1
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Dai Y, Fernandes BS, Zhao Z. Revisiting the Relative Contribution of Common and Rare Genetic Variants to Attention-Deficit/Hyperactivity Disorder Among Diverse Populations. Biol Psychiatry 2024; 95:822-824. [PMID: 38599708 DOI: 10.1016/j.biopsych.2024.02.1007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 02/26/2024] [Indexed: 04/12/2024]
Affiliation(s)
- Yulin Dai
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas.
| | - Brisa S Fernandes
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Zhongming Zhao
- Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas; Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas; Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas; Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas.
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2
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Wang T, Weiss A, You L. A generic approach to infer community-level fitness of microbial genes. Proc Natl Acad Sci U S A 2024; 121:e2318380121. [PMID: 38635629 PMCID: PMC11047084 DOI: 10.1073/pnas.2318380121] [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: 10/20/2023] [Accepted: 03/26/2024] [Indexed: 04/20/2024] Open
Abstract
The gene content in a metagenomic pool defines the function potential of a microbial community. Natural selection, operating on the level of genomes or genes, shapes the evolution of community functions by enriching some genes while depriving the others. Despite the importance of microbiomes in the environment and health, a general metric to evaluate the community-wide fitness of microbial genes remains lacking. In this work, we adapt the classic neutral model of species and use it to predict how the abundances of different genes will be shaped by selection, regardless of at which level the selection acts. We establish a simple metric that quantitatively infers the average survival capability of each gene in a microbiome. We then experimentally validate the predictions using synthetic communities of barcoded Escherichia coli strains undergoing neutral assembly and competition. We further show that this approach can be applied to publicly available metagenomic datasets to gain insights into the environment-function interplay of natural microbiomes.
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Affiliation(s)
- Teng Wang
- Department of Biomedical Engineering, Duke University, Durham, NC27705
| | - Andrea Weiss
- Department of Biomedical Engineering, Duke University, Durham, NC27705
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, NC27705
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC27710
- Center for Quantitative Biodesign, Duke University, Durham, NC27705
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3
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Lara MK, Brabec JL, Hernan AE, Scott RC, Tyler AL, Mahoney JM. Network-based analysis predicts interacting genetic modifiers from a meta-mapping study of spike-wave discharge in mice. GENES, BRAIN, AND BEHAVIOR 2024; 23:e12879. [PMID: 38444174 PMCID: PMC10915378 DOI: 10.1111/gbb.12879] [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: 05/22/2023] [Revised: 11/29/2023] [Accepted: 12/19/2023] [Indexed: 03/07/2024]
Abstract
Absence seizures are characterized by brief lapses in awareness accompanied by a hallmark spike-and-wave discharge (SWD) electroencephalographic pattern and are common to genetic generalized epilepsies (GGEs). While numerous genes have been associated with increased risk, including some Mendelian forms with a single causal allele, most cases of GGE are idiopathic and there are many unknown genetic modifiers of GGE influencing risk and severity. In a previous meta-mapping study, crosses between transgenic C57BL/6 and C3HeB/FeJ strains, each carrying one of three SWD-causing mutations (Gabrg2tm1Spet(R43Q) , Scn8a8j or Gria4spkw1 ), demonstrated an antagonistic epistatic interaction between loci on mouse chromosomes 2 and 7 influencing SWD. These results implicate universal modifiers in the B6 background that mitigate SWD severity through a common pathway, independent of the causal mutation. In this study, we prioritized candidate modifiers in these interacting loci. Our approach integrated human genome-wide association results with gene interaction networks and mouse brain gene expression to prioritize candidate genes and pathways driving variation in SWD outcomes. We considered candidate genes that are functionally associated with human GGE risk genes and genes with evidence for coding or non-coding allele effects between the B6 and C3H backgrounds. Our analyses output a summary ranking of gene pairs, one gene from each locus, as candidates for explaining the epistatic interaction. Our top-ranking gene pairs implicate microtubule function, cytoskeletal stability and cell cycle regulation as novel hypotheses about the source of SWD variation across strain backgrounds, which could clarify underlying mechanisms driving differences in GGE severity in humans.
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Affiliation(s)
- Montana Kay Lara
- Department of Neurological SciencesUniversity of VermontBurlingtonVermontUSA
| | - Jeffrey L. Brabec
- Department of Neurological SciencesUniversity of VermontBurlingtonVermontUSA
| | - Amanda E. Hernan
- Department of Neurological SciencesUniversity of VermontBurlingtonVermontUSA
- Division of NeuroscienceNemours Children's HealthWilmingtonDelawareUSA
- Department of Psychological and Brain SciencesUniversity of DelawareNewarkDelawareUSA
| | - Rod C. Scott
- Division of NeuroscienceNemours Children's HealthWilmingtonDelawareUSA
- Department of Psychological and Brain SciencesUniversity of DelawareNewarkDelawareUSA
| | | | - J. Matthew Mahoney
- Department of Neurological SciencesUniversity of VermontBurlingtonVermontUSA
- The Jackson LaboratoryBar HarborMaineUSA
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4
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Alfayyadh MM, Maksemous N, Sutherland HG, Lea RA, Griffiths LR. Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches. Genes (Basel) 2024; 15:443. [PMID: 38674378 PMCID: PMC11049430 DOI: 10.3390/genes15040443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024] Open
Abstract
Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.
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Affiliation(s)
| | | | | | | | - Lyn R. Griffiths
- Centre for Genomics and Personalised Health, Genomics Research Centre, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, QLD 4059, Australia; (M.M.A.); (N.M.); (H.G.S.); (R.A.L.)
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5
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Richard-St-Hilaire A, Gamache I, Pelletier J, Grenier JC, Poujol R, Hussin JG. Signatures of Co-evolution and Co-regulation in the CYP3A and CYP4F Genes in Humans. Genome Biol Evol 2024; 16:evad236. [PMID: 38207129 PMCID: PMC10805436 DOI: 10.1093/gbe/evad236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 12/19/2023] [Accepted: 12/22/2023] [Indexed: 01/13/2024] Open
Abstract
Cytochromes P450 (CYP450) are hemoproteins generally involved in the detoxification of the body of xenobiotic molecules. They participate in the metabolism of many drugs and genetic polymorphisms in humans have been found to impact drug responses and metabolic functions. In this study, we investigate the genetic diversity of CYP450 genes. We found that two clusters, CYP3A and CYP4F, are notably differentiated across human populations with evidence for selective pressures acting on both clusters: we found signals of recent positive selection in CYP3A and CYP4F genes and signals of balancing selection in CYP4F genes. Furthermore, an extensive amount of unusual linkage disequilibrium is detected in this latter cluster, indicating co-evolution signatures among CYP4F genes. Several of the selective signals uncovered co-localize with expression quantitative trait loci (eQTL), which could suggest epistasis acting on co-regulation in these gene families. In particular, we detected a potential co-regulation event between CYP3A5 and CYP3A43, a gene whose function remains poorly characterized. We further identified a causal relationship between CYP3A5 expression and reticulocyte count through Mendelian randomization analyses, potentially involving a regulatory region displaying a selective signal specific to African populations. Our findings linking natural selection and gene expression in CYP3A and CYP4F subfamilies are of importance in understanding population differences in metabolism of nutrients and drugs.
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Affiliation(s)
- Alex Richard-St-Hilaire
- Département de biochimie et médecine moléculaire, Université de Montréal, Montreal, QC, Canada
- Sainte-Justine Hospital, Research Center, Montreal, QC, Canada
| | - Isabel Gamache
- Département de biochimie et médecine moléculaire, Université de Montréal, Montreal, QC, Canada
- Montreal Heart Institute, Research Center, Montreal, QC, Canada
| | - Justin Pelletier
- Département de biochimie et médecine moléculaire, Université de Montréal, Montreal, QC, Canada
- McGill CERC in Genomic Medicine, McGill University, Montreal, Canada
| | | | - Raphaël Poujol
- Montreal Heart Institute, Research Center, Montreal, QC, Canada
| | - Julie G Hussin
- Montreal Heart Institute, Research Center, Montreal, QC, Canada
- Département de médecine, Université de Montréal, Montreal, QC, Canada
- Mila-Quebec AI institute, Montreal, QC, Canada
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6
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Leung AM, Rao MB, Raju N, Chung M, Klinger A, Rowe DJ, Li X, Levine EM. A framework to identify functional interactors that contribute to disrupted early retinal development in Vsx2 ocular retardation J mice. Dev Dyn 2023; 252:1338-1362. [PMID: 37259952 PMCID: PMC10689574 DOI: 10.1002/dvdy.629] [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: 11/23/2022] [Revised: 04/29/2023] [Accepted: 05/08/2023] [Indexed: 06/02/2023] Open
Abstract
BACKGROUND A goal of developmental genetics is to identify functional interactions that underlie phenotypes caused by mutations. We sought to identify functional interactors of Vsx2, which when mutated, disrupts early retinal development. We utilized the Vsx2 loss-of-function mouse, ocular retardation J (orJ), to assess interactions based on principles of positive and negative epistasis as applied to bulk transcriptome data. This was first tested in vivo with Mitf, a target of Vsx2 repression, and then to cultures of orJ retina treated with inhibitors of Retinoid-X Receptors (RXR) to target Rxrg, an up-regulated gene in the orJ retina, and gamma-Secretase, an enzyme required for Notch signaling, a key mediator of retinal proliferation and neurogenesis. RESULTS Whereas Mitf exhibited robust positive epistasis with Vsx2, it only partially accounts for the orJ phenotype, suggesting other functional interactors. RXR inhibition yielded minimal evidence for epistasis between Vsx2 and Rxrg. In contrast, gamma-Secretase inhibition caused hundreds of Vsx2-dependent genes associated with proliferation to deviate further from wild-type, providing evidence for convergent negative epistasis with Vsx2 in regulating tissue growth. CONCLUSIONS Combining in vivo and ex vivo testing with transcriptome analysis revealed quantitative and qualitative characteristics of functional interaction between Vsx2, Mitf, RXR, and gamma-Secretase activities.
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Affiliation(s)
- Amanda M. Leung
- Department of Cell and Developmental Biology, Vanderbilt
University, Nashville TN 37232
| | - Mahesh B. Rao
- Department of Ophthalmology and Visual Sciences, Vanderbilt
University Medical Center, Nashville TN 37232
| | - Nathan Raju
- Department of Ophthalmology and Visual Sciences, Vanderbilt
University Medical Center, Nashville TN 37232
| | - Minh Chung
- Department of Ophthalmology and Visual Sciences, Vanderbilt
University Medical Center, Nashville TN 37232
| | - Allison Klinger
- Department of Ophthalmology and Visual Sciences, Vanderbilt
University Medical Center, Nashville TN 37232
| | - DiAnna J. Rowe
- Department of Ophthalmology and Visual Sciences, Vanderbilt
University Medical Center, Nashville TN 37232
| | - Xiaodong Li
- Department of Ophthalmology and Visual Sciences, Vanderbilt
University Medical Center, Nashville TN 37232
| | - Edward M. Levine
- Department of Cell and Developmental Biology, Vanderbilt
University, Nashville TN 37232
- Department of Ophthalmology and Visual Sciences, Vanderbilt
University Medical Center, Nashville TN 37232
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7
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Wade MJ, Sultan SE. Niche construction and the environmental term of the price equation: How natural selection changes when organisms alter their environments. Evol Dev 2023; 25:451-469. [PMID: 37530093 DOI: 10.1111/ede.12452] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 06/30/2023] [Accepted: 07/07/2023] [Indexed: 08/03/2023]
Abstract
Organisms construct their own environments and phenotypes through the adaptive processes of habitat choice, habitat construction, and phenotypic plasticity. We examine how these processes affect the dynamics of mean fitness change through the environmental change term of the Price Equation. This tends to be ignored in evolutionary theory, owing to the emphasis on the first term describing the effect of natural selection on mean fitness (the additive genetic variance for fitness of Fisher's Fundamental Theorem). Using population genetic models and the Price Equation, we show how adaptive niche constructing traits favorably alter the distribution of environments that organisms encounter and thereby increase population mean fitness. Because niche-constructing traits increase the frequency of higher-fitness environments, selection favors their evolution. Furthermore, their alteration of the actual or experienced environmental distribution creates selective feedback between niche constructing traits and other traits, especially those with genotype-by-environment interaction for fitness. By altering the distribution of experienced environments, niche constructing traits can increase the additive genetic variance for such traits. This effect accelerates the process of overall adaption to the niche-constructed environmental distribution and can contribute to the rapid refinement of alternative phenotypic adaptations to different environments. Our findings suggest that evolutionary biologists revisit and reevaluate the environmental term of the Price Equation: owing to adaptive niche construction, it contributes directly to positive change in mean fitness; its magnitude can be comparable to that of natural selection; and, when there is fitness G × E, it increases the additive genetic variance for fitness, the much-celebrated first term.
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Affiliation(s)
- Michael J Wade
- Department of Biology, Indiana University, Bloomington, Indiana, USA
| | - Sonia E Sultan
- Department of Biology, Wesleyan University, Middletown, Connecticut, USA
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8
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Aguirre L, Hendelman A, Hutton SF, McCandlish DM, Lippman ZB. Idiosyncratic and dose-dependent epistasis drives variation in tomato fruit size. Science 2023; 382:315-320. [PMID: 37856609 PMCID: PMC10602613 DOI: 10.1126/science.adi5222] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 09/06/2023] [Indexed: 10/21/2023]
Abstract
Epistasis between genes is traditionally studied with mutations that eliminate protein activity, but most natural genetic variation is in cis-regulatory DNA and influences gene expression and function quantitatively. In this study, we used natural and engineered cis-regulatory alleles in a plant stem-cell circuit to systematically evaluate epistatic relationships controlling tomato fruit size. Combining a promoter allelic series with two other loci, we collected over 30,000 phenotypic data points from 46 genotypes to quantify how allele strength transforms epistasis. We revealed a saturating dose-dependent relationship but also allele-specific idiosyncratic interactions, including between alleles driving a step change in fruit size during domestication. Our approach and findings expose an underexplored dimension of epistasis, in which cis-regulatory allelic diversity within gene regulatory networks elicits nonlinear, unpredictable interactions that shape phenotypes.
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Affiliation(s)
- Lyndsey Aguirre
- Cold Spring Harbor Laboratory, School of Biological Sciences, Cold Spring Harbor, NY, USA
| | - Anat Hendelman
- Cold Spring Harbor Laboratory; Cold Spring Harbor, NY, USA
| | - Samuel F. Hutton
- Gulf Coast Research and Education Center, University of Florida, Wimauma, FL, USA
| | | | - Zachary B. Lippman
- Cold Spring Harbor Laboratory, School of Biological Sciences, Cold Spring Harbor, NY, USA
- Cold Spring Harbor Laboratory; Cold Spring Harbor, NY, USA
- Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
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9
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Ünlü B, Pons C, Ho UL, Batté A, Aloy P, van Leeuwen J. Global analysis of suppressor mutations that rescue human genetic defects. Genome Med 2023; 15:78. [PMID: 37821946 PMCID: PMC10568808 DOI: 10.1186/s13073-023-01232-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 09/12/2023] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND Genetic suppression occurs when the deleterious effects of a primary "query" mutation, such as a disease-causing mutation, are rescued by a suppressor mutation elsewhere in the genome. METHODS To capture existing knowledge on suppression relationships between human genes, we examined 2,400 published papers for potential interactions identified through either genetic modification of cultured human cells or through association studies in patients. RESULTS The resulting network encompassed 476 unique suppression interactions covering a wide spectrum of diseases and biological functions. The interactions frequently linked genes that operate in the same biological process. Suppressors were strongly enriched for genes with a role in stress response or signaling, suggesting that deleterious mutations can often be buffered by modulating signaling cascades or immune responses. Suppressor mutations tended to be deleterious when they occurred in absence of the query mutation, in apparent contrast with their protective role in the presence of the query. We formulated and quantified mechanisms of genetic suppression that could explain 71% of interactions and provided mechanistic insight into disease pathology. Finally, we used these observations to predict suppressor genes in the human genome. CONCLUSIONS The global suppression network allowed us to define principles of genetic suppression that were conserved across diseases, model systems, and species. The emerging frequency of suppression interactions among human genes and range of underlying mechanisms, together with the prevalence of suppression in model organisms, suggest that compensatory mutations may exist for most genetic diseases.
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Affiliation(s)
- Betül Ünlü
- Center for Integrative Genomics, University of Lausanne, Génopode Building, 1015, Lausanne, Switzerland
| | - Carles Pons
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Spain
| | - Uyen Linh Ho
- Center for Integrative Genomics, University of Lausanne, Génopode Building, 1015, Lausanne, Switzerland
| | - Amandine Batté
- Center for Integrative Genomics, University of Lausanne, Génopode Building, 1015, Lausanne, Switzerland
| | - Patrick Aloy
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Spain
- Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Jolanda van Leeuwen
- Center for Integrative Genomics, University of Lausanne, Génopode Building, 1015, Lausanne, Switzerland.
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10
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Verplaetse N, Passemiers A, Arany A, Moreau Y, Raimondi D. Large sample size and nonlinear sparse models outline epistatic effects in inflammatory bowel disease. Genome Biol 2023; 24:224. [PMID: 37798735 PMCID: PMC10552306 DOI: 10.1186/s13059-023-03064-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 09/20/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND Despite clear evidence of nonlinear interactions in the molecular architecture of polygenic diseases, linear models have so far appeared optimal in genotype-to-phenotype modeling. A key bottleneck for such modeling is that genetic data intrinsically suffers from underdetermination ([Formula: see text]). Millions of variants are present in each individual while the collection of large, homogeneous cohorts is hindered by phenotype incidence, sequencing cost, and batch effects. RESULTS We demonstrate that when we provide enough training data and control the complexity of nonlinear models, a neural network outperforms additive approaches in whole exome sequencing-based inflammatory bowel disease case-control prediction. To do so, we propose a biologically meaningful sparsified neural network architecture, providing empirical evidence for positive and negative epistatic effects present in the inflammatory bowel disease pathogenesis. CONCLUSIONS In this paper, we show that underdetermination is likely a major driver for the apparent optimality of additive modeling in clinical genetics today.
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Affiliation(s)
- Nora Verplaetse
- Department of of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium.
| | - Antoine Passemiers
- Department of of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Adam Arany
- Department of of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Yves Moreau
- Department of of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Daniele Raimondi
- Department of of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium.
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11
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Mollon J, Schultz LM, Huguet G, Knowles EEM, Mathias SR, Rodrigue A, Alexander-Bloch A, Saci Z, Jean-Louis M, Kumar K, Douard E, Almasy L, Jacquemont S, Glahn DC. Impact of Copy Number Variants and Polygenic Risk Scores on Psychopathology in the UK Biobank. Biol Psychiatry 2023; 94:591-600. [PMID: 36764568 PMCID: PMC10409883 DOI: 10.1016/j.biopsych.2023.01.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 01/31/2023] [Accepted: 01/31/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Our understanding of the impact of copy number variants (CNVs) on psychopathology and their joint influence with polygenic risk scores (PRSs) remains limited. METHODS The UK Biobank recruited 502,534 individuals ages 37 to 73 years living in the United Kingdom between 2006 and 2010. After quality control, genotype data from 459,855 individuals were available for CNV calling. A total of 61 commonly studied recurrent neuropsychiatric CNVs were selected for analyses and examined individually and in aggregate (any CNV, deletion, or duplication). CNV risk scores were used to quantify intolerance of CNVs to haploinsufficiency. Major depressive disorder and generalized anxiety disorder PRSs were generated for White British individuals (N = 408,870). Mood/anxiety factor scores were generated using item-level questionnaire data (N = 501,289). RESULTS CNV carriers showed higher mood/anxiety scores than noncarriers, with the largest effects seen for intolerant deletions. A total of 11 individual deletions and 8 duplications were associated with higher mood/anxiety. Carriers of the 9p24.3 (DMRT1) duplication showed lower mood/anxiety. Associations remained significant for most CNVs when excluding individuals with psychiatric diagnoses. Nominally significant CNV × PRS interactions provided preliminary evidence that associations between select individual CNVs, but not CNVs in aggregate, and mood/anxiety may be modulated by PRSs. CONCLUSIONS CNVs associated with risk for psychiatric disorders showed small to large effects on dimensional mood/anxiety scores in a general population cohort, even when excluding individuals with psychiatric diagnoses. CNV × PRS interactions showed that associations between select CNVs and mood/anxiety may be modulated by PRSs.
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Affiliation(s)
- Josephine Mollon
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
| | - Laura M Schultz
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Guillaume Huguet
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Emma E M Knowles
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Samuel R Mathias
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Amanda Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Zohra Saci
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Martineau Jean-Louis
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Kuldeep Kumar
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Elise Douard
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Laura Almasy
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Department of Genetics, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sebastien Jacquemont
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts; Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut
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12
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Singhal P, Verma SS, Ritchie MD. Gene Interactions in Human Disease Studies-Evidence Is Mounting. Annu Rev Biomed Data Sci 2023; 6:377-395. [PMID: 37196359 DOI: 10.1146/annurev-biodatasci-102022-120818] [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] [Indexed: 05/19/2023]
Abstract
Despite monumental advances in molecular technology to generate genome sequence data at scale, there is still a considerable proportion of heritability in most complex diseases that remains unexplained. Because many of the discoveries have been single-nucleotide variants with small to moderate effects on disease, the functional implication of many of the variants is still unknown and, thus, we have limited new drug targets and therapeutics. We, and many others, posit that one primary factor that has limited our ability to identify novel drug targets from genome-wide association studies may be due to gene interactions (epistasis), gene-environment interactions, network/pathway effects, or multiomic relationships. We propose that many of these complex models explain much of the underlying genetic architecture of complex disease. In this review, we discuss the evidence from multiple research avenues, ranging from pairs of alleles to multiomic integration studies and pharmacogenomics, that supports the need for further investigation of gene interactions (or epistasis) in genetic and genomic studies of human disease. Our goal is to catalog the mounting evidence for epistasis in genetic studies and the connections between genetic interactions and human health and disease that could enable precision medicine of the future.
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Affiliation(s)
- Pankhuri Singhal
- Genetics and Epigenetics Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Shefali Setia Verma
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA;
- Penn Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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13
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Yang A, Jude KM, Lai B, Minot M, Kocyla AM, Glassman CR, Nishimiya D, Kim YS, Reddy ST, Khan AA, Garcia KC. Deploying synthetic coevolution and machine learning to engineer protein-protein interactions. Science 2023; 381:eadh1720. [PMID: 37499032 PMCID: PMC10403280 DOI: 10.1126/science.adh1720] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 06/16/2023] [Indexed: 07/29/2023]
Abstract
Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain-affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. The integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.
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Affiliation(s)
- Aerin Yang
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Kevin M. Jude
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ben Lai
- Toyota Technological Institute at Chicago, Chicago, IL 60637, USA
| | - Mason Minot
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Anna M. Kocyla
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Caleb R. Glassman
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Daisuke Nishimiya
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yoon Seok Kim
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sai T. Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Aly A. Khan
- Toyota Technological Institute at Chicago, Chicago, IL 60637, USA
- Departments of Pathology, and Family Medicine, University of Chicago, Chicago, IL 60637, USA
| | - K. Christopher Garcia
- Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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14
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Johnson MS, Reddy G, Desai MM. Epistasis and evolution: recent advances and an outlook for prediction. BMC Biol 2023; 21:120. [PMID: 37226182 PMCID: PMC10206586 DOI: 10.1186/s12915-023-01585-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/30/2023] [Indexed: 05/26/2023] Open
Abstract
As organisms evolve, the effects of mutations change as a result of epistatic interactions with other mutations accumulated along the line of descent. This can lead to shifts in adaptability or robustness that ultimately shape subsequent evolution. Here, we review recent advances in measuring, modeling, and predicting epistasis along evolutionary trajectories, both in microbial cells and single proteins. We focus on simple patterns of global epistasis that emerge in this data, in which the effects of mutations can be predicted by a small number of variables. The emergence of these patterns offers promise for efforts to model epistasis and predict evolution.
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Affiliation(s)
- Milo S Johnson
- Department of Integrative Biology, University of California, Berkeley, CA, USA
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Gautam Reddy
- Physics & Informatics Laboratories, NTT Research, Inc., Sunnyvale, CA, USA
- Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology and Department of Physics, Harvard University, Cambridge, MA, USA.
