Summary: FTO catalytic domain
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FTO gene Edit Wikipedia article
|Fat mass and obesity associated|
|RNA expression pattern|
Fat mass and obesity-associated protein also known as alpha-ketoglutarate-dependent dioxygenase FTO is an enzyme that in humans is encoded by the FTO gene located on chromosome 16. As one homolog in the AlkB family proteins, it is the first mRNA demethylase that has been identified. Certain variants of the FTO gene appear to be correlated with obesity in humans.
The amino acid sequence of the transcribed FTO protein shows high similarity with the enzyme AlkB which oxidatively demethylates DNA. Recombinant FTO protein was first discovered to catalyze demethylation of 3-methylthymine in single-stranded DNA, and 3-methyluridine in single-stranded RNA, with low efficiency. The nucleoside N6-methyladenosine, an abundant modification in RNA, was then found to be a major substrate of FTO. The FTO gene expression was also found to be significantly upregulated in the hypothalamus of rats after food deprivation and strongly negatively correlated with the expression of orexigenic galanin like peptide which is involved in the stimulation of food intake.
Increases in hypothalamic expression of FTO are associated with the regulation of energy intake but not feeding reward.
FTO demethylates m6A in mRNA
N6-methyladenosine (m6A) is an abundant modification in mRNA and is found within some viruses, and most eukaryotes including mammals, insects, plants,and yeast. It is also found in tRNA, rRNA, and small nuclear RNA (snRNA) as well as several long non-coding RNA, such as Xist. Adenosine methylation is directed by a large m6A methyltransferase complex containing METTL3 as the SAM-binding sub-unit. In vitro, this methyltransferase complex preferentially methylates RNA oligonucleotides containing GGACU and a similar preference was identified in vivo in mapped m6A sites in Rous sarcoma virus genomic RNA and in bovine prolactin mRNA. In plants, the majority of the m6A is found within 150 nucleotides before the start of the poly(A) tail.
Mapping of m6A in human and mouse RNA has identified over 18,000 m6A sites in the transcripts of more than 7,000 human genes with a consensus sequence of [G/A/U][G>A]m6AC[U>A/C]< consistent with the previously identified motif. Sites preferentially appear in two distinct landmarks—around stop codons and within long internal exons—and are highly conserved between human and mouse. A subset of stimulus-dependent, dynamically modulated sites has been identified. Silencing the m6A methyltransferase significantly affects gene expression and alternative RNA splicing patterns, resulting in modulation of the p53 (also known as TP53) signalling pathway and apoptosis.
FTO demethylates m6A containing RNA efficiently in vitro. FTO knockdown with siRNA led to increased amounts of m6A in polyA-RNA, whereas overexpression of FTO resulted in decreased amounts of m6A in human cells. FTO partially co-localizes with nuclear speckles, which supports the notion that m6A in nuclear RNA is a major physiological substrate of FTO. Function of FTO likely affects the processing of pre-mRNA, other nuclear RNAs, or both. The discovery of the FTO-mediated oxidative demethylation of m6A in nuclear RNA may initiate further investigations on biological regulation based on reversible chemical modification of RNA.
The FTO gene is widely expressed in both fetal and adult tissues.
Association with obesity
A study of 38,759 Europeans for variants of FTO identified an obesity risk allele. In particular, carriers of one copy of the allele weighed on average 1.2 kilograms (2.6 lb) more than people with no copies. Carriers of two copies (16% of the subjects) weighed 3 kilograms (6.6 lb) more and had a 1.67-fold higher rate of obesity than those with no copies. The association was observed in ages 7 and upwards. This gene is not directly associated with diabetes however increased body-fat also increases the risk of developing Type 2 Diabetes.
Simultaneously, a study in 2,900 affected individuals and 5,100 controls of French descent, together with 500 trios (confirming an association independent of population stratification) found association of SNPs in the very same region of FTO (rs1421085). The authors found that this variation, or a variation in strong LD with this variation explains 1% of the population BMI variance and 22% of the population attributable risk of obesity. The authors of this study claim that while obesity was already known to have a genetic component (from twin studies), no replicated previous study has ever identified an obesity risk allele that was so common in the human population. The risk allele is a cluster of 10 single nucleotide polymorphism in the first intron of FTO called rs9939609. According to HapMap, it has population frequencies of 45% in the West/Central Europeans, 52% in Yorubans (West African natives) and 14% in Chinese/Japanese. Furthermore morbid obesity is associated with a combination of FTO and INSIG2 single nucleotide polymorphisms.
In adult humans it was shown that adults bearing the at risk AT and AA alleles at rs9939609 consumed between 500 and 1250 kJ more each day than those carrying the protective TT genotype (equivalent to between 125 and 280 kcal per day more intake). The same study showed that there was no impact of the polymorphism on energy expenditure. This finding of an effect of the rs9939609 polymorphism on food intake or satiety has been independently replicated in five subsequent studies (in order of publication). Three of these subsequent studies also measured resting energy expenditure and confirmed the original finding that there is no impact of the polymorphic variation at the rs9939609 locus on energy expenditure. A different study explored the effects of variation in two different SNPs in the FTO gene (rs17817449 and rs1421085) and suggested there might be an effect on circulating leptin levels and energy expenditure, but this latter effect disappeared when the expenditure was normalised for differences in body composition. The accumulated data across seven independent studies therefore clearly implicates the FTO gene in humans as having a direct impact on food intake but no effect on energy expenditure.
The obesity-associated noncoding region within the FTO gene interacts directly with the promoter of IRX3, a homeobox gene. This noncoding region of FTO interacts with the promoters of IRX3 and FTO in human, mouse and zebrafish. Results suggest that IRