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Wei X, Chen M, Zhang Q, Gong J, Liu J, Yong K, Wang Q, Fan J, Chen S, Hua H, Luo Z, Zhao X, Wang X, Li W, Cong J, Yu X, Wang Z, Huang R, Chen J, Zhou X, Qiu J, Xu P, Murray J, Wang H, Xu Y, Xu C, Xu G, Yang J, Han B, Huang X. Genomic investigation of 18,421 lines reveals the genetic architecture of rice. Science 2024; 385:eadm8762. [PMID: 38963845 DOI: 10.1126/science.adm8762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/29/2024] [Indexed: 07/06/2024]
Abstract
Understanding how numerous quantitative trait loci (QTL) shape phenotypic variation is an important question in genetics. To address this, we established a permanent population of 18,421 (18K) rice lines with reduced population structure. We generated reference-level genome assemblies of the founders and genotyped all 18K-rice lines through whole-genome sequencing. Through high-resolution mapping, 96 high-quality candidate genes contributing to variation in 16 traits were identified, including OsMADS22 and OsFTL1 verified as causal genes for panicle number and heading date, respectively. We identified epistatic QTL pairs and constructed a genetic interaction network with 19 genes serving as hubs. Overall, 170 masking epistasis pairs were characterized, serving as an important factor contributing to genetic background effects across diverse varieties. The work provides a basis to guide grain yield and quality improvements in rice.
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Affiliation(s)
- Xin Wei
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Mengjiao Chen
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Qi Zhang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Junyi Gong
- State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310006, China
| | - Jie Liu
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Kaicheng Yong
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Qin Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jiongjiong Fan
- State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310006, China
| | - Suhui Chen
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Hua Hua
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Zhaowei Luo
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xiaoyan Zhao
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xuan Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Wei Li
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jia Cong
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xiting Yu
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Zhihan Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Ruipeng Huang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jiaxin Chen
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xiaoyi Zhou
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jie Qiu
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Ping Xu
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jeremy Murray
- CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200233, China
| | - Hai Wang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Yang Xu
- Key Laboratory of Plant Functional Genomics of Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou 225009, China
| | - Chenwu Xu
- Key Laboratory of Plant Functional Genomics of Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou 225009, China
| | - Gen Xu
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
| | - Jinliang Yang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
| | - Bin Han
- CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200233, China
| | - Xuehui Huang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
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Hale JJ, Matsui T, Goldstein I, Mullis MN, Roy KR, Ville CN, Miller D, Wang C, Reynolds T, Steinmetz LM, Levy SF, Ehrenreich IM. Genome-scale analysis of interactions between genetic perturbations and natural variation. Nat Commun 2024; 15:4234. [PMID: 38762544 PMCID: PMC11102447 DOI: 10.1038/s41467-024-48626-1] [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: 06/05/2023] [Accepted: 04/30/2024] [Indexed: 05/20/2024] Open
Abstract
Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual's response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.
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Affiliation(s)
- Joseph J Hale
- Department of Biological Sciences, Molecular and Computational Biology Section, University of Southern California, Los Angeles, CA, 90089, USA
| | - Takeshi Matsui
- SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA
| | - Ilan Goldstein
- Department of Biological Sciences, Molecular and Computational Biology Section, University of Southern California, Los Angeles, CA, 90089, USA
| | - Martin N Mullis
- Department of Biological Sciences, Molecular and Computational Biology Section, University of Southern California, Los Angeles, CA, 90089, USA
| | - Kevin R Roy
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Christopher Ne Ville
- Department of Biological Sciences, Molecular and Computational Biology Section, University of Southern California, Los Angeles, CA, 90089, USA
| | - Darach Miller
- SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA
| | - Charley Wang
- Department of Biological Sciences, Molecular and Computational Biology Section, University of Southern California, Los Angeles, CA, 90089, USA
| | - Trevor Reynolds
- Department of Biological Sciences, Molecular and Computational Biology Section, University of Southern California, Los Angeles, CA, 90089, USA
| | - Lars M Steinmetz
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Sasha F Levy
- SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA.
- BacStitch DNA, Los Altos, CA, USA.
| | - Ian M Ehrenreich
- Department of Biological Sciences, Molecular and Computational Biology Section, University of Southern California, Los Angeles, CA, 90089, USA.
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Hale JJ, Matsui T, Goldstein I, Mullis MN, Roy KR, Ville CN, Miller D, Wang C, Reynolds T, Steinmetz LM, Levy SF, Ehrenreich IM. Genome-scale analysis of interactions between genetic perturbations and natural variation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.06.539663. [PMID: 38293072 PMCID: PMC10827069 DOI: 10.1101/2023.05.06.539663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 7,700 CRISPRi perturbations targeting 1,712 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual's response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.
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Affiliation(s)
- Joseph J. Hale
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Takeshi Matsui
- SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA
| | - Ilan Goldstein
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Martin N. Mullis
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Kevin R. Roy
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Chris Ne Ville
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Darach Miller
- SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA
| | - Charley Wang
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Trevor Reynolds
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Lars M. Steinmetz
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Sasha F. Levy
- SLAC National Accelerator Laboratory, Menlo Park, CA, 94025, USA
- Present address: BacStitch DNA, Los Altos, California, USA
| | - Ian M. Ehrenreich
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
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Tsouris A, Fournier T, Friedrich A, Hou J, Dunham MJ, Schacherer J. Species-wide survey of the expressivity and complexity spectrum of traits in yeast. PLoS Genet 2024; 20:e1011119. [PMID: 38236897 PMCID: PMC10826966 DOI: 10.1371/journal.pgen.1011119] [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: 08/28/2023] [Revised: 01/30/2024] [Accepted: 01/02/2024] [Indexed: 01/31/2024] Open
Abstract
Assessing the complexity and expressivity of traits at the species level is an essential first step to better dissect the genotype-phenotype relationship. As trait complexity behaves dynamically, the classic dichotomy between monogenic and complex traits is too simplistic. However, no systematic assessment of this complexity spectrum has been carried out on a population scale to date. In this context, we generated a large diallel hybrid panel composed of 190 unique hybrids coming from 20 natural isolates representative of the S. cerevisiae genetic diversity. For each of these hybrids, a large progeny of 160 individuals was obtained, leading to a total of 30,400 offspring individuals. Their mitotic growth was evaluated on 38 conditions inducing various cellular stresses. We developed a classification algorithm to analyze the phenotypic distributions of offspring and assess the trait complexity. We clearly found that traits are mainly complex at the population level. On average, we found that 91.2% of cross/trait combinations exhibit high complexity, while monogenic and oligogenic cases accounted for only 4.1% and 4.7%, respectively. However, the complexity spectrum is very dynamic, trait specific and tightly related to genetic backgrounds. Overall, our study provided greater insight into trait complexity as well as the underlying genetic basis of its spectrum in a natural population.
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Affiliation(s)
- Andreas Tsouris
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
| | - Téo Fournier
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
| | - Anne Friedrich
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
| | - Jing Hou
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
| | - Maitreya J. Dunham
- Genome Sciences Department, University of Washington, Seattle, Washington, United States of America
| | - Joseph Schacherer
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
- Institut Universitaire de France (IUF), Paris, France
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5
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Sauters TJC, Roth C, Murray D, Sun S, Floyd Averette A, Onyishi CU, May RC, Heitman J, Magwene PM. Amoeba predation of Cryptococcus: A quantitative and population genomic evaluation of the accidental pathogen hypothesis. PLoS Pathog 2023; 19:e1011763. [PMID: 37956179 PMCID: PMC10681322 DOI: 10.1371/journal.ppat.1011763] [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: 04/18/2023] [Revised: 11/27/2023] [Accepted: 10/18/2023] [Indexed: 11/15/2023] Open
Abstract
The "Amoeboid Predator-Fungal Animal Virulence Hypothesis" posits that interactions with environmental phagocytes shape the evolution of virulence traits in fungal pathogens. In this hypothesis, selection to avoid predation by amoeba inadvertently selects for traits that contribute to fungal escape from phagocytic immune cells. Here, we investigate this hypothesis in the human fungal pathogens Cryptococcus neoformans and Cryptococcus deneoformans. Applying quantitative trait locus (QTL) mapping and comparative genomics, we discovered a cross-species QTL region that is responsible for variation in resistance to amoeba predation. In C. neoformans, this same QTL was found to have pleiotropic effects on melanization, an established virulence factor. Through fine mapping and population genomic comparisons, we identified the gene encoding the transcription factor Bzp4 that underlies this pleiotropic QTL and we show that decreased expression of this gene reduces melanization and increases susceptibility to amoeba predation. Despite the joint effects of BZP4 on amoeba resistance and melanin production, we find no relationship between BZP4 genotype and escape from macrophages or virulence in murine models of disease. Our findings provide new perspectives on how microbial ecology shapes the genetic architecture of fungal virulence, and suggests the need for more nuanced models for the evolution of pathogenesis that account for the complexities of both microbe-microbe and microbe-host interactions.
