only the second study that reports vQTL for litter size in pigs and the first one that shows GWAS results when using two methods to evaluate variability of TNB: LnVar and DHGLM. RESULTS Based on LnVar, three candidate vQTL regions were detected, on Sus scrofa chromosomes (SSC) 1, 7, and 18, which comprised 18 SNPs. Based on the DHGLM, three candidate vQTL regions were detected, i.e. two on SSC7 and one on SSC11, which comprised 32 SNPs. Only one candidate vQTL region overlapped between the two methods, on SSC7, which also contained the most significant SNP. Within this vQTL region, two candidate genes were identified, ADGRF1, which is involved in neurodevelopment of the brain, and ADGRF5, which is involved in the function of the respiratory system and in vascularization. The correlation between estimated breeding values based on the two methods was 0.86. Three-fold cross-validation indicated that DHGLM yielded EBV that were much more accurate and had better prediction of missing observations than LnVar. CONCLUSIONS The results indicated that the LnVar and DHGLM methods resulted in genetically different traits. Based on their validation, we recommend the use of DHGLM over the simpler method of log-transformed variance of residuals. These conclusions can be useful for future studies on the evaluation of the variability of any trait in any species.
Collapse
Affiliation(s)
- Ewa Sell-Kubiak
- Department of Genetics and Animal Breeding, Poznan University of Life Sciences, Poznań, Poland.
| | - Egbert F Knol
- Topigs Norsvin Research Centre, Beuningen, The Netherlands
| | - Marcos Lopes
- Topigs Norsvin Research Centre, Beuningen, The Netherlands.,Topigs Norsvin, Curitiba, Brazil
| |
Collapse
|
11
|
Abley K, Formosa-Jordan P, Tavares H, Chan EY, Afsharinafar M, Leyser O, Locke JC. An ABA-GA bistable switch can account for natural variation in the variability of Arabidopsis seed germination time. eLife 2021; 10:59485. [PMID: 34059197 PMCID: PMC8169117 DOI: 10.7554/elife.59485] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 03/01/2021] [Indexed: 12/31/2022] Open
Abstract
Genetically identical plants growing in the same conditions can display heterogeneous phenotypes. Here we use Arabidopsis seed germination time as a model system to examine phenotypic variability and its underlying mechanisms. We show extensive variation in seed germination time variability between Arabidopsis accessions and use a multiparent recombinant inbred population to identify two genetic loci involved in this trait. Both loci include genes implicated in modulating abscisic acid (ABA) sensitivity. Mutually antagonistic regulation between ABA, which represses germination, and gibberellic acid (GA), which promotes germination, underlies the decision to germinate and can act as a bistable switch. A simple stochastic model of the ABA-GA network shows that modulating ABA sensitivity can generate the range of germination time distributions we observe experimentally. We validate the model by testing its predictions on the effects of exogenous hormone addition. Our work provides a foundation for understanding the mechanism and functional role of phenotypic variability in germination time.
Collapse
Affiliation(s)
- Katie Abley
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Pau Formosa-Jordan
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Hugo Tavares
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Emily Yt Chan
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Mana Afsharinafar
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Ottoline Leyser
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - James Cw Locke
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
12
|
Autran D, Bassel GW, Chae E, Ezer D, Ferjani A, Fleck C, Hamant O, Hartmann FP, Jiao Y, Johnston IG, Kwiatkowska D, Lim BL, Mahönen AP, Morris RJ, Mulder BM, Nakayama N, Sozzani R, Strader LC, ten Tusscher K, Ueda M, Wolf S. What is quantitative plant biology? QUANTITATIVE PLANT BIOLOGY 2021; 2:e10. [PMID: 37077212 PMCID: PMC10095877 DOI: 10.1017/qpb.2021.8] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 04/07/2021] [Accepted: 04/07/2021] [Indexed: 05/03/2023]
Abstract
Quantitative plant biology is an interdisciplinary field that builds on a long history of biomathematics and biophysics. Today, thanks to high spatiotemporal resolution tools and computational modelling, it sets a new standard in plant science. Acquired data, whether molecular, geometric or mechanical, are quantified, statistically assessed and integrated at multiple scales and across fields. They feed testable predictions that, in turn, guide further experimental tests. Quantitative features such as variability, noise, robustness, delays or feedback loops are included to account for the inner dynamics of plants and their interactions with the environment. Here, we present the main features of this ongoing revolution, through new questions around signalling networks, tissue topology, shape plasticity, biomechanics, bioenergetics, ecology and engineering. In the end, quantitative plant biology allows us to question and better understand our interactions with plants. In turn, this field opens the door to transdisciplinary projects with the society, notably through citizen science.
Collapse
Affiliation(s)
- Daphné Autran
- DIADE, University of Montpellier, IRD, CIRAD, Montpellier, France
| | - George W. Bassel
- School of Life Sciences, University of Warwick, Coventry, United Kingdom
| | - Eunyoung Chae
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Daphne Ezer
- The Alan Turing Institute, London, United Kingdom
- Department of Statistics, University of Warwick, Coventry, United Kingdom
- Department of Biology, University of York, York, United Kingdom
| | - Ali Ferjani
- Department of Biology, Tokyo Gakugei University, Tokyo, Japan
| | - Christian Fleck
- Freiburg Center for Data Analysis and Modeling (FDM), University of Freiburg, Breisgau, Germany
| | - Olivier Hamant
- Laboratoire de Reproduction et Développement des Plantes, École normale supérieure (ENS) de Lyon, Université Claude Bernard Lyon (UCBL), Lyon, France
- Institut national de recherche pour l’agriculture, l’alimentation et l’environnement (INRAE), CNRS, Université de Lyon, Lyon, France
- Author for correspondence: O. Hamant and A. P. Mahönen, E-mail: ,
| | | | - Yuling Jiao
- State Key Laboratory of Plant Genomics and National Center for Plant Gene Research (Beijing), Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | | | - Dorota Kwiatkowska
- Institute of Biology, Biotechnology and Environment Protection, Faculty of Natural Sciences, University of Silesia in Katowice, Katowice, Poland
| | - Boon L. Lim
- School of Biological Sciences, University of Hong Kong, Hong Kong, China
| | - Ari Pekka Mahönen
- Institute of Biotechnology, HiLIFE, University of Helsinki, Helsinki, Finland
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
- Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland
| | - Richard J. Morris
- Computational and Systems Biology, John Innes Centre, Norwich, United Kingdom
| | - Bela M. Mulder
- Department of Living Matter, Institute AMOLF, Amsterdam, The Netherlands
| | - Naomi Nakayama
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Ross Sozzani
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North CarolinaUSA
| | - Lucia C. Strader
- Department of Biology, Duke University, Durham, North Carolina, USA
- NSF Science and Technology Center for Engineering Mechanobiology, Department of Biology, Washington University in St. Louis, St. Louis, MissouriUSA
| | - Kirsten ten Tusscher
- Theoretical Biology, Department of Biology, Utrecht University, Utrecht, The Netherlands
| | - Minako Ueda
- Graduate School of Life Sciences, Tohoku University, Sendai, Japan
| | - Sebastian Wolf
- Centre for Organismal Studies (COS) Heidelberg, Heidelberg University, Heidelberg, Germany
| |
Collapse
|
13
|
Cortijo S, Bhattarai M, Locke JCW, Ahnert SE. Co-expression Networks From Gene Expression Variability Between Genetically Identical Seedlings Can Reveal Novel Regulatory Relationships. FRONTIERS IN PLANT SCIENCE 2020; 11:599464. [PMID: 33384705 PMCID: PMC7770228 DOI: 10.3389/fpls.2020.599464] [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: 08/27/2020] [Accepted: 11/05/2020] [Indexed: 06/12/2023]
Abstract
Co-expression networks are a powerful tool to understand gene regulation. They have been used to identify new regulation and function of genes involved in plant development and their response to the environment. Up to now, co-expression networks have been inferred using transcriptomes generated on plants experiencing genetic or environmental perturbation, or from expression time series. We propose a new approach by showing that co-expression networks can be constructed in the absence of genetic and environmental perturbation, for plants at the same developmental stage. For this, we used transcriptomes that were generated from genetically identical individual plants that were grown under the same conditions and for the same amount of time. Twelve time points were used to cover the 24-h light/dark cycle. We used variability in gene expression between individual plants of the same time point to infer a co-expression network. We show that this network is biologically relevant and use it to suggest new gene functions and to identify new targets for the transcriptional regulators GI, PIF4, and PRR5. Moreover, we find different co-regulation in this network based on changes in expression between individual plants, compared to the usual approach requiring environmental perturbation. Our work shows that gene co-expression networks can be identified using variability in gene expression between individual plants, without the need for genetic or environmental perturbations. It will allow further exploration of gene regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild.
Collapse
Affiliation(s)
- Sandra Cortijo
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
- UMR5004 Biochimie et Physiologie Moléculaire des Plantes, Univ Montpellier, CNRS, INRAE, Institut Agro, Montpellier, France
| | - Marcel Bhattarai
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - James C. W. Locke
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - Sebastian E. Ahnert
- The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
- Theory of Condensed Matter, Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom
- Department of Chemical Engineering and Biotechnology, Philippa Fawcett Drive, University of Cambridge, Cambridge, United Kingdom
- The Alan Turing Institute, British Library, London, United Kingdom
| |
Collapse
|
14
|
Cruz DF, De Meyer S, Ampe J, Sprenger H, Herman D, Van Hautegem T, De Block J, Inzé D, Nelissen H, Maere S. Using single-plant-omics in the field to link maize genes to functions and phenotypes. Mol Syst Biol 2020; 16:e9667. [PMID: 33346944 PMCID: PMC7751767 DOI: 10.15252/msb.20209667] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 10/29/2020] [Accepted: 11/17/2020] [Indexed: 12/14/2022] Open
Abstract
Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.
Collapse
Affiliation(s)
- Daniel Felipe Cruz
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Sam De Meyer
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Joke Ampe
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Heike Sprenger
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Dorota Herman
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Tom Van Hautegem
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Jolien De Block
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Dirk Inzé
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Hilde Nelissen
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| | - Steven Maere
- Department of Plant Biotechnology and BioinformaticsGhent UniversityGhentBelgium
- VIB Center for Plant Systems BiologyGhentBelgium
| |
Collapse
|
15
|
Sterken MG, Bevers RPJ, Volkers RJM, Riksen JAG, Kammenga JE, Snoek BL. Dissecting the eQTL Micro-Architecture in Caenorhabditis elegans. Front Genet 2020; 11:501376. [PMID: 33240309 PMCID: PMC7670075 DOI: 10.3389/fgene.2020.501376] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Accepted: 10/13/2020] [Indexed: 01/11/2023] Open
Abstract
The study of expression quantitative trait loci (eQTL) using natural variation in inbred populations has yielded detailed information about the transcriptional regulation of complex traits. Studies on eQTL using recombinant inbred lines (RILs) led to insights on cis and trans regulatory loci of transcript abundance. However, determining the underlying causal polymorphic genes or variants is difficult, but ultimately essential for the understanding of regulatory networks of complex traits. This requires insight into whether associated loci are single eQTL or a combination of closely linked eQTL, and how this QTL micro-architecture depends on the environment. We addressed these questions by testing for independent replication of previously mapped eQTL in Caenorhabditis elegans using new data from introgression lines (ILs). Both populations indicate that the overall heritability of gene expression, number, and position of eQTL differed among environments. Across environments we were able to replicate 70% of the cis- and 40% of the trans-eQTL using the ILs. Testing eight different simulation models, we suggest that additive effects explain up to 60-93% of RIL/IL heritability for all three environments. Closely linked eQTL explained up to 40% of RIL/IL heritability in the control environment whereas only 7% in the heat-stress and recovery environments. In conclusion, we show that reproducibility of eQTL was higher for cis vs. trans eQTL and that the environment affects the eQTL micro-architecture.
Collapse
Affiliation(s)
- Mark G. Sterken
- Laboratory of Nematology, Wageningen University & Research, Wageningen, Netherlands
| | - Roel P. J. Bevers
- Laboratory of Nematology, Wageningen University & Research, Wageningen, Netherlands
| | - Rita J. M. Volkers
- Laboratory of Nematology, Wageningen University & Research, Wageningen, Netherlands
| | - Joost A. G. Riksen
- Laboratory of Nematology, Wageningen University & Research, Wageningen, Netherlands
| | - Jan E. Kammenga
- Laboratory of Nematology, Wageningen University & Research, Wageningen, Netherlands
| | - Basten L. Snoek
- Laboratory of Nematology, Wageningen University & Research, Wageningen, Netherlands
- Theoretical Biology & Bioinformatics, Utrecht University, Utrecht, Netherlands
| |
Collapse
|
16
|
Cortijo S, Locke JCW. Does Gene Expression Noise Play a Functional Role in Plants? TRENDS IN PLANT SCIENCE 2020; 25:1041-1051. [PMID: 32467064 DOI: 10.1016/j.tplants.2020.04.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 04/22/2020] [Accepted: 04/28/2020] [Indexed: 05/20/2023]
Abstract
Gene expression in individual cells can be surprisingly noisy. In unicellular organisms this noise can be functional; for example, by allowing a subfraction of the population to prepare for environmental stress. The role of gene expression noise in multicellular organisms has, however, remained unclear. In this review, we discuss how new techniques are revealing an unexpected level of variability in gene expression between and within genetically identical plants. We describe recent progress as well as speculate on the function of transcriptional noise as a mechanism for generating functional phenotypic diversity in plants.
Collapse
Affiliation(s)
- Sandra Cortijo
- Sainsbury Laboratory, University of Cambridge, Cambridge CB2 1LR, UK
| | - James C W Locke
- Sainsbury Laboratory, University of Cambridge, Cambridge CB2 1LR, UK.
| |
Collapse
|
17
|
Okamoto S, Negishi K, Toyama Y, Ushijima T, Morohashi K. Leaf Trichome Distribution Pattern in Arabidopsis Reveals Gene Expression Variation Associated with Environmental Adaptation. PLANTS 2020; 9:plants9070909. [PMID: 32709158 PMCID: PMC7412270 DOI: 10.3390/plants9070909] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/12/2020] [Accepted: 07/15/2020] [Indexed: 01/28/2023]
Abstract
Gene expression varies stochastically even in both heterogenous and homogeneous cell populations. This variation is not simply useless noise; rather, it is important for many biological processes. Unicellular organisms or cultured cell lines are useful for analyzing the variation in gene expression between cells; however, owing to technical challenges, the biological relevance of this variation in multicellular organisms such as higher plants remain unclear. Here, we addressed the biological relevance of this variation between cells by examining the genetic basis of trichome distribution patterns in Arabidopsis thaliana. The distribution pattern of a trichome on a leaf is stochastic and can be mathematically represented using Turing’s reaction-diffusion (RD) model. We analyzed simulations based on the RD model and found that the variability in the trichome distribution pattern increased with the increase in stochastic variation in a particular gene expression. Moreover, differences in heat-dependent variability of the trichome distribution pattern between the accessions showed a strong correlation with environmental factors to which each accession was adapted. Taken together, we successfully visualized variations in gene expression by quantifying the variability in the Arabidopsis trichome distribution pattern. Thus, our data provide evidence for the biological importance of variations in gene expression for environmental adaptation.
Collapse
Affiliation(s)
- Shotaro Okamoto
- Department of Applied Biological Science, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan; (S.O.); (K.N.); (Y.T.)
| | - Kohei Negishi
- Department of Applied Biological Science, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan; (S.O.); (K.N.); (Y.T.)
| | - Yuko Toyama
- Department of Applied Biological Science, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan; (S.O.); (K.N.); (Y.T.)
| | - Takeo Ushijima
- Department of Mathematics, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan;
| | - Kengo Morohashi
- Department of Applied Biological Science, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan; (S.O.); (K.N.); (Y.T.)
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA
- Correspondence: or ; Tel.: +1-614-407-6676
| |
Collapse
|
18
|
Beral A, Rincent R, Le Gouis J, Girousse C, Allard V. Wheat individual grain-size variance originates from crop development and from specific genetic determinism. PLoS One 2020; 15:e0230689. [PMID: 32214360 PMCID: PMC7098578 DOI: 10.1371/journal.pone.0230689] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 03/05/2020] [Indexed: 11/19/2022] Open
Abstract
Wheat grain yield is usually decomposed in the yield components: number of spikes / m2, number of grains / spike, number of grains / m2 and thousand kernel weight (TKW). These are correlated one with another due to yield component compensation. Under optimal conditions, the number of grains per m2 has been identified as the main determinant of yield. However, with increasing occurrences of post-flowering abiotic stress associated with climate change, TKW may become severely limiting and hence a target for breeding. TKW is usually studied at the plot scale as it represents the average mass of a grain. However, this view disregards the large intra-genotypic variance of individual grain mass and its effect on TKW. The aim of this study is to investigate the determinism of the variance of individual grain size. We measured yield components and individual grain size variances of two large genetic wheat panels grown in two environments. We also carried out a genome-wide association study using a dense SNPs array. We show that the variance of individual grain size partly originates from the pre-flowering components of grain yield; in particular it is driven by canopy structure via its negative correlation with the number of spikes per m2. But the variance of final grain size also has a specific genetic basis. The genome-wide analysis revealed the existence of QTL with strong effects on the variance of individual grain size, independently from the other yield components. Finally, our results reveal some interesting drivers for manipulating individual grain size variance either through canopy structure or through specific chromosomal regions.
Collapse
Affiliation(s)
- Aurore Beral
- UMR 1095 GDEC, INRAE, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Renaud Rincent
- UMR 1095 GDEC, INRAE, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Jacques Le Gouis
- UMR 1095 GDEC, INRAE, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Christine Girousse
- UMR 1095 GDEC, INRAE, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Vincent Allard
- UMR 1095 GDEC, INRAE, Université Clermont Auvergne, Clermont-Ferrand, France
| |
Collapse
|
19
|
Morgan MD, Patin E, Jagla B, Hasan M, Quintana-Murci L, Marioni JC. Quantitative genetic analysis deciphers the impact of cis and trans regulation on cell-to-cell variability in protein expression levels. PLoS Genet 2020; 16:e1008686. [PMID: 32168362 PMCID: PMC7094872 DOI: 10.1371/journal.pgen.1008686] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 03/25/2020] [Accepted: 02/19/2020] [Indexed: 11/19/2022] Open
Abstract
Identifying the factors that shape protein expression variability in complex multi-cellular organisms has primarily focused on promoter architecture and regulation of single-cell expression in cis. However, this targeted approach has to date been unable to identify major regulators of cell-to-cell gene expression variability in humans. To address this, we have combined single-cell protein expression measurements in the human immune system using flow cytometry with a quantitative genetics analysis. For the majority of proteins whose variability in expression has a heritable component, we find that genetic variants act in trans, with notably fewer variants acting in cis. Furthermore, we highlight using Mendelian Randomization that these variability-Quantitative Trait Loci might be driven by the cis regulation of upstream genes. This indicates that natural selection may balance the impact of gene regulation in cis with downstream impacts on expression variability in trans.