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15
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Daalman WKG, Sweep E, Laan L. A tractable physical model for the yeast polarity predicts epistasis and fitness. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220044. [PMID: 37004720 PMCID: PMC10067261 DOI: 10.1098/rstb.2022.0044] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023] Open
Abstract
Accurate phenotype prediction based on genetic information has numerous societal applications, such as crop design or cellular factories. Epistasis, when biological components interact, complicates modelling phenotypes from genotypes. Here we show an approach to mitigate this complication for polarity establishment in budding yeast, where mechanistic information is abundant. We coarse-grain molecular interactions into a so-called mesotype, which we combine with gene expression noise into a physical cell cycle model. First, we show with computer simulations that the mesotype allows validation of the most current biochemical polarity models by quantitatively matching doubling times. Second, the mesotype elucidates epistasis emergence as exemplified by evaluating the predicted mutational effect of key polarity protein Bem1p when combined with known interactors or under different growth conditions. This example also illustrates how unlikely evolutionary trajectories can become more accessible. The tractability of our biophysically justifiable approach inspires a road-map towards bottom-up modelling complementary to statistical inferences. This article is part of the theme issue ‘Interdisciplinary approaches to predicting evolutionary biology’.
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Affiliation(s)
| | - Els Sweep
- Department of Bionanoscience, TU Delft, 2629 HZ Delft, The Netherlands
| | - Liedewij Laan
- Department of Bionanoscience, TU Delft, 2629 HZ Delft, The Netherlands
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16
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Hung PH, Liao CW, Ko FH, Tsai HK, Leu JY. Differential Hsp90-dependent gene expression is strain-specific and common among yeast strains. iScience 2023; 26:106635. [PMID: 37138775 PMCID: PMC10149407 DOI: 10.1016/j.isci.2023.106635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 02/21/2023] [Accepted: 04/05/2023] [Indexed: 05/05/2023] Open
Abstract
Enhanced phenotypic diversity increases a population's likelihood of surviving catastrophic conditions. Hsp90, an essential molecular chaperone and a central network hub in eukaryotes, has been observed to suppress or enhance the effects of genetic variation on phenotypic diversity in response to environmental cues. Because many Hsp90-interacting genes are involved in signaling transduction pathways and transcriptional regulation, we tested how common Hsp90-dependent differential gene expression is in natural populations. Many genes exhibited Hsp90-dependent strain-specific differential expression in five diverse yeast strains. We further identified transcription factors (TFs) potentially contributing to variable expression. We found that on Hsp90 inhibition or environmental stress, activities or abundances of Hsp90-dependent TFs varied among strains, resulting in differential strain-specific expression of their target genes, which consequently led to phenotypic diversity. We provide evidence that individual strains can readily display specific Hsp90-dependent gene expression, suggesting that the evolutionary impacts of Hsp90 are widespread in nature.
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Affiliation(s)
- Po-Hsiang Hung
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei 115, Taiwan
- Institute of Molecular Biology, Academia Sinica, Taipei 115, Taiwan
- Institute of Information Science, Academia Sinica, Taipei 115, Taiwan
| | - Chia-Wei Liao
- Institute of Molecular Biology, Academia Sinica, Taipei 115, Taiwan
| | - Fu-Hsuan Ko
- Institute of Molecular Biology, Academia Sinica, Taipei 115, Taiwan
| | - Huai-Kuang Tsai
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei 115, Taiwan
- Institute of Information Science, Academia Sinica, Taipei 115, Taiwan
- Corresponding author
| | - Jun-Yi Leu
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei 115, Taiwan
- Institute of Molecular Biology, Academia Sinica, Taipei 115, Taiwan
- Corresponding author
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17
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Montesinos-López OA, Saint Pierre C, Gezan SA, Bentley AR, Mosqueda-González BA, Montesinos-López A, van Eeuwijk F, Beyene Y, Gowda M, Gardner K, Gerard GS, Crespo-Herrera L, Crossa J. Optimizing Sparse Testing for Genomic Prediction of Plant Breeding Crops. Genes (Basel) 2023; 14:genes14040927. [PMID: 37107685 PMCID: PMC10137724 DOI: 10.3390/genes14040927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 04/07/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023] Open
Abstract
While sparse testing methods have been proposed by researchers to improve the efficiency of genomic selection (GS) in breeding programs, there are several factors that can hinder this. In this research, we evaluated four methods (M1-M4) for sparse testing allocation of lines to environments under multi-environmental trails for genomic prediction of unobserved lines. The sparse testing methods described in this study are applied in a two-stage analysis to build the genomic training and testing sets in a strategy that allows each location or environment to evaluate only a subset of all genotypes rather than all of them. To ensure a valid implementation, the sparse testing methods presented here require BLUEs (or BLUPs) of the lines to be computed at the first stage using an appropriate experimental design and statistical analyses in each location (or environment). The evaluation of the four cultivar allocation methods to environments of the second stage was done with four data sets (two large and two small) under a multi-trait and uni-trait framework. We found that the multi-trait model produced better genomic prediction (GP) accuracy than the uni-trait model and that methods M3 and M4 were slightly better than methods M1 and M2 for the allocation of lines to environments. Some of the most important findings, however, were that even under a scenario where we used a training-testing relation of 15-85%, the prediction accuracy of the four methods barely decreased. This indicates that genomic sparse testing methods for data sets under these scenarios can save considerable operational and financial resources with only a small loss in precision, which can be shown in our cost-benefit analysis.
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Affiliation(s)
| | - Carolina Saint Pierre
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico
| | | | - Alison R Bentley
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico
| | - Brandon A Mosqueda-González
- Centro de Investigación en Computación (CIC), Instituto Politécnico Nacional (IPN), Mexico City 07738, Mexico
| | - Abelardo Montesinos-López
- Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, Guadalajara 44430, Mexico
| | - Fred van Eeuwijk
- Department of Plant Science Mathematical and Statistical Methods-Biometrics, P.O. Box 16, 6700AA Wageningen, The Netherlands
| | - Yoseph Beyene
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico
| | - Manje Gowda
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico
| | - Keith Gardner
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico
| | - Guillermo S Gerard
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico
| | - Leonardo Crespo-Herrera
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico
| | - José Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera Mexico-Veracruz, El Batan, Texcoco 56237, Mexico
- Colegio de Postgraduados, Montecillos 56230, Mexico
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18
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Lai HY, Yu YH, Jhou YT, Liao CW, Leu JY. Multiple intermolecular interactions facilitate rapid evolution of essential genes. Nat Ecol Evol 2023; 7:745-755. [PMID: 36997737 PMCID: PMC10172115 DOI: 10.1038/s41559-023-02029-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 02/21/2023] [Indexed: 04/01/2023]
Abstract
Essential genes are commonly assumed to function in basic cellular processes and to change slowly. However, it remains unclear whether all essential genes are similarly conserved or if their evolutionary rates can be accelerated by specific factors. To address these questions, we replaced 86 essential genes of Saccharomyces cerevisiae with orthologues from four other species that diverged from S. cerevisiae about 50, 100, 270 and 420 Myr ago. We identify a group of fast-evolving genes that often encode subunits of large protein complexes, including anaphase-promoting complex/cyclosome (APC/C). Incompatibility of fast-evolving genes is rescued by simultaneously replacing interacting components, suggesting it is caused by protein co-evolution. Detailed investigation of APC/C further revealed that co-evolution involves not only primary interacting proteins but also secondary ones, suggesting the evolutionary impact of epistasis. Multiple intermolecular interactions in protein complexes may provide a microenvironment facilitating rapid evolution of their subunits.
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Affiliation(s)
- Huei-Yi Lai
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Yen-Hsin Yu
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Yu-Ting Jhou
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Chia-Wei Liao
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Jun-Yi Leu
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.
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19
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Ortega DC, Cárdenas H, González R, Barreto G. Ancestral reconstruction and correlation of the frequencies of the hemoglobin S allele and the Duffy blood group alleles in human populations. Am J Hum Biol 2023; 35:e23832. [PMID: 36376949 DOI: 10.1002/ajhb.23832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 10/25/2022] [Accepted: 10/26/2022] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVES Malaria is an important selective force for human genetic adaptation due to the sustained, lethal impact it has had on populations worldwide. High frequencies of both hemoglobin S and the null allele FYBES of the Duffy blood group have been found in areas where this disease is endemic, attributed to the protective action of the carriers of these variants against malaria infection. The objective of this work was to perform ancestral reconstruction and analyze the correlation of the frequencies of these alleles throughout the phylogeny of 24 human populations. METHODS A tree topology and the allelic frequencies reported in the literature for the 24 populations were used. The ancestral frequencies for the two alleles were reconstructed using the maximum likelihood method and the Brownian model of evolution (CI = 95%), and the correlation analysis was performed using phylogenetically independent contrasts (PICs). Statistical analyses were performed with the statistical software R version 3.4.1. RESULTS For both alleles, a correspondence was found in the reconstruction of the ancestral frequencies, and a significant statistical correlation (p = .001) was observed between the S and FYBES alleles. CONCLUSIONS These results provide evidence of an epistatic relationship between the two alleles, which may influence the fitness of the individuals who present with them when they are subjected to a selective force such as malaria.
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Affiliation(s)
| | - Heiber Cárdenas
- Department of Biology, Universidad del Valle, Cali, Colombia
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20
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Densi A, Iyer RS, Bhat PJ. Synonymous and Nonsynonymous Substitutions in Dictyostelium discoideum Ammonium Transporter amtA Are Necessary for Functional Complementation in Saccharomyces cerevisiae. Microbiol Spectr 2023; 11:e0384722. [PMID: 36840598 PMCID: PMC10100761 DOI: 10.1128/spectrum.03847-22] [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: 09/21/2022] [Accepted: 01/24/2023] [Indexed: 02/24/2023] Open
Abstract
Ammonium transporters are present in all three domains of life. They have undergone extensive horizontal gene transfer (HGT), gene duplication, and functional diversification and therefore offer an excellent paradigm to study protein evolution. We attempted to complement a mep1Δmep2Δmep3Δ strain of Saccharomyces cerevisiae (triple-deletion strain), which otherwise cannot grow on ammonium as a sole nitrogen source at concentrations of <3 mM, with amtA of Dictyostelium discoideum, an orthologue of S. cerevisiae MEP2. We observed that amtA did not complement the triple-deletion strain of S. cerevisiae for growth on low-ammonium medium. We isolated two mutant derivatives of amtA (amtA M1 and amtA M2) from a PCR-generated mutant plasmid library that complemented the triple-deletion strain of S. cerevisiae. amtA M1 bears three nonsynonymous and two synonymous substitutions, which are necessary for its functionality. amtA M2 bears two nonsynonymous substitutions and one synonymous substitution, all of which are necessary for functionality. Interestingly, AmtA M1 transports ammonium but does not confer methylamine toxicity, while AmtA M2 transports ammonium and confers methylamine toxicity, demonstrating functional diversification. Preliminary biochemical analyses indicated that the mutants differ in their conformations as well as their mechanisms of ammonium transport. These intriguing results clearly point out that protein evolution cannot be fathomed by studying nonsynonymous and synonymous substitutions in isolation. The above-described observations have significant implications for various facets of biological processes and are discussed in detail. IMPORTANCE Functional diversification following gene duplication is one of the major driving forces of protein evolution. While the role of nonsynonymous substitutions in the functional diversification of proteins is well recognized, knowledge of the role of synonymous substitutions in protein evolution is in its infancy. Using functional complementation, we isolated two functional alleles of the D. discoideum ammonium transporter gene (amtA), which otherwise does not function in S. cerevisiae as an ammonium transporters. One of them is an ammonium transporter, while the other is an ammonium transporter that also confers methylammonium (ammonium analogue) toxicity, suggesting functional diversification. Surprisingly, both alleles require a combination of synonymous and nonsynonymous substitutions for their functionality. These results bring out a hitherto-unknown pathway of protein evolution and pave the way for not only understanding protein evolution but also interpreting single nucleotide polymorphisms (SNPs).
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Affiliation(s)
- Asha Densi
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Revathi S. Iyer
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Paike Jayadeva Bhat
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
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21
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Huh E, Agosto MA, Wensel TG, Lichtarge O. Coevolutionary signals in metabotropic glutamate receptors capture residue contacts and long-range functional interactions. J Biol Chem 2023; 299:103030. [PMID: 36806686 PMCID: PMC10060750 DOI: 10.1016/j.jbc.2023.103030] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/18/2023] Open
Abstract
Upon ligand binding to a G protein-coupled receptor, extracellular signals are transmitted into a cell through sets of residue interactions that translate ligand binding into structural rearrangements. These interactions needed for functions impose evolutionary constraints so that, on occasion, mutations in one position may be compensated by other mutations at functionally coupled positions. To quantify the impact of amino acid substitutions in the context of major evolutionary divergence in the G protein-coupled receptor subfamily of metabotropic glutamate receptors (mGluRs), we combined two phylogenetic-based algorithms, Evolutionary Trace and covariation Evolutionary Trace, to infer potential structure-function couplings and roles in mGluRs. We found a subset of evolutionarily important residues at known functional sites and evidence of coupling among distinct structural clusters in mGluR. In addition, experimental mutagenesis and functional assays confirmed that some highly covariant residues are coupled, revealing their synergy. Collectively, these findings inform a critical step toward understanding the molecular and structural basis of amino acid variation patterns within mGluRs and provide insight for drug development, protein engineering, and analysis of naturally occurring variants.
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Affiliation(s)
- Eunna Huh
- Department of Pharmacology and Chemical Biology, Baylor College of Medicine, Houston, Texas, USA
| | - Melina A Agosto
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, USA; Retina and Optic Nerve Research Laboratory, Department of Physiology and Biophysics, Dalhousie University, Halifax, Canada
| | - Theodore G Wensel
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, USA
| | - Olivier Lichtarge
- Department of Pharmacology and Chemical Biology, Baylor College of Medicine, Houston, Texas, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA.
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22
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Learning high-order interactions for polygenic risk prediction. PLoS One 2023; 18:e0281618. [PMID: 36763605 PMCID: PMC9916647 DOI: 10.1371/journal.pone.0281618] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 01/27/2023] [Indexed: 02/11/2023] Open
Abstract
Within the framework of precision medicine, the stratification of individual genetic susceptibility based on inherited DNA variation has paramount relevance. However, one of the most relevant pitfalls of traditional Polygenic Risk Scores (PRS) approaches is their inability to model complex high-order non-linear SNP-SNP interactions and their effect on the phenotype (e.g. epistasis). Indeed, they incur in a computational challenge as the number of possible interactions grows exponentially with the number of SNPs considered, affecting the statistical reliability of the model parameters as well. In this work, we address this issue by proposing a novel PRS approach, called High-order Interactions-aware Polygenic Risk Score (hiPRS), that incorporates high-order interactions in modeling polygenic risk. The latter combines an interaction search routine based on frequent itemsets mining and a novel interaction selection algorithm based on Mutual Information, to construct a simple and interpretable weighted model of user-specified dimensionality that can predict a given binary phenotype. Compared to traditional PRSs methods, hiPRS does not rely on GWAS summary statistics nor any external information. Moreover, hiPRS differs from Machine Learning-based approaches that can include complex interactions in that it provides a readable and interpretable model and it is able to control overfitting, even on small samples. In the present work we demonstrate through a comprehensive simulation study the superior performance of hiPRS w.r.t. state of the art methods, both in terms of scoring performance and interpretability of the resulting model. We also test hiPRS against small sample size, class imbalance and the presence of noise, showcasing its robustness to extreme experimental settings. Finally, we apply hiPRS to a case study on real data from DACHS cohort, defining an interaction-aware scoring model to predict mortality of stage II-III Colon-Rectal Cancer patients treated with oxaliplatin.
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23
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Cisneros AF, Gagnon-Arsenault I, Dubé AK, Després PC, Kumar P, Lafontaine K, Pelletier JN, Landry CR. Epistasis between promoter activity and coding mutations shapes gene evolvability. SCIENCE ADVANCES 2023; 9:eadd9109. [PMID: 36735790 PMCID: PMC9897669 DOI: 10.1126/sciadv.add9109] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 12/22/2022] [Indexed: 06/01/2023]
Abstract
The evolution of protein-coding genes proceeds as mutations act on two main dimensions: regulation of transcription level and the coding sequence. The extent and impact of the connection between these two dimensions are largely unknown because they have generally been studied independently. By measuring the fitness effects of all possible mutations on a protein complex at various levels of promoter activity, we show that promoter activity at the optimal level for the wild-type protein masks the effects of both deleterious and beneficial coding mutations. Mutations that are deleterious at low activity but masked at optimal activity are slightly destabilizing for individual subunits and binding interfaces. Coding mutations that increase protein abundance are beneficial at low expression but could potentially incur a cost at high promoter activity. We thereby demonstrate that promoter activity in interaction with protein properties can dictate which coding mutations are beneficial, neutral, or deleterious.
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Affiliation(s)
- Angel F. Cisneros
- Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, G1V 0A6, Québec, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, G1V 0A6, Québec, Canada
- Centre de recherche sur les données massives, Université Laval, G1V 0A6, Québec, Canada
| | - Isabelle Gagnon-Arsenault
- Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, G1V 0A6, Québec, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, G1V 0A6, Québec, Canada
- Centre de recherche sur les données massives, Université Laval, G1V 0A6, Québec, Canada
- Département de biologie, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
| | - Alexandre K. Dubé
- Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, G1V 0A6, Québec, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, G1V 0A6, Québec, Canada
- Centre de recherche sur les données massives, Université Laval, G1V 0A6, Québec, Canada
- Département de biologie, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
| | - Philippe C. Després
- Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, G1V 0A6, Québec, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, G1V 0A6, Québec, Canada
- Centre de recherche sur les données massives, Université Laval, G1V 0A6, Québec, Canada
| | - Pradum Kumar
- Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
- Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India
| | - Kiana Lafontaine
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, G1V 0A6, Québec, Canada
- Département de biochimie et de médecine moléculaire, Faculté de médecine, Université de Montréal, H3C 3J7, Montréal, Canada
| | - Joelle N. Pelletier
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, G1V 0A6, Québec, Canada
- Département de biochimie et de médecine moléculaire, Faculté de médecine, Université de Montréal, H3C 3J7, Montréal, Canada
- Département de chimie, Faculté des arts et des sciences, Université de Montréal, H3C 3J7, Montréal, Canada
| | - Christian R. Landry
- Département de biochimie, de microbiologie et de bio-informatique, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, G1V 0A6, Québec, Canada
- PROTEO, Le regroupement québécois de recherche sur la fonction, l’ingénierie et les applications des protéines, Université Laval, G1V 0A6, Québec, Canada
- Centre de recherche sur les données massives, Université Laval, G1V 0A6, Québec, Canada
- Département de biologie, Faculté des sciences et de génie, Université Laval, G1V 0A6, Québec, Canada
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24
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Olivieri F, Prattichizzo F, Lattanzio F, Bonfigli AR, Spazzafumo L. Antifragility and antiinflammaging: Can they play a role for a healthy longevity? Ageing Res Rev 2023; 84:101836. [PMID: 36574863 DOI: 10.1016/j.arr.2022.101836] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 12/14/2022] [Accepted: 12/21/2022] [Indexed: 12/25/2022]
Abstract
One of the most exciting challenges of the research on aging is to explain how the environmental factors interact with the genetic background to modulate the chances to reach the extreme limit of human life in healthy conditions. The complex epigenetic mechanisms can explain both the interaction between DNA and environmental factors, and the long-distance persistence of lifestyle effects, due to the so called "epigenetic memory". One of the most extensively investigated theories on aging focuses on the inflammatory responses, suggesting that the age-related progression of low-grade and therefore for long time subclinical, chronic, systemic, inflammatory process, named "inflammaging", could be the most relevant risk factor for the development and progression of the most common age-related diseases and ultimately of death. The results of many studies on long-lived people, especially on centenarians, suggested that healthy old people can cope with inflammaging upregulating the antiinflammaging responses. Overall, a genetic make-up coding for a strong antiinflammaging response and an age-related ability to remodel key metabolic pathways to cope with a plethora of antigens and stressors seem to be the best ways for reach the extreme limit of human lifespan in health status. In this scenario, we wondered if the antifragility concept, recently developed in the framework of business and risk analysis, could add some information to disentangle the heterogeneous nature of the aging process in human. The antifragility is the property of the complex systems to increase their performances because of high stress. Based on this theory we were wondering if some subjects could be able to modulate faster than others their epigenome to cope with a plethora of stressors during life, probably modulating the inflammatory and anti-inflammatory responses. In this framework, antifragility could share some common mechanisms with anti-inflammaging, modulating the ability to restrain the inflammatory responses, so that antifragility and antiinflammaging could be viewed as different pieces of the same puzzle, both impinging upon the chances to travel along the healthy aging trajectory.
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Affiliation(s)
- Fabiola Olivieri
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica Delle Marche, Ancona, Italy; Clinica di Medicina di Laboratorio e di Precisione, IRCCS INRCA, Ancona, Italy.
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25
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Saeidnia F, Majidi MM, Mirlohi A, Ahmadi B. Association analysis revealed loci linked to post-drought recovery and traits related to persistence of smooth bromegrass (Bromus inermis). PLoS One 2022; 17:e0278687. [PMID: 36477736 PMCID: PMC9728867 DOI: 10.1371/journal.pone.0278687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 11/22/2022] [Indexed: 12/12/2022] Open
Abstract
Association analysis has been proven as a powerful tool for the genetic dissection of complex traits. This study was conducted to identify association of recovery, persistence, and summer dormancy with sequence related amplified polymorphism (SRAP) markers in 36 smooth bromegrass genotypes under two moisture conditions and find stable associations. In this study, a diverse panel of polycross-derived progenies of smooth bromegrass was phenotyped under normal and water deficit regimes for three consecutive years. Under water deficit, dry matter yield of cut 1 was approximately reduced by 36, 39, and 37% during 2013, 2014, and 2015, respectively, compared with the normal regime. For dry matter yield of cut 2, these reductions were approximately 38, 60, and 56% in the same three consecutive years relative to normal regime. Moreover, water deficit decreased the RY and PER of the genotypes by 35 and 28%, respectively. Thirty primer combinations were screened by polymerase chain reaction (PCR). From these, 541 polymorphic bands were developed and subjected to association analysis using the mixed linear model (MLM). Population structure analysis identified five main subpopulations possessing significant genetic differences. Association analysis identified 69 and 46 marker-trait associations under normal and water deficit regimes, respectively. Some of these markers were associated with more than one trait; which can be attributed to pleiotropic effects or tightly linked genes affecting several traits. In normal and water-deficit regimes, these markers could potentially be incorporated into marker-assisted selection and targeted trait introgression for the improvement of drought tolerance of smooth bromegrass.
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Affiliation(s)
- Fatemeh Saeidnia
- Assistant Professor of Agricultural and Horticultural Science Research Department, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Mashhad, Iran
- * E-mail:
| | - Mohammad Mahdi Majidi
- Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan, Iran
| | - Aghafakhr Mirlohi
- Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan, Iran
| | - Benyamin Ahmadi
- Department of Horticulture, College of Agriculture, Isfahan University of Technology, Isfahan, Iran
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26
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Montesinos-López OA, Carter AH, Bernal-Sandoval DA, Cano-Paez B, Montesinos-López A, Crossa J. A Comparison between Three Tuning Strategies for Gaussian Kernels in the Context of Univariate Genomic Prediction. Genes (Basel) 2022; 13:genes13122282. [PMID: 36553547 PMCID: PMC9778581 DOI: 10.3390/genes13122282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/15/2022] [Accepted: 11/29/2022] [Indexed: 12/07/2022] Open
Abstract
Genomic prediction is revolutionizing plant breeding since candidate genotypes can be selected without the need to measure their trait in the field. When a reference population contains both phenotypic and genotypic information, it is trained by a statistical machine learning method that is subsequently used for making predictions of breeding or phenotypic values of candidate genotypes that were only genotyped. Nevertheless, the successful implementation of the genomic selection (GS) methodology depends on many factors. One key factor is the type of statistical machine learning method used since some are unable to capture nonlinear patterns available in the data. While kernel methods are powerful statistical machine learning algorithms that capture complex nonlinear patterns in the data, their successful implementation strongly depends on the careful tuning process of the involved hyperparameters. As such, in this paper we compare three methods of tuning (manual tuning, grid search, and Bayesian optimization) for the Gaussian kernel under a Bayesian best linear unbiased predictor model. We used six real datasets of wheat (Triticum aestivum L.) to compare the three strategies of tuning. We found that if we want to obtain the major benefits of using Gaussian kernels, it is very important to perform a careful tuning process. The best prediction performance was observed when the tuning process was performed with grid search and Bayesian optimization. However, we did not observe relevant differences between the grid search and Bayesian optimization approach. The observed gains in terms of prediction performance were between 2.1% and 27.8% across the six datasets under study.
