Abstract

By analyzing multitissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalog of expression quantitative trait loci (eQTLs) in a nonhuman primate model. This catalog contains more genome-wide significant eQTLs per sample than comparable human resources and identifies sex- and age-related expression patterns. Findings include a master regulatory locus that likely has a role in immune function and a locus regulating hippocampal long noncoding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

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Acknowledgements

We thank S. Groman for assistance with tissue resources; T. Chavanne, K. Finnie, M. Long, J. Gardin and D. Swaim for technical assistance with necropsies and tissue collections; and M. Vermunt for sharing rhesus macaque epigenetic data. This work was supported by the following grants, all from the US National Institutes of Health: U54HG00307907 (to R.K.W.); P40RR019963/OD010965 (to J.R.K.); R01RR016300/OD010980 (to N.B.F.); R37MH060233 (to D. Geschwind); UL1DE019580 (to R. Bilder); PL1NS062410 (to C. Evans); RL1MH083270 (to J.D.J.); P30NS062691 (to N.B.F. and G.C.); and R01MH101782 (to C.S. and E.E.). R.N., B.L.A. and P.F. acknowledge support from the Wellcome Trust. P.F., B.L.A. and R.N. acknowledge support from the Wellcome Trust (grant WT108749/Z/15/Z) and the European Molecular Biology Laboratory. E.S.W. was supported by an EMBO Advanced Fellowship (aALTF1672-2014). A.E.F. was supported by US National Institutes of Health award T32MH073526. Data were generated as part of the CommonMind Consortium supported by funding from Takeda Pharmaceuticals Company, F. Hoffman-La Roche and US National Institutes of Health grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1MH-075916, P50M096891, P50MH084053S1, R37MH057881 and R37MH057881S1, HHSN271201300031C, AG02219, AG05138 and MH06692. Brain tissue for the study was obtained from the following brain bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer's Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, and the National Institute of Mental Health (NIMH) Human Brain Collection Core. CMC Leadership: P. Sklar, J. Buxbaum (Icahn School of Medicine at Mount Sinai), B. Devlin, D. Lewis (University of Pittsburgh), R. Gur, C.-G. Hahn (University of Pennsylvania), K. Hirai, H. Toyoshiba (Takeda Pharmaceuticals Company), E. Domenici, L. Essioux (F. Hoffman-La Roche), L. Mangravite, M. Peters (Sage Bionetworks), T. Lehner, B. Lipska (NIMH).

Author information

Author notes

    • Yu S Huang
    • , Vasily Ramensky
    • , Christopher A Schmitt
    • , Richard K Wilson
    •  & J David Jentsch

    Present addresses: State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China (Y.S.H.), Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation (V.R.), Department of Anthropology, Boston University, Boston, Massachusetts, USA (C.A.S.), Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio, USA (R.K.W.) and Department of Psychology, Binghamton University, Binghamton, New York, USA (J.D.J.).

Affiliations

  1. Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.

    • Anna J Jasinska
    • , Susan K Service
    • , Rita M Cantor
    • , Oi-Wa Choi
    • , Joseph DeYoung
    • , Lynn A Fairbanks
    • , Scott Fears
    • , Yu S Huang
    • , Vasily Ramensky
    • , Christopher A Schmitt
    • , Giovanni Coppola
    •  & Nelson B Freimer
  2. Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland.

    • Anna J Jasinska
  3. Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, USA.

    • Ivette Zelaya
  4. Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

    • Christine B Peterson
  5. Department of Human Genetics, University of California, Los Angeles, Los Angeles, California, USA.

    • Rita M Cantor
    • , Eleazar Eskin
    •  & Nelson B Freimer
  6. Department of Computer Science, University of California, Los Angeles, Los Angeles, California, USA.

    • Eleazar Eskin
  7. Interdepartmental Graduate Program in Neuroscience, University of California, Los Angeles, Los Angeles, California, USA.

    • Allison E Furterer
  8. Wellcome Trust Sanger Institute, Hinxton, UK.

    • Hannes Svardal
  9. Department of Pathology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.

    • Matthew J Jorgensen
    •  & Jay R Kaplan
  10. University of Cambridge, Cancer Research UK Cambridge Institute, Cambridge, UK.

    • Diego Villar
  11. European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, UK.

    • Bronwen L Aken
    • , Paul Flicek
    • , Rishi Nag
    •  & Emily S Wong
  12. South Texas Diabetes and Obesity Institute, UTHSCSA/UTRGV, Brownsville, Texas, USA.

    • John Blangero
    •  & Thomas D Dyer
  13. Faculty of Industrial Engineering and Management, Technion, Haifa, Israel.

    • Marina Bogomolov
  14. Department of Statistics and Operation Research, Tel Aviv University, Tel Aviv, Israel.

    • Yoav Benjamini
  15. Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA.

    • George M Weinstock
  16. Department of Human Genetics, McGill University, Montreal, Quebec, Canada.

    • Ken Dewar
  17. Department of Biomedical Data Science, Stanford University, Stanford, California, USA.

    • Chiara Sabatti
  18. Department of Statistics, Stanford University, Stanford, California, USA.

    • Chiara Sabatti
  19. McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, USA.

    • Richard K Wilson
    •  & Wesley Warren
  20. Department of Psychology, University of California, Los Angeles, Los Angeles, California, USA.

    • J David Jentsch
  21. Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.

    • J David Jentsch
    •  & Roger P Woods
  22. Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.

    • Giovanni Coppola
    •  & Roger P Woods

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Contributions

A.J.J., J.R.K., G.M.W., K.D., R.K.W., J.D.J., W.W., R.P.W. and N.B.F. designed the study. A.J.J., I.Z., O.-W.C., J.D., L.A.F., S.F., A.E.F., Y.S.H., V.R., C.A.S., J.D.J., G.C. and R.P.W. produced the data. A.J.J., I.Z., S.K.S., C.B.P., R.M.C., E.E., L.A.F., S.F., Y.S.H., V.R., C.A.S., H.S., D.V., B.L.A., P.F., R.N., E.S.W., J.B., T.D.D., M.B., Y.B., C.S. and G.C. analyzed the data. O.-W.C., J.D. and M.J.J. managed data and samples. A.J.J., S.K.S. and N.B.F. wrote the manuscript. All authors reviewed the final draft.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Nelson B Freimer.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–12, Supplementary Tables 1, 2, 4–6 and 10–24, and Supplementary Note

  2. 2.

    Life Sciences Reporting Summary

Excel files

  1. 1.

    Supplementary Table 3

    Genes with high expression in one of the seven tissues evaluated with RNA-seq.

  2. 2.

    Supplementary Table 7

    Genes in the top or bottom 10% of loadings on PC1–PC3.

  3. 3.

    Supplementary Table 8

    Genes in the top or bottom 10% of loadings on PC1 for caudate and BA46.

  4. 4.

    Supplementary Table 9

    Genes with a significant age effect from either ANOVA or linear regression.

  5. 5.

    Supplementary Data 1

    Listing of all 22,184 probes on the HumanRef-8 v2 array and indicators for different probe filtering criteria.

  6. 6.

    Supplementary Data 2

    Estimates of heritability for 6,018 probes that passed filtering criteria described in Supplementary Table 1.

  7. 7.

    Supplementary Data 3

    All significant probe–SNP combinations (at Bonferroni thresholds) from the analysis of microarray gene expression.

  8. 8.

    Supplementary Data 4

    All significant gene–SNP combinations (at Bonferroni thresholds) from the analysis of RNA-seq expression data.