Evidence map›Paper›PMID 26541291›Full record

ArticleBMC genomics2015

Comprehensive transcriptional landscape of aging mouse liver.

Ryan R White, Brandon Milholland, Sheila L MacRae, Mingyan Lin, Deyou Zheng, Jan Vijg

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 5% 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

76 citing papers in PubMed, 1 synthesis or guideline pooled it, 123 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Stem cell-based therapeutic strategies for liver aging.Liver research (Beijing, China) · 2025
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

16 more citing papers are in PubMed but not listed here.

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

6 authors at 1 institution in 1 country.

Ryan R WhiteDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA. ryan.white@phd.einstein.yu.edu.
Brandon MilhollandDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA. brandon.milholland@phd.einstein.yu.edu.
Sheila L MacRaeDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA. sheila.macrae@phd.einstein.yu.edu.
Mingyan LinDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA. mingyan.lin@phd.einstein.yu.edu.
Deyou ZhengDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA. deyou.zheng@einstein.yu.edu.
Jan VijgDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA. jan.vijg@einstein.yu.edu.
Albert Einstein College of Medicine · US

Funding

WORD PROCESSORP30CA013330 · NCI · YESHIVA UNIVERSITY · PI ALYSON B MOADEL · 1985 to 2026
$111.2M
THE IMPACT OF CELLULAR DEFENSE ON THE ROLE OF Ku80 IN GENOME MAINTENANCE AND LONGP01AG017242 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR SAN ANT · PI VIJG, JAN · 1999 to 2023
$46.1M
TRAINING PROGRAM IN CELLULAR &MOLEC. BIOLOGY &GENETICST32GM007491 · NIGMS · YESHIVA UNIVERSITY · PI QUERY, CHARLES C · 1985 to 2021
$17.0M
Training in Aging ResearchT32AG023475 · NIA · ALBERT EINSTEIN COL OF MED YESHIVA UNIV · PI NIR J BARZILAI, DEREK Major HUFFMAN · 2004 to 2026
$8.6M
NCI NIH HHS P30 CA013330NIA NIH HHS P01 AG017242NIA NIH HHS T32 AG023475NIGMS NIH HHS T32 GM007491
6 · The paper itself

Abstract

backgroundMammalian aging is a highly complex process, a full mechanistic understanding of which is still lacking. One way to help understand the molecular changes underlying aging is through a comprehensive analysis of the transcriptome, the primary determinant of age-related phenotypic diversity. Previous studies have relied on microarray analysis to examine gene expression profiles in different tissues of aging organisms. However, studies have shown microarray-based transcriptional profiling is less accurate and not fully capable of capturing certain intricacies of the global transcriptome.

methodsHere, using directional whole transcriptome RNA-sequencing of aged mouse liver we have identified a comprehensive high-resolution profile of differentially expressed liver transcripts comprised of canonical protein-coding transcripts, transcript isoforms, and non-coding RNA transcripts, including pseudogenes, long non-coding RNAs and small RNA species.

resultsResults show extensive age-related changes in every component of the mouse liver transcriptome and a pronounced increase in inter-individual variation. Functional annotation of the protein-coding mRNAs and isoforms indicated broad alterations in immune response, cell activation, metabolic processes, and RNA modification. Interestingly, multiple lncRNAs (Meg3, Rian, Mirg) from the Dlk-Dio3 microRNA locus were found up-regulated in aging liver, classifying this locus as a putative regulatory hotspot locus in aging liver. Moreover, integration of the altered non-coding RNAs and protein-coding transcripts into interaction networks of age-related change revealed inflammation, cellular proliferation, and metabolism as the dominant aging phenotypes in mouse liver.

conclusionsOur analyses provide the first comprehensive dissection of the transcriptional landscape in aging mouse liver.

Indexed as

AgingAnimalsLiverMaleMiceMice, Inbred BALB CTranscriptome

Identifiers

PMID26541291
PMCPMC4636074
OpenAlexW2149524489

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.