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Affiliation(s)
| | - Arron H. Carter
- Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99164, USA
| | | | - Bernabe Cano-Paez
- Facultad de Ciencias, Universidad Nacional Autónoma de México (UNAM), Mexico City 04510, Mexico
| | - Abelardo Montesinos-López
- Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, Guadalajara 44430, Mexico
- Correspondence: (A.M.-L.); (J.C.)
| | - José Crossa
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco 56237, Mexico
- Hidrociencias, Colegio de Postgraduados, Campus Montecillos, Carretera México-Texcoco Km. 36.5, Montecillo 56230, Mexico
- Correspondence: (A.M.-L.); (J.C.)
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27
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Missing Causality and Heritability of Autoimmune Hepatitis. Dig Dis Sci 2022; 68:1585-1604. [PMID: 36261672 DOI: 10.1007/s10620-022-07728-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 10/10/2022] [Indexed: 12/09/2022]
Abstract
BACKGROUND Autoimmune hepatitis has an unknown cause and genetic associations that are not disease-specific or always present. Clarification of its missing causality and heritability could improve prevention and management strategies. AIMS Describe the key epigenetic and genetic mechanisms that could account for missing causality and heritability in autoimmune hepatitis; indicate the prospects of these mechanisms as pivotal factors; and encourage investigations of their pathogenic role and therapeutic potential. METHODS English abstracts were identified in PubMed using multiple key search phases. Several hundred abstracts and 210 full-length articles were reviewed. RESULTS Environmental induction of epigenetic changes is the prime candidate for explaining the missing causality of autoimmune hepatitis. Environmental factors (diet, toxic exposures) can alter chromatin structure and the production of micro-ribonucleic acids that affect gene expression. Epistatic interaction between unsuspected genes is the prime candidate for explaining the missing heritability. The non-additive, interactive effects of multiple genes could enhance their impact on the propensity and phenotype of autoimmune hepatitis. Transgenerational inheritance of acquired epigenetic marks constitutes another mechanism of transmitting parental adaptations that could affect susceptibility. Management strategies could range from lifestyle adjustments and nutritional supplements to precision editing of the epigenetic landscape. CONCLUSIONS Autoimmune hepatitis has a missing causality that might be explained by epigenetic changes induced by environmental factors and a missing heritability that might reflect epistatic gene interactions or transgenerational transmission of acquired epigenetic marks. These unassessed or under-evaluated areas warrant investigation.
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28
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Nucleotide-based genetic networks: Methods and applications. J Biosci 2022. [PMID: 36226367 PMCID: PMC9554864 DOI: 10.1007/s12038-022-00290-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Genomic variations have been acclaimed as among the key players in understanding the biological mechanisms behind migration, evolution, and adaptation to extreme conditions. Due to stochastic evolutionary forces, the frequency of polymorphisms is affected by changes in the frequency of nearby polymorphisms in the same DNA sample, making them connected in terms of evolution. This article presents all the ingredients to understand the cumulative effects and complex behaviors of genetic variations in the human mitochondrial genome by analyzing co-occurrence networks of nucleotides, and shows key results obtained from such analyses. The article emphasizes recent investigations of these co-occurrence networks, describing the role of interactions between nucleotides in fundamental processes of human migration and viral evolution. The corresponding co-mutation-based genetic networks revealed genetic signatures of human adaptation in extreme environments. This article provides the methods of constructing such networks in detail, along with their graph-theoretical properties, and applications of the genomic networks in understanding the role of nucleotide co-evolution in evolution of the whole genome.
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29
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Pang H, Lin J, Luo S, Huang G, Li X, Xie Z, Zhou Z. The missing heritability in type 1 diabetes. Diabetes Obes Metab 2022; 24:1901-1911. [PMID: 35603907 PMCID: PMC9545639 DOI: 10.1111/dom.14777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/04/2022] [Accepted: 05/17/2022] [Indexed: 12/15/2022]
Abstract
Type 1 diabetes (T1D) is a complex autoimmune disease characterized by an absolute deficiency of insulin. It affects more than 20 million people worldwide and imposes an enormous financial burden on patients. The underlying pathogenic mechanisms of T1D are still obscure, but it is widely accepted that both genetics and the environment play an important role in its onset and development. Previous studies have identified more than 60 susceptible loci associated with T1D, explaining approximately 80%-85% of the heritability. However, most identified variants confer only small increases in risk, which restricts their potential clinical application. In addition, there is still a so-called 'missing heritability' phenomenon. While the gap between known heritability and true heritability in T1D is small compared with that in other complex traits and disorders, further elucidation of T1D genetics has the potential to bring novel insights into its aetiology and provide new therapeutic targets. Many hypotheses have been proposed to explain the missing heritability, including variants remaining to be found (variants with small effect sizes, rare variants and structural variants) and interactions (gene-gene and gene-environment interactions; e.g. epigenetic effects). In the following review, we introduce the possible sources of missing heritability and discuss the existing related knowledge in the context of T1D.
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Affiliation(s)
- Haipeng Pang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Jian Lin
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Shuoming Luo
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Gan Huang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Xia Li
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Zhiguo Xie
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
| | - Zhiguang Zhou
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaChina
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30
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Alemrajabi M, Macias Calix K, Assis R. Epistasis-Driven Evolution of the SARS-CoV-2 Secondary Structure. J Mol Evol 2022; 90:429-437. [PMID: 36178491 PMCID: PMC9523185 DOI: 10.1007/s00239-022-10073-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 09/02/2022] [Indexed: 11/25/2022]
Abstract
Epistasis is an evolutionary phenomenon whereby the fitness effect of a mutation depends on the genetic background in which it arises. A key source of epistasis in an RNA molecule is its secondary structure, which contains functionally important topological motifs held together by hydrogen bonds between Watson–Crick (WC) base pairs. Here we study epistasis in the secondary structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by examining properties of derived alleles arising from substitution mutations at ancestral WC base-paired and unpaired (UP) sites in 15 conserved topological motifs across the genome. We uncover fewer derived alleles and lower derived allele frequencies at WC than at UP sites, supporting the hypothesis that modifications to the secondary structure are often deleterious. At WC sites, we also find lower derived allele frequencies for mutations that abolish base pairing than for those that yield G·U “wobbles,” illustrating that weak base pairing can partially preserve the integrity of the secondary structure. Last, we show that WC sites under the strongest epistatic constraint reside in a three-stemmed pseudoknot motif that plays an essential role in programmed ribosomal frameshifting, whereas those under the weakest epistatic constraint are located in 3’ UTR motifs that regulate viral replication and pathogenicity. Our findings demonstrate the importance of epistasis in the evolution of the SARS-CoV-2 secondary structure, as well as highlight putative structural and functional targets of different forms of natural selection.
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Affiliation(s)
- Mahsa Alemrajabi
- Department of Physics, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Ksenia Macias Calix
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Raquel Assis
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA.
- Institute for Human Health and Disease Intervention, Florida Atlantic University, Boca Raton, FL, 33431, USA.
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31
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Sohail MS, Louie RHY, Hong Z, Barton JP, McKay MR. Inferring Epistasis from Genetic Time-series Data. Mol Biol Evol 2022; 39:6710201. [PMID: 36130322 PMCID: PMC9558069 DOI: 10.1093/molbev/msac199] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Epistasis refers to fitness or functional effects of mutations that depend on the sequence background in which these mutations arise. Epistasis is prevalent in nature, including populations of viruses, bacteria, and cancers, and can contribute to the evolution of drug resistance and immune escape. However, it is difficult to directly estimate epistatic effects from sampled observations of a population. At present, there are very few methods that can disentangle the effects of selection (including epistasis), mutation, recombination, genetic drift, and genetic linkage in evolving populations. Here we develop a method to infer epistasis, along with the fitness effects of individual mutations, from observed evolutionary histories. Simulations show that we can accurately infer pairwise epistatic interactions provided that there is sufficient genetic diversity in the data. Our method also allows us to identify which fitness parameters can be reliably inferred from a particular data set and which ones are unidentifiable. Our approach therefore allows for the inference of more complex models of selection from time-series genetic data, while also quantifying uncertainty in the inferred parameters.
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Affiliation(s)
- Muhammad Saqib Sohail
- Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong SAR, People’s Republic of China
| | - Raymond H Y Louie
- The Kirby Institute, University of New South Wales, Sydney, New South Wales, Australia
| | - Zhenchen Hong
- Department of Physics and Astronomy, University of California, Riverside, CA, USA
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32
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Lopes-Marques M, Silva R, Serrano C, Gomes V, Cardoso A, Prata MJ, Amorim A, Azevedo L. Complex interactions between p.His558Arg and linked variants in the sodium voltage-gated channel alpha subunit 5 (Na V 1.5). PeerJ 2022; 10:e13913. [PMID: 35996667 PMCID: PMC9392453 DOI: 10.7717/peerj.13913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 07/27/2022] [Indexed: 01/19/2023] Open
Abstract
Common genetic polymorphisms may modify the phenotypic outcome when co-occurring with a disease-causing variant, and therefore understanding their modulating role in health and disease is of great importance. The polymorphic p.His558Arg variant of the sodium voltage-gated channel alpha subunit 5 (Na V 1.5) encoded by the SCN5A gene is a case in point, as several studies have shown it can modify the clinical phenotype in a number of cardiac diseases. To evaluate the genetic backgrounds associated with this modulating effect, we reanalysed previous electrophysiological findings regarding the p.His558Arg variant and further assessed its patterns of genetic diversity in human populations. The Na V 1.5 p.His558Arg variant was found to be in linkage disequilibrium with six other polymorphic variants that previously were also associated with cardiac traits in GWAS analyses. On account of this, incongruent reports that Arg558 allele can compensate, aggravate or have no effect on Na V 1.5, likely might have arose due to a role of p.His558Arg depending on the additional linked variants. Altogether, these results indicate a major influence of the epistatic interactions between SCN5A variants, revealing also that phenotypic severity may depend on the polymorphic background associated to each individual genome.
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Affiliation(s)
- Monica Lopes-Marques
- IPATIMUP-Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal,Faculty of Sciences, University of Porto, Porto, Portugal,Population Genetics and Evolution, Institute of Innovation and Investigation in Health (i3S), Porto, Portugal
| | - Raquel Silva
- Center for Interdisciplinary Research in Health (CIIS), Universidade Católica Portuguesa, Faculdade de Medicina Dentária, Viseu, Portugal
| | - Catarina Serrano
- IPATIMUP-Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal,Faculty of Sciences, University of Porto, Porto, Portugal,Population Genetics and Evolution, Institute of Innovation and Investigation in Health (i3S), Porto, Portugal
| | - Verónica Gomes
- IPATIMUP-Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal,Population Genetics and Evolution, Institute of Innovation and Investigation in Health (i3S), Porto, Portugal
| | - Ana Cardoso
- IPATIMUP-Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal,Faculty of Sciences, University of Porto, Porto, Portugal,Population Genetics and Evolution, Institute of Innovation and Investigation in Health (i3S), Porto, Portugal
| | - Maria João Prata
- IPATIMUP-Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal,Faculty of Sciences, University of Porto, Porto, Portugal,Population Genetics and Evolution, Institute of Innovation and Investigation in Health (i3S), Porto, Portugal
| | - Antonio Amorim
- IPATIMUP-Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal,Faculty of Sciences, University of Porto, Porto, Portugal,Population Genetics and Evolution, Institute of Innovation and Investigation in Health (i3S), Porto, Portugal
| | - Luisa Azevedo
- IPATIMUP-Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal,Faculty of Sciences, University of Porto, Porto, Portugal,Population Genetics and Evolution, Institute of Innovation and Investigation in Health (i3S), Porto, Portugal
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33
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Johnson MS, Desai MM. Mutational robustness changes during long-term adaptation in laboratory budding yeast populations. eLife 2022; 11:76491. [PMID: 35880743 PMCID: PMC9355567 DOI: 10.7554/elife.76491] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
As an adapting population traverses the fitness landscape, its local neighborhood (i.e., the collection of fitness effects of single-step mutations) can change shape because of interactions with mutations acquired during evolution. These changes to the distribution of fitness effects can affect both the rate of adaptation and the accumulation of deleterious mutations. However, while numerous models of fitness landscapes have been proposed in the literature, empirical data on how this distribution changes during evolution remains limited. In this study, we directly measure how the fitness landscape neighborhood changes during laboratory adaptation. Using a barcode-based mutagenesis system, we measure the fitness effects of 91 specific gene disruption mutations in genetic backgrounds spanning 8000–10,000 generations of evolution in two constant environments. We find that the mean of the distribution of fitness effects decreases in one environment, indicating a reduction in mutational robustness, but does not change in the other. We show that these distribution-level patterns result from differences in the relative frequency of certain patterns of epistasis at the level of individual mutations, including fitness-correlated and idiosyncratic epistasis.
