The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Behavior-specific changes in transcriptional modules lead to distinct and predictable neurogenomic states
Abstract
Using brain transcriptomic profiles from 853 individual honey bees exhibiting 48 distinct behavioral phenotypes in naturalistic contexts, we report that behavior-specific neurogenomic states can be inferred from the coordinated action of transcription factors (TFs) and their predicted target genes. Unsupervised hierarchical clustering of these transcriptomic profiles showed three clusters that correspond to three ecologically important behavioral categories: aggression, maturation, and foraging. To explore the genetic influences potentially regulating these behavior-specific neurogenomic states, we reconstructed a brain transcriptional regulatory network (TRN) model. This brain TRN quantitatively predicts with high accuracy gene expression changes of more than 2,000 genes involved in behavior, even for behavioral phenotypes on which it was not trained, suggesting that there is a core set of TFs that regulates behavior-specific gene expression in the bee brain, and other TFs more specific to particular categories. TFs playing key roles in the TRN include well-known regulators of neural and behavioral plasticity, e.g., Creb , as well as TFs better known in other biological contexts, e.g., NF-κB (immunity). Our results reveal three insights concerning the relationship between genes and behavior. First, distinct behaviors are subserved by distinct neurogenomic states in the brain. Second, the neurogenomic states underlying different behaviors rely upon both shared and distinct transcriptional modules. Third, despite the complexity of the brain, simple linear relationships between TFs and their putative target genes are a surprisingly prominent feature of the networks underlying behavior.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Many studies have found significant, predictable, and specific changes in brain gene expression profiles associated with behavioral responses to particular environmental stimuli (7–14).”
From Behavior-related gene regulatory networks: A new level of organization in the brain (2020) · cites this paper as [8]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Efron, B., Hastie, T., Johnstone, I., & Tibshirani, R. (2004) · The Annals of Statistics · doi:10.1214/009053604000000067 · Cited by 9,357
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Pvclust: an R package for assessing the uncertainty in hierarchical clustering
Suzuki, R., & Shimodaira, H. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl117 · Cited by 2,482
Margolin, A. A., Nemenman, I., Basso, K., Wiggins, C., Stolovitzky, G., Favera, R. D., & Califano, A. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-s1-s7 · Cited by 2,420
Margolin, A. A., Nemenman, I. M., Basso, K., Wiggins, C. H., Stolovitzky, G. A., Favera, R. D., & Califano, A. (2006) · BMC Bioinformatics · doi:10.7916/d8g15zbp · Cited by 2,259
Winston, M. L. (1987) · Cited by 2,071
THE COMPARISON OF DENDROGRAMS BY OBJECTIVE METHODS
Sokal, R. R., & Rohlf, F. J. (1962) · TAXON · doi:10.2307/1217208 · Cited by 1,727
(2009) · Elsevier eBooks · doi:10.1016/c2009-1-03789-7 · Cited by 1,539
Reverse engineering of regulatory networks in human B cells
Basso, K., Margolin, A. A., Stolovitzky, G. A., Klein, U., Dalla‐Favera, R., & Califano, A. (2005) · Nature Genetics · doi:10.1038/ng1532 · Cited by 1,418
The transcriptional network for mesenchymal transformation of brain tumours
Carro, M. S., Lim, W. K., Alvarez, M. J., Bollo, R. J., Zhao, X., Snyder, E. Y., Sulman, E. P., Anne, S. L., Doetsch, F., Colman, H., et al. (2010) · Nature · doi:10.1038/nature08712 · Cited by 1,259
Cited by
Genomic signatures of evolutionary transitions from solitary to group living
Kapheim, K. M., Pan, H., Li, C., Salzberg, S. L., Puiu, D., Magoc, T., Robertson, H. M., Hudson, M. E., Venkat, A., Fischman, B. J., et al. (2015) · Science · doi:10.1126/science.aaa4788 · Cited by 409
Self-citationRittschof, C. C., Bukhari, S. A., Sloofman, L. G., Troy, J. M., Caetano-Anollés, D., Cash-Ahmed, A., Kent, M., Lu, X., Sanogo, Y. O., Weisner, P. A., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1420369111 · Cited by 163
Self-citationBehavior-related gene regulatory networks: A new level of organization in the brain
Sinha, S., Jones, B. M., Traniello, I. M., Bukhari, S. A., Halfon, M. S., Hofmann, H. A., Huang, S., Katz, P. S., Keagy, J., Lynch, V. J., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1921625117 · Cited by 85
Self-citationYork, R. A., Patil, C., Abdilleh, K., Johnson, Z. V., Conte, M. A., Genner, M. J., McGrath, P. T., Fraser, H. B., Fernald, R. D., & Streelman, J. T. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1810140115 · Cited by 60
Saul, M. C., Seward, C. H., Troy, J. M., Zhang, H., Sloofman, L. G., Lu, X., Weisner, P. A., Caetano-Anolles, D., Sun, H., Zhao, S. D., et al. (2017) · Genome Research · doi:10.1101/gr.214221.116 · Cited by 46
Self-citationKudo, A., Shigenobu, S., Kadota, K., Nozawa, M., Shibata, T. F., Ishikawa, Y., & Matsuo, T. (2017) · Insect Biochemistry and Molecular Biology · doi:10.1016/j.ibmb.2017.01.006 · Cited by 37
Cross‐species systems analysis of evolutionary toolkits of neurogenomic response to social challenge
Saul, M. C., Blatti, C., Yang, W., Bukhari, S. A., Shpigler, H. Y., Troy, J. M., Seward, C. H., Sloofman, L., Chandrasekaran, S., Bell, A. M., et al. (2019) · Genes, Brain and Behavior · doi:10.1111/gbb.12502 · Cited by 38
Self-citationHoney bee neurogenomic responses to affiliative and agonistic social interactions
Shpigler, H. Y., Saul, M. C., Murdoch, E. E., Corona, F., Cash‐Ahmed, A. C., Seward, C. H., Chandrasekaran, S., Stubbs, L. J., & Robinson, G. E. (2019) · Genes, Brain and Behavior · doi:10.1111/gbb.12509 · Cited by 29
Self-citation
Metadata
- Authors
- Chandrasekaran, S., Ament, S. A., Eddy, J. A., Rodriguez-Zas, S. L., Schatz, B. R., Price, N. D., & Robinson, G. E.
- Affiliations
- Center for Biophysics and Computational Biology,
- Neuroscience Program,
- Department of Bioengineering,
- Department of Animal Sciences,
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-09-29
- Volume
- 108
- Issue
- 44
- Pages
- 18020-18025
- ISSN
- 0027-8424
- 1091-6490
- Cited by
- 176
- References
- 30
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