Collapse
Affiliation(s)
- Michael D. Morgan
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- Cancer Research UK–Cambridge Institute, Robinson Way, Cambridge, United Kingdom
| | - Etienne Patin
- Human Evolutionary Genetics Unit, Institut Pasteur, CNRS UMR2000, Paris, France
| | - Bernd Jagla
- Cytometry and Biomarkers UTechS, Institut Pasteur, Paris, France
- Hub Bioinformatique et Biostatisque, Départment de Biologie Computationalle—USR 3756 CNRS, Institut Pasteur, Paris, France
| | - Milena Hasan
- Cytometry and Biomarkers UTechS, Institut Pasteur, Paris, France
| | - Lluís Quintana-Murci
- Human Evolutionary Genetics Unit, Institut Pasteur, CNRS UMR2000, Paris, France
- Human Genomics and Evolution, Collège de France, Paris, France
| | - John C. Marioni
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
- Cancer Research UK–Cambridge Institute, Robinson Way, Cambridge, United Kingdom
- EMBL-EBI, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| |
Collapse
|
20
|
The strength and pattern of natural selection on gene expression in rice. Nature 2020; 578:572-576. [PMID: 32051590 DOI: 10.1038/s41586-020-1997-2] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 12/13/2019] [Indexed: 01/12/2023]
Abstract
Levels of gene expression underpin organismal phenotypes1,2, but the nature of selection that acts on gene expression and its role in adaptive evolution remain unknown1,2. Here we assayed gene expression in rice (Oryza sativa)3, and used phenotypic selection analysis to estimate the type and strength of selection on the levels of more than 15,000 transcripts4,5. Variation in most transcripts appears (nearly) neutral or under very weak stabilizing selection in wet paddy conditions (with median standardized selection differentials near zero), but selection is stronger under drought conditions. Overall, more transcripts are conditionally neutral (2.83%) than are antagonistically pleiotropic6 (0.04%), and transcripts that display lower levels of expression and stochastic noise7-9 and higher levels of plasticity9 are under stronger selection. Selection strength was further weakly negatively associated with levels of cis-regulation and network connectivity9. Our multivariate analysis suggests that selection acts on the expression of photosynthesis genes4,5, but that the efficacy of selection is genetically constrained under drought conditions10. Drought selected for earlier flowering11,12 and a higher expression of OsMADS18 (Os07g0605200), which encodes a MADS-box transcription factor and is a known regulator of early flowering13-marking this gene as a drought-escape gene11,12. The ability to estimate selection strengths provides insights into how selection can shape molecular traits at the core of gene action.
Collapse
|
21
|
Bruijning M, Metcalf CJE, Jongejans E, Ayroles JF. The Evolution of Variance Control. Trends Ecol Evol 2020; 35:22-33. [PMID: 31519463 PMCID: PMC7482585 DOI: 10.1016/j.tree.2019.08.005] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 08/08/2019] [Accepted: 08/12/2019] [Indexed: 12/12/2022]
Abstract
Genetically identical individuals can be phenotypically variable, even in constant environmental conditions. The ubiquity of this phenomenon, known as 'intra-genotypic variability', is increasingly evident and the relevant mechanistic underpinnings are beginning to be understood. In parallel, theory has delineated a number of formal expectations for contexts in which such a feature would be adaptive. Here, we review empirical evidence across biological systems and theoretical expectations, including nonlinear averaging and bet hedging. We synthesize existing results to illustrate the dependence of selection outcomes both on trait characteristics, features of environmental variability, and species' demographic context. We conclude by discussing ways to bridge the gap between empirical evidence of intra-genotypic variability, studies demonstrating its genetic component, and evidence that it is adaptive.
Collapse
Affiliation(s)
- Marjolein Bruijning
- Department of Animal Ecology and Physiology, Radboud University, 6500, GL, Nijmegen, The Netherlands; Department of Ecology and Evolutionary Biology, Princeton University, 08540 Princeton, NJ, USA
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, 08540 Princeton, NJ, USA
| | - Eelke Jongejans
- Department of Animal Ecology and Physiology, Radboud University, 6500, GL, Nijmegen, The Netherlands
| | - Julien F Ayroles
- Department of Ecology and Evolutionary Biology, Princeton University, 08540 Princeton, NJ, USA.
| |
Collapse
|
22
|
Duan R, Ning Y, Wang S, Lindsay BG, Carroll RJ, Chen Y. A fast score test for generalized mixture models. Biometrics 2019; 76:811-820. [PMID: 31863595 DOI: 10.1111/biom.13204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 11/15/2019] [Accepted: 12/04/2019] [Indexed: 11/30/2022]
Abstract
In biomedical studies, testing for homogeneity between two groups, where one group is modeled by mixture models, is often of great interest. This paper considers the semiparametric exponential family mixture model proposed by Hong et al. (2017) and studies the score test for homogeneity under this model. The score test is nonregular in the sense that nuisance parameters disappear under the null hypothesis. To address this difficulty, we propose a modification of the score test, so that the resulting test enjoys the Wilks phenomenon. In finite samples, we show that with fixed nuisance parameters the score test is locally most powerful. In large samples, we establish the asymptotic power functions under two types of local alternative hypotheses. Our simulation studies illustrate that the proposed score test is powerful and computationally fast. We apply the proposed score test to an UK ovarian cancer DNA methylation data for identification of differentially methylated CpG sites.
Collapse
Affiliation(s)
- Rui Duan
- Department of Biostatistics, Epidemiology, and Informatics, The University of Pennsylvania, Philadelphia, Pennsylvania
| | - Yang Ning
- Department of Statistical Science, Cornell University, Ithaca, New York
| | - Shuang Wang
- Department of Biostatistics, Columbia University, New York, New York
| | - Bruce G Lindsay
- Department of Statistics, Pennsylvania State University, State College, Pennsylvania
| | - Raymond J Carroll
- Department of Statistics, Texas A&M University, College Station, Texas
| | - Yong Chen
- Department of Biostatistics, Epidemiology, and Informatics, The University of Pennsylvania, Philadelphia, Pennsylvania
| |
Collapse
|
23
|
Ding X, Hu Y, Guo X, Guo X, Morgan I, He M. Possible Causes of Discordance in Refraction in Monozygotic Twins: Nearwork, Time Outdoors and Stochastic Variation. Invest Ophthalmol Vis Sci 2019; 59:5349-5354. [PMID: 30398626 DOI: 10.1167/iovs.18-24526] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Purpose To evaluate the impact of differences in nearwork and time spent outdoors on difference in refraction in monozygotic (MZ) twins. Methods Data on MZ twins aged 7 to 18 years from the Guangzhou Twin Eye Study were used in this analysis. A standard questionnaire was administered by personal interview to estimate time spent on nearwork and time spent outdoors. Spherical equivalent (SE) was measured by autorefraction under cycloplegia. The interaction between age and nearwork or time spent outdoors was also estimated. Results A total of 490 MZ twin pairs (233 male and 257 female) were eligible in this analysis, the mean age was 13.14 ± 2.49. In the mixed-effects model, nearwork difference was a risk factor of discordance in myopic SE (β = -0.11 diopter (D)/h, P = 0.009), the overall association between time outdoors difference and SE discordance was not significant (β = -0.89 (D)/h, P = 0.120) although an interaction between time spent outdoors difference and age was detected (β = 0.07 (D)/h, P = 0.002). Furthermore, difference in nearwork and time outdoors explained about 1.8% and 2.5% of the variation in SE discordance, respectively. Conclusions Given the very marked genetic similarity of MZ twins, and the small effects of known risk factors on SE discordance, we suggest that the SE discordance across MZ twins largely results from stochastic variations at the genomic or epigenetic levels, or from uncollected environmental factors.
Collapse
Affiliation(s)
- Xiaohu Ding
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Yin Hu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Xinxing Guo
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.,Dana Center of Preventive Ophthalmology, Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland, United States
| | - Xiaobo Guo
- Department of Statistics, School of Mathematics & Computational Science, Sun Yat-Sen University, Guangzhou, China
| | - Ian Morgan
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.,Research School of Biology, College of Medicine, Biology and Environment, Australia National University, Canberra, Australia
| | - Mingguang He
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.,Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia
| |
Collapse
|
24
|
Cortijo S, Aydin Z, Ahnert S, Locke JC. Widespread inter-individual gene expression variability in Arabidopsis thaliana. Mol Syst Biol 2019; 15:e8591. [PMID: 30679203 PMCID: PMC6346214 DOI: 10.15252/msb.20188591] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
A fundamental question in biology is how gene expression is regulated to give rise to a phenotype. However, transcriptional variability is rarely considered although it could influence the relationship between genotype and phenotype. It is known in unicellular organisms that gene expression is often noisy rather than uniform, and this has been proposed to be beneficial when environmental conditions are unpredictable. However, little is known about inter-individual transcriptional variability in multicellular organisms. Using transcriptomic approaches, we analysed gene expression variability between individual Arabidopsis thaliana plants growing in identical conditions over a 24-h time course. We identified hundreds of genes that exhibit high inter-individual variability and found that many are involved in environmental responses, with different classes of genes variable between the day and night. We also identified factors that might facilitate gene expression variability, such as gene length, the number of transcription factors regulating the genes and the chromatin environment. These results shed new light on the impact of transcriptional variability in gene expression regulation in plants.