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Affiliation(s)
- Milo S Johnson
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
| | - Michael M Desai
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States
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34
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Steenwyk JL, Phillips MA, Yang F, Date SS, Graham TR, Berman J, Hittinger CT, Rokas A. An orthologous gene coevolution network provides insight into eukaryotic cellular and genomic structure and function. SCIENCE ADVANCES 2022; 8:eabn0105. [PMID: 35507651 PMCID: PMC9067921 DOI: 10.1126/sciadv.abn0105] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 03/16/2022] [Indexed: 06/14/2023]
Abstract
The evolutionary rates of functionally related genes often covary. We present a gene coevolution network inferred from examining nearly 3 million orthologous gene pairs from 332 budding yeast species spanning ~400 million years of evolution. Network modules provide insight into cellular and genomic structure and function. Examination of the phenotypic impact of network perturbation using deletion mutant data from the baker's yeast Saccharomyces cerevisiae, which were obtained from previously published studies, suggests that fitness in diverse environments is affected by orthologous gene neighborhood and connectivity. Mapping the network onto the chromosomes of S. cerevisiae and Candida albicans revealed that coevolving orthologous genes are not physically clustered in either species; rather, they are often located on different chromosomes or far apart on the same chromosome. The coevolution network captures the hierarchy of cellular structure and function, provides a roadmap for genotype-to-phenotype discovery, and portrays the genome as a linked ensemble of genes.
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Affiliation(s)
- Jacob L. Steenwyk
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Megan A. Phillips
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Feng Yang
- Shmunis School of Biomedical and Cancer Research, Tel Aviv University, Ramat Aviv, Israel
- Department of Pharmacology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
| | - Swapneeta S. Date
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Todd R. Graham
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
| | - Judith Berman
- Shmunis School of Biomedical and Cancer Research, Tel Aviv University, Ramat Aviv, Israel
| | - Chris Todd Hittinger
- Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, Center for Genomic Science Innovation, J.F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, WI, USA
| | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA
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35
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Feng S, Wu Z, Liang W, Zhang X, Cai X, Li J, Liang L, Lin D, Stoesser N, Doi Y, Zhong LL, Liu Y, Xia Y, Dai M, Zhang L, Chen X, Yang JR, Tian GB. Prediction of Antibiotic Resistance Evolution by Growth Measurement of All Proximal Mutants of Beta-Lactamase. Mol Biol Evol 2022; 39:msac086. [PMID: 35485492 PMCID: PMC9087888 DOI: 10.1093/molbev/msac086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
The antibiotic resistance crisis continues to threaten human health. Better predictions of the evolution of antibiotic resistance genes could contribute to the design of more sustainable treatment strategies. However, comprehensive prediction of antibiotic resistance gene evolution via laboratory approaches remains challenging. By combining site-specific integration and high-throughput sequencing, we quantified relative growth under the respective selection of cefotaxime or ceftazidime selection in ∼23,000 Escherichia coli MG1655 strains that each carried a unique, single-copy variant of the extended-spectrum β-lactamase gene blaCTX-M-14 at the chromosomal att HK022 site. Significant synergistic pleiotropy was observed within four subgenic regions, suggesting key regions for the evolution of resistance to both antibiotics. Moreover, we propose PEARP and PEARR, two deep-learning models with strong clinical correlations, for the prospective and retrospective prediction of blaCTX-M-14 evolution, respectively. Single to quintuple mutations of blaCTX-M-14 predicted to confer resistance by PEARP were significantly enriched among the clinical isolates harboring blaCTX-M-14 variants, and the PEARR scores matched the minimal inhibitory concentrations obtained for the 31 intermediates in all hypothetical trajectories. Altogether, we conclude that the measurement of local fitness landscape enables prediction of the evolutionary trajectories of antibiotic resistance genes, which could be useful for a broad range of clinical applications, from resistance prediction to designing novel treatment strategies.
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Affiliation(s)
- Siyuan Feng
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-sen University, Ministry of Education, Guangzhou 510080, China
| | - Zhuoxing Wu
- Department of Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
| | - Wanfei Liang
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-sen University, Ministry of Education, Guangzhou 510080, China
| | - Xin Zhang
- Department of Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiujuan Cai
- Department of Genetics and Cellular Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
| | - Jiachen Li
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-sen University, Ministry of Education, Guangzhou 510080, China
| | - Lujie Liang
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-sen University, Ministry of Education, Guangzhou 510080, China
| | - Daixi Lin
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-sen University, Ministry of Education, Guangzhou 510080, China
| | - Nicole Stoesser
- Modernising Medical Microbiology, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Yohei Doi
- Division of Infectious Diseases, University of Pittsburgh School of Medicine, Pittsburgh 15261, PA, USA
- Department of Microbiology, Fujita Health University School of Medicine, Aichi 470-1192, Japan
- Department of Infectious Diseases, Fujita Health University School of Medicine, Aichi 470-1192, Japan
| | - Lan-lan Zhong
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-sen University, Ministry of Education, Guangzhou 510080, China
| | - Yan Liu
- Clinical Laboratory, Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai 519000, China
| | - Yong Xia
- Department of Clinical Laboratory Medicine, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Min Dai
- School of Laboratory Medicine, Chengdu Medical College, Chengdu 610500, China
| | - Liyan Zhang
- Department of Clinical Laboratory, Guangdong Provincial People’s Hospital/Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, China
| | - Xiaoshu Chen
- Department of Genetics and Cellular Biology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
| | - Jian-Rong Yang
- Key Laboratory of Tropical Diseases Control, Sun Yat-sen University, Ministry of Education, Guangzhou 510080, China
- Department of Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Guo-bao Tian
- Department of Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-sen University, Ministry of Education, Guangzhou 510080, China
- School of Medicine, Xizang Minzu University, Xianyang, Shaanxi 712082, China
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Nachtegael C, Gravel B, Dillen A, Smits G, Nowé A, Papadimitriou S, Lenaerts T. Scaling up oligogenic diseases research with OLIDA: the Oligogenic Diseases Database. Database (Oxford) 2022; 2022:6566807. [PMID: 35411390 PMCID: PMC9216476 DOI: 10.1093/database/baac023] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 11/19/2022]
Abstract
Improving the understanding of the oligogenic nature of diseases requires access to high-quality, well-curated Findable, Accessible, Interoperable, Reusable (FAIR) data. Although first steps were taken with the development of the Digenic Diseases Database, leading to novel computational advancements to assist the field, these were also linked with a number of limitations, for instance, the ad hoc curation protocol and the inclusion of only digenic cases. The OLIgogenic diseases DAtabase (OLIDA) presents a novel, transparent and rigorous curation protocol, introducing a confidence scoring mechanism for the published oligogenic literature. The application of this protocol on the oligogenic literature generated a new repository containing 916 oligogenic variant combinations linked to 159 distinct diseases. Information extracted from the scientific literature is supplemented with current knowledge support obtained from public databases. Each entry is an oligogenic combination linked to a disease, labelled with a confidence score based on the level of genetic and functional evidence that supports its involvement in this disease. These scores allow users to assess the relevance and proof of pathogenicity of each oligogenic combination in the database, constituting markers for reporting improvements on disease-causing oligogenic variant combinations. OLIDA follows the FAIR principles, providing detailed documentation, easy data access through its application programming interface and website, use of unique identifiers and links to existing ontologies.
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Affiliation(s)
- Charlotte Nachtegael
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, Brussels 1050, Belgium
| | - Barbara Gravel
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, Brussels 1050, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
| | - Arnau Dillen
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
- Human Physiology and Sports Physiotherapy research group, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
| | - Guillaume Smits
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Hôpital Universitaire des Enfants Reine Fabiola, Université Libre de Bruxelles, Avenue Jean Joseph Crocq 15, Brussels 1020, Belgium
- Center of Human Genetics, Hôpital Erasme, Université Libre de Bruxelles, Route de Lennik 808, Brussels 1070, Belgium
| | - Ann Nowé
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
| | - Sofia Papadimitriou
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, Brussels 1050, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
| | - Tom Lenaerts
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de Bruxelles-Vrije Universiteit Brussel, Boulevard du Triomphe, CP 263, Brussels 1050, Belgium
- Machine Learning Group, Université Libre de Bruxelles, Boulevard du Triomphe, CP 212, Brussels 1050, Belgium
- Artificial Intelligence Laboratory, Vrije Universiteit Brussel, Pleinlaan 2, Brussels 1050, Belgium
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37
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Chen Z, Hu K, Yin Y, Tang D, Ni J, Li P, Wang L, Rong T, Liu J. Identification of a major QTL and genome-wide epistatic interactions for single vs. paired spikelets in a maize-teosinte F 2 population. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:9. [PMID: 37309321 PMCID: PMC10248651 DOI: 10.1007/s11032-022-01276-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Accepted: 01/16/2022] [Indexed: 06/14/2023]
Abstract
Maize ear carries paired spikelets, whereas the ear of its wild ancestor, teosinte, bears single spikelets. However, little is known about the genetic basis of the processes of transformation of single spikelets in teosinte ear to paired spikelets in maize ear. In this study, a two-ranked, paired-spikelets primitive maize and a two-ranked, single-spikelet teosinte were utilized to develop an F2 population, and quantitative trait locus (loci) (QTL) mapping for single vs. paired spikelets (PEDS) was performed. One major QTL (qPEDS3.1) for PEDS located on chromosome 3S was identified in the 162 F2 plants using the inclusive composite interval mapping of additive (ICIM-ADD) module, explaining 23.79% of the phenotypic variance. Out of the 409 F2 plants, 43 plants with PEDS = 0% and 43 plants with PEDS > 20% were selected for selective genotyping, and the QTL (qPEDS3.1) was detected again. Moreover, the QTL (qPEDS3.1) was validated in three environments, which explained 31.05%, 38.94%, and 23.16% of the phenotypic variance, respectively. In addition, 50 epistatic QTLs were detected in the 162 F2 plants using the two-locus epistatic QTL (ICIM-EPI) module; they were distributed on all 10 chromosomes and explained 94.40% of the total phenotypic variance. The results contribute to a better understanding of the genetic basis of domestication of paired spikelets and provide a genetic resource for future map-based cloning; in addition, the systematic dissection of epistatic interactions underlies a theoretical framework for overcoming epistatic effects on QTL fine mapping. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01276-x.