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Affiliation(s)
- Thomas J. C. Sauters
- Department of Biology, Duke University, Durham, North Carolina, United States of America
- University Program in Genetics and Genomics, Duke University, Durham, North Carolina, United States of America
| | - Cullen Roth
- Department of Biology, Duke University, Durham, North Carolina, United States of America
- University Program in Genetics and Genomics, Duke University, Durham, North Carolina, United States of America
| | - Debra Murray
- Department of Biology, Duke University, Durham, North Carolina, United States of America
| | - Sheng Sun
- Department of Molecular Genetics and Microbiology, Duke University, Durham, North Carolina, United States of America
| | - Anna Floyd Averette
- Department of Molecular Genetics and Microbiology, Duke University, Durham, North Carolina, United States of America
| | - Chinaemerem U. Onyishi
- School of Biosciences, College of Life and Environmental Sciences, The University of Birmingham, Birmingham, United Kingdom
| | - Robin C. May
- School of Biosciences, College of Life and Environmental Sciences, The University of Birmingham, Birmingham, United Kingdom
| | - Joseph Heitman
- Department of Molecular Genetics and Microbiology, Duke University, Durham, North Carolina, United States of America
| | - Paul M. Magwene
- Department of Biology, Duke University, Durham, North Carolina, United States of America
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Cacheiro P, Smedley D. Essential genes: a cross-species perspective. Mamm Genome 2023; 34:357-363. [PMID: 36897351 PMCID: PMC10382395 DOI: 10.1007/s00335-023-09984-1] [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: 12/15/2022] [Accepted: 02/17/2023] [Indexed: 03/11/2023]
Abstract
Protein coding genes exhibit different degrees of intolerance to loss-of-function variation. The most intolerant genes, whose function is essential for cell or/and organism survival, inform on fundamental biological processes related to cell proliferation and organism development and provide a window on the molecular mechanisms of human disease. Here we present a brief overview of the resources and knowledge gathered around gene essentiality, from cancer cell lines to model organisms to human development. We outline the implications of using different sources of evidence and definitions to determine which genes are essential and highlight how information on the essentiality status of a gene can inform novel disease gene discovery and therapeutic target identification.
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Affiliation(s)
- Pilar Cacheiro
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Damian Smedley
- William Harvey Research Institute, Queen Mary University of London, London, UK.
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Aromolaran OT, Isewon I, Adedeji E, Oswald M, Adebiyi E, Koenig R, Oyelade J. Heuristic-enabled active machine learning: A case study of predicting essential developmental stage and immune response genes in Drosophila melanogaster. PLoS One 2023; 18:e0288023. [PMID: 37556452 PMCID: PMC10411809 DOI: 10.1371/journal.pone.0288023] [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: 04/03/2023] [Accepted: 06/18/2023] [Indexed: 08/11/2023] Open
Abstract
Computational prediction of absolute essential genes using machine learning has gained wide attention in recent years. However, essential genes are mostly conditional and not absolute. Experimental techniques provide a reliable approach of identifying conditionally essential genes; however, experimental methods are laborious, time and resource consuming, hence computational techniques have been used to complement the experimental methods. Computational techniques such as supervised machine learning, or flux balance analysis are grossly limited due to the unavailability of required data for training the model or simulating the conditions for gene essentiality. This study developed a heuristic-enabled active machine learning method based on a light gradient boosting model to predict essential immune response and embryonic developmental genes in Drosophila melanogaster. We proposed a new sampling selection technique and introduced a heuristic function which replaces the human component in traditional active learning models. The heuristic function dynamically selects the unlabelled samples to improve the performance of the classifier in the next iteration. Testing the proposed model with four benchmark datasets, the proposed model showed superior performance when compared to traditional active learning models (random sampling and uncertainty sampling). Applying the model to identify conditionally essential genes, four novel essential immune response genes and a list of 48 novel genes that are essential in embryonic developmental condition were identified. We performed functional enrichment analysis of the predicted genes to elucidate their biological processes and the result evidence our predictions. Immune response and embryonic development related processes were significantly enriched in the essential immune response and embryonic developmental genes, respectively. Finally, we propose the predicted essential genes for future experimental studies and use of the developed tool accessible at http://heal.covenantuniversity.edu.ng for conditional essentiality predictions.
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Affiliation(s)
- Olufemi Tony Aromolaran
- Department of Computer & Information Sciences, Covenant University, Ota, Ogun State, Nigeria
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
| | - Itunu Isewon
- Department of Computer & Information Sciences, Covenant University, Ota, Ogun State, Nigeria
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
| | - Eunice Adedeji
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
- Department of Biochemistry, Covenant University, Ota, Ogun State, Nigeria
| | - Marcus Oswald
- Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, Am Klinikum, Jena, Germany
- Institute of Infectious Diseases and Infection Control, Jena University Hospital, Am Klinikum, Jena, Germany
| | - Ezekiel Adebiyi
- Department of Computer & Information Sciences, Covenant University, Ota, Ogun State, Nigeria
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
| | - Rainer Koenig
- Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, Am Klinikum, Jena, Germany
- Institute of Infectious Diseases and Infection Control, Jena University Hospital, Am Klinikum, Jena, Germany
| | - Jelili Oyelade
- Department of Computer & Information Sciences, Covenant University, Ota, Ogun State, Nigeria
- Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Ogun State, Nigeria
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Loeillet S, Nicolas A. DNA polymerase δ: A single Pol31 polymorphism suppresses the strain background-specific lethality of Pol32 inactivation in Saccharomyces cerevisiae. DNA Repair (Amst) 2023; 127:103514. [PMID: 37244009 DOI: 10.1016/j.dnarep.2023.103514] [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: 02/07/2023] [Revised: 05/12/2023] [Accepted: 05/14/2023] [Indexed: 05/29/2023]
Abstract
The evolutionarily conserved DNA polymerase delta (Polδ) plays several essential roles in eukaryotic DNA replication and repair, responsible for the synthesis of the lagging-strand, lower replicative mutagenesis via its proof-reading exonuclease activity and synthetizes both strands during break-induced replication. In Saccharomyces cerevisiae, the Polδ protein complex consists of three subunits encoded by the POL3, POL31 and POL32 genes. Surprisingly, in contrast to POL3 and POL31, the POL32 gene deletion was found to be viable but lethal in all other eukaryotes, raising the question to which extent the viability of the POL32 deletion in S. cerevisiae was species specific. To address this issue, we inactivated the POL32 gene in 10 evolutionary close or distant S. cerevisiae strains and found that POL32 was either essential (3 strains including SK1), non-essential (5 strains including the reference S288C strain) or confers a slow-growth phenotype (2 strains). Whole-genome sequencing of S288C/SK1 pol32∆ meiotic segregants identified the lethal/suppressor effect of the single Pol31-C43Y polymorphism. Consistently, the introduction of the Pol31-43C allele in the SK1 and West African (WA) pol32∆ mutants was sufficient to restore cell viability and wild-type growth upon introduction of two copies of POL31-43C in the SK1 haploid strain. Reciprocally, introduction of the SK1 POL31-43Y allele in the S288C pol32∆ mutant was lethal. Sequence analyses of the POL31 polymorphisms in the 1,011 yeasts genome dataset correlates with the strict occurrence of the POL31-43Y allele in the yeast African palm wine clade. Differently, the single Pol31-E400G polymorphism confers pol32∆ lethality in the Malaysian strain. In the yeast two-hybrid assay, we observed a weakened interaction between Pol3 and Pol31-43Y versus Pol31-43C suggesting an insufficient level of the Polδ holoenzyme stability/activity. Thus, the enigmatic non-essentiality of Pol32 in S. cerevisiae results from single Pol31 amino acid polymorphism and is clade rather than species specific.