Collapse
Affiliation(s)
- Sandra Cortijo
- The Sainsbury Laboratory, University of Cambridge, Cambridge, UK
| | - Zeynep Aydin
- The Sainsbury Laboratory, University of Cambridge, Cambridge, UK
| | - Sebastian Ahnert
- The Sainsbury Laboratory, University of Cambridge, Cambridge, UK
| | - James Cw Locke
- The Sainsbury Laboratory, University of Cambridge, Cambridge, UK
| |
Collapse
|
25
|
Serra L, Arnaud N, Selka F, Rechenmann C, Andrey P, Laufs P. Heterogeneity and its multiscale integration in plant morphogenesis. CURRENT OPINION IN PLANT BIOLOGY 2018; 46:18-24. [PMID: 30015106 DOI: 10.1016/j.pbi.2018.07.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 06/25/2018] [Accepted: 07/02/2018] [Indexed: 06/08/2023]
Abstract
Heterogeneity is observed at all levels in living organisms, but its role during the development of an individual is not well understood. Heterogeneity has either to be limited to ensure robust development or can be an actor of the biological processes leading to reproducible development. Here we review the sources of heterogeneity in plants, stress the interplay between noise in elementary processes and regulated biological mechanisms, and highlight how heterogeneity is integrated at multiple scales during plant morphogenesis.
Collapse
Affiliation(s)
- Léo Serra
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, 78000 Versailles, France
| | - Nicolas Arnaud
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, 78000 Versailles, France
| | - Faïçal Selka
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, 78000 Versailles, France
| | - Catherine Rechenmann
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, 78000 Versailles, France
| | - Philippe Andrey
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, 78000 Versailles, France
| | - Patrick Laufs
- Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, 78000 Versailles, France.
| |
Collapse
|
26
|
Lachowiec J, Mason GA, Schultz K, Queitsch C. Redundancy, Feedback, and Robustness in the Arabidopsis thaliana BZR/BEH Gene Family. Front Genet 2018; 9:523. [PMID: 30542366 PMCID: PMC6277886 DOI: 10.3389/fgene.2018.00523] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 10/17/2018] [Indexed: 11/19/2022] Open
Abstract
Organismal development is remarkably robust, tolerating stochastic errors to produce consistent, so-called canalized adult phenotypes. The mechanistic underpinnings of developmental robustness are poorly understood, but recent studies implicate certain features of genetic networks such as functional redundancy, connectivity, and feedback. Here, we examine the BZR/BEH gene family, whose function contributes to embryonic stem development in the plant Arabidopsis thaliana, to test current assumptions on functional redundancy and trait robustness. Our analyses of BZR/BEH gene mutants and mutant combinations revealed that functional redundancy among these gene family members is not necessary for trait robustness. Connectivity is another commonly cited determinant of robustness; however, we found no correlation between connectivity among gene family members or their connectivity with other transcription factors and effects on developmental robustness. Instead, our data suggest that BEH4, the earliest diverged family member, modulates developmental robustness. We present evidence indicating that regulatory cross-talk among gene family members is integrated by BEH4 to promote wild-type levels of developmental robustness. Further, the chaperone HSP90, a known determinant of developmental robustness, appears to act via BEH4 in maintaining robustness of embryonic stem length. In summary, we demonstrate that even among closely related transcription factors, trait robustness can arise through the activity of a single gene family member, challenging common assumptions about the molecular underpinnings of robustness.
Collapse
Affiliation(s)
- Jennifer Lachowiec
- Department of Genome Sciences, University of Washington, Seattle, WA, United States.,Molecular and Cellular Biology Program, University of Washington, Seattle, WA, United States
| | - G Alex Mason
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Karla Schultz
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Christine Queitsch
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| |
Collapse
|
27
|
Comparison of the Relative Potential for Epigenetic and Genetic Variation To Contribute to Trait Stability. G3-GENES GENOMES GENETICS 2018; 8:1733-1746. [PMID: 29563187 PMCID: PMC5940164 DOI: 10.1534/g3.118.200127] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
The theoretical ability of epigenetic variation to influence the heritable variation of complex traits is gaining traction in the study of adaptation. This theory posits that epigenetic marks can control adaptive phenotypes but the relative potential of epigenetic variation in comparison to genetic variation in these traits is not presently understood. To compare the potential of epigenetic and genetic variation in adaptive traits, we analyzed the influence of DNA methylation variation on the accumulation of chemical defense compounds glucosinolates from the order Brassicales. Several decades of work on glucosinolates has generated extensive knowledge about their synthesis, regulation, genetic variation and contribution to fitness establishing this pathway as a model pathway for complex adaptive traits. Using high-throughput phenotyping with a randomized block design of ddm1 derived Arabidopsis thaliana epigenetic Recombinant Inbred Lines, we measured the correlation between DNA methylation variation and mean glucosinolate variation and within line stochastic variation. Using this information, we identified epigenetic Quantitative Trait Loci that contained specific Differentially Methylated Regions associated with glucosinolate traits. This showed that variation in DNA methylation correlates both with levels and variance of glucosinolates and flowering time with trait-specific loci. By conducting a meta-analysis comparing the results to different genetically variable populations, we conclude that the influence of DNA methylation variation on these adaptive traits is much lower than the corresponding impact of standing genetic variation. As such, selective pressure on these traits should mainly affect standing genetic variation to lead to adaptation.
Collapse
|
28
|
Pesce CG, Zdraljevic S, Peria WJ, Bush A, Repetto MV, Rockwell D, Yu RC, Colman-Lerner A, Brent R. Single-cell profiling screen identifies microtubule-dependent reduction of variability in signaling. Mol Syst Biol 2018; 14:e7390. [PMID: 29618636 PMCID: PMC5884679 DOI: 10.15252/msb.20167390] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2016] [Revised: 01/25/2018] [Accepted: 02/06/2018] [Indexed: 01/01/2023] Open
Abstract
Populations of isogenic cells often respond coherently to signals, despite differences in protein abundance and cell state. Previously, we uncovered processes in the Saccharomyces cerevisiae pheromone response system (PRS) that reduced cell-to-cell variability in signal strength and cellular response. Here, we screened 1,141 non-essential genes to identify 50 "variability genes". Most had distinct, separable effects on strength and variability of the PRS, defining these quantities as genetically distinct "axes" of system behavior. Three genes affected cytoplasmic microtubule function: BIM1, GIM2, and GIM4 We used genetic and chemical perturbations to show that, without microtubules, PRS output is reduced but variability is unaffected, while, when microtubules are present but their function is perturbed, output is sometimes lowered, but its variability is always high. The increased variability caused by microtubule perturbations required the PRS MAP kinase Fus3 and a process at or upstream of Ste5, the membrane-localized scaffold to which Fus3 must bind to be activated. Visualization of Ste5 localization dynamics demonstrated that perturbing microtubules destabilized Ste5 at the membrane signaling site. The fact that such microtubule perturbations cause aberrant fate and polarity decisions in mammals suggests that microtubule-dependent signal stabilization might also operate throughout metazoans.
Collapse
Affiliation(s)
| | - Stefan Zdraljevic
- Department of Molecular Biosciences, Northwestern University, Evanston, IL, USA
| | | | - Alan Bush
- IFIBYNE-UBA-CONICET and Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - María Victoria Repetto
- IFIBYNE-UBA-CONICET and Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | | | | | - Alejandro Colman-Lerner
- IFIBYNE-UBA-CONICET and Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Roger Brent
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| |
Collapse
|
29
|
Conley D, Johnson R, Domingue B, Dawes C, Boardman J, Siegal M. A sibling method for identifying vQTLs. PLoS One 2018; 13:e0194541. [PMID: 29617452 PMCID: PMC5884517 DOI: 10.1371/journal.pone.0194541] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Accepted: 03/05/2018] [Indexed: 12/11/2022] Open
Abstract
The propensity of a trait to vary within a population may have evolutionary, ecological, or clinical significance. In the present study we deploy sibling models to offer a novel and unbiased way to ascertain loci associated with the extent to which phenotypes vary (variance-controlling quantitative trait loci, or vQTLs). Previous methods for vQTL-mapping either exclude genetically related individuals or treat genetic relatedness among individuals as a complicating factor addressed by adjusting estimates for non-independence in phenotypes. The present method uses genetic relatedness as a tool to obtain unbiased estimates of variance effects rather than as a nuisance. The family-based approach, which utilizes random variation between siblings in minor allele counts at a locus, also allows controls for parental genotype, mean effects, and non-linear (dominance) effects that may spuriously appear to generate variation. Simulations show that the approach performs equally well as two existing methods (squared Z-score and DGLM) in controlling type I error rates when there is no unobserved confounding, and performs significantly better than these methods in the presence of small degrees of confounding. Using height and BMI as empirical applications, we investigate SNPs that alter within-family variation in height and BMI, as well as pathways that appear to be enriched. One significant SNP for BMI variability, in the MAST4 gene, replicated. Pathway analysis revealed one gene set, encoding members of several signaling pathways related to gap junction function, which appears significantly enriched for associations with within-family height variation in both datasets (while not enriched in analysis of mean levels). We recommend approximating laboratory random assignment of genotype using family data and more careful attention to the possible conflation of mean and variance effects.
