Summary: Oestrogen receptor
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Estrogen receptor Edit Wikipedia article
|estrogen receptor 1 (ER-alpha)|
|A dimer of the ligand-binding region of ERα (PDB rendering based on ).|
|Alt. symbols||ER-α, NR3A1|
|Locus||Chr. 6 q24-q27|
|estrogen receptor 2 (ER-beta)|
|A dimer of the ligand-binding region of ERβ (PDB rendering based on ).|
|Alt. symbols||ER-β, NR3A2|
|Locus||Chr. 14 q21-q22|
Estrogen receptors are a group of proteins found inside cells. They are receptors that are activated by the hormone estrogen (17β-estradiol). Two classes of estrogen receptor exist: ER, which is a member of the nuclear hormone family of intracellular receptors, and GPER, which is a member of the rhodopsin-like family of G protein-coupled receptors. This article refers to the former (ER).
Once activated by estrogen, the ER is able to translocate into the nucleus and bind to DNA to regulate the activity of different genes (i.e. it is a DNA-binding transcription factor). However, it also has additional functions independent of DNA binding.
There are two different forms of the estrogen receptor, usually referred to as α and β, each encoded by a separate gene (ESR1 and ESR2, respectively). Hormone-activated estrogen receptors form dimers, and, since the two forms are coexpressed in many cell types, the receptors may form ERα (αα) or ERβ (ββ) homodimers or ERαβ (αβ) heterodimers. Estrogen receptor alpha and beta show significant overall sequence homology, and both are composed of five domains (listed from the N- to C-terminus; amino acid sequence numbers refer to human ER):(A-F domain)
The N-terminal A/B domain is able to transactivate gene transcription in the absence of bound ligand (e.g., the estrogen hormone). While this region is able to activate gene transcription without ligand, this activation is weak and more selective compared to the activation provided by the E domain. The C domain, also known as the DNA-binding domain, binds to estrogen response elements in DNA. The D domain is a hinge region that connects the C and E domains. The E domain contains the ligand binding cavity as well as binding sites for coactivator and corepressor proteins. The E-domain in the presence of bound ligand is able to activate gene transcription. The C-terminal F domain function is not entirely clear and is variable in length.
Due to alternative RNA splicing, several ER isoforms are known to exist. At least three ERalpha and five ERbeta isoforms have been identified. The ERbeta isoforms receptor subtypes can transactivate transcription only when a heterodimer with the functional ERß1 receptor of 59 kDa is formed. The ERß3 receptor was detected at high levels in the testis. The two other ERalpha isoforms are 36 and 46kDa.
Only in fish, but not in humans, an ERgamma receptor has been described.
Both ERs are widely expressed in different tissue types, however there are some notable differences in their expression patterns:
- The ERα is found in endometrium, breast cancer cells, ovarian stroma cells, and the hypothalamus. In males, ERα protein is found in the epithelium of the efferent ducts.
- The expression of the ERβ protein has been documented in kidney, brain, bone, heart, lungs, intestinal mucosa, prostate, and endothelial cells.
The ERs are regarded to be cytoplasmic receptors in their unliganded state, but visualization research has shown that a fraction of the ERs resides in the nucleus. The "ERα" primary transcript gives rise to several alternatively spliced variants of unknown function.
 Binding and functional selectivity
Different ligands may differ in their affinity for alpha and beta isoforms of the estrogen receptor:
- 17-beta-estradiol binds equally well to both receptors
- estrone, and raloxifene bind preferentially to the alpha receptor
- estriol, and genistein to the beta receptor
Subtype selective estrogen receptor modulators preferentially bind to either the α- or the β-subtype of the receptor. In addition, the different estrogen receptor combinations may respond differently to various ligands, which may translate into tissue selective agonistic and antagonistic effects. The ratio of α- to β- subtype concentration has been proposed to play a role in certain diseases.
