TY - JOUR
T1 - Loss-of-function genetic tools for animal models
T2 - cross-species and cross-platform differences
AU - Housden, Benjamin E.
AU - Muhar, Matthias
AU - Gemberling, Matthew
AU - Gersbach, Charles A.
AU - Stainier, Didier Y.R.
AU - Seydoux, Geraldine
AU - Mohr, Stephanie E.
AU - Zuber, Johannes
AU - Perrimon, Norbert
PY - 2016/12/13
Y1 - 2016/12/13
N2 - Our understanding of the genetic mechanisms that underlie biological processes has relied extensively on loss-of-function (LOF) analyses. LOF methods target DNA, RNA or protein to reduce or to ablate gene function. By analysing the phenotypes that are caused by these perturbations the wild-type function of genes can be elucidated. Although all LOF methods reduce gene activity, the choice of approach (for example, mutagenesis, CRISPR-based gene editing, RNA interference, morpholinos or pharmacological inhibition) can have a major effect on phenotypic outcomes. Interpretation of the LOF phenotype must take into account the biological process that is targeted by each method. The practicality and efficiency of LOF methods also vary considerably between model systems. We describe parameters for choosing the optimal combination of method and system, and for interpreting phenotypes within the constraints of each method.
AB - Our understanding of the genetic mechanisms that underlie biological processes has relied extensively on loss-of-function (LOF) analyses. LOF methods target DNA, RNA or protein to reduce or to ablate gene function. By analysing the phenotypes that are caused by these perturbations the wild-type function of genes can be elucidated. Although all LOF methods reduce gene activity, the choice of approach (for example, mutagenesis, CRISPR-based gene editing, RNA interference, morpholinos or pharmacological inhibition) can have a major effect on phenotypic outcomes. Interpretation of the LOF phenotype must take into account the biological process that is targeted by each method. The practicality and efficiency of LOF methods also vary considerably between model systems. We describe parameters for choosing the optimal combination of method and system, and for interpreting phenotypes within the constraints of each method.
UR - http://www.scopus.com/inward/record.url?scp=84992753525&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84992753525&partnerID=8YFLogxK
U2 - 10.1038/nrg.2016.118
DO - 10.1038/nrg.2016.118
M3 - Review article
C2 - 27795562
AN - SCOPUS:84992753525
SN - 1471-0056
VL - 18
SP - 24
EP - 40
JO - Nature Reviews Genetics
JF - Nature Reviews Genetics
IS - 1
ER -