Multiomic profiling of the liver across diets and age in a diverse mouse population
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
We profiled the liver transcriptome, proteome, and metabolome in 347 individuals from 58 isogenic strains of the BXD mouse population across age (7 to 24 months) and diet (low or high fat) to link molecular variations to metabolic traits. Several hundred genes are affected by diet and/or age at the transcript and protein levels. Orthologs of two aging-associated genes, St7 and Ctsd, were knocked down in C. elegans, reducing longevity in wild-type and mutant long-lived strains. The multiomics data were analyzed as segregating gene networks according to each independent variable, providing causal insight into dietary and aging effects. Candidates were cross-examined in an independent diversity outbred mouse liver dataset segregating for similar diets, with ∼80%–90% of diet-related candidate genes found in common across datasets. Together, we have developed a large multiomics resource for multivariate analysis of complex traits and demonstrate a methodology for moving from observational associations to causal connections.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Cell Systems |
| Vol/bind | 13 |
| Udgave nummer | 1 |
| Sider (fra-til) | 43-57, e1-6 |
| ISSN | 2405-4712 |
| DOI | |
| Status | Udgivet - 2022 |
Bibliografisk note
Funding Information:
Research was further supported by the EPFL , ETHZ , the NIH ( R01AG043930 to R.W.W.), the European Research Council (Proteomics4D) (AdvG grant 670821 and proteomics v3.0; AdvG-233226 to R.A.), and SNSF ( 31003A-140780 , 31003A-143914 , and CSRII3-136201 to R.A., PP00P3_163898 to C.S. and C.Y.E.). N.P. and P.B. were supported by ERC no. 786461 (CausalStats - ERC-2017-AdvG ). E.G.W. was supported by an NIH F32 Ruth Kirchstein Fellowship ( F32GM119190 ). Thanks to Lorne Rose at the University of Tennessee Center of Excellence Sequencing Facility for transcriptomics; to Sebastien Lamy at the EPFL phenotyping unit (UDP) for clinical blood analysis; to Casey Chapman for BXD colony maintenance; and to Ludovic Gillet, Patrick Pedrioli, Özgen Eren, Chloe Lee, and Yansheng Liu for proteomics discussions.
Funding Information:
Research was further supported by the EPFL, ETHZ, the NIH (R01AG043930 to R.W.W.), the European Research Council (Proteomics4D) (AdvG grant 670821 and proteomics v3.0; AdvG-233226 to R.A.), and SNSF (31003A-140780, 31003A-143914, and CSRII3-136201 to R.A. PP00P3_163898 to C.S. and C.Y.E.). N.P. and P.B. were supported by ERC no. 786461 (CausalStats - ERC-2017-AdvG). E.G.W. was supported by an NIH F32 Ruth Kirchstein Fellowship (F32GM119190). Thanks to Lorne Rose at the University of Tennessee Center of Excellence Sequencing Facility for transcriptomics; to Sebastien Lamy at the EPFL phenotyping unit (UDP) for clinical blood analysis; to Casey Chapman for BXD colony maintenance; and to Ludovic Gillet, Patrick Pedrioli, ?zgen Eren, Chloe Lee, and Yansheng Liu for proteomics discussions. E.G.W. and R.W.W. established the BXD aging project and secured funding. S.R. E.G.W. C.B. J.I. R.W.W. and L.L. managed the colony and the tissue collections. J.I. and C.B. managed the daily needs of the BXD colony. J.I. S.R. and R.W.W. performed the transcriptomics. R.A. and E.G.W. performed the proteomics. J.H. calculated the QTLs. M.H. N.Z. and E.G.W. performed the metabolomics. J.C. normalized the proteomics data. N.P. and P.B. developed and performed the causality/stability analyses. E.G.W. performed all other statistical analyses on the omics data. C.S. and C.Y.E. performed the C. elegans experiments. The paper was written primarily by E.G.W. N.P. R.W.W. and R.A. with input from the other authors for their specific contributions. The authors declare no competing interests.
Publisher Copyright:
© 2021 Elsevier Inc.
Links
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776606/pdf/nihms-1743558.pdf
Accepteret manuskript
ID: 304515902