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Affiliation(s)
- S Loeillet
- Institut Curie Research Center, CNRS UMR3244, PSL Research University, 26 rue d'Ulm, 75248 Paris Cedex 05, France
| | - A Nicolas
- Institut Curie Research Center, CNRS UMR3244, PSL Research University, 26 rue d'Ulm, 75248 Paris Cedex 05, France; IRCAN, CNRS UMR7284, INSERM U1081, Université Côte d'Azur, 28 avenue de Valombrose, 06107 Nice, France.
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9
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Klinkaewboonwong N, Ohnuki S, Chadani T, Nishida I, Ushiyama Y, Tomiyama S, Isogai A, Goshima T, Ghanegolmohammadi F, Nishi T, Kitamoto K, Akao T, Hirata D, Ohya Y. Targeted Mutations Produce Divergent Characteristics in Pedigreed Sake Yeast Strains. Microorganisms 2023; 11:1274. [PMID: 37317248 DOI: 10.3390/microorganisms11051274] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 04/29/2023] [Accepted: 05/09/2023] [Indexed: 06/16/2023] Open
Abstract
Modification of the genetic background and, in some cases, the introduction of targeted mutations can play a critical role in producing trait characteristics during the breeding of crops, livestock, and microorganisms. However, the question of how similar trait characteristics emerge when the same target mutation is introduced into different genetic backgrounds is unclear. In a previous study, we performed genome editing of AWA1, CAR1, MDE1, and FAS2 on the standard sake yeast strain Kyokai No. 7 to breed a sake yeast with multiple excellent brewing characteristics. By introducing the same targeted mutations into other pedigreed sake yeast strains, such as Kyokai strains No. 6, No. 9, and No. 10, we were able to create sake yeasts with the same excellent brewing characteristics. However, we found that other components of sake made by the genome-edited yeast strains did not change in the exact same way. For example, amino acid and isobutanol contents differed among the strain backgrounds. We also showed that changes in yeast cell morphology induced by the targeted mutations also differed depending on the strain backgrounds. The number of commonly changed morphological parameters was limited. Thus, divergent characteristics were produced by the targeted mutations in pedigreed sake yeast strains, suggesting a breeding strategy to generate a variety of sake yeasts with excellent brewing characteristics.
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Affiliation(s)
- Norapat Klinkaewboonwong
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan
| | - Shinsuke Ohnuki
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan
| | - Tomoya Chadani
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan
| | - Ikuhisa Nishida
- Sakeology Center, Niigata University, 2-8050, Ikarashi, Niigata 950-2181, Japan
| | - Yuto Ushiyama
- Sakeology Course, Graduate School of Science and Technology, Niigata University, 2-8050, Ikarashi, Niigata 950-2181, Japan
| | - Saki Tomiyama
- Sakeology Course, Graduate School of Science and Technology, Niigata University, 2-8050, Ikarashi, Niigata 950-2181, Japan
| | - Atsuko Isogai
- National Research Institute of Brewing, Higashi-Hiroshima, Hiroshima 739-0046, Japan
- Program of Biotechnology, Graduate School of Integrated Sciences for Life, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8530, Japan
| | - Tetsuya Goshima
- National Research Institute of Brewing, Higashi-Hiroshima, Hiroshima 739-0046, Japan
| | - Farzan Ghanegolmohammadi
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Tomoyuki Nishi
- Sake Research Center, Asahi Sake Brewing Co., Ltd., Nagaoka, Niigata 949-5494, Japan
| | - Katsuhiko Kitamoto
- Department of Pharmaceutical and Medical Business Sciences, Nihon Pharmaceutical University, Bunkyo-ku, Tokyo 113-0034, Japan
| | - Takeshi Akao
- National Research Institute of Brewing, Higashi-Hiroshima, Hiroshima 739-0046, Japan
- Program of Biotechnology, Graduate School of Integrated Sciences for Life, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8530, Japan
| | - Dai Hirata
- Sakeology Center, Niigata University, 2-8050, Ikarashi, Niigata 950-2181, Japan
- Sakeology Course, Graduate School of Science and Technology, Niigata University, 2-8050, Ikarashi, Niigata 950-2181, Japan
- Program of Biotechnology, Graduate School of Integrated Sciences for Life, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima 739-8530, Japan
- Sake Research Center, Asahi Sake Brewing Co., Ltd., Nagaoka, Niigata 949-5494, Japan
| | - Yoshikazu Ohya
- Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8562, Japan
- Collaborative Research Institute for Innovative Microbiology, The University of Tokyo, Tokyo 113-8657, Japan
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10
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Messner CB, Demichev V, Muenzner J, Aulakh SK, Barthel N, Röhl A, Herrera-Domínguez L, Egger AS, Kamrad S, Hou J, Tan G, Lemke O, Calvani E, Szyrwiel L, Mülleder M, Lilley KS, Boone C, Kustatscher G, Ralser M. The proteomic landscape of genome-wide genetic perturbations. Cell 2023; 186:2018-2034.e21. [PMID: 37080200 PMCID: PMC7615649 DOI: 10.1016/j.cell.2023.03.026] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 01/20/2023] [Accepted: 03/21/2023] [Indexed: 04/22/2023]
Abstract
Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.
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Affiliation(s)
- Christoph B Messner
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK; Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, 7265 Davos, Switzerland
| | - Vadim Demichev
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK; Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany; Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge CB2 1QW, UK
| | - Julia Muenzner
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Simran K Aulakh
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK
| | - Natalie Barthel
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Annika Röhl
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | | | - Anna-Sophia Egger
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK
| | - Stephan Kamrad
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK
| | - Jing Hou
- The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada
| | - Guihong Tan
- The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada
| | - Oliver Lemke
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Enrica Calvani
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK
| | - Lukasz Szyrwiel
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK; Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Michael Mülleder
- Charité Universitätsmedizin, Core Facility - High Throughput Mass Spectrometry, 10117 Berlin, Germany
| | - Kathryn S Lilley
- Department of Biochemistry, Cambridge Centre for Proteomics, University of Cambridge, Cambridge CB2 1QW, UK
| | - Charles Boone
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada; The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; RIKEN Center for Sustainable Resource Science, Wako, 351-0198 Saitama, Japan
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh EH9 3BF, Scotland, UK.
| | - Markus Ralser
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW1 1AT, UK; Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany; The Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK; Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany.
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11
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Schaal KA, Yu YTN, Vasse M, Velicer GJ. Allopatric divergence of cooperators confers cheating resistance and limits effects of a defector mutation. BMC Ecol Evol 2022; 22:141. [PMID: 36510120 PMCID: PMC9746145 DOI: 10.1186/s12862-022-02094-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 11/23/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Social defectors may meet diverse cooperators. Genotype-by-genotype interactions may constrain the ranges of cooperators upon which particular defectors can cheat, limiting cheater spread. Upon starvation, the soil bacterium Myxococcus xanthus cooperatively develops into spore-bearing fruiting bodies, using a complex regulatory network and several intercellular signals. Some strains (cheaters) are unable to sporulate effectively in pure culture due to mutations that reduce signal production but can exploit and outcompete cooperators within mixed groups. RESULTS In this study, interactions between a cheater disrupted at the signaling gene csgA and allopatrically diversified cooperators reveal a very small cheating range. Expectedly, the cheater failed to cheat on all natural-isolate cooperators owing to non-cheater-specific antagonisms. Surprisingly, some lab-evolved cooperators had already exited the csgA mutant's cheating range after accumulating fewer than 20 mutations and without experiencing cheating during evolution. Cooperators might also diversify in the potential for a mutation to reduce expression of a cooperative trait or generate a cheating phenotype. A new csgA mutation constructed in several highly diverged cooperators generated diverse sporulation phenotypes, ranging from a complete defect to no defect, indicating that genetic backgrounds can limit the set of genomes in which a mutation creates a defector. CONCLUSIONS Our results demonstrate that natural populations may feature geographic mosaics of cooperators that have diversified in their susceptibility to particular cheaters, limiting defectors' cheating ranges and preventing them from spreading. This diversification may also lead to variation in the phenotypes generated by any given cooperation-gene mutation, further decreasing the chance of a cheater emerging which threatens the persistence of cooperation in the system.
