Evidence map›Paper›PMID 33037901›Full record

ReviewCurrent genetics2021

The Boggarts of biology: how non-genetic changes influence the genotype.

Laasya Samhita

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. The impact of mistranslation on phenotypic variability and fitness.Evolution; international journal of organic evolution · 2021
    Article
  2. Article
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 at 1 institution in 1 country.

Laasya SamhitaNational Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India. laasyas@ncbs.res.in.ORCID http://orcid.org/0000-0002-3445-2828
Tata Institute of Fundamental Research · IN

Funding

The Wellcome Trust DBT India Alliance IA/E/14/1/501771
6 · The paper itself

Abstract

The notion that there is a one-one mapping from genotype to phenotype was overturned a long time ago. Along with genotype and environment, 'non-genetic changes' orchestrated by altered RNA and protein molecules also guide the development of phenotype. The idea that there is a route through which changes in phenotype can lead to changes in genotype impinges on several phenomena of molecular, developmental, evolutionary and applied interest. Phenotypic changes that do not alter the underlying DNA sequence have been studied across model systems (eg: DNA and histone modifications, RNA editing, prion formation) and are known to play an important role in short-term adaptation. However, because of their transient nature and unstable inheritance, the role of such changes in long-term evolution has remained controversial. I classify and review three ways in which non-genetic changes can influence genotype and impact cellular fitness across generations, with an emphasis on the enticing idea that they may act as stepping stones for genetic adaptation. I focus on work from microbial systems and attempt to highlight recent experiments and models that bear on this idea. Overall, I review evidence which suggests that non-genetic changes can impact phenotype via their influence on the genotype, and thus play a role in evolutionary change.

Indexed as

Biological EvolutionEvolution, MolecularGenetic Association StudiesAnimalsBase SequenceEpigenesis, GeneticGene-Environment InteractionHistone CodeAdaptationEvolutionNon-genetic changePhenotypic variabilityTranslation errors

Identifiers

PMID33037901
OpenAlexW3048706233

What OpenQuestion holds

Textmetadata
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.