Back

Transcriptome analysis of different strains of the turquoise killifish Nothobranchius furzeri identifies signatures associated with heritable lifespan differences

Mazzetto, M.; Reichwald, K.; Kelmer Sacramento, E.; Koch, P.; Ori, A.; Groth, M.; Cellerino, A.

2023-11-21 genomics
10.1101/2023.11.20.567823 bioRxiv
Show abstract

The killifish Nothobranchius furzeri is the shortest-lived vertebrate model organism and is characterized by laboratory strains differing in lifespan by more than a factor of two. The genetic architecture underlying this difference is complex and the pathways responsive remain elusive. We performed an analysis in N. furzeri of public transcritomic datasets comprehensive of four different tissues and one embryonic stage in two strains: the shorter-lived GRZ and the longer-lived MZM0410. Remarkably, the two strains differ in their transcriptome profile already at the embryonic stage. The short-lived strain GRZ shows an anticipated aging profile consistently in all tissues investigated, with differences in expression of aging-related genes detected already at sexual maturity. In addition, analysis of a longitudinal dataset revealed that genes whose expression is prognostic of longer lifespan at the individual level are also differentially expressed between strains at an early adult age, suggesting antagonistic pleiotropism.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Aging Cell
○ 165 papers in training set
Top 0.2%
18.4%
Similar papers in this journal
2
GeroScience
○ 109 papers in training set
Top 0.2%
12.4%
Similar papers in this journal
3
Aging
○ 75 papers in training set
Top 0.1%
7.8%
Similar papers in this journal
4
BMC Biology
○ 265 papers in training set
Top 0.6%
3.5%
Similar papers in this journal
5
International Journal of Molecular Sciences
○ 494 papers in training set
Top 3%
3.4%
Similar papers in this journal
6
Scientific Reports
○ 3612 papers in training set
Top 36%
2.8%
7
BMC Genomics
○ 406 papers in training set
Top 3%
2.6%
50% of probability mass above
8
eLife
● 5828 papers in training set
Top 42%
2.4%
9
Advanced Biology
○ 29 papers in training set
Top 0.2%
2.4%
10
Molecular Neurobiology
○ 53 papers in training set
Top 0.4%
2.4%
11
Biology of Sex Differences
○ 32 papers in training set
Top 0.2%
2.1%
12
iScience
○ 1154 papers in training set
Top 14%
2.1%
13
PLOS ONE
● 5266 papers in training set
Top 45%
1.9%
14
Nature Communications
○ 5641 papers in training set
Top 45%
1.7%
15
Biology
○ 45 papers in training set
Top 0.2%
1.5%
16
Communications Biology
○ 993 papers in training set
Top 18%
1.4%
17
Genes
○ 144 papers in training set
Top 2%
1.4%
18
Cells
○ 249 papers in training set
Top 4%
1.4%
19
Life Science Alliance
● 285 papers in training set
Top 5%
1.1%
20
Nature Aging
○ 60 papers in training set
Top 1%
1.1%
21
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 5%
1.1%
22
Frontiers in Genetics
○ 230 papers in training set
Top 5%
1.0%
23
GigaScience
◐ 212 papers in training set
Top 4%
0.9%
24
FEBS Open Bio
○ 31 papers in training set
Top 0.9%
0.8%
25
EMBO Reports
○ 263 papers in training set
Top 7%
0.8%
26
Physiological Genomics
● 16 papers in training set
Top 0.4%
0.8%
27
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 4%
0.8%
28
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease
○ 26 papers in training set
Top 1%
0.6%
29
Cell Reports
○ 1498 papers in training set
Top 29%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.