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Affiliation(s)
- Kaitlin A. Schaal
- grid.5801.c0000 0001 2156 2780Institute of Integrative Biology, ETH Zürich, 8092 Zurich, Switzerland
| | - Yuen-Tsu Nicco Yu
- grid.5801.c0000 0001 2156 2780Institute of Integrative Biology, ETH Zürich, 8092 Zurich, Switzerland
| | - Marie Vasse
- grid.5801.c0000 0001 2156 2780Institute of Integrative Biology, ETH Zürich, 8092 Zurich, Switzerland ,grid.121334.60000 0001 2097 0141Institute MIVEGEC (UMR 5290 CNRS, IRD, UM), 34394 Montpellier, France
| | - Gregory J. Velicer
- grid.5801.c0000 0001 2156 2780Institute of Integrative Biology, ETH Zürich, 8092 Zurich, Switzerland
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12
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Loss-of-function mutation survey revealed that genes with background-dependent fitness are rare and functionally related in yeast. Proc Natl Acad Sci U S A 2022; 119:e2204206119. [PMID: 36067306 PMCID: PMC9478683 DOI: 10.1073/pnas.2204206119] [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: 11/30/2022] Open
Abstract
In different individuals, the same mutation can lead to different phenotypes due to genetic background effects. This is commonly observed in various systems, including many human diseases. While isolated examples of such background effects have been observed, a systematic view across a large number of individuals is still lacking. Here, we surveyed genetic background effects associated with gene loss-of-function mutations across a population of natural isolates of the yeast Saccharomyces cerevisiae. We found that ∼15% of genes can display a background-dependent fitness change. Genes related to mitochondrial functions are significantly overrepresented, and showed reversed patterns of fitness gain or loss with genes involved in transcription and chromatin remodeling as well as in nuclear–cytoplasmic transport, suggesting a potential functional rewiring. In natural populations, the same mutation can lead to different phenotypic outcomes due to the genetic variation that exists among individuals. Such genetic background effects are commonly observed, including in the context of many human diseases. However, systematic characterization of these effects at the species level is still lacking to date. Here, we sought to comprehensively survey background-dependent traits associated with gene loss-of-function (LoF) mutations in 39 natural isolates of Saccharomyces cerevisiae using a transposon saturation strategy. By analyzing the modeled fitness variability of a total of 4,469 genes, we found that 15% of them, when impacted by a LoF mutation, exhibited a significant gain- or loss-of-fitness phenotype in certain natural isolates compared with the reference strain S288C. Out of these 632 genes with predicted background-dependent fitness effects, around 2/3 impact multiple backgrounds with a gradient of predicted fitness change while 1/3 are specific to a single genetic background. Genes related to mitochondrial function are significantly overrepresented in the set of genes showing a continuous variation and display a potential functional rewiring with other genes involved in transcription and chromatin remodeling as well as in nuclear–cytoplasmic transport. Such rewiring effects are likely modulated by both the genetic background and the environment. While background-specific cases are rare and span diverse cellular processes, they can be functionally related at the individual level. All genes with background-dependent fitness effects tend to have an intermediate connectivity in the global genetic interaction network and have shown relaxed selection pressure at the population level, highlighting their potential evolutionary characteristics.
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13
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Bosch-Guiteras N, van Leeuwen J. Exploring conditional gene essentiality through systems genetics approaches in yeast. Curr Opin Genet Dev 2022; 76:101963. [PMID: 35939967 DOI: 10.1016/j.gde.2022.101963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 06/25/2022] [Accepted: 07/04/2022] [Indexed: 11/25/2022]
Abstract
An essential gene encodes for a cellular function that is required for viability. Although viability is a straightforward phenotype to analyze in yeast, defining a gene as essential is not always trivial. Gene essentiality has generally been studied in specific laboratory strains and under standard growth conditions, however, essentiality can vary across species, strains, and environments. Recent systematic studies of gene essentiality revealed that two sets of essential genes exist: core essential genes that are always required for viability and conditional essential genes that vary in essentiality in different genetic and environmental contexts. Here, we review recent advances made in the systematic analysis of gene essentiality in yeast and discuss the properties that distinguish core from context-dependent essential genes.
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Affiliation(s)
| | - Jolanda van Leeuwen
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
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14
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Stephan A, Graca FA, Hunt LC, Demontis F. Electroporation of Small Interfering RNAs into Tibialis Anterior Muscles of Mice. Bio Protoc 2022; 12:e4428. [PMID: 35799907 PMCID: PMC9244496 DOI: 10.21769/bioprotoc.4428] [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: 02/06/2022] [Revised: 03/08/2022] [Accepted: 04/06/2022] [Indexed: 12/29/2022] Open
Abstract
Aging and wasting of skeletal muscle reduce organismal fitness. Regrettably, only limited interventions are currently available to address this unmet medical need. Many methods have been developed to study this condition, including the intramuscular electroporation of DNA plasmids. However, this technique requires surgery and high electrical fields, which cause tissue damage. Here, we report an optimized protocol for the electroporation of small interfering RNAs (siRNAs) into the tibialis anterior muscle of mice. This protocol does not require surgery and, because of the small siRNA size, mild electroporation conditions are utilized. By inducing target mRNA knockdown, this method can be used to interrogate gene function in muscles of mice from different strains, genotypes, and ages. Moreover, a complementary method for siRNA transfection into differentiated myotubes can be used for testing siRNA efficacy before in vivo use. Altogether, this streamlined protocol is instrumental for basic science and translational studies in muscles of mice and other animal models.
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Affiliation(s)
- Anna Stephan
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Flavia A. Graca
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Liam C. Hunt
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Fabio Demontis
- Department of Developmental Neurobiology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
,
*For correspondence:
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15
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Chen P, Michel AH, Zhang J. Transposon insertional mutagenesis of diverse yeast strains suggests coordinated gene essentiality polymorphisms. Nat Commun 2022; 13:1490. [PMID: 35314699 PMCID: PMC8938418 DOI: 10.1038/s41467-022-29228-1] [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] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 03/01/2022] [Indexed: 12/18/2022] Open
Abstract
Due to epistasis, the same mutation can have drastically different phenotypic consequences in different individuals. This phenomenon is pertinent to precision medicine as well as antimicrobial drug development, but its general characteristics are largely unknown. We approach this question by genome-wide assessment of gene essentiality polymorphism in 16 Saccharomyces cerevisiae strains using transposon insertional mutagenesis. Essentiality polymorphism is observed for 9.8% of genes, most of which have had repeated essentiality switches in evolution. Genes exhibiting essentiality polymorphism lean toward having intermediate numbers of genetic and protein interactions. Gene essentiality changes tend to occur concordantly among components of the same protein complex or metabolic pathway and among a group of over 100 mitochondrial proteins, revealing molecular machines or functional modules as units of gene essentiality variation. Most essential genes tolerate transposon insertions consistently among strains in one or more coding segments, delineating nonessential regions within essential genes.
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Affiliation(s)
- Piaopiao Chen
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Agnès H Michel
- Department of Biochemistry, University of Oxford, Oxford, OX1 3QU, UK
| | - Jianzhi Zhang
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, 48109, USA.
