Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 205

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Origin of phenotypes: Genes and transcripts

Open access
Gingeras, Thomas R.·2007·Genome Research

Abstract

While the concept of a gene has been helpful in defining the relationship of a portion of a genome to a phenotype, this traditional term may not be as useful as it once was. Currently, “gene” has come to refer principally to a genomic region producing a polyadenylated mRNA that encodes a protein. However, the recent emergence of a large collection of unannotated transcripts with apparently little protein coding capacity, collectively called transcripts of unknown function (TUFs), has begun to blur the physical boundaries and genomic organization of genic regions with noncoding transcripts often overlapping protein-coding genes on the same (sense) and opposite strand (antisense). Moreover, they are often located in intergenic regions, making the genic portions of the human genome an interleaved network of both annotated polyadenylated and nonpolyadenylated transcripts, including splice variants with novel 5′ ends extending hundreds of kilobases. This complex transcriptional organization and other recently observed features of genomes argue for the reconsideration of the term “gene” and suggests that transcripts may be used to define the operational unit of a genome.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/gr.6525007

Cites

10 of 10 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 10 references

Cited by

See all 205

Metadata

Authors
Gingeras, T. R.
Venue
Genome Research
Published
2007-06
Volume
17
Issue
6
Pages
682-690
ISSN
1088-9051 (ISSN-L)
OpenAlex
W2111619522
Cited by
205
References
10
Type
posted content
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Origin of phenotypes: Genes and transcripts. https://app.cochat.ai/papers/10.1101/gr.6525007
The paper
Gingeras, T. R. (2007). Origin of phenotypes: Genes and transcripts. Genome Research. https://doi.org/10.1101/gr.6525007

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.