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Affiliation(s)
- Zhengjie Chen
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
- Industrial Crop Research Institute, Sichuan Academy of Agricultural Science, No.159 Huajin Avenue, Qingbaijiang District, Chengdu, 610300 Sichuan China
| | - Kun Hu
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
| | - Yong Yin
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
| | - Dengguo Tang
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
| | - Jixing Ni
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
| | - Peng Li
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
| | - Le Wang
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
| | - Tingzhao Rong
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
| | - Jian Liu
- Maize Research Institute, Sichuan Agricultural University, No.211 Huiming Road, Wenjiang District, Chengdu, 611130 Sichuan China
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38
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Puromycin Labeling Coupled with Proximity Ligation Assays to Define Sites of mRNA Translation in Drosophila Embryos and Human Cells. Methods Mol Biol 2021. [PMID: 34590282 DOI: 10.1007/978-1-0716-1740-3_15] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Genetic mutations, whether they occur within protein-coding or noncoding regions of the genome, can affect various aspects of gene expression by influencing the complex network of intra- and intermolecular interactions that occur between cellular nucleic acids and proteins. One aspect of gene expression control that can be impacted is the intracellular trafficking and translation of mRNA molecules. To study the occurrence and dynamics of translational regulation, researchers have developed approaches such as genome-wide ribosome profiling and artificial reporters that enable single molecule imaging. In this paper, we describe a complementary and optimized approach that combines puromycin labeling with a proximity ligation assay (Puro-PLA) to define sites of translation of specific mRNAs in tissues or cells. This method can be used to study the mechanisms driving the translation of select mRNAs and to access the impact of genetic mutations on local protein synthesis. This approach involves the treatment of cell or tissue specimens with puromycin to label nascently translated peptides, rapid fixation, followed by immunolabeling with appropriate primary and secondary antibodies coupled to PLA oligonucleotide probes, ligation, amplification, and signal detection via fluorescence microscopy. Puro-PLA can be performed at small scale in individual tubes or in chambered slides, or in a high-throughput setup with 96-well plate, for both in situ and in vitro experimentation.
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Luo Y, Jiang G, Yu T, Liu Y, Vo L, Ding H, Su Y, Qian WW, Zhao H, Peng J. ECNet is an evolutionary context-integrated deep learning framework for protein engineering. Nat Commun 2021; 12:5743. [PMID: 34593817 PMCID: PMC8484459 DOI: 10.1038/s41467-021-25976-8] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Accepted: 09/09/2021] [Indexed: 11/28/2022] Open
Abstract
Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited. Here, we report ECNet (evolutionary context-integrated neural network), a deep-learning algorithm that exploits evolutionary contexts to predict functional fitness for protein engineering. This algorithm integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. As such, it enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-order mutants. We show that ECNet predicts the sequence-function relationship more accurately as compared to existing machine learning algorithms by using ~50 deep mutational scanning and random mutagenesis datasets. Moreover, we used ECNet to guide the engineering of TEM-1 β-lactamase and identified variants with improved ampicillin resistance with high success rates.
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Affiliation(s)
- Yunan Luo
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA
| | - Guangde Jiang
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA
| | - Tianhao Yu
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA
| | - Yang Liu
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA
| | - Lam Vo
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA
| | - Hantian Ding
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA
| | - Yufeng Su
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA
| | - Wesley Wei Qian
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA
| | - Huimin Zhao
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA.
| | - Jian Peng
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA.
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40
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Quan M, Liu X, Du Q, Xiao L, Lu W, Fang Y, Li P, Ji L, Zhang D. Genome-wide association studies reveal the coordinated regulatory networks underlying photosynthesis and wood formation in Populus. JOURNAL OF EXPERIMENTAL BOTANY 2021; 72:5372-5389. [PMID: 33733665 DOI: 10.1093/jxb/erab122] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 03/16/2021] [Indexed: 06/12/2023]
Abstract
Photosynthesis and wood formation underlie the ability of trees to provide renewable resources and perform ecological functions; however, the genetic basis and regulatory pathways coordinating these two linked processes remain unclear. Here, we used a systems genetics strategy, integrating genome-wide association studies, transcriptomic analyses, and transgenic experiments, to investigate the genetic architecture of photosynthesis and wood properties among 435 unrelated individuals of Populus tomentosa, and unravel the coordinated regulatory networks resulting in two trait categories. We detected 222 significant single-nucleotide polymorphisms, annotated to 177 candidate genes, for 10 traits of photosynthesis and wood properties. Epistasis uncovered 74 epistatic interactions for phenotypes. Strikingly, we deciphered the coordinated regulation patterns of pleiotropic genes underlying phenotypic variations for two trait categories. Furthermore, expression quantitative trait nucleotide mapping and coexpression analysis were integrated to unravel the potential transcriptional regulatory networks of candidate genes coordinating photosynthesis and wood properties. Finally, heterologous expression of two pleiotropic genes, PtoMYB62 and PtoMYB80, in Arabidopsis thaliana demonstrated that they control regulatory networks balancing photosynthesis and stem secondary cell wall components, respectively. Our study provides insights into the regulatory mechanisms coordinating photosynthesis and wood formation in poplar, and should facilitate genetic breeding in trees via molecular design.
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Affiliation(s)
- Mingyang Quan
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, P. R. China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Xin Liu
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Qingzhang Du
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, P. R. China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Liang Xiao
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Wenjie Lu
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Yuanyuan Fang
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Peng Li
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Li Ji
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, P. R. China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
| | - Deqiang Zhang
- Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, P. R. China
- National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
- Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, P. R. China
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Jakutis G, Stainier DYR. Genotype-Phenotype Relationships in the Context of Transcriptional Adaptation and Genetic Robustness. Annu Rev Genet 2021; 55:71-91. [PMID: 34314597 DOI: 10.1146/annurev-genet-071719-020342] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Genetic manipulations with a robust and predictable outcome are critical to investigate gene function, as well as for therapeutic genome engineering. For many years, knockdown approaches and reagents including RNA interference and antisense oligonucleotides dominated functional studies; however, with the advent of precise genome editing technologies, CRISPR-based knockout systems have become the state-of-the-art tools for such studies. These technologies have helped decipher the role of thousands of genes in development and disease. Their use has also revealed how limited our understanding of genotype-phenotype relationships is. The recent discovery that certain mutations can trigger the transcriptional modulation of other genes, a phenomenon called transcriptional adaptation, has provided an additional explanation for the contradicting phenotypes observed in knockdown versus knockout models and increased awareness about the use of each of these approaches. In this review, we first cover the strengths and limitations of different gene perturbation strategies. Then we highlight the diverse ways in which the genotype-phenotype relationship can be discordant between these different strategies. Finally, we review the genetic robustness mechanisms that can lead to such discrepancies, paying special attention to the recently discovered phenomenon of transcriptional adaptation. Expected final online publication date for the Annual Review of Genetics, Volume 55 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Gabrielius Jakutis
- Department of Developmental Genetics, Max Planck Institute for Heart and Lung Research, 61231 Bad Nauheim, Germany;
| | - Didier Y R Stainier
- Department of Developmental Genetics, Max Planck Institute for Heart and Lung Research, 61231 Bad Nauheim, Germany; .,German Centre for Cardiovascular Research (DZHK), Partner site Rhine-Main, 60590 Frankfurt am Main, Germany.,Excellence Cluster Cardio-Pulmonary Institute (CPI), 35392 Giessen, Germany
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42
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The genetic architecture of primary biliary cholangitis. Eur J Med Genet 2021; 64:104292. [PMID: 34303876 DOI: 10.1016/j.ejmg.2021.104292] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 07/03/2021] [Accepted: 07/21/2021] [Indexed: 12/12/2022]
Abstract
Primary biliary cholangitis (PBC) is a rare autoimmune disease of the liver affecting the small bile ducts. From a genetic point of view, PBC is a complex trait and several genetic and environmental factors have been called in action to explain its etiopathogenesis. Similarly to other complex traits, PBC has benefited from the introduction of genome-wide association studies (GWAS), which identified many variants predisposing or protecting toward the development of the disease. While a progressive endeavour toward the characterization of candidate loci and downstream pathways is currently ongoing, there is still a relatively large portion of heritability of PBC to be revealed. In addition, genetic variation behind progression of the disease and therapeutic response are mostly to be investigated yet. This review outlines the state-of-the-art regarding the genetic architecture of PBC and provides some hints for future investigations, focusing on the study of gene-gene interactions, the application of whole-genome sequencing techniques, and the investigation of X chromosome that can be helpful to cover the missing heritability gap in PBC.
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43
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Lopes‐Marques M, Pacheco AR, Peixoto MJ, Cardoso AR, Serrano C, Amorim A, Prata MJ, Cooper DN, Azevedo L. Common polymorphic OTC variants can act as genetic modifiers of enzymatic activity. Hum Mutat 2021; 42:978-989. [PMID: 34015158 PMCID: PMC8362079 DOI: 10.1002/humu.24221] [Citation(s) in RCA: 6] [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: 12/12/2020] [Revised: 05/05/2021] [Accepted: 05/18/2021] [Indexed: 12/24/2022]
Abstract
Understanding the role of common polymorphisms in modulating the clinical phenotype when they co‐occur with a disease‐causing lesion is of critical importance in medical genetics. We explored the impact of apparently neutral common polymorphisms, using the gene encoding the urea cycle enzyme, ornithine transcarbamylase (OTC), as a model system. Distinct combinations of genetic backgrounds embracing two missense polymorphisms were created in cis with the pathogenic p.Arg40His replacement. In vitro enzymatic assays revealed that the polymorphic variants were able to modulate OTC activity both in the presence or absence of the pathogenic lesion. First, we found that the combination of the minor alleles of polymorphisms p.Lys46Arg and p.Gln270Arg significantly enhanced enzymatic activity in the wild‐type protein. Second, enzymatic assays revealed that the minor allele of the p.Gln270Arg polymorphism was capable of ameliorating OTC activity when combined in cis with the pathogenic p.Arg40His replacement. Structural analysis predicted that the minor allele of the p.Gln270Arg polymorphism would serve to stabilize the OTC wild‐type protein, thereby corroborating the results of the experimental assays. Our findings demonstrate the potential importance of cis‐interactions between common polymorphic variants and pathogenic missense mutations and illustrate how standing genetic variation can modulate protein function.
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Affiliation(s)
- Mónica Lopes‐Marques
- i3S‐Instituto de Investigação e Inovação em Saúde, Population Genetics and Evolution GroupUniversidade do PortoPortoPortugal
- IPATIMUP‐Institute of Molecular Pathology and Immunology, Population Genetics and Evolution GroupUniversity of PortoPortoPortugal
- Faculty of Sciences, Department of BiologyUniversity of PortoPortoPortugal
| | - Ana Rita Pacheco
- i3S‐Instituto de Investigação e Inovação em Saúde, Population Genetics and Evolution GroupUniversidade do PortoPortoPortugal
- IPATIMUP‐Institute of Molecular Pathology and Immunology, Population Genetics and Evolution GroupUniversity of PortoPortoPortugal
| | - Maria João Peixoto
- ICVS‐ Life and Health Sciences Research Institute, School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B's‐PT Government Associate LaboratoryBragaGuimarãesPortugal
| | - Ana Rita Cardoso
- i3S‐Instituto de Investigação e Inovação em Saúde, Population Genetics and Evolution GroupUniversidade do PortoPortoPortugal
- IPATIMUP‐Institute of Molecular Pathology and Immunology, Population Genetics and Evolution GroupUniversity of PortoPortoPortugal
- Faculty of Sciences, Department of BiologyUniversity of PortoPortoPortugal
| | - Catarina Serrano
- i3S‐Instituto de Investigação e Inovação em Saúde, Population Genetics and Evolution GroupUniversidade do PortoPortoPortugal
- IPATIMUP‐Institute of Molecular Pathology and Immunology, Population Genetics and Evolution GroupUniversity of PortoPortoPortugal
- Faculty of Sciences, Department of BiologyUniversity of PortoPortoPortugal
| | - António Amorim
- i3S‐Instituto de Investigação e Inovação em Saúde, Population Genetics and Evolution GroupUniversidade do PortoPortoPortugal
- IPATIMUP‐Institute of Molecular Pathology and Immunology, Population Genetics and Evolution GroupUniversity of PortoPortoPortugal
- Faculty of Sciences, Department of BiologyUniversity of PortoPortoPortugal
| | - Maria João Prata
- i3S‐Instituto de Investigação e Inovação em Saúde, Population Genetics and Evolution GroupUniversidade do PortoPortoPortugal
- IPATIMUP‐Institute of Molecular Pathology and Immunology, Population Genetics and Evolution GroupUniversity of PortoPortoPortugal
- Faculty of Sciences, Department of BiologyUniversity of PortoPortoPortugal
| | - David N. Cooper
- Institute of Medical Genetics; School of MedicineCardiff UniversityCardiffUK
| | - Luísa Azevedo
- i3S‐Instituto de Investigação e Inovação em Saúde, Population Genetics and Evolution GroupUniversidade do PortoPortoPortugal
- IPATIMUP‐Institute of Molecular Pathology and Immunology, Population Genetics and Evolution GroupUniversity of PortoPortoPortugal
- Faculty of Sciences, Department of BiologyUniversity of PortoPortoPortugal
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Montesinos-López A, Montesinos-López OA, Montesinos-López JC, Flores-Cortes CA, de la Rosa R, Crossa J. A guide for kernel generalized regression methods for genomic-enabled prediction. Heredity (Edinb) 2021; 126:577-596. [PMID: 33649571 PMCID: PMC8115678 DOI: 10.1038/s41437-021-00412-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 01/23/2021] [Accepted: 01/24/2021] [Indexed: 01/30/2023] Open
Abstract
The primary objective of this paper is to provide a guide on implementing Bayesian generalized kernel regression methods for genomic prediction in the statistical software R. Such methods are quite efficient for capturing complex non-linear patterns that conventional linear regression models cannot. Furthermore, these methods are also powerful for leveraging environmental covariates, such as genotype × environment (G×E) prediction, among others. In this study we provide the building process of seven kernel methods: linear, polynomial, sigmoid, Gaussian, Exponential, Arc-cosine 1 and Arc-cosine L. Additionally, we highlight illustrative examples for implementing exact kernel methods for genomic prediction under a single-environment, a multi-environment and multi-trait framework, as well as for the implementation of sparse kernel methods under a multi-environment framework. These examples are followed by a discussion on the strengths and limitations of kernel methods and, subsequently by conclusions about the main contributions of this paper.