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16
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Schell R, Hale JJ, Mullis MN, Matsui T, Foree R, Ehrenreich IM. Genetic basis of a spontaneous mutation’s expressivity. Genetics 2022; 220:6515283. [PMID: 35078232 PMCID: PMC8893249 DOI: 10.1093/genetics/iyac013] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 01/19/2022] [Indexed: 11/12/2022] Open
Abstract
Abstract
Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this phenomenon is not fully understood. Here, we comprehensively identify loci in a budding yeast cross that impact the growth of individuals carrying a spontaneous missense mutation in the nuclear-encoded mitochondrial ribosomal gene MRP20. Initial results suggested that a single large effect locus influences the mutation’s expressivity, with one allele causing inviability in mutants. However, further experiments revealed this simplicity was an illusion. In fact, many additional loci shape the mutation’s expressivity, collectively leading to a wide spectrum of mutational responses. These results exemplify how complex combinations of alleles can produce a diversity of qualitative and quantitative responses to the same mutation.
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Affiliation(s)
- Rachel Schell
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Joseph J Hale
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Martin N Mullis
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Takeshi Matsui
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Ryan Foree
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Ian M Ehrenreich
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
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17
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Singh RS. Decoding 'Unnecessary Complexity': A Law of Complexity and a Concept of Hidden Variation Behind "Missing Heritability" in Precision Medicine. J Mol Evol 2021; 89:513-526. [PMID: 34341835 PMCID: PMC8327892 DOI: 10.1007/s00239-021-10023-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 07/20/2021] [Indexed: 01/06/2023]
Abstract
The high hopes for the Human Genome Project and personalized medicine were not met because the relationship between genotypes and phenotypes turned out to be more complex than expected. In a previous study we laid the foundation of a theory of complexity and showed that because of the blind nature of evolution, and molecular and historical contingency, cells have accumulated unnecessary complexity, complexity beyond what is necessary and sufficient to describe an organism. Here we provide empirical evidence and show that unnecessary complexity has become integrated into the genome in the form of redundancy and is relevant to molecular evolution of phenotypic complexity. Unnecessary complexity creates uncertainty between molecular and phenotypic complexity, such that phenotypic complexity (CP) is higher than molecular complexity (CM), which is higher than DNA complexity (CD). The qualitative inequality in complexity is based on the following hierarchy: CP > CM > CD. This law-like relationship holds true for all complex traits, including complex diseases. We present a hypothesis of two types of variation, namely open and closed (hidden) systems, show that hidden variation provides a hitherto undiscovered "third source" of phenotypic variation, beside genotype and environment, and argue that "missing heritability" for some complex diseases is likely to be a case of "diluted heritability". There is a need for radically new ways of thinking about the principles of genotype-phenotype relationship. Understanding how cells use hidden, pathway variation to respond to stress can shed light on why two individuals who share the same risk factors may not develop the same disease, or how cancer cells escape death.
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Affiliation(s)
- Rama S Singh
- Department of Biology, and Origins Institute, McMaster University, 1280 Main Street West, Hamilton, ON, L8S4K1, Canada.
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18
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van Leeuwen J, Pons C, Tan G, Wang JZ, Hou J, Weile J, Gebbia M, Liang W, Shuteriqi E, Li Z, Lopes M, Ušaj M, Dos Santos Lopes A, van Lieshout N, Myers CL, Roth FP, Aloy P, Andrews BJ, Boone C. Systematic analysis of bypass suppression of essential genes. Mol Syst Biol 2021; 16:e9828. [PMID: 32939983 PMCID: PMC7507402 DOI: 10.15252/msb.20209828] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 08/11/2020] [Accepted: 08/13/2020] [Indexed: 12/15/2022] Open
Abstract
Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.
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Affiliation(s)
- Jolanda van Leeuwen
- Center for Integrative Genomics, Bâtiment Génopode, University of Lausanne, Lausanne, Switzerland.,Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Carles Pons
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Spain
| | - Guihong Tan
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Jason Zi Wang
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Jing Hou
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Jochen Weile
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.,Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | - Marinella Gebbia
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.,Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | - Wendy Liang
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Ermira Shuteriqi
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Zhijian Li
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Maykel Lopes
- Center for Integrative Genomics, Bâtiment Génopode, University of Lausanne, Lausanne, Switzerland
| | - Matej Ušaj
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Andreia Dos Santos Lopes
- Center for Integrative Genomics, Bâtiment Génopode, University of Lausanne, Lausanne, Switzerland
| | - Natascha van Lieshout
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.,Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | - Chad L Myers
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, Minneapolis, MN, USA
| | - Frederick P Roth
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.,Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.,Department of Computer Science, University of Toronto, Toronto, ON, Canada
| | - Patrick Aloy
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Brenda J Andrews
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Charles Boone
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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19
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Kumar A. The Complex Genetic Basis and Multilayered Regulatory Control of Yeast Pseudohyphal Growth. Annu Rev Genet 2021; 55:1-21. [PMID: 34280314 DOI: 10.1146/annurev-genet-071719-020249] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Eukaryotic cells are exquisitely responsive to external and internal cues, achieving precise control of seemingly diverse growth processes through a complex interplay of regulatory mechanisms. The budding yeast Saccharomyces cerevisiae provides a fascinating model of cell growth in its stress-responsive transition from planktonic single cells to a filamentous pseudohyphal growth form. During pseudohyphal growth, yeast cells undergo changes in morphology, polarity, and adhesion to form extended and invasive multicellular filaments. This pseudohyphal transition has been studied extensively as a model of conserved signaling pathways regulating cell growth and for its relevance in understanding the pathogenicity of the related opportunistic fungus Candida albicans, wherein filamentous growth is required for virulence. This review highlights the broad gene set enabling yeast pseudohyphal growth, signaling pathways that regulate this process, the role and regulation of proteins conferring cell adhesion, and interesting regulatory mechanisms enabling the pseudohyphal transition. 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)
- Anuj Kumar
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan 48109, USA;
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20
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Liu Y, Lin Y, Guo Y, Wu F, Zhang Y, Qi X, Wang Z, Wang Q. Stress tolerance enhancement via SPT15 base editing in Saccharomyces cerevisiae. BIOTECHNOLOGY FOR BIOFUELS 2021; 14:155. [PMID: 34229745 PMCID: PMC8259078 DOI: 10.1186/s13068-021-02005-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 06/26/2021] [Indexed: 05/12/2023]
Abstract
BACKGROUND Saccharomyces cerevisiae is widely used in traditional brewing and modern fermentation industries to produce biofuels, chemicals and other bioproducts, but challenged by various harsh industrial conditions, such as hyperosmotic, thermal and ethanol stresses. Thus, its stress tolerance enhancement has been attracting broad interests. Recently, CRISPR/Cas-based genome editing technology offers unprecedented tools to explore genetic modifications and performance improvement of S. cerevisiae. RESULTS Here, we presented that the Target-AID (activation-induced cytidine deaminase) base editor of enabling C-to-T substitutions could be harnessed to generate in situ nucleotide changes on the S. cerevisiae genome, thereby introducing protein point mutations in cells. The general transcription factor gene SPT15 was targeted, and total 36 mutants with diversified stress tolerances were obtained. Among them, the 18 tolerant mutants against hyperosmotic, thermal and ethanol stresses showed more than 1.5-fold increases of fermentation capacities. These mutations were mainly enriched at the N-terminal region and the convex surface of the saddle-shaped structure of Spt15. Comparative transcriptome analysis of three most stress-tolerant (A140G, P169A and R238K) and two most stress-sensitive (S118L and L214V) mutants revealed common and distinctive impacted global transcription reprogramming and transcriptional regulatory hubs in response to stresses, and these five amino acid changes had different effects on the interactions of Spt15 with DNA and other proteins in the RNA Polymerase II transcription machinery according to protein structure alignment analysis. CONCLUSIONS Taken together, our results demonstrated that the Target-AID base editor provided a powerful tool for targeted in situ mutagenesis in S. cerevisiae and more potential targets of Spt15 residues for enhancing yeast stress tolerance.
