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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.

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

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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