The concept of selective estrogen receptor modulators is based on the ability to promote ER interactions with different proteins such as transcriptional coactivator or corepressors. Furthermore, the ratio of coactivator to corepressor protein varies in different tissues. As a consequence, the same ligand may be an agonist in some tissue (where coactivators predominate) while antagonistic in other tissues (where corepressors dominate). Tamoxifen, for example, is an antagonist in breast and is, therefore, used as a breast cancer treatment but an ER agonist in bone (thereby preventing osteoporosis) and a partial agonist in the endometrium (increasing the risk of uterine cancer) .
 Signal transduction
In the absence of hormone, estrogen receptors are largely located in the cytosol. Hormone binding to the receptor triggers a number of events starting with migration of the receptor from the cytosol into the nucleus, dimerization of the receptor, and subsequent binding of the receptor dimer to specific sequences of DNA known as hormone response elements. The DNA/receptor complex then recruits other proteins that are responsible for the transcription of downstream DNA into mRNA and finally protein that results in a change in cell function. Estrogen receptors also occur within the cell nucleus, and both estrogen receptor subtypes have a DNA-binding domain and can function as transcription factors to regulate the production of proteins.
In addition, some ER may associate with cell membranes by attachment to caveolin-1 and form complexes with G proteins, striatin, receptor tyrosine kinases (e.g., EGFR and IGF-1), and non-receptor tyrosine kinases (e.g., Src). Through striatin, some of this membrane bound ER may lead to increased levels of Ca2+ and nitric oxide (NO). Through the receptor tyrosine kinases, signals are sent to the nucleus through the mitogen-activated protein kinase (MAPK/ERK) pathway and phosphoinositide 3-kinase (Pl3K/AKT) pathway. Glycogen synthase kinase-3 (GSK)-3β inhibits transcription by nuclear ER by inhibiting phosphorylation of serine 118 of nuclear ERα. Phosphorylation of GSK-3β removes its inhibitory effect, and this can be achieved by the PI3K/AKT pathway and the MAPK/ERK pathway, via rsk.
Estrogen receptors are over-expressed in around 70% of breast cancer cases, referred to as "ER-positive", and can be demonstrated in such tissues using immunohistochemistry. Two hypotheses have been proposed to explain why this causes tumorigenesis, and the available evidence suggests that both mechanisms contribute:
- First, binding of estrogen to the ER stimulates proliferation of mammary cells, with the resulting increase in cell division and DNA replication, leading to mutations.
- Second, estrogen metabolism produces genotoxic waste.
The result of both processes is disruption of cell cycle, apoptosis and DNA repair, and, therefore, tumour formation. ERα is certainly associated with more differentiated tumours, while evidence that ERβ is involved is controversial. Different versions of the ESR1 gene have been identified (with single-nucleotide polymorphisms) and are associated with different risks of developing breast cancer.
Endocrine therapy for breast cancer involves selective estrogen receptor modulators (SERMS), such as tamoxifen, which behave as ER antagonists in breast tissue, or aromatase inhibitors, such as anastrozole. ER status is used to determine sensitivity of breast cancer lesions to tamoxifen and aromatase inhibitors. Another SERM, raloxifene, has been used as a preventive chemotherapy for women judged to have a high risk of developing breast cancer. Another chemotherapeutic anti-estrogen, ICI 182,780 (Faslodex), which acts as a complete antagonist, also promotes degradation of the estrogen receptor.
Estrogen and the ERs have also been implicated in breast cancer, ovarian cancer, colon cancer, prostate cancer, and endometrial cancer. Advanced colon cancer is associated with a loss of ERβ, the predominant ER in colon tissue, and colon cancer is treated with ERβ-specific agonists.