Collapse
Affiliation(s)
- Dalton Conley
- Department of Sociology, Princeton University, Princeton, NJ, United States of America
| | - Rebecca Johnson
- Department of Sociology, Princeton University, Princeton, NJ, United States of America
| | - Ben Domingue
- Graduate School of Education, Stanford University, Stanford, CA, United States of America
| | - Christopher Dawes
- Wilff Family Department of Politics, New York University, New York City, NY, United States of America
| | - Jason Boardman
- Institute for Behavioral Sciences, University of Colorado, Boulder, Boulder, CO, United States of America
| | - Mark Siegal
- Center for Genomics and Systems Biology, New York University, New York University, New York City, NY, United States of America
| |
Collapse
|
30
|
Yang E, Wang G, Yang J, Zhou B, Tian Y, Cai JJ. Epistasis and destabilizing mutations shape gene expression variability in humans via distinct modes of action. Hum Mol Genet 2018; 25:4911-4919. [PMID: 28171656 DOI: 10.1093/hmg/ddw314] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Revised: 08/19/2016] [Accepted: 09/12/2016] [Indexed: 11/14/2022] Open
Abstract
Increasing evidence shows that phenotypic variance is genetically determined, but the underlying mechanisms of genetic control over the variance remain obscure. Here, we conducted variance-association mapping analyses to identify expression variability QTLs (evQTLs), i.e. genomic loci associated with gene expression variance, in humans. We discovered that common genetic variants may contribute to increasing gene expression variance via two distinct modes of action—epistasis and destabilization. Specifically, epistasis explains a quarter of the identified evQTLs, of which the formation is attributed to the presence of ‘third-party’ eQTLs that influence the gene expression mean in a fraction, rather than the entire set, of sampled individuals. On the other hand, the destabilization model explains the other three-quarters of evQTLs, caused by mutations that disrupt the stability of the transcription process of genes. To show the destabilizing effect, we measured discordant gene expression between monozygotic twins, and estimated the stability of gene expression in single samples using repetitive qRT-PCR assays. The mutations that cause destabilizing evQTLs were found to be associated with more pronounced expression discordance between twin pairs and less stable gene expression in single samples. Together, our results suggest that common genetic variants work either interactively or independently to shape the variability of gene expression in humans. Our findings contribute to the understanding of the mechanisms of genetic control over phenotypic variance and may have implications for the development of variance-centred analytic methods for quantitative trait mapping.
Collapse
Affiliation(s)
- Ence Yang
- Department of Veterinary Integrative Biosciences.,Institute for Systems Biomedicine, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
| | - Gang Wang
- Department of Veterinary Integrative Biosciences
| | - Jizhou Yang
- Department of Veterinary Integrative Biosciences
| | - Beiyan Zhou
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA.,Department of Immunology, University of Connecticut Health Center, Farmington, CT, USA
| | - Yanan Tian
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA
| | - James J Cai
- Department of Veterinary Integrative Biosciences.,Interdisciplinary Program of Genetics, Texas A&M University, College Station, TX, USA
| |
Collapse
|
31
|
Katsanos D, Koneru SL, Mestek Boukhibar L, Gritti N, Ghose R, Appleford PJ, Doitsidou M, Woollard A, van Zon JS, Poole RJ, Barkoulas M. Stochastic loss and gain of symmetric divisions in the C. elegans epidermis perturbs robustness of stem cell number. PLoS Biol 2017; 15:e2002429. [PMID: 29108019 PMCID: PMC5690688 DOI: 10.1371/journal.pbio.2002429] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Revised: 11/16/2017] [Accepted: 10/20/2017] [Indexed: 11/19/2022] Open
Abstract
Biological systems are subject to inherent stochasticity. Nevertheless, development is remarkably robust, ensuring the consistency of key phenotypic traits such as correct cell numbers in a certain tissue. It is currently unclear which genes modulate phenotypic variability, what their relationship is to core components of developmental gene networks, and what is the developmental basis of variable phenotypes. Here, we start addressing these questions using the robust number of Caenorhabditis elegans epidermal stem cells, known as seam cells, as a readout. We employ genetics, cell lineage tracing, and single molecule imaging to show that mutations in lin-22, a Hes-related basic helix-loop-helix (bHLH) transcription factor, increase seam cell number variability. We show that the increase in phenotypic variability is due to stochastic conversion of normally symmetric cell divisions to asymmetric and vice versa during development, which affect the terminal seam cell number in opposing directions. We demonstrate that LIN-22 acts within the epidermal gene network to antagonise the Wnt signalling pathway. However, lin-22 mutants exhibit cell-to-cell variability in Wnt pathway activation, which correlates with and may drive phenotypic variability. Our study demonstrates the feasibility to study phenotypic trait variance in tractable model organisms using unbiased mutagenesis screens.
Collapse
Affiliation(s)
- Dimitris Katsanos
- Department of Life Sciences, Imperial College, London, United Kingdom
| | - Sneha L. Koneru
- Department of Life Sciences, Imperial College, London, United Kingdom
| | | | - Nicola Gritti
- Institute for Atomic and Molecular Physics (AMOLF), Amsterdam, The Netherlands
| | - Ritobrata Ghose
- Department of Life Sciences, Imperial College, London, United Kingdom
| | - Peter J. Appleford
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | - Maria Doitsidou
- Centre for Integrative Physiology, University of Edinburgh, Edinburgh, United Kingdom
| | - Alison Woollard
- Department of Biochemistry, University of Oxford, Oxford, United Kingdom
| | - Jeroen S. van Zon
- Institute for Atomic and Molecular Physics (AMOLF), Amsterdam, The Netherlands
| | - Richard J. Poole
- Department of Cell and Developmental Biology, University College London, London, United Kingdom
| | | |
Collapse
|
32
|
Alseekh S, Tong H, Scossa F, Brotman Y, Vigroux F, Tohge T, Ofner I, Zamir D, Nikoloski Z, Fernie AR. Canalization of Tomato Fruit Metabolism. THE PLANT CELL 2017; 29:2753-2765. [PMID: 29093214 PMCID: PMC5728129 DOI: 10.1105/tpc.17.00367] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Revised: 10/10/2017] [Accepted: 10/31/2017] [Indexed: 05/23/2023]
Abstract
To explore the genetic robustness (canalization) of metabolism, we examined the levels of fruit metabolites in multiple harvests of a tomato introgression line (IL) population. The IL partitions the whole genome of the wild species Solanum pennellii in the background of the cultivated tomato (Solanum lycopersicum). We identified several metabolite quantitative trait loci that reduce variability for both primary and secondary metabolites, which we named canalization metabolite quantitative trait loci (cmQTL). We validated nine cmQTL using an independent population of backcross inbred lines, derived from the same parents, which allows increased resolution in mapping the QTL previously identified in the ILs. These cmQTL showed little overlap with QTL for the metabolite levels themselves. Moreover, the intervals they mapped to harbored few metabolism-associated genes, suggesting that the canalization of metabolism is largely controlled by regulatory genes.
Collapse
Affiliation(s)
- Saleh Alseekh
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Hao Tong
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Federico Scossa
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
- Consiglio per la Ricerca in Agricoltura e l'analisi dell'Economia Agraria, 00134 Rome, Italy
| | - Yariv Brotman
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
- Department of Life Sciences, Ben Gurion University of the Negev, 653 Beersheva, Israel
| | - Florian Vigroux
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Takayuki Tohge
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Itai Ofner
- Faculty of Agriculture, The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture at the Hebrew University of Jerusalem, Rehovot 76100, Israel
| | - Dani Zamir
- Faculty of Agriculture, The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture at the Hebrew University of Jerusalem, Rehovot 76100, Israel
| | - Zoran Nikoloski
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| |
Collapse
|
33
|
Mendenhall A, Crane MM, Tedesco PM, Johnson TE, Brent R. Caenorhabditis elegans Genes Affecting Interindividual Variation in Life-span Biomarker Gene Expression. J Gerontol A Biol Sci Med Sci 2017; 72:1305-1310. [PMID: 28158434 DOI: 10.1093/gerona/glw349] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Accepted: 12/30/2016] [Indexed: 01/12/2023] Open
Abstract
Genetically identical organisms grown in homogenous environments differ in quantitative phenotypes. Differences in one such trait, expression of a single biomarker gene, can identify isogenic cells or organisms that later manifest different fates. For example, in isogenic populations of young adult Caenorhabditis elegans, differences in Green Fluorescent Protein (GFP) expressed from the hsp-16.2 promoter predict differences in life span. Thus, it is of interest to determine how interindividual differences in biomarker gene expression arise. Prior reports showed that the thermosensory neurons and insulin signaling systems controlled the magnitude of the heat shock response, including absolute expression of hsp-16.2. Here, we tested whether these regulatory signals might also influence variation in hsp-16.2 reporter expression. Genetic experiments showed that the action of AFD thermosensory neurons increases interindividual variation in biomarker expression. Further genetic experimentation showed the insulin signaling system acts to decrease interindividual variation in life-span biomarker expression; in other words, insulin signaling canalizes expression of the hsp-16.2-driven life-span biomarker. Our results show that specific signaling systems regulate not only expression level, but also the amount of interindividual expression variation for a life-span biomarker gene. They raise the possibility that manipulation of these systems might offer means to reduce heterogeneity in the aging process.
Collapse
Affiliation(s)
| | | | | | - Thomas E Johnson
- Institute for Behavioral Genetics.,Department of Integrative Physiology.,Biofrontiers Institute, University of Colorado, Boulder
| | - Roger Brent
- Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| |
Collapse
|
34
|
Fisher J, Bensal E, Zamir D. Bimodality of stable and plastic traits in plants. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2017; 130:1915-1926. [PMID: 28608227 DOI: 10.1007/s00122-017-2933-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2017] [Accepted: 05/30/2017] [Indexed: 06/07/2023]
Abstract
We discovered an unexpected mode of bimodal distribution of stable and plastic traits, which was consistent for homologous traits of 32 varieties of seven species both in well-irrigated fields and dry conditions. We challenged archived genetic mapping data for 36 fruit, seed, flower and yield traits in tomato and found an unexpected bimodal distribution in one measure of trait variability, the mean coefficient of variation, with some traits being consistently more variable than others. To determine the degree of conservation of this distribution among higher plants, we compared 18 homologous phenotypes, including yield and seed production, across different crop species grown in a common 'crop garden' experiment. The set included 32 varieties of tomato, eggplant, pepper, melon, watermelon, sunflower and maize. Estimates of canalization were obtained using a 'canalization replication' experimental design that generated multiple estimates of the coefficient of variation of traits, as well as their reaction norms in optimal and water-stressed field plots. A common pattern of bimodal distribution of stable and plastic traits was observed for all the varieties and for a wild weed (Solanum nigrum). We propose that canalization profiles of traits in a variety of taxa were ancestrally selected to maximize adaptation and reproductive success.
