The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.
Evolutionary Genomics of Nuclear Receptors: From Twenty-Five Ancestral Genes to Derived Endocrine Systems
Open accessAbstract
Bilaterian animals are notably characterized by complex endocrine systems. The receptors for many steroids, retinoids, and other hormones belong to the superfamily of nuclear receptors, which are transcription factors regulating many aspects of development and homeostasis. Despite a diversity of regulatory mechanisms and physiological roles, nuclear receptors share a common protein organization. To obtain the broad picture of bilaterian nuclear hormone receptor evolution, we have characterized the complete set of nuclear receptor genes from nine animal genome sequences and analyzed it in a phylogenetic framework. In addition, expressed sequence tags from key lineages with no available genome sequence were also searched. This allows us to date the evolutionary events that led from an ancestral nuclear receptor gene, in an early metazoan, to present day diversity. We show that there were approximately 25 nuclear receptor genes in Urbilateria, the ancestor of bilaterians, at which point the fundamental diversity of the subfamily was already established. Surprisingly, differential gene loss played an important role in the evolution of different nuclear receptor sets in bilaterian lineages. The nuclear receptor distribution was also shaped by periods of gene duplication, essentially in vertebrates, as well as a lineage-specific duplication burst in nematodes. Our results imply that the genes for major receptors such as steroid receptors or thyroid hormone receptors were present in Urbilateria.
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.
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
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
The neighbor-joining method: a new method for reconstructing phylogenetic trees.
(1987) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040454 · Cited by 59,715
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
Guindon, S., & Gascuel, O. (2003) · Systematic Biology · doi:10.1080/10635150390235520 · Cited by 16,806
Initial sequencing and comparative analysis of the mouse genome
Mouse Genome Sequencing Consortium (2002) · Nature · doi:10.1038/nature01262 · Cited by 7,187
The rapid generation of mutation data matrices from protein sequences
Jones, D. T., Taylor, W. R., & Thornton, J. M. (1992) · Bioinformatics · doi:10.1093/bioinformatics/8.3.275 · Cited by 6,947
The Genome Sequence of Drosophila melanogaster
Adams, M. D., Celniker, S. E., Holt, R. A., Evans, C. A., Gocayne, J. D., Amanatides, P. G., Scherer, S. E., Li, P. W., Hoskins, R. A., Galle, R. F., et al. (2000) · Science · doi:10.1126/science.287.5461.2185 · Cited by 5,929
Multiple Comparisons of Log-Likelihoods with Applications to Phylogenetic Inference
Shimodaira, H., & Hasegawa, M. (1999) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a026201 · Cited by 4,237
TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing
Schmidt, H. A., Strimmer, K., Vingron, M., & von Haeseler, A. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.3.502 · Cited by 2,532
SEAVIEW and PHYLO_WIN: two graphic tools for sequence alignment and molecular phylogeny
Galtier, N., Gouy, M., & Gautier, C. (1996) · Bioinformatics · doi:10.1093/bioinformatics/12.6.543 · Cited by 2,263
Genome sequence of the Brown Norway rat yields insights into mammalian evolution
Rat Genome Sequencing Project Consortium, DNA sequencing: Baylor College of Medicine, Gibbs, R. A., Weinstock, G. M., Metzker, M. L., Muzny, D. M., Sodergren, E. J., Scherer, S., Scott, G., Steffen, D., et al. (2004) · Nature · doi:10.1038/nature02426 · Cited by 2,164
Cited by
State-of-the-science of endocrine disrupting chemicals, 2012
Bergman, Å., Heindel, J., Jobling, S., Kidd, K., & Zoeller, R. T. (2012) · Toxicology Letters · doi:10.1016/j.toxlet.2012.03.020 · Cited by 1,388
The evolutionary significance of ancient genome duplications
Van de Peer, Y., Maere, S., & Meyer, A. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2600 · Cited by 1,129
Brown, D. D., & Cai, L. (2007) · Developmental Biology · doi:10.1016/j.ydbio.2007.03.021 · Cited by 498
Nuclear Hormone Receptor NHR-49 Controls Fat Consumption and Fatty Acid Composition in C. elegans
Gilst, M. R. V., Hadjivassiliou, H., Jolly, A., & Yamamoto, K. R. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030053 · Cited by 428
Retinoic acid receptors: From molecular mechanisms to cancer therapy
di Masi, A., Leboffe, L., De Marinis, E., Pagano, F., Cicconi, L., Rochette-Egly, C., Lo-Coco, F., Ascenzi, P., & Nervi, C. (2015) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2014.12.003 · Cited by 403
Metadata
- Authors
- Bertrand, S., Brunet, F. G., Escriva, H., Parmentier, G., Laudet, V., & Robinson-Rechavi, M.
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-06-30
- Volume
- 21
- Issue
- 10
- Pages
- 1923-1937
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- OpenAlex
- W2142693509
- Cited by
- 351
- References
- 78
- FWCI
- 22.12
- Type
- journal article
- Language
- en
- Open access
- bronze
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Evolutionary Genomics of Nuclear Receptors: From Twenty-Five Ancestral Genes to Derived Endocrine Systems. https://app.cochat.ai/papers/10.1093/molbev/msh200
- The paper
- Bertrand, S., Brunet, F. G., Escriva, H., Parmentier, G., Laudet, V., & Robinson-Rechavi, M. (2004). Evolutionary Genomics of Nuclear Receptors: From Twenty-Five Ancestral Genes to Derived Endocrine Systems. Molecular Biology and Evolution. https://doi.org/10.1093/molbev/msh200
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.