Phytoestrogens such as quercetin can modulate estrogen receptor’s activities in such a way that it may prevent cancers including breasts, prostate, and colon all by promoting apoptosis. Quercetin selectively binds to the estrogen receptor beta (ERβ). This was tested in HeLa cells which were treated with a pure estrogen receptor antagonist which blocked both estradiol and quercetin from inducing the caspase-3 activation. ERβ is expressed in the human colon and activates a specific signal transduction pathway that controls apoptosis in the colon and works by being activated by estradiol and more recently found to possibly be activated by quercetin. Quercetin activates the ERβ along with the apoptotic cascade when caspase-3 is present by the phosphorylation of p38 kinase. In colon cancers and tumors ERβ and its pathway have been proven to be significantly decreased thus allowing the tumors to thrive.
Studies in female mice have shown that estrogen receptor-alpha declines in the pre-optic hypothalamus as they grow old. Female mice that were given a calorically restricted diet during the majority of their lives maintained higher levels of ERα in the pre-optic hypothalamus than their non-calorically restricted counterparts.
A dramatic demonstration of the importance of estrogens in the regulation of fat deposition comes from transgenic mice that were genetically engineered to lack a functional aromatase gene. These mice have very low levels of estrogen and are obese. Obesity was also observed in estrogen deficient female mice lacking the follicle-stimulating hormone receptor. The effect of low estrogen on increased obesity has been linked to estrogen receptor alpha.
 Research history
Estrogen receptors were first identified by Elwood V. Jensen at the University of Chicago in 1958, for which Jensen was awarded the Lasker Award. The gene for a second estrogen receptor (ERβ) was identified in 1996 by Kuiper et al. in rat prostate and ovary using degenerate ERalpha primers.
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- Pfeffer U, Fecarotta E, Vidali G (15 May 1995). "Coexpression of multiple estrogen receptor variant messenger RNAs in normal and neoplastic breast tissues and in MCF-7 cells". Cancer Res 55 (10): 2158–65. PMID 7743517.
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- Bourguet W, Germain P, Gronemeyer H (October 2000). "Nuclear receptor ligand-binding domains: three-dimensional structures, molecular interactions and pharmacological implications". Trends Pharmacol Sci 21 (10): 381–8. doi:10.1016/S0165-6147(00)01548-0. PMID 11050318.
- Kansra S, Yamagata S, Sneade L, Foster L, Ben-Jonathan N (2005). "Differential effects of estrogen receptor antagonists on pituitary lactotroph proliferation and prolactin release". Mol. Cell. Endocrinol. 239 (1-2): 27–36. doi:10.1016/j.mce.2005.04.008. PMID 15950373.
- Bakas P, Liapis A, Vlahopoulos S, Giner M, Logotheti S, Creatsas G, Meligova AK, Alexis MN, Zoumpourlis V (December 2007). "Estrogen receptor alpha and beta in uterine fibroids: a basis for altered estrogen responsiveness". Fertil. Steril. 90 (5): 1878–85. doi:10.1016/j.fertnstert.2007.09.019. PMID 18166184.
- Shang Y, Brown M (2002). "Molecular determinants for the tissue specificity of SERMs". Science 295 (5564): 2465–8. doi:10.1126/science.1068537. PMID 11923541.
- Deroo BJ, Korach KS (2006). "Estrogen receptors and human disease". J. Clin. Invest. 116 (3): 561–7. doi:10.1172/JCI27987. PMC 2373424. PMID 16511588. //www.ncbi.nlm.nih.gov/pmc/articles/PMC2373424/.
- Zivadinovic D, Gametchu B, Watson CS (2005). "Membrane estrogen receptor-alpha levels in MCF-7 breast cancer cells predict cAMP and proliferation responses". Breast Cancer Res. 7 (1): R101–12. doi:10.1186/bcr958. PMC 1064104. PMID 15642158. //www.ncbi.nlm.nih.gov/pmc/articles/PMC1064104/.
- Björnström L, Sjöberg M (2004). "Estrogen receptor-dependent activation of AP-1 via non-genomic signalling". Nucl Recept 2 (1): 3. doi:10.1186/1478-1336-2-3. PMC 434532. PMID 15196329. //www.ncbi.nlm.nih.gov/pmc/articles/PMC434532/.
- Lu Q, Pallas DC, Surks HK, Baur WE, Mendelsohn ME, Karas RH (2004). "Striatin assembles a membrane signaling complex necessary for rapid, nongenomic activation of endothelial NO synthase by estrogen receptor alpha". Proc. Natl. Acad. Sci. U.S.A. 101 (49): 17126–31. doi:10.1073/pnas.0407492101. PMC 534607. PMID 15569929. //www.ncbi.nlm.nih.gov/pmc/articles/PMC534607/.
- Kato S, Endoh H, Masuhiro Y, Kitamoto T, Uchiyama S, Sasaki H, Masushige S, Gotoh Y, Nishida E, Kawashima H, Metzger D, Chambon P (1995). "Activation of the estrogen receptor through phosphorylation by mitogen-activated protein kinase". Science 270 (5241): 1491–4. doi:10.1126/science.270.5241.1491. PMID 7491495.
- Prossnitz ER, Arterburn JB, Sklar LA (2007). "GPR30: A G protein-coupled receptor for estrogen". Mol. Cell. Endocrinol. 265-266: 138–42. doi:10.1016/j.mce.2006.12.010. PMC 1847610. PMID 17222505. //www.ncbi.nlm.nih.gov/pmc/articles/PMC1847610/.
- Otto C, Rohde-Schulz B, Schwarz G, Fuchs I, Klewer M, Brittain D, Langer G, Bader B, Prelle K, Nubbemeyer R, Fritzemeier KH (2008). "G protein-coupled receptor 30 localizes to the endoplasmic reticulum and is not activated by estradiol.". Endocrinology. 149 (10): 4846–56. doi:10.1210/en.2008-0269. PMID 18566127.
- Clemons M, Danson S, Howell A (2002). "Tamoxifen (Nolvadox): A Review". Cancer Treat. Rev. 28 (4): 165–180. PMID 12363457.
- Fabian CJ, Kimler BF (2005). "Selective estrogen-receptor modulators for primary prevention of breast cancer". J. Clin. Oncol. 23 (8): 1644–55. doi:10.1200/JCO.2005.11.005. PMID 15755972.
- Harris HA, Albert LM, Leathurby Y, Malamas MS, Mewshaw RE, Miller CP, Kharode YP, Marzolf J, Komm BS, Winneker RC, Frail DE, Henderson RA, Zhu Y, Keith JC (2003). "Evaluation of an estrogen receptor-beta agonist in animal models of human disease". Endocrinology 144 (10): 4241–9. doi:10.1210/en.2003-0550. PMID 14500559.
- Bulzomi P, Galluzzo P, Bolli A, Leone S, Acconcia F, Marino M (May 2012). "The pro-apoptotic effect of quercetin in cancer cell lines requires ERβ-dependent signals". J. Cell. Physiol. 227 (5): 1891–8. doi:10.1002/jcp.22917. PMID 21732360.
- Ascenzi P, Bocedi A, Marino M (August 2006). "Structure-function relationship of estrogen receptor alpha and beta: impact on human health". Mol. Aspects Med. 27 (4): 299–402. doi:10.1016/j.mam.2006.07.001. PMID 16914190.
- Konstantinopoulos PA, Kominea A, Vandoros G, Sykiotis GP, Andricopoulos P, Varakis I, Sotiropoulou-Bonikou G, Papavassiliou AG (June 2003). "Oestrogen receptor beta (ERbeta) is abundantly expressed in normal colonic mucosa, but declines in colon adenocarcinoma paralleling the tumour's dedifferentiation". Eur. J. Cancer 39 (9): 1251–8. PMID 12763213.
- Hewitt KN, Boon WC, Murata Y, Jones ME, Simpson ER (2003). "The aromatase knockout mouse presents with a sexually dimorphic disruption to cholesterol homeostasis". Endocrinology 144 (9): 3895–903. doi:10.1210/en.2003-0244. PMID 12933663.
