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      The complex role of genetic background in shaping the effects of spontaneous and induced mutations

      research-article
      1 , 1 ,
      Yeast (Chichester, England)
      John Wiley and Sons Inc.

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          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.

          Take Aways

          • 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.

          Abstract

          Spontaneous and induced mutations can show different phenotypic effects in genetically distinct individuals (or ‘background effects’). Here, we review current work aimed at generally understanding this phenomenon.

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          Most cited references87

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          Multiplex genome engineering using CRISPR/Cas systems.

          Functional elucidation of causal genetic variants and elements requires precise genome editing technologies. The type II prokaryotic CRISPR (clustered regularly interspaced short palindromic repeats)/Cas adaptive immune system has been shown to facilitate RNA-guided site-specific DNA cleavage. We engineered two different type II CRISPR/Cas systems and demonstrate that Cas9 nucleases can be directed by short RNAs to induce precise cleavage at endogenous genomic loci in human and mouse cells. Cas9 can also be converted into a nicking enzyme to facilitate homology-directed repair with minimal mutagenic activity. Lastly, multiple guide sequences can be encoded into a single CRISPR array to enable simultaneous editing of several sites within the mammalian genome, demonstrating easy programmability and wide applicability of the RNA-guided nuclease technology.
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            RNA-guided human genome engineering via Cas9.

            Bacteria and archaea have evolved adaptive immune defenses, termed clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems, that use short RNA to direct degradation of foreign nucleic acids. Here, we engineer the type II bacterial CRISPR system to function with custom guide RNA (gRNA) in human cells. For the endogenous AAVS1 locus, we obtained targeting rates of 10 to 25% in 293T cells, 13 to 8% in K562 cells, and 2 to 4% in induced pluripotent stem cells. We show that this process relies on CRISPR components; is sequence-specific; and, upon simultaneous introduction of multiple gRNAs, can effect multiplex editing of target loci. We also compute a genome-wide resource of ~190 K unique gRNAs targeting ~40.5% of human exons. Our results establish an RNA-guided editing tool for facile, robust, and multiplexable human genome engineering.
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              Common SNPs explain a large proportion of the heritability for human height.

              SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date.
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                Author and article information

                Contributors
                ian.ehrenreich@usc.edu
                Journal
                Yeast
                Yeast
                10.1002/(ISSN)1097-0061
                YEA
                Yeast (Chichester, England)
                John Wiley and Sons Inc. (Hoboken )
                0749-503X
                1097-0061
                14 December 2020
                March 2021
                : 38
                : 3 ( doiID: 10.1002/yea.v38.3 )
                : 187-196
                Affiliations
                [ 1 ] Molecular and Computational Biology Section, Department of Biological Sciences University of Southern California Los Angeles California 90089‐2910 USA
                Author notes
                [*] [* ] Correspondence

                Ian M. Ehrenreich, Molecular and Computational Biology Section, Ray R. Irani Hall 201, University of Southern California, Los Angeles, CA 90089‐2910, USA.

                Email: ian.ehrenreich@ 123456usc.edu

                Author information
                https://orcid.org/0000-0001-5065-9063
                Article
                YEA3530 YEA-Jul-20-0078.R1
                10.1002/yea.3530
                7984271
                33125810
                e9e47b07-0b42-4ff5-ae9f-fed065f86ba2
                © 2020 The Authors. Yeast published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 09 October 2020
                : 27 July 2020
                : 24 October 2020
                Page count
                Figures: 5, Tables: 0, Pages: 10, Words: 9918
                Funding
                Funded by: University of Southern California , open-funder-registry 10.13039/100006034;
                Funded by: National Institutes of Health , open-funder-registry 10.13039/100000002;
                Award ID: R35GM130381
                Categories
                Yeast Extracts
                Yeast Extract
                Custom metadata
                2.0
                March 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.0 mode:remove_FC converted:22.03.2021

                Molecular biology
                Molecular biology

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