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Affiliation(s)
- Yanfang Liu
- CAS Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- National Technology Innovation Center of Synthetic Biology, Tianjin, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yuping Lin
- CAS Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- National Technology Innovation Center of Synthetic Biology, Tianjin, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yufeng Guo
- CAS Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- National Technology Innovation Center of Synthetic Biology, Tianjin, China
| | - Fengli Wu
- CAS Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- National Technology Innovation Center of Synthetic Biology, Tianjin, China
| | - Yuanyuan Zhang
- CAS Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- National Technology Innovation Center of Synthetic Biology, Tianjin, China
| | - Xianni Qi
- CAS Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- National Technology Innovation Center of Synthetic Biology, Tianjin, China
| | - Zhen Wang
- CAS Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- National Technology Innovation Center of Synthetic Biology, Tianjin, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Qinhong Wang
- CAS Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- National Technology Innovation Center of Synthetic Biology, Tianjin, China
- University of Chinese Academy of Sciences, Beijing, China
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21
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Parts L, Batté A, Lopes M, Yuen MW, Laver M, San Luis BJ, Yue JX, Pons C, Eray E, Aloy P, Liti G, van Leeuwen J. Natural variants suppress mutations in hundreds of essential genes. Mol Syst Biol 2021; 17:e10138. [PMID: 34042294 PMCID: PMC8156963 DOI: 10.15252/msb.202010138] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 04/22/2021] [Accepted: 04/23/2021] [Indexed: 01/04/2023] Open
Abstract
The consequence of a mutation can be influenced by the context in which it operates. For example, loss of gene function may be tolerated in one genetic background, and lethal in another. The extent to which mutant phenotypes are malleable, the architecture of modifiers and the identities of causal genes remain largely unknown. Here, we measure the fitness effects of ~ 1,100 temperature‐sensitive alleles of yeast essential genes in the context of variation from ten different natural genetic backgrounds and map the modifiers for 19 combinations. Altogether, fitness defects for 149 of the 580 tested genes (26%) could be suppressed by genetic variation in at least one yeast strain. Suppression was generally driven by gain‐of‐function of a single, strong modifier gene, and involved both genes encoding complex or pathway partners suppressing specific temperature‐sensitive alleles, as well as general modifiers altering the effect of many alleles. The emerging frequency of suppression and range of possible mechanisms suggest that a substantial fraction of monogenic diseases could be managed by modulating other gene products.
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Affiliation(s)
- Leopold Parts
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.,Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.,Department of Computer Science, University of Tartu, Tartu, Estonia
| | - Amandine Batté
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Maykel Lopes
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Michael W Yuen
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Meredith Laver
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Bryan-Joseph San Luis
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Jia-Xing Yue
- University of Côte d'Azur, CNRS, INSERM, IRCAN, Nice, France
| | - Carles Pons
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Spain
| | - Elise Eray
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Patrick Aloy
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute for Science and Technology, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Gianni Liti
- University of Côte d'Azur, CNRS, INSERM, IRCAN, Nice, France
| | - Jolanda van Leeuwen
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
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22
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Costanzo M, Hou J, Messier V, Nelson J, Rahman M, VanderSluis B, Wang W, Pons C, Ross C, Ušaj M, San Luis BJ, Shuteriqi E, Koch EN, Aloy P, Myers CL, Boone C, Andrews B. Environmental robustness of the global yeast genetic interaction network. Science 2021; 372:372/6542/eabf8424. [PMID: 33958448 DOI: 10.1126/science.abf8424] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 03/30/2021] [Indexed: 12/18/2022]
Abstract
Phenotypes associated with genetic variants can be altered by interactions with other genetic variants (GxG), with the environment (GxE), or both (GxGxE). Yeast genetic interactions have been mapped on a global scale, but the environmental influence on the plasticity of genetic networks has not been examined systematically. To assess environmental rewiring of genetic networks, we examined 14 diverse conditions and scored 30,000 functionally representative yeast gene pairs for dynamic, differential interactions. Different conditions revealed novel differential interactions, which often uncovered functional connections between distantly related gene pairs. However, the majority of observed genetic interactions remained unchanged in different conditions, suggesting that the global yeast genetic interaction network is robust to environmental perturbation and captures the fundamental functional architecture of a eukaryotic cell.
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Affiliation(s)
- Michael Costanzo
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
| | - Jing Hou
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
| | - Vincent Messier
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
| | - Justin Nelson
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA.,Program in Biomedical Informatics and Computational Biology, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA
| | - Mahfuzur Rahman
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA.,Program in Biomedical Informatics and Computational Biology, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA
| | - Benjamin VanderSluis
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA
| | - Wen Wang
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA
| | - Carles Pons
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute for Science and Technology, Barcelona, Spain
| | - Catherine Ross
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
| | - Matej Ušaj
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
| | - Bryan-Joseph San Luis
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
| | - Emira Shuteriqi
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
| | - Elizabeth N Koch
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA
| | - Patrick Aloy
- Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute for Science and Technology, Barcelona, Spain.,Institució Catalana de Recerca I Estudis Avaçats (ICREA), Barcelona, Spain
| | - Chad L Myers
- Department of Computer Science and Engineering, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA. .,Program in Biomedical Informatics and Computational Biology, University of Minnesota-Twin Cities, 200 Union Street, Minneapolis, MN 55455, USA
| | - Charles Boone
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada. .,Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada.,RIKEN Center for Sustainable Resource Science, Wako, Saitama, Japan
| | - Brenda Andrews
- The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada. .,Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
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23
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Lalanne J, Parker DJ, Li G. Spurious regulatory connections dictate the expression-fitness landscape of translation factors. Mol Syst Biol 2021; 17:e10302. [PMID: 33900014 PMCID: PMC8073009 DOI: 10.15252/msb.202110302] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 12/21/2022] Open
Abstract
During steady-state cell growth, individual enzymatic fluxes can be directly inferred from growth rate by mass conservation, but the inverse problem remains unsolved. Perturbing the flux and expression of a single enzyme could have pleiotropic effects that may or may not dominate the impact on cell fitness. Here, we quantitatively dissect the molecular and global responses to varied expression of translation termination factors (peptide release factors, RFs) in the bacterium Bacillus subtilis. While endogenous RF expression maximizes proliferation, deviations in expression lead to unexpected distal regulatory responses that dictate fitness reduction. Molecularly, RF depletion causes expression imbalance at specific operons, which activates master regulators and detrimentally overrides the transcriptome. Through these spurious connections, RF abundances are thus entrenched by focal points within the regulatory network, in one case located at a single stop codon. Such regulatory entrenchment suggests that predictive bottom-up models of expression-fitness landscapes will require near-exhaustive characterization of parts.
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Affiliation(s)
- Jean‐Benoît Lalanne
- Department of BiologyMassachusetts Institute of TechnologyCambridgeMAUSA
- Department of PhysicsMassachusetts Institute of TechnologyCambridgeMAUSA
- Present address:
Department of Genome SciencesUniversity of WashingtonSeattleWAUSA
| | - Darren J Parker
- Department of BiologyMassachusetts Institute of TechnologyCambridgeMAUSA
- Present address:
Biosciences DivisionOak Ridge National LaboratoryOak RidgeTNUSA
| | - Gene‐Wei Li
- Department of BiologyMassachusetts Institute of TechnologyCambridgeMAUSA
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24
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Goldstein I, Ehrenreich IM. The complex role of genetic background in shaping the effects of spontaneous and induced mutations. Yeast 2020; 38:187-196. [PMID: 33125810 PMCID: PMC7984271 DOI: 10.1002/yea.3530] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/09/2020] [Accepted: 10/24/2020] [Indexed: 12/27/2022] Open
Abstract
Spontaneous and induced mutations frequently show different phenotypic effects across genetically distinct individuals. It is generally appreciated that these background effects mainly result from genetic interactions between the mutations and segregating loci. However, the architectures and molecular bases of these genetic interactions are not well understood. Recent work in a number of model organisms has tried to advance knowledge of background effects both by using large‐scale screens to find mutations that exhibit this phenomenon and by identifying the specific loci that are involved. Here, we review this body of research, emphasizing in particular the insights it provides into both the prevalence of background effects across different mutations and the mechanisms that cause these background effects. A large fraction of mutations show different effects in distinct individuals. These background effects are mainly caused by epistasis with segregating loci. Mapping studies show a diversity of genetic architectures can be involved. Genetically complex changes in gene expression are often, but not always, causative.
