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SystGeneEdit SIGNED

Dissecting quantitative traits and their underlying genetic interactions via systematic genome editing

Total Cost €


EC-Contrib. €






 SystGeneEdit project word cloud

Explore the words cloud of the SystGeneEdit project. It provides you a very rough idea of what is the project "SystGeneEdit" about.

throughput    overexpression    efforts    functionally    contexts    variations    deletion    indels    verified    relevance    interrogation    single    diverse    nucleotide    insights    despite    reveal    competitive    barcodes    fitness    connected    engineering    contributions    circumvent    phenotypes    predictive    genomics    collection    snvs    naturally    dissect    insertion    cellular    rapid    ubiquity    strain    genetic    biological    roles    traits    limited    human    genome    background    pooled    pairwise    variation    isolation    sequence    systematic    crispr    date    interactions    editing    aid    genomic    partly    screens    modulate    data    small    dna    cerevisiae    strains    backgrounds    environment    multiple    pleiotropic    assay    unprecedented    functional    profiling    tools    quantitative    principles    primarily    polymorphisms    subtle    create    function    combined    combine    genes    limitations    guiding    perturbation    systematically    occurring    environmental    generate    clear    species    variants    unravelling    models    greatest    phenotypic    diversity   

Project "SystGeneEdit" data sheet

The following table provides information about the project.


Organization address
address: Meyerhofstrasse 1
postcode: 69117

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Total cost 2˙499˙995 €
 EC max contribution 2˙499˙995 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-ADG
 Funding Scheme ERC-ADG
 Starting year 2017
 Duration (year-month-day) from 2017-11-01   to  2022-10-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Despite the ubiquity of genome sequence data, unravelling the contributions of genetic variation to phenotypic diversity remains one of the greatest challenges in genomics. This is partly due to our very limited knowledge of how multiple variations combine to create phenotypes. There is a clear need for a systematic, perturbation-based approach to study the phenotypic consequences of genetic variants in different genomic and environmental contexts. Previous efforts have primarily used loss-of-function or overexpression approaches, but it is known that subtle, naturally occurring variants have the most relevance for complex, quantitative traits. Our proposal aims to dissect these effects by systematically engineering and functionally profiling naturally occurring single-nucleotide variants (SNVs) and small insertion/deletion polymorphisms (indels) in the S. cerevisiae species in three diverse genetic backgrounds. To generate such an unprecedented collection, we will apply a high-throughput CRISPR approach that allows rapid isolation of sequence-verified strains. DNA barcodes integrated into the genome of each strain will enable pooled, competitive growth, which will reveal how variants modulate fitness as a function of environment and genetic background. We will test our collection for pairwise and higher order interactions, assay their impact on cellular processes and dissect pleiotropic roles of highly connected genes. Our work will circumvent the key limitations in current high-throughput genome editing screens and enable the largest interrogation of the functional impact of genetic variation in different environmental and genetic contexts to date. The combined insights and tools generated by our work will aid in developing predictive models of the effects of genetic variation within specific environmental and biological contexts, providing guiding principles for understanding the consequences of human genetic variation.

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The information about "SYSTGENEEDIT" are provided by the European Opendata Portal: CORDIS opendata.

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