- Danilovich N, Babu PS, Xing W, Gerdes M, Krishnamurthy H, Sairam MR (2000). "Estrogen deficiency, obesity, and skeletal abnormalities in follicle-stimulating hormone receptor knockout (FORKO) female mice". Endocrinology 141 (11): 4295–308. doi:10.1210/en.141.11.4295. PMID 11089565.
- Ohlsson C, Hellberg N, Parini P, Vidal O, Bohlooly-Y M, Bohlooly M, Rudling M, Lindberg MK, Warner M, Angelin B, Gustafsson JA (2000). "Obesity and disturbed lipoprotein profile in estrogen receptor-alpha-deficient male mice". Biochem. Biophys. Res. Commun. 278 (3): 640–5. doi:10.1006/bbrc.2000.3827. PMID 11095962.
- Jensen EV, Jordan VC (1 June 2003). "The estrogen receptor: a model for molecular medicine" (abstract). Clin. Cancer Res. 9 (6): 1980–9. PMID 12796359. http://clincancerres.aacrjournals.org/cgi/content/abstract/9/6/1980.
- Moore DD (2011). "A Conversation with Elwood Jensen.". Annu Rev Physiol 74: 1–11. doi:10.1146/annurev-physiol-020911-153327. PMID 21888507.
- David Bracey, 2004 "UC Scientist Wins 'American Nobel' Research Award." University of Cincinnati press release.
- Kuiper GG, Enmark E, Pelto-Huikko M, Nilsson S, Gustafsson JA (1996). "Cloning of a novel receptor expressed in rat prostate and ovary". Proc. Natl. Acad. Sci. U.S.A. 93 (12): 5925–30. doi:10.1073/pnas.93.12.5925. PMC 39164. PMID 8650195. //www.ncbi.nlm.nih.gov/pmc/articles/PMC39164/.
- Estrogen Receptors at the US National Library of Medicine Medical Subject Headings (MeSH)
- David S. Goodsell (2003-09-01). "Estrogen Receptor". Protein Data Bank, Research Collaboratory for Structural Bioinformatics (RCSB). http://www.rcsb.org/pdb/static.do?p=education_discussion/molecule_of_the_month/pdb45_1.html. Retrieved 2008-03-15.
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This tab holds annotation information from the InterPro database.
InterPro entry IPR001292
Steroid or nuclear hormone receptors (4A nuclear receptor, NRs) constitute an important superfamily of transcription regulators that are involved in widely diverse physiological functions, including control of embryonic development, cell differentiation and homeostasis. Members of the superfamily include the steroid hormone receptors and receptors for thyroid hormone, retinoids, 1,25-dihydroxy-vitamin D3 and a variety of other ligands [PUBMED:14747695]. The proteins function as dimeric molecules in nuclei to regulate the transcription of target genes in a ligand-responsive manner [PUBMED:7899080, PUBMED:8165128]. In addition to C-terminal ligand-binding domains, these nuclear receptors contain a highly-conserved, N-terminal zinc-finger that mediates specific binding to target DNA sequences, termed ligand-responsive elements. In the absence of ligand, steroid hormone receptors are thought to be weakly associated with nuclear components; hormone binding greatly increases receptor affinity.
NRs are extremely important in medical research, a large number of them being implicated in diseases such as cancer, diabetes, hormone resistance syndromes, etc. While several NRs act as ligand-inducible transcription factors, many do not yet have a defined ligand and are accordingly termed 'orphan' receptors. During the last decade, more than 300 NRs have been described, many of which are orphans, which cannot easily be named due to current nomenclature confusions in the literature. However, a new system has recently been introduced in an attempt to rationalise the increasingly complex set of names used to describe superfamily members.
The oestrogen receptors (ERs) are steroid or nuclear hormone receptors that act as transcription regulators involved in diverse physiological functions. Oestrogen receptors function as dimeric molecules in nuclei to regulate the transcription of target genes in a ligand-responsive manner. The ER consists of three functional and structural domains: an N-terminal modulatory domain, a highly conserved DNA-binding domain that recognises specific sequences (INTERPRO), and a C-terminal ligand-binding domain (INTERPRO).
The N-terminal modulatory domain spans the first 180 residues and contains the activation function 1 (AF1) region. Nuclear receptors differ considerably with respect to AF1 activity and regulation, as it is a poorly conserved region [PUBMED:15831449]. There is another activation function region, namely AF2, which resides in the C-terminal end of the ligand-binding domain. Transcription activation is facilitated by both AF1 and AF2, which appear to act synergistically in the ER complex [PUBMED:15728727, PUBMED:14612550]. For example, the ER can recruit TIF2 (transcription intermediary factor 2) via the AF1 and AF2 regions, whose synergistic action results in the activation of transcription.
The mapping between Pfam and Gene Ontology is provided by InterPro. If you use this data please cite InterPro.
|Cellular component||nucleus (GO:0005634)|
|Molecular function||DNA binding (GO:0003677)|
|estrogen receptor activity (GO:0030284)|
|steroid binding (GO:0005496)|
|Biological process||regulation of transcription, DNA-dependent (GO:0006355)|
|steroid hormone mediated signaling pathway (GO:0043401)|
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You can also download a FASTA format file containing the full-length sequences for all sequences in the full alignment.
MyHits provides a collection of tools to handle multiple sequence alignments. For example, one can refine a seed alignment (sequence addition or removal, re-alignment or manual edition) and then search databases for remote homologs using HMMER3.
HMM logos is one way of visualising profile HMMs. Logos provide a quick overview of the properties of an HMM in a graphical form. You can see a more detailed description of HMM logos and find out how you can interpret them here. More...
If you find these logos useful in your own work, please consider citing the following article:
This page displays the phylogenetic tree for this family's seed alignment. We use FastTree to calculate neighbour join trees with a local bootstrap based on 100 resamples (shown next to the tree nodes). FastTree calculates approximately-maximum-likelihood phylogenetic trees from our seed alignment.
Note: You can also download the data file for the tree.
Curation and family details
This section shows the detailed information about the Pfam family. You can see the definitions of many of the terms in this section in the glossary and a fuller explanation of the scoring system that we use in the scores section of the help pages.
|Author:||Mian N, Bateman A|
|Number in seed:||11|
|Number in full:||220|
|Average length of the domain:||120.80 aa|
|Average identity of full alignment:||46 %|
|Average coverage of the sequence by the domain:||25.14 %|
|HMM build commands:||
build method: hmmbuild -o /dev/null HMM SEED
search method: hmmsearch -Z 23193494 -E 1000 --cpu 4 HMM pfamseq
|Family (HMM) version:||10|
|Download:||download the raw HMM for this family|
Weight segments by...
Change the size of the sunburst
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a FASTA-format file
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This visualisation provides a simple graphical representation of the distribution of this family across species. You can find the original interactive tree in the More....
This chart is a modified "sunburst" visualisation of the species tree for this family. It shows each node in the tree as a separate arc, arranged radially with the superkingdoms at the centre and the species arrayed around the outermost ring.
How the sunburst is generated
The tree is built by considering the taxonomic lineage of each sequence that has a match to this family. For each node in the resulting tree, we draw an arc in the sunburst. The radius of the arc, its distance from the root node at the centre of the sunburst, shows the taxonomic level ("superkingdom", "kingdom", etc). The length of the arc represents either the number of sequences represented at a given level, or the number of species that are found beneath the node in the tree. The weighting scheme can be changed using the sunburst controls.
In order to reduce the complexity of the representation, we reduce the number of taxonomic levels that we show. We consider only the following eight major taxonomic levels:
Colouring and labels
Segments of the tree are coloured approximately according to their superkingdom. For example, archeal branches are coloured with shades of orange, eukaryotes in shades of purple, etc. The colour assignments are shown under the sunburst controls. Where space allows, the name of the taxonomic level will be written on the arc itself.