Collapse
Affiliation(s)
- Josef Fisher
- The Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, The Hebrew University of Jerusalem, PO Box 12, 76100, Rehovot, Israel
| | - Elad Bensal
- The Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, The Hebrew University of Jerusalem, PO Box 12, 76100, Rehovot, Israel
| | - Dani Zamir
- The Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, The Hebrew University of Jerusalem, PO Box 12, 76100, Rehovot, Israel.
| |
Collapse
|
35
|
Ran D, Daye ZJ. Gene expression variability and the analysis of large-scale RNA-seq studies with the MDSeq. Nucleic Acids Res 2017; 45:e127. [PMID: 28535263 PMCID: PMC5737414 DOI: 10.1093/nar/gkx456] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Revised: 04/10/2017] [Accepted: 05/19/2017] [Indexed: 12/21/2022] Open
Abstract
Rapidly decreasing cost of next-generation sequencing has led to the recent availability of large-scale RNA-seq data, that empowers the analysis of gene expression variability, in addition to gene expression means. In this paper, we present the MDSeq, based on the coefficient of dispersion, to provide robust and computationally efficient analysis of both gene expression means and variability on RNA-seq counts. The MDSeq utilizes a novel reparametrization of the negative binomial to provide flexible generalized linear models (GLMs) on both the mean and dispersion. We address challenges of analyzing large-scale RNA-seq data via several new developments to provide a comprehensive toolset that models technical excess zeros, identifies outliers efficiently, and evaluates differential expressions at biologically interesting levels. We evaluated performances of the MDSeq using simulated data when the ground truths are known. Results suggest that the MDSeq often outperforms current methods for the analysis of gene expression mean and variability. Moreover, the MDSeq is applied in two real RNA-seq studies, in which we identified functionally relevant genes and gene pathways. Specifically, the analysis of gene expression variability with the MDSeq on the GTEx human brain tissue data has identified pathways associated with common neurodegenerative disorders when gene expression means were conserved.
Collapse
Affiliation(s)
- Di Ran
- Mel and Enid Zuckerman College of Public Health, The University of Arizona, Tucson, AZ 85724, USA
| | | |
Collapse
|
36
|
Resolving the Complex Genetic Basis of Phenotypic Variation and Variability of Cellular Growth. Genetics 2017; 206:1645-1657. [PMID: 28495957 DOI: 10.1534/genetics.116.195180] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 05/02/2017] [Indexed: 01/10/2023] Open
Abstract
In all organisms, the majority of traits vary continuously between individuals. Explaining the genetic basis of quantitative trait variation requires comprehensively accounting for genetic and nongenetic factors as well as their interactions. The growth of microbial cells can be characterized by a lag duration, an exponential growth phase, and a stationary phase. Parameters that characterize these growth phases can vary among genotypes (phenotypic variation), environmental conditions (phenotypic plasticity), and among isogenic cells in a given environment (phenotypic variability). We used a high-throughput microscopy assay to map genetic loci determining variation in lag duration and exponential growth rate in growth rate-limiting and nonlimiting glucose concentrations, using segregants from a cross of two natural isolates of the budding yeast, Saccharomyces cerevisiae We find that some quantitative trait loci (QTL) are common between traits and environments whereas some are unique, exhibiting gene-by-environment interactions. Furthermore, whereas variation in the central tendency of growth rate or lag duration is explained by many additive loci, differences in phenotypic variability are primarily the result of genetic interactions. We used bulk segregant mapping to increase QTL resolution by performing whole-genome sequencing of complex mixtures of an advanced intercross mapping population grown in selective conditions using glucose-limited chemostats. We find that sequence variation in the high-affinity glucose transporter HXT7 contributes to variation in growth rate and lag duration. Allele replacements of the entire locus, as well as of a single polymorphic amino acid, reveal that the effect of variation in HXT7 depends on genetic, and allelic, background. Amplifications of HXT7 are frequently selected in experimental evolution in glucose-limited environments, but we find that HXT7 amplifications result in antagonistic pleiotropy that is absent in naturally occurring variants of HXT7 Our study highlights the complex nature of the genotype-to-phenotype map within and between environments.
Collapse
|
37
|
Variability in a Short Tandem Repeat Mediates Complex Epistatic Interactions in Arabidopsis thaliana. Genetics 2016; 205:455-464. [PMID: 27866166 DOI: 10.1534/genetics.116.193359] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 10/27/2016] [Indexed: 01/15/2023] Open
Abstract
Short tandem repeats (STRs) are hypervariable genetic elements that occur frequently in coding regions. Their high mutation rate readily generates genetic variation, contributing to adaptive evolution and human diseases. We previously reported that natural ELF3 polyglutamine variants cause reciprocal genetic incompatibilities in two divergent Arabidopsis thaliana backgrounds. Here, we dissect the genetic architecture of this incompatibility, revealing as many as four loci putatively interacting with ELF3 We were able to specifically identify one such ELF3-interacting gene, LSH9 We further used a yeast two-hybrid strategy to identify proteins whose physical interactions with ELF3 were affected by polyglutamine tract length. We found two proteins for which this was the case, ELF4 and AtGLDP1. Using these two approaches, we identify specific genetic interactions and physical mechanisms by which the ELF3 polyglutamine tract may mediate the observed genetic incompatibilities. Our work elucidates how STR variation, which is generally underascertained in population-scale sequencing, can contribute to phenotypic variation. Furthermore, our results support our proposal that highly variable STR loci can contribute to the epistatic component of heritability.
Collapse
|
38
|
Abstract
One of the central goals in biology is to understand how and how much of the phenotype of an organism is encoded in its genome. Although many genes that are crucial for organismal processes have been identified, much less is known about the genetic bases underlying quantitative phenotypic differences in natural populations. We discuss the fundamental gap between the large body of knowledge generated over the past decades by experimental genetics in the laboratory and what is needed to understand the genotype-to-phenotype problem on a broader scale. We argue that systems genetics, a combination of systems biology and the study of natural variation using quantitative genetics, will help to address this problem. We present major advances in these two mostly disconnected areas that have increased our understanding of the developmental processes of flowering time control and root growth. We conclude by illustrating and discussing the efforts that have been made toward systems genetics specifically in plants.
Collapse
Affiliation(s)
- Takehiko Ogura
- Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), 1030 Vienna, Austria;
| | - Wolfgang Busch
- Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), 1030 Vienna, Austria;
| |
Collapse
|
39
|
An Integrative Genetic Study of Rice Metabolism, Growth and Stochastic Variation Reveals Potential C/N Partitioning Loci. Sci Rep 2016; 6:30143. [PMID: 27440503 PMCID: PMC4954952 DOI: 10.1038/srep30143] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Accepted: 06/29/2016] [Indexed: 11/26/2022] Open
Abstract
Studying the genetic basis of variation in plant metabolism has been greatly facilitated by genomic and metabolic profiling advances. In this study, we use metabolomics and growth measurements to map QTL in rice, a major staple crop. Previous rice metabolism studies have largely focused on identifying genes controlling major effect loci. To complement these studies, we conducted a replicated metabolomics analysis on a japonica (Lemont) by indica (Teqing) rice recombinant inbred line population and focused on the genetic variation for primary metabolism. Using independent replicated studies, we show that in contrast to other rice studies, the heritability of primary metabolism is similar to Arabidopsis. The vast majority of metabolic QTLs had small to moderate effects with significant polygenic epistasis. Two metabolomics QTL hotspots had opposing effects on carbon and nitrogen rich metabolites suggesting that they may influence carbon and nitrogen partitioning, with one locus co-localizing with SUSIBA2 (WRKY78). Comparing QTLs for metabolomic and a variety of growth related traits identified few overlaps. Interestingly, the rice population displayed fewer loci controlling stochastic variation for metabolism than was found in Arabidopsis. Thus, it is possible that domestication has differentially impacted stochastic metabolite variation more than average metabolite variation.
Collapse
|
40
|
Margaritopoulou T, Kryovrysanaki N, Megkoula P, Prassinos C, Samakovli D, Milioni D, Hatzopoulos P. HSP90 canonical content organizes a molecular scaffold mechanism to progress flowering. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2016; 87:174-87. [PMID: 27121421 DOI: 10.1111/tpj.13191] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 04/04/2016] [Accepted: 04/05/2016] [Indexed: 05/28/2023]
Abstract
Highly interactive signaling processes constitute a set of parameters intertwining in a continuum mode to shape body formation and development. A sophisticated gene network is required to integrate environmental and endogenous cues in order to modulate flowering. However, the molecular mechanisms that coordinate the circuitries of flowering genes remain unclear. Here using complemented experimental approaches, we uncover the decisive and essential role of HEAT SHOCK PROTEIN 90 (HSP90) in restraining developmental noise to an acceptable limit. Localized depletion of HSP90 mRNAs in the shoot apex resulted in low penetrance of vegetative-to-reproductive phase transition and completely abolished flower formation. Extreme variation in expression of flowering genes was also observed in HSP90 mRNA-depleted transformed plants. Transient heat-shock treatments moderately increased HSP90 mRNA levels and rescued flower arrest. The offspring had a low, nevertheless noticeable failure to promote transition from vegetative into the reproductive phase and showed flower morphological heterogeneity. In floral tissues a moderate variation in HSP90 transcript levels and in the expression of flowering genes was detected. Key flowering proteins comprised clientele of the molecular chaperone demonstrating that the HSP90 is essential during vegetative-to-reproductive phase transition and flower development. Our results uncover that HSP90 consolidates a molecular scaffold able to arrange and organize flowering gene network and protein circuitry, and effectively counterbalance the extent to which developmental noise perturbs phenotypic traits.
