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High-throughput screening of mouse gene knockouts identifies established and novel skeletal phenotypes

Authors: Brommage, Robert; Liu, Jeff; Hansen, Gwenn M; Kirkpatrick, Laura L; Potter, David G; Sands, Arthur T; Zambrowicz, Brian; +2 Authors

High-throughput screening of mouse gene knockouts identifies established and novel skeletal phenotypes

Abstract

Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening (HTS) data for 3 762 distinct global gene knockout (KO) mouse lines with viable adult homozygous mice generated using either gene-trap or homologous recombination technologies. Bone mass was determined from DEXA scans of male and female mice at 14 weeks of age and by microCT analyses of bones from male mice at 16 weeks of age. Wild-type (WT) cagemates/littermates were examined for each gene KO. Lethality was observed in an additional 850 KO lines. Since primary HTS are susceptible to false positive findings, additional cohorts of mice from KO lines with intriguing HTS bone data were examined. Aging, ovariectomy, histomorphometry and bone strength studies were performed and possible non-skeletal phenotypes were explored. Together, these screens identified multiple genes affecting bone mass: 23 previously reported genes (Calcr, Cebpb, Crtap, Dcstamp, Dkk1, Duoxa2, Enpp1, Fgf23, Kiss1/Kiss1r, Kl (Klotho), Lrp5, Mstn, Neo1, Npr2, Ostm1, Postn, Sfrp4, Slc30a5, Slc39a13, Sost, Sumf1, Src, Wnt10b), five novel genes extensively characterized (Cldn18, Fam20c, Lrrk1, Sgpl1, Wnt16), five novel genes with preliminary characterization (Agpat2, Rassf5, Slc10a7, Slc26a7, Slc30a10) and three novel undisclosed genes coding for potential osteoporosis drug targets.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
99
Top 10%
Top 10%
Top 1%
Green
gold