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Affiliation(s)
- Abelardo Montesinos-López
- Departamento de Matemáticas, Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, 44430, Guadalajara, Jalisco, México
| | | | | | | | - Roberto de la Rosa
- Colegio de Postgraduados (CP), Campus Tabasco, Producción Agroalimentaria en el Trópico, H. Cárdenas, Tabasco, México
| | - José Crossa
- Colegio de Postgraduados, Campus Montecillos, CP 56230, Montecillos, Edo. de México, México.
- Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Km 45, CP 52640, Carretera Mexico-Veracruz, México.
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Saeidnia F, Majidi MM, Mirlohi A. Marker-trait association analysis for drought tolerance in smooth bromegrass. BMC PLANT BIOLOGY 2021; 21:116. [PMID: 33632123 PMCID: PMC7908751 DOI: 10.1186/s12870-021-02891-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 02/13/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Little information is available on the application of marker-trait association (MTA) analysis for traits related to drought tolerance in smooth bromegrass. The objectives of this study were to identify marker loci associated with important agronomic traits and drought tolerance indices as well as fining stable associations in a diverse panel of polycross derived genotypes of smooth bromegrass. Phenotypic evaluations were performed at two irrigation regimes (normal and deficit irrigation) during 2 years; and association analysis was done with 626 SRAP markers. RESULTS The results of population structure analysis identified three main subpopulations possessing significant genetic differences. Under normal irrigation, 68 and 57 marker-trait associations were identified using general linear model (GLM) and mixed linear mode1 (MLM), respectively. While under deficit irrigation, 61 and 54 markers were associated with the genes controlling the studied traits, based on these two models, respectively. Some of the markers were associated with more than one trait. It was revealed that markers Me1/Em5-11, Me1/Em3-15, and Me5/Em4-7 were consistently linked with drought-tolerance indices. CONCLUSION Following marker validation, the MTAs reported in this panel could be useful tools to initiate marker-assisted selection (MAS) and targeted trait introgression of smooth bromegrass under normal and deficit irrigation regimes, and possibly fine mapping and cloning of the underlying genes and QTLs.
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Affiliation(s)
- F. Saeidnia
- Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111 Iran
| | - M. M. Majidi
- Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111 Iran
| | - A. Mirlohi
- Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111 Iran
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Labroo MR, Studer AJ, Rutkoski JE. Heterosis and Hybrid Crop Breeding: A Multidisciplinary Review. Front Genet 2021; 12:643761. [PMID: 33719351 PMCID: PMC7943638 DOI: 10.3389/fgene.2021.643761] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 02/08/2021] [Indexed: 11/24/2022] Open
Abstract
Although hybrid crop varieties are among the most popular agricultural innovations, the rationale for hybrid crop breeding is sometimes misunderstood. Hybrid breeding is slower and more resource-intensive than inbred breeding, but it allows systematic improvement of a population by recurrent selection and exploitation of heterosis simultaneously. Inbred parental lines can identically reproduce both themselves and their F1 progeny indefinitely, whereas outbred lines cannot, so uniform outbred lines must be bred indirectly through their inbred parents to harness heterosis. Heterosis is an expected consequence of whole-genome non-additive effects at the population level over evolutionary time. Understanding heterosis from the perspective of molecular genetic mechanisms alone may be elusive, because heterosis is likely an emergent property of populations. Hybrid breeding is a process of recurrent population improvement to maximize hybrid performance. Hybrid breeding is not maximization of heterosis per se, nor testing random combinations of individuals to find an exceptional hybrid, nor using heterosis in place of population improvement. Though there are methods to harness heterosis other than hybrid breeding, such as use of open-pollinated varieties or clonal propagation, they are not currently suitable for all crops or production environments. The use of genomic selection can decrease cycle time and costs in hybrid breeding, particularly by rapidly establishing heterotic pools, reducing testcrossing, and limiting the loss of genetic variance. Open questions in optimal use of genomic selection in hybrid crop breeding programs remain, such as how to choose founders of heterotic pools, the importance of dominance effects in genomic prediction, the necessary frequency of updating the training set with phenotypic information, and how to maintain genetic variance and prevent fixation of deleterious alleles.
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Affiliation(s)
| | | | - Jessica E. Rutkoski
- Department of Crop Sciences, University of Illinois at Urbana–Champaign, Urbana, IL, United States
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Kryazhimskiy S. Emergence and propagation of epistasis in metabolic networks. eLife 2021; 10:e60200. [PMID: 33527897 PMCID: PMC7924954 DOI: 10.7554/elife.60200] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 02/01/2021] [Indexed: 12/11/2022] Open
Abstract
Epistasis is often used to probe functional relationships between genes, and it plays an important role in evolution. However, we lack theory to understand how functional relationships at the molecular level translate into epistasis at the level of whole-organism phenotypes, such as fitness. Here, I derive two rules for how epistasis between mutations with small effects propagates from lower- to higher-level phenotypes in a hierarchical metabolic network with first-order kinetics and how such epistasis depends on topology. Most importantly, weak epistasis at a lower level may be distorted as it propagates to higher levels. Computational analyses show that epistasis in more realistic models likely follows similar, albeit more complex, patterns. These results suggest that pairwise inter-gene epistasis should be common, and it should generically depend on the genetic background and environment. Furthermore, the epistasis coefficients measured for high-level phenotypes may not be sufficient to fully infer the underlying functional relationships.
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Affiliation(s)
- Sergey Kryazhimskiy
- Division of Biological Sciences, University of California, San DiegoLa JollaUnited States
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Saito Y, Koya J, Kataoka K. Multiple mutations within individual oncogenes. Cancer Sci 2021; 112:483-489. [PMID: 33073435 PMCID: PMC7894016 DOI: 10.1111/cas.14699] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 10/05/2020] [Accepted: 10/14/2020] [Indexed: 01/12/2023] Open
Abstract
Recent studies of the cancer genome have identified numerous patients harboring multiple mutations (MM) within individual oncogenes. These MM (de novo MM) in cis synergistically activate the mutated oncogene and promote tumorigenesis, indicating a positive epistatic interaction between mutations. The relatively frequent de novo MM suggest that intramolecular positive epistasis is widespread in oncogenes. Studies also suggest that negative and higher-order epistasis affects de novo MM. Comparison of de novo MM and MM associated with drug-resistant secondary mutations (secondary MM) revealed several similarities with respect to allelic configuration, mutational selection and functionality of individual mutations. Conversely, they have several differences, most notably the difference in drug sensitivities. Secondary MM usually confer resistance to molecularly targeted therapies, whereas several de novo MM are associated with increased sensitivity, implying that both can be useful as therapeutic biomarkers. Unlike secondary MM in which specific secondary resistant mutations are selected, minor (infrequent) functionally weak mutations are convergently selected in de novo MM, which may provide an explanation as to why such mutations accumulate in cancer. The third type of MM is MM from different subclones. This type of MM is associated with parallel evolution, which may contribute to relapse and treatment failure. Collectively, MM within individual oncogenes are diverse, but all types of MM are associated with cancer evolution and therapeutic response. Further evaluation of oncogenic MM is warranted to gain a deeper understanding of cancer genetics and evolution.
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Affiliation(s)
- Yuki Saito
- Division of Molecular Oncology, National Cancer Center Research Institute, Tokyo, Japan.,Department of Gastroenterology, Keio University School of Medicine, Tokyo, Japan
| | - Junji Koya
- Division of Molecular Oncology, National Cancer Center Research Institute, Tokyo, Japan
| | - Keisuke Kataoka
- Division of Molecular Oncology, National Cancer Center Research Institute, Tokyo, Japan
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Tyler AL, Emerson J, El Kassaby B, Wells AE, Philip VM, Carter GW. The Combined Analysis of Pleiotropy and Epistasis (CAPE). Methods Mol Biol 2021; 2212:55-67. [PMID: 33733350 DOI: 10.1007/978-1-0716-0947-7_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Epistasis, or gene-gene interaction, contributes substantially to trait variation in organisms ranging from yeast to humans, and modeling epistasis directly is critical to understanding the genotype-phenotype map. However, inference of genetic interactions is challenging compared to inference of individual allele effects due to low statistical power. Furthermore, genetic interactions can appear inconsistent across different quantitative traits, presenting a challenge for the interpretation of detected interactions. Here we present a method called the Combined Analysis of Pleiotropy and Epistasis (CAPE) that combines information across multiple quantitative traits to infer directed epistatic interactions. By combining information across multiple traits, CAPE not only increases power to detect genetic interactions but also interprets these interactions across traits to identify a single interaction that is consistent across all observed data. This method generates informative, interpretable interaction networks that explain how variants interact with each other to influence groups of related traits. This method could potentially be used to link genetic variants to gene expression, physiological endophenotypes, and higher-level disease traits.
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Lee HMT, Sayegh NY, Gayek AS, Jao SLJ, Chalfie M, Zheng C. Epistatic, synthetic, and balancing interactions among tubulin missense mutations affecting neurite growth in Caenorhabditis elegans. Mol Biol Cell 2020; 32:331-347. [PMID: 33378215 PMCID: PMC8098816 DOI: 10.1091/mbc.e20-07-0492] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Mutations in tubulins affect microtubule (MT) dynamics and functions during neuronal differentiation and their genetic interaction provides insights into the regulation of MT functions. We previously used Caenorhabditis elegans touch receptor neurons to analyze the cellular impact of tubulin mutations and reported the phenotypes of 67 tubulin missense mutations, categorized into three classes: loss-of-function (lf), antimorphic (anti), and neomorphic (neo) alleles. In this study, we isolated 54 additional tubulin alleles through suppressor screens in sensitized backgrounds that caused excessive neurite growth. These alleles included 32 missense mutations not analyzed before, bringing the total number of mutations in our collection to 99. Phenotypic characterization of these newly isolated mutations identified three new types of alleles: partial lf and weak neo alleles of mec-7/β-tubulin that had subtle effects and strong anti alleles of mec-12/α-tubulin. We also discovered complex genetic interactions among the tubulin mutations, including the suppression of neo mutations by intragenic lf and anti alleles, additive and synthetic effects between mec-7 neo alleles, and unexpected epistasis, in which weaker neo alleles masked the effects of stronger neo alleles in inducing ectopic neurite growth. We also observed balancing between neo and anti alleles, whose respective MT-hyperstablizing and -destabilizing effects neutralized each other.
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Affiliation(s)
- Ho Ming Terence Lee
- School of Biological Sciences, The University of Hong Kong, Hong Kong SAR, China
| | | | - A Sophia Gayek
- Department of Biological Sciences, Columbia University, New York, NY 10027
| | | | - Martin Chalfie
- Department of Biological Sciences, Columbia University, New York, NY 10027
| | - Chaogu Zheng
- School of Biological Sciences, The University of Hong Kong, Hong Kong SAR, China
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