Collapse
Affiliation(s)
- Theoni Margaritopoulou
- Molecular Biology Laboratory, Agricultural University of Athens, Iera Odos 75, 118 55, Athens, Greece
| | - Nikoleta Kryovrysanaki
- Molecular Biology Laboratory, Agricultural University of Athens, Iera Odos 75, 118 55, Athens, Greece
| | - Panagiota Megkoula
- Molecular Biology Laboratory, Agricultural University of Athens, Iera Odos 75, 118 55, Athens, Greece
| | - Constantinos Prassinos
- Molecular Biology Laboratory, Agricultural University of Athens, Iera Odos 75, 118 55, Athens, Greece
| | - Despoina Samakovli
- Molecular Biology Laboratory, Agricultural University of Athens, Iera Odos 75, 118 55, Athens, Greece
| | - Dimitra Milioni
- Molecular Biology Laboratory, Agricultural University of Athens, Iera Odos 75, 118 55, Athens, Greece
| | - Polydefkis Hatzopoulos
- Molecular Biology Laboratory, Agricultural University of Athens, Iera Odos 75, 118 55, Athens, Greece
| |
Collapse
|
41
|
Lachowiec J, Queitsch C, Kliebenstein DJ. Molecular mechanisms governing differential robustness of development and environmental responses in plants. ANNALS OF BOTANY 2016; 117:795-809. [PMID: 26473020 PMCID: PMC4845800 DOI: 10.1093/aob/mcv151] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2015] [Revised: 07/08/2015] [Accepted: 08/25/2015] [Indexed: 05/04/2023]
Abstract
BACKGROUND Robustness to genetic and environmental perturbation is a salient feature of multicellular organisms. Loss of developmental robustness can lead to severe phenotypic defects and fitness loss. However, perfect robustness, i.e. no variation at all, is evolutionarily unfit as organisms must be able to change phenotype to properly respond to changing environments and biotic challenges. Plasticity is the ability to adjust phenotypes predictably in response to specific environmental stimuli, which can be considered a transient shift allowing an organism to move from one robust phenotypic state to another. Plants, as sessile organisms that undergo continuous development, are particularly dependent on an exquisite fine-tuning of the processes that balance robustness and plasticity to maximize fitness. SCOPE AND CONCLUSIONS This paper reviews recently identified mechanisms, both systems-level and molecular, that modulate robustness, and discusses their implications for the optimization of plant fitness. Robustness in living systems arises from the structure of genetic networks, the specific molecular functions of the underlying genes, and their interactions. This very same network responsible for the robustness of specific developmental states also has to be built such that it enables plastic yet robust shifts in response to environmental changes. In plants, the interactions and functions of signal transduction pathways activated by phytohormones and the tendency for plants to tolerate whole-genome duplications, tandem gene duplication and hybridization are emerging as major regulators of robustness in development. Despite their obvious implications for plant evolution and plant breeding, the mechanistic underpinnings by which plants modulate precise levels of robustness, plasticity and evolvability in networks controlling different phenotypes are under-studied.
Collapse
Affiliation(s)
- Jennifer Lachowiec
- Department of Ecology and Evolutionary Biology, University of Michigan, 830 North University Avenue, Ann Arbor, MI 48197, USA
| | - Christine Queitsch
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, WA 98155, USA
| | - Daniel J Kliebenstein
- Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA and DynaMo Center of Excellence, University of Copenhagen, Thorvaldsensvej 40, DK-1871, Frederiksberg C, Denmark
| |
Collapse
|
42
|
Abley K, Locke JCW, Leyser HMO. Developmental mechanisms underlying variable, invariant and plastic phenotypes. ANNALS OF BOTANY 2016; 117:733-48. [PMID: 27072645 PMCID: PMC4845803 DOI: 10.1093/aob/mcw016] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Accepted: 12/18/2015] [Indexed: 05/02/2023]
Abstract
BACKGROUND Discussions of phenotypic robustness often consider scenarios where invariant phenotypes are optimal and assume that developmental mechanisms have evolved to buffer the phenotypes of specific traits against stochastic and environmental perturbations. However, plastic plant phenotypes that vary between environments or variable phenotypes that vary stochastically within an environment may also be advantageous in some scenarios. SCOPE Here the conditions under which invariant, plastic and variable phenotypes of specific traits may confer a selective advantage in plants are examined. Drawing on work from microbes and multicellular organisms, the mechanisms that may give rise to each type of phenotype are discussed. CONCLUSION In contrast to the view of robustness as being the ability of a genotype to produce a single, invariant phenotype, changes in a phenotype in response to the environment, or phenotypic variability within an environment, may also be delivered consistently (i.e. robustly). Thus, for some plant traits, mechanisms have probably evolved to produce plasticity or variability in a reliable manner.
Collapse
Affiliation(s)
- Katie Abley
- The Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK
| | - James C W Locke
- The Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK
| | - H M Ottoline Leyser
- The Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK
| |
Collapse
|
43
|
Mestek Boukhibar L, Barkoulas M. The developmental genetics of biological robustness. ANNALS OF BOTANY 2016; 117:699-707. [PMID: 26292993 PMCID: PMC4845795 DOI: 10.1093/aob/mcv128] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Revised: 05/07/2015] [Accepted: 06/29/2015] [Indexed: 05/10/2023]
Abstract
BACKGROUND Living organisms are continuously confronted with perturbations, such as environmental changes that include fluctuations in temperature and nutrient availability, or genetic changes such as mutations. While some developmental systems are affected by such challenges and display variation in phenotypic traits, others continue consistently to produce invariable phenotypes despite perturbation. This ability of a living system to maintain an invariable phenotype in the face of perturbations is termed developmental robustness. Biological robustness is a phenomenon observed across phyla, and studying its mechanisms is central to deciphering the genotype-phenotype relationship. Recent work in yeast, animals and plants has shown that robustness is genetically controlled and has started to reveal the underlying mechinisms behind it. SCOPE AND CONCLUSIONS Studying biological robustness involves focusing on an important property of developmental traits, which is the phenotypic distribution within a population. This is often neglected because the vast majority of developmental biology studies instead focus on population aggregates, such as trait averages. By drawing on findings in animals and yeast, this Viewpoint considers how studies on plant developmental robustness may benefit from strict definitions of what is the developmental system of choice and what is the relevant perturbation, and also from clear distinctions between gene effects on the trait mean and the trait variance. Recent advances in quantitative developmental biology and high-throughput phenotyping now allow the design of targeted genetic screens to identify genes that amplify or restrict developmental trait variance and to study how variation propagates across different phenotypic levels in biological systems. The molecular characterization of more quantitative trait loci affecting trait variance will provide further insights into the evolution of genes modulating developmental robustness. The study of robustness mechanisms in closely related species will address whether mechanisms of robustness are evolutionarily conserved.
Collapse
Affiliation(s)
- Lamia Mestek Boukhibar
- Imperial College London, Department of Life Sciences, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, UK
| | - Michalis Barkoulas
- Imperial College London, Department of Life Sciences, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, UK
| |
Collapse
|
44
|
Forsberg SKG, Andreatta ME, Huang XY, Danku J, Salt DE, Carlborg Ö. The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance. PLoS Genet 2015; 11:e1005648. [PMID: 26599497 PMCID: PMC4657900 DOI: 10.1371/journal.pgen.1005648] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Accepted: 10/14/2015] [Indexed: 12/17/2022] Open
Abstract
Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations. Most biological traits vary in natural populations, and understanding the genetic basis of this variation remains an important challenge. Genome-wide association (GWA) studies have emerged as a powerful tool to address this challenge by dissecting the genetic architecture of trait variation into the contribution of individual genes. This contribution has traditionally been measured as the difference in the phenotypic means between groups of individuals with alternative genotypes at one, or multiple loci. However, instead of altering the trait mean, certain loci alter the variability of the trait. Here, we describe the genetic dissection of one such variance-controlling locus that drives variation in leaf molybdenum concentrations amongst natural accessions of Arabidopsis thaliana. The variance-controlling locus was found to result from the contributions of multiple alleles at multiple loci that are closely linked on the chromosome and is a major contributor to the “missing heritability” for this trait identified in previous studies. This illustrates that multi-allelic genetic architectures can hide large amounts of additive genetic variation, and that it is possible to uncover this hidden variation using the appropriate experimental designs and statistical methods described here.
