Evidence map›Paper›PMID 18030334›Full record

ArticlePloS one2007

Covert genetic selections to optimize phenotypes.

Di Wu, Elizabeth Townsley, Alan Michael Tartakoff

Abstract read
In one paragraph

Article in PloS one, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Di WuMonash Institute of Medical Research, Monash University, Monash Medical Centre, Melbourne, Victoria, Australia.
Elizabeth Townsley
Alan Michael Tartakoff

Funding

TUMOR METABOLISM PROGRAMP30CA043703 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI MARK R CHANCE · 1987 to 2026
$142.3M
NCI NIH HHS P30 CA043703NCI NIH HHS P30CA43703
6 · The paper itself

Abstract

In many high complexity systems (cells, organisms, institutions, societies, economies, etc.), it is unclear which components should be regulated to affect overall performance. To identify and prioritize molecular targets which impact cellular phenotypes, we have developed a selection procedure ("SPI"-single promoting/inhibiting target identification) which monitors the abundance of ectopic cDNAs. We have used this approach to identify growth regulators. For this purpose, complex pools of S. cerevisiae cDNA transformants were established and we quantitated the evolution of the spectrum of cDNAs which was initially present. These data emphasized the importance of translation initiation and ER-Golgi traffic for growth. SPI provides functional insight into the stability of cellular phenotypes under circumstances in which established genetic approaches cannot be implemented. It provides a functional "synthetic genetic signature" for each state of the cell (i.e. genotype and environment) by surveying complex genetic libraries, and does not require specialized arrays of cDNAs/shRNAs, deletion strains, direct assessment of clonal growth or even a conditional phenotype. Moreover, it establishes a hierarchy of importance of those targets which can contribute, either positively or negatively, to modify the prevailing phenotype. Extensions of these proof-of-principle experiments to other cell types should provide a novel and powerful approach to analyze multiple aspects of the basic biology of yeast and animal cells as well as clinically-relevant issues.

Indexed as

Selection, GeneticDNA, ComplementaryPhenotypeTemperatureDNA, Complementary

Identifiers

PMID18030334
PMCPMC2075469

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.