Evidence map›Paper›PMID 29231847›Full record

ArticleBiology2017

Natural Knockouts: Natural Selection Knocked Out.

Peter Borger

Open access · goldAbstract read
In one paragraph

Article in Biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 32% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Emerging significance of butyrylcholinesterase.World journal of experimental medicine · 2024
    Review
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

1 author.

Peter BorgerThe Independent Research Initiative on Information & Origins, 79540 Loerrach, Germany. peterborger@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In functional genomics studies, research is dedicated to unveiling the function of genes using gene-knockouts, model organisms in which a gene is artificially inactivated. The idea is that, by knocking out the gene, the provoked phenotype would inform us about the function of the gene. Still, the function of many genes cannot be elucidated, because disruption of conserved sequences, including protein-coding genes, often does not directly affect the phenotype. Since the phenomenon was first observed in the early nineties of the last century, these so-called 'no-phenotype knockouts' have met with great skepticism and resistance by died-in-the-wool selectionists. Still, functional genomics of the late 20th and early 21st centuries has taught us two important lessons. First, two or more unrelated genes can often substitute for each other; and second, some genes are only present in the genome in a silent state. In the laboratory, the disruption of such genes does not negatively influence reproductive success, and does not show measurable fitness effects of the species. The genes are redundant. Genetic redundancy, one of the big surprises of modern biology, can thus be defined as the condition in which the inactivation of a gene is selectively neutral. The no-phenotype knockout is not just a freak of the laboratory. Genetic variants known as homozygous loss-of-function (HLOF) variants are of considerable scientific and clinical interest, as they represent experiments of nature qualifying as "natural knockouts". Such natural knockouts challenge the conventional NeoDarwinian appraisal that genetic information is the result of natural selection acting on random genetic variation.

Indexed as

genetic redundancyhomozygous loss-of-functionnatural knockoutnatural selection

Identifiers

PMID29231847
PMCPMC5745448
OpenAlexW2771174971

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.