Collapse
Affiliation(s)
- Simon K. G. Forsberg
- Department of Clinical Sciences, Division of Computational Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Matthew E. Andreatta
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom
| | - Xin-Yuan Huang
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom
| | - John Danku
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom
| | - David E. Salt
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom
| | - Örjan Carlborg
- Department of Clinical Sciences, Division of Computational Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
- * E-mail:
| |
Collapse
|
45
|
Huang W, Carbone MA, Magwire MM, Peiffer JA, Lyman RF, Stone EA, Anholt RRH, Mackay TFC. Genetic basis of transcriptome diversity in Drosophila melanogaster. Proc Natl Acad Sci U S A 2015; 112:E6010-9. [PMID: 26483487 PMCID: PMC4640795 DOI: 10.1073/pnas.1519159112] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Understanding how DNA sequence variation is translated into variation for complex phenotypes has remained elusive but is essential for predicting adaptive evolution, for selecting agriculturally important animals and crops, and for personalized medicine. Gene expression may provide a link between variation in DNA sequence and organismal phenotypes, and its abundance can be measured efficiently and accurately. Here we quantified genome-wide variation in gene expression in the sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP), increasing the annotated Drosophila transcriptome by 11%, including thousands of novel transcribed regions (NTRs). We found that 42% of the Drosophila transcriptome is genetically variable in males and females, including the NTRs, and is organized into modules of genetically correlated transcripts. We found that NTRs often were negatively correlated with the expression of protein-coding genes, which we exploited to annotate NTRs functionally. We identified regulatory variants for the mean and variance of gene expression, which have largely independent genetic control. Expression quantitative trait loci (eQTLs) for the mean, but not for the variance, of gene expression were concentrated near genes. Notably, the variance eQTLs often interacted epistatically with local variants in these genes to regulate gene expression. This comprehensive characterization of population-scale diversity of transcriptomes and its genetic basis in the DGRP is critically important for a systems understanding of quantitative trait variation.
Collapse
Affiliation(s)
- Wen Huang
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695; Program in Genetics, North Carolina State University, Raleigh, NC 27695; W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695
| | - Mary Anna Carbone
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695; Program in Genetics, North Carolina State University, Raleigh, NC 27695; W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695
| | - Michael M Magwire
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695; Program in Genetics, North Carolina State University, Raleigh, NC 27695; W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695
| | - Jason A Peiffer
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695; Program in Genetics, North Carolina State University, Raleigh, NC 27695; W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695
| | - Richard F Lyman
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695; Program in Genetics, North Carolina State University, Raleigh, NC 27695; W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695
| | - Eric A Stone
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695; Program in Genetics, North Carolina State University, Raleigh, NC 27695; W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695
| | - Robert R H Anholt
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695; Program in Genetics, North Carolina State University, Raleigh, NC 27695; W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695
| | - Trudy F C Mackay
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695; Program in Genetics, North Carolina State University, Raleigh, NC 27695; W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695
| |
Collapse
|
46
|
Soltis NE, Kliebenstein DJ. Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights. PLANT PHYSIOLOGY 2015; 169:1456-68. [PMID: 26272883 PMCID: PMC4634085 DOI: 10.1104/pp.15.01108] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Accepted: 08/12/2015] [Indexed: 05/06/2023]
Abstract
Combining quantitative genetics studies with metabolomics/metabolic profiling platforms, genomics, and transcriptomics is creating significant progress in identifying the causal genes controlling natural variation in metabolite accumulations and profiles. In this review, we discuss key mechanistic and evolutionary insights that are arising from these studies. This includes the potential role of transport and other processes in leading to a separation of the site of mechanistic causation and metabolic consequence. A reilluminated observation is the potential for genomic variation in the organelle to alter phenotypic variation alone and in epistatic interaction with the nuclear genetic variation. These studies are also highlighting new aspects of metabolic pleiotropy both in terms of the breadth of loci altering metabolic variation as well as the potential for broader effects on plant defense regulation of the metabolic variation than has previously been predicted. We also illustrate caveats that can be overlooked when translating quantitative genetics descriptors such as heritability and per-locus r(2) to mechanistic or evolutionary interpretations.
Collapse
Affiliation(s)
- Nicole E Soltis
- Department of Plant Sciences, University of California, Davis, California 95616 (N.E.S., D.J.K.); andDynaMo Center of Excellence, University of Copenhagen, DK-1871 Frederiksberg C, Denmark (D.J.K.)
| | - Daniel J Kliebenstein
- Department of Plant Sciences, University of California, Davis, California 95616 (N.E.S., D.J.K.); andDynaMo Center of Excellence, University of Copenhagen, DK-1871 Frederiksberg C, Denmark (D.J.K.)
| |
Collapse
|
47
|
Genetic Control of Environmental Variation of Two Quantitative Traits of Drosophila melanogaster Revealed by Whole-Genome Sequencing. Genetics 2015; 201:487-97. [PMID: 26269504 DOI: 10.1534/genetics.115.180273] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2015] [Accepted: 08/05/2015] [Indexed: 11/18/2022] Open
Abstract
Genetic studies usually focus on quantifying and understanding the existence of genetic control on expected phenotypic outcomes. However, there is compelling evidence suggesting the existence of genetic control at the level of environmental variability, with some genotypes exhibiting more stable and others more volatile performance. Understanding the mechanisms responsible for environmental variability not only informs medical questions but is relevant in evolution and in agricultural science. In this work fully sequenced inbred lines of Drosophila melanogaster were analyzed to study the nature of genetic control of environmental variance for two quantitative traits: starvation resistance (SR) and startle response (SL). The evidence for genetic control of environmental variance is compelling for both traits. Sequence information is incorporated in random regression models to study the underlying genetic signals, which are shown to be different in the two traits. Genomic variance in sexual dimorphism was found for SR but not for SL. Indeed, the proportion of variance captured by sequence information and the contribution to this variance from four chromosome segments differ between sexes in SR but not in SL. The number of studies of environmental variation, particularly in humans, is limited. The availability of full sequence information and modern computationally intensive statistical methods provides opportunities for rigorous analyses of environmental variability.
Collapse
|
48
|
Joseph B, Lau L, Kliebenstein DJ. Quantitative Variation in Responses to Root Spatial Constraint within Arabidopsis thaliana. THE PLANT CELL 2015; 27:2227-43. [PMID: 26243313 PMCID: PMC4568506 DOI: 10.1105/tpc.15.00335] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2015] [Revised: 07/06/2015] [Accepted: 07/21/2015] [Indexed: 05/03/2023]
Abstract
Among the myriad of environmental stimuli that plants utilize to regulate growth and development to optimize fitness are signals obtained from various sources in the rhizosphere that give an indication of the nutrient status and volume of media available. These signals include chemical signals from other plants, nutrient signals, and thigmotropic interactions that reveal the presence of obstacles to growth. Little is known about the genetics underlying the response of plants to physical constraints present within the rhizosphere. In this study, we show that there is natural variation among Arabidopsis thaliana accessions in their growth response to physical rhizosphere constraints and competition. We mapped growth quantitative trait loci that regulate a positive response of foliar growth to short physical constraints surrounding the root. This is a highly polygenic trait and, using quantitative validation studies, we showed that natural variation in EARLY FLOWERING3 (ELF3) controls the link between root constraint and altered shoot growth. This provides an entry point to study how root and shoot growth are integrated to respond to environmental stimuli.
Collapse
Affiliation(s)
- Bindu Joseph
- Department of Plant Sciences, University of California, Davis, California 95616 Bayer Crop Science, Crop Genetics Department, Morrisville, North Carolina 27560
| | - Lillian Lau
- Department of Plant Sciences, University of California, Davis, California 95616
| | - Daniel J Kliebenstein
- Department of Plant Sciences, University of California, Davis, California 95616 DynaMo Center of Excellence, University of Copenhagen, DK-1871 Frederiksberg C, Denmark
| |
Collapse
|
49
|
Heritable environmental variance causes nonlinear relationships between traits: application to birth weight and stillbirth of pigs. Genetics 2015; 199:1255-69. [PMID: 25631318 DOI: 10.1534/genetics.114.173070] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Accepted: 01/23/2015] [Indexed: 11/18/2022] Open
Abstract
There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of other traits, however. A genetic covariance between these is expected to lead to nonlinearity between them, for example between birth weight and survival of piglets, where animals of extreme weights have lower survival. The objectives were to derive this nonlinear relationship analytically using multiple regression and apply it to data on piglet birth weight and survival. This study provides a framework to study such nonlinear relationships caused by genetic covariance of environmental variance of one trait and the mean of the other. It is shown that positions of phenotypic and genetic optima may differ and that genetic relationships are likely to be more curvilinear than phenotypic relationships, dependent mainly on the environmental correlation between these traits. Genetic correlations may change if the population means change relative to the optimal phenotypes. Data of piglet birth weight and survival show that the presence of nonlinearity can be partly explained by the genetic covariance between environmental variance of birth weight and survival. The framework developed can be used to assess effects of artificial and natural selection on means and variances of traits and the statistical method presented can be used to estimate trade-offs between environmental variance of one trait and mean levels of others.
Collapse
|
50
|
Pettersson ME, Carlborg O. Capacitating epistasis--detection and role in the genetic architecture of complex traits. Methods Mol Biol 2015; 1253:185-196. [PMID: 25403533 DOI: 10.1007/978-1-4939-2155-3_10] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Here, we discuss the potential role of capacitating epistasis in the genetic architecture of complex traits. Two alternative methods for identifying such gene-gene interactions in genetic association studies-mapping of variance controlling loci and the variance plane ratio (VPR) method-are introduced. An overview of the theoretical foundation of the methods is presented together with a discussion on their implementation and available software for performing these analyses. We conclude by highlighting a few examples of capacitating epistasis described in the literature and its potential impacts on the genetics of complex traits.
Collapse
Affiliation(s)
- Mats E Pettersson
- Division of Computational Genetics, Department of Clinical Sciences, Swedish University of Agricultural Sciences, Box 7078, SE-750 07, Uppsala, Sweden
| | | |
Collapse
|