Evidence map›Paper›PMID 18410680›Full record

ArticleBMC genomics2008

Overlapping genes in the human and mouse genomes.

Chaitanya R Sanna, Wen-Hsiung Li, Liqing Zhang

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

40 citing papers in PubMed, 70 citations in OpenAlex.

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  9. The Functional Meaning of 5'UTR in Protein-Coding Genes.International journal of molecular sciences · 2023
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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 at 2 institutions in 2 countries.

Chaitanya R SannaDepartment of Computer Science, Virginia Tech, Blacksburg, USA. csanna@vt.edu
Wen-Hsiung Li
Liqing Zhang
Virginia Tech · USUniversity of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncreasing evidence suggests that overlapping genes are much more common in eukaryotic genomes than previously thought. In this study we identified and characterized the overlapping genes in a set of 13,484 pairs of human-mouse orthologous genes.

resultsAbout 10% of the genes under study are overlapping genes, the majority of which are different-strand overlaps. The majority of the same-strand overlaps are embedded forms, whereas most different-strand overlaps are not embedded and in the convergent transcription orientation. Most of the same-strand overlapping gene pairs show at least a tenfold difference in length, much larger than the length difference between non-overlapping neighboring gene pairs. The length difference between the two different-strand overlapping genes is less dramatic. Over 27% of the different-strand-overlap relationships are shared between human and mouse, compared to only approximately 8% conservation for same-strand-overlap relationships. More than 96% of the same-strand and different-strand overlaps that are not shared between human and mouse have both genes located on the same chromosomes in the species that does not show the overlap. We examined the causes of transition between the overlapping and non-overlapping states in the two species and found that 3' UTR change plays an important role in the transition.

conclusionOur study contributes to the understanding of the evolutionary transition between overlapping genes and non-overlapping genes and demonstrates the high rates of evolutionary changes in the un-translated regions.

Indexed as

Evolution, MolecularAnimalsComputational BiologyGenes, OverlappingGenome, HumanHumansMiceModels, GeneticSpecies SpecificityUntranslated RegionsUntranslated Regions

Identifiers

PMID18410680
PMCPMC2335118
OpenAlexW2009965783

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.