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Affiliation(s)
- Ilan Goldstein
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, California, 90089-2910, USA
| | - Ian M Ehrenreich
- Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, California, 90089-2910, USA
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25
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Du LL. Resurrection from lethal knockouts: Bypass of gene essentiality. Biochem Biophys Res Commun 2020; 528:405-412. [PMID: 32507598 DOI: 10.1016/j.bbrc.2020.05.207] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 05/27/2020] [Indexed: 01/03/2023]
Abstract
Understanding genotype-phenotype relationships is a central pursuit in biology. Gene knockout generates a complete loss-of-function genotype and is a commonly used approach for probing gene functions. The most severe phenotypic consequence of gene knockout is lethality. Genes with a lethal knockout phenotype are called essential genes. Based on genome-wide knockout analyses in yeasts, up to approximately a quarter of genes in a genome can be essential. Like other genotype-phenotype relationships, gene essentiality is subject to background effects and can vary due to gene-gene interactions. In particular, for some essential genes, lethality caused by knockout can be rescued by extragenic suppressors. Such "bypass of essentiality" (BOE) gene-gene interactions have been an understudied type of genetic suppression. A recent systematic analysis revealed that, remarkably, the essentiality of nearly 30% of essential genes in the fission yeast Schizosaccharomyces pombe can be bypassed by BOE interactions. Here, I review the history and recent progress on uncovering and understanding the bypass of gene essentiality.
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Affiliation(s)
- Li-Lin Du
- National Institute of Biological Sciences, Beijing, 102206, China; Tsinghua Institute of Multidisciplinary Biomedical Research, Tsinghua University, Beijing, 100084, China.
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26
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Genç Ö, An JY, Fetter RD, Kulik Y, Zunino G, Sanders SJ, Davis GW. Homeostatic plasticity fails at the intersection of autism-gene mutations and a novel class of common genetic modifiers. eLife 2020; 9:55775. [PMID: 32609087 PMCID: PMC7394548 DOI: 10.7554/elife.55775] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 06/07/2020] [Indexed: 01/08/2023] Open
Abstract
We identify a set of common phenotypic modifiers that interact with five independent autism gene orthologs (RIMS1, CHD8, CHD2, WDFY3, ASH1L) causing a common failure of presynaptic homeostatic plasticity (PHP) in Drosophila. Heterozygous null mutations in each autism gene are demonstrated to have normal baseline neurotransmission and PHP. However, PHP is sensitized and rendered prone to failure. A subsequent electrophysiology-based genetic screen identifies the first known heterozygous mutations that commonly genetically interact with multiple ASD gene orthologs, causing PHP to fail. Two phenotypic modifiers identified in the screen, PDPK1 and PPP2R5D, are characterized. Finally, transcriptomic, ultrastructural and electrophysiological analyses define one mechanism by which PHP fails; an unexpected, maladaptive up-regulation of CREG, a conserved, neuronally expressed, stress response gene and a novel repressor of PHP. Thus, we define a novel genetic landscape by which diverse, unrelated autism risk genes may converge to commonly affect the robustness of synaptic transmission.
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Affiliation(s)
- Özgür Genç
- Department of Biochemistry and Biophysics Kavli Institute for Fundamental Neuroscience University of California, San Francisco, San Francisco, United States
| | - Joon-Yong An
- Department of Psychiatry UCSF Weill Institute for Neurosciences University of California, San Francisco, San Francisco, United States.,School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, Republic of Korea
| | - Richard D Fetter
- Department of Biochemistry and Biophysics Kavli Institute for Fundamental Neuroscience University of California, San Francisco, San Francisco, United States
| | - Yelena Kulik
- Department of Biochemistry and Biophysics Kavli Institute for Fundamental Neuroscience University of California, San Francisco, San Francisco, United States
| | - Giulia Zunino
- Department of Biochemistry and Biophysics Kavli Institute for Fundamental Neuroscience University of California, San Francisco, San Francisco, United States
| | - Stephan J Sanders
- Department of Psychiatry UCSF Weill Institute for Neurosciences University of California, San Francisco, San Francisco, United States
| | - Graeme W Davis
- Department of Biochemistry and Biophysics Kavli Institute for Fundamental Neuroscience University of California, San Francisco, San Francisco, United States
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27
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Huang L, Li L, Li Q, Chen J, Lin S, Li K, Fan D, Jin W, Li Y, Yang X, Xiong Y, Li M, Yang X. Different Clinical Phenotypes Caused by Three F8 Missense Mutations in Three Chinese Families with Moderate Hemophilia A. DNA Cell Biol 2020; 39:1685-1690. [PMID: 32589464 DOI: 10.1089/dna.2020.5359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In families with a monogenic disorder, the causal mutation usually cosegregates with the disease phenotype. In rare cases, however, individuals carrying the same mutation within a family may show various phenotypes. This study aimed to analyze the discrepancy between genotype and phenotype in three families with moderate hemophilia A (HA) caused by missense mutation in the F8 gene. Among the 67 noninversion moderate HA families in our cohort, incomplete penetrance was found in three families. In these three families, the grandfathers were asymptomatic, whereas the probands had different clinical phenotypes. Apart from one mutation in the VWF gene (c.1330 G>A) found in one grandfather, only one missense mutation (c.5837A>T, c.6679G>A, and c.6506G>A, in the respective families) in the F8 gene was identified in each proband and their grandfathers. Subsequent Sanger sequencing results combined with bioinformatic analysis indicated that the three missense mutations in the F8 gene were the causative mutations. Our study demonstrated incomplete penetrance of missense mutation within HA families in China. Therefore, genetic counseling and management of such cases need to be reappraised.
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Affiliation(s)
- Limin Huang
- Institute of Antibody Engineering, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, China
| | - Liyan Li
- Technology Center of Prenatal Diagnosis and Genetic Diseases Diagnosis, Department of Gynecology and Obstetrics, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Qiang Li
- The Department of Laboratory Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Juanjuan Chen
- Institute of Antibody Engineering, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, China
| | - Sheng Lin
- Lab of Molecular Medicine, Shenzhen Health Development Research Center, Shenzhen, China
| | - Kun Li
- Institute of Antibody Engineering, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, China
| | - Dongmei Fan
- Institute of Antibody Engineering, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, China
| | - Wangjie Jin
- Technology Center of Prenatal Diagnosis and Genetic Diseases Diagnosis, Department of Gynecology and Obstetrics, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yihong Li
- Technology Center of Prenatal Diagnosis and Genetic Diseases Diagnosis, Department of Gynecology and Obstetrics, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xu Yang
- Clinical Innovation & Research Center, Shenzhen Hospital of Southern Medical University, Shenzhen, China
| | - Yufeng Xiong
- Department of Clinical Laboratory, Guangdong Women and Children's Hospital, Guangzhou, China
| | - Ming Li
- Institute of Antibody Engineering, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, China
| | - Xuexi Yang
- Institute of Antibody Engineering, School of Laboratory Medicine and Biotechnology, Southern Medical University, Guangzhou, China
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28
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Sexual Selection Does Not Increase the Rate of Compensatory Adaptation to a Mutation Influencing a Secondary Sexual Trait in Drosophila melanogaster. G3-GENES GENOMES GENETICS 2020; 10:1541-1551. [PMID: 32122961 PMCID: PMC7202011 DOI: 10.1534/g3.119.400934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Theoretical work predicts that sexual selection can enhance natural selection, increasing the rate of adaptation to new environments and helping purge harmful mutations. While some experiments support these predictions, remarkably little work has addressed the role of sexual selection on compensatory adaptation—populations’ ability to compensate for the costs of deleterious alleles that are already present. We tested whether sexual selection, as well as the degree of standing genetic variation, affect the rate of compensatory evolution via phenotypic suppression in experimental populations of Drosophila melanogaster. These populations were fixed for a spontaneous mutation causing mild abnormalities in the male sex comb, a structure important for mating success. We fine-mapped this mutation to an ∼85 kb region on the X chromosome containing three candidate genes, showed that the mutation is deleterious, and that its phenotypic expression and penetrance vary by genetic background. We then performed experimental evolution, including a treatment where opportunity for mate choice was limited by experimentally enforced monogamy. Although evolved populations did show some phenotypic suppression of the morphological abnormalities in the sex comb, the amount of suppression did not depend on the opportunity for sexual selection. Sexual selection, therefore, may not always enhance natural selection; instead, the interaction between these two forces may depend on additional factors.