As you move your mouse across the sunburst, the current node will be highlighted. In the top section of the controls panel we show a summary of the lineage of the currently highlighed node. If you pause over an arc, a tooltip will be shown, giving the name of the taxonomic level in the title and a summary of the number of sequences and species below that node in the tree.
Anomalies in the taxonomy tree
There are some situations that the sunburst tree cannot easily handle and for which we have work-arounds in place.
Missing taxonomic levels
Some species in the taxonomic tree may not have one or more of the main eight levels that we display. For example, Bos taurus is not assigned an order in the NCBI taxonomic tree. In such cases we mark the omitted level with, for example, "No order", in both the tooltip and the lineage summary.
Unmapped species names
The tree is built by looking at each sequence in the full alignment for the family. We take the name of the species given by UniProt and try to map that to the full taxonomic tree from NCBI. In some cases, the name chosen by UniProt does not map to any node in the NCBI tree, perhaps because the chosen name is listed as a synonym or a misspelling in the NCBI taxonomy.
So that these nodes are not simply omitted from the sunburst tree, we group them together in a separate branch (or segment of the sunburst tree). Since we cannot determine the lineage for these unmapped species, we show all levels between the superkingdom and the species as "uncategorised".
Since we reduce the species tree to only the eight main taxonomic levels, sequences that are mapped to the sub-species level in the tree would not normally be shown. Rather than leave out these species, we map them instead to their parent species. So, for example, for sequences belonging to one of the Vibrio cholerae sub-species in the NCBI taxonomy, we show them instead as belonging to the species Vibrio cholerae.
Too many species/sequences
For large species trees, you may see blank regions in the outer layers of the sunburst. These occur when there are large numbers of arcs to be drawn in a small space. If an arc is less than approximately one pixel wide, it will not be drawn and the space will be left blank. You may still be able to get some information about the species in that region by moving your mouse across the area, but since each arc will be very small, it will be difficult to accurately locate a particular species.
The tree shows the occurrence of this domain across different species. More...
We show the species tree in one of two ways. For smaller trees we try to show an interactive representation, which allows you to select specific nodes in the tree and view them as an alignment or as a set of Pfam domain graphics.
Unfortunately we have found that there are problems viewing the interactive tree when the it becomes larger than a certain limit. Furthermore, we have found that Internet Explorer can become unresponsive when viewing some trees, regardless of their size. We therefore show a text representation of the species tree when the size is above a certain limit or if you are using Internet Explorer to view the site.
If you are using IE you can still load the interactive tree by clicking the "Generate interactive tree" button, but please be aware of the potential problems that the interactive species tree can cause.
For all of the domain matches in a full alignment, we count the number that are found on all sequences in the alignment. This total is shown in the purple box.
We also count the number of unique sequences on which each domain is found, which is shown in green. Note that a domain may appear multiple times on the same sequence, leading to the difference between these two numbers.
Finally, we group sequences from the same organism according to the NCBI code that is assigned by UniProt, allowing us to count the number of distinct sequences on which the domain is found. This value is shown in the pink boxes.
We use the NCBI species tree to group organisms according to their taxonomy and this forms the structure of the displayed tree. Note that in some cases the trees are too large (have too many nodes) to allow us to build an interactive tree, but in most cases you can still view the tree in a plain text, non-interactive representation. Those species which are represented in the seed alignment for this domain are highlighted.
You can use the tree controls to manipulate how the interactive tree is displayed:
- show/hide the summary boxes
- highlight species that are represented in the seed alignment
- expand/collapse the tree or expand it to a given depth
- select a sub-tree or a set of species within the tree and view them graphically or as an alignment
- save a plain text representation of the tree
Please note: for large trees this can take some time. While the tree is loading, you can safely switch away from this tab but if you browse away from the family page entirely, the tree will not be loaded.