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29
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Unpredictable Effects of the Genetic Background of Transgenic Lines in Physiological Quantitative Traits. G3-GENES GENOMES GENETICS 2019; 9:3877-3890. [PMID: 31540975 PMCID: PMC6829147 DOI: 10.1534/g3.119.400715] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Physiology, fitness and disease phenotypes are complex traits exhibiting continuous variation in natural populations. To understand complex trait gene functions transgenic lines of undefined genetic background are often combined to assess quantitative phenotypes ignoring the impact of genetic polymorphisms. Here, we used inbred wild-type strains of the Drosophila Genetics Reference Panel to assess the phenotypic variation of six physiological and fitness traits, namely, female fecundity, survival and intestinal mitosis upon oral infection, defecation rate and fecal pH upon oral infection, and terminal tracheal cell branching in hypoxia. We found continuous variation in the approximately 150 strains tested for each trait, with extreme values differing by more than four standard deviations for all traits. In addition, we assessed the effects of commonly used Drosophila UAS-RNAi transgenic strains and their backcrossed isogenized counterparts, in the same traits plus baseline intestinal mitosis and tracheal branching in normoxia, in heterozygous conditions, when only half of the genetic background was different among strains. We tested 20 non-isogenic strains (10 KK and 10 GD) from the Vienna Drosophila Resource Center and their isogenized counterparts without Gal4 induction. Survival upon infection and female fecundity exhibited differences in 50% and 40% of the tested isogenic vs. non-isogenic pairs, respectively, whereas all other traits were affected in only 10–25% of the cases. When 11 isogenic and their corresponding non-isogenic UAS-RNAi lines were expressed ubiquitously with Gal4, 4 isogenic vs. non-isogenic pairs exhibited differences in survival to infection. Furthermore, when a single UAS-RNAi line was crossed with the same Gal4 transgene inserted in different genetic backgrounds, the quantitative variations observed were unpredictable on the basis of pure line performance. Thus, irrespective of the trait of interest, the genetic background of commonly used transgenic strains needs to be considered carefully during experimentation.
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30
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Fournier T, Abou Saada O, Hou J, Peter J, Caudal E, Schacherer J. Extensive impact of low-frequency variants on the phenotypic landscape at population-scale. eLife 2019; 8:49258. [PMID: 31647416 PMCID: PMC6892612 DOI: 10.7554/elife.49258] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 10/23/2019] [Indexed: 12/14/2022] Open
Abstract
Genome-wide association studies (GWAS) allow to dissect complex traits and map genetic variants, which often explain relatively little of the heritability. One potential reason is the preponderance of undetected low-frequency variants. To increase their allele frequency and assess their phenotypic impact in a population, we generated a diallel panel of 3025 yeast hybrids, derived from pairwise crosses between natural isolates and examined a large number of traits. Parental versus hybrid regression analysis showed that while most phenotypic variance is explained by additivity, a third is governed by non-additive effects, with complete dominance having a key role. By performing GWAS on the diallel panel, we found that associated variants with low frequency in the initial population are overrepresented and explain a fraction of the phenotypic variance as well as an effect size similar to common variants. Overall, we highlighted the relevance of low-frequency variants on the phenotypic variation.
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Affiliation(s)
- Téo Fournier
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
| | - Omar Abou Saada
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
| | - Jing Hou
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
| | - Jackson Peter
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
| | - Elodie Caudal
- Université de Strasbourg, CNRS, GMGM UMR 7156, Strasbourg, France
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31
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Eguchi Y, Bilolikar G, Geiler-Samerotte K. Why and how to study genetic changes with context-dependent effects. Curr Opin Genet Dev 2019; 58-59:95-102. [PMID: 31593884 DOI: 10.1016/j.gde.2019.08.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Revised: 08/21/2019] [Accepted: 08/29/2019] [Indexed: 01/18/2023]
Abstract
The phenotypic impacts of a genetic change can depend on genetic background (e.g. epistasis), as well as other contexts including environment, developmental stage, cell type, disease state, and higher-order combinations thereof. Recent advances in high-throughput phenotyping are uncovering examples of context dependence faster than genotype-phenotype maps and other core concepts are changing to reflect the dynamic nature of biological systems. Here, we review several approaches to study context dependence and their findings. In our opinion, these findings encourage more studies that examine the spectrum of effects a genetic change may have, as opposed to studies that exclusively measure the impact of a genetic change in a particular context. Studies that elucidate the mechanisms that cause the effects of genetic change to vary with context are of special interest. Previous studies of the mechanisms underlying context dependence have improved predictions of phenotype from genotype and have provided insight about how biological systems function and evolve.
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Affiliation(s)
- Yuichi Eguchi
- Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States
| | - Gaurav Bilolikar
- Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States
| | - Kerry Geiler-Samerotte
- Center for Mechanisms of Evolution, School of Life Sciences, Arizona State University, Tempe, AZ 85287, United States.
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32
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Busby BP, Niktab E, Roberts CA, Sheridan JP, Coorey NV, Senanayake DS, Connor LM, Munkacsi AB, Atkinson PH. Genetic interaction networks mediate individual statin drug response in Saccharomyces cerevisiae. NPJ Syst Biol Appl 2019; 5:35. [PMID: 31602312 PMCID: PMC6776536 DOI: 10.1038/s41540-019-0112-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 08/20/2019] [Indexed: 01/19/2023] Open
Abstract
Eukaryotic genetic interaction networks (GINs) are extensively described in the Saccharomyces cerevisiae S288C model using deletion libraries, yet being limited to this one genetic background, not informative to individual drug response. Here we created deletion libraries in three additional genetic backgrounds. Statin response was probed with five queries against four genetic backgrounds. The 20 resultant GINs representing drug–gene and gene–gene interactions were not conserved by functional enrichment, hierarchical clustering, and topology-based community partitioning. An unfolded protein response (UPR) community exhibited genetic background variation including different betweenness genes that were network bottlenecks, and we experimentally validated this UPR community via measurements of the UPR that were differentially activated and regulated in statin-resistant strains relative to the statin-sensitive S288C background. These network analyses by topology and function provide insight into the complexity of drug response influenced by genetic background. Genes are wired together in functional genetic interaction networks (GINs) specific for different traits. We asked a simple question: do GINs for particular traits vary with individuals? The trait we investigated was response to statins, cholesterol-lowering drugs prescribed to 30 million people worldwide. Building comprehensive GINs requires a library of cells with a different gene deleted covering the entire genome that is available only in Saccharomyces cerevisiae (Baker’s yeast), a well-defined model for human genetics. However, the yeast libraries being limited to one genetic background are not informative of individuals. Therefore, we constructed GINs in additional genetic backgrounds and showed statin-specific GINs were not conserved, albeit there was a common fundamental process mediating statin-resistance. Our results identify a mechanism to further investigate in the millions of people that do not respond to statins and the methodology will enhance the discovery and development of drugs to treat other major diseases.
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Affiliation(s)
- Bede P Busby
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand.,2European Molecular Biology Laboratory, Meyerhofstraße 1, 69117 Heidelberg, Germany
| | - Eliatan Niktab
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Christina A Roberts
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Jeffrey P Sheridan
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Namal V Coorey
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Dinindu S Senanayake
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Lisa M Connor
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Andrew B Munkacsi
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Paul H Atkinson
- 1Centre for Biodiscovery, School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
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Tuite MF. Yeast models of neurodegenerative diseases. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 168:351-379. [DOI: 10.1016/bs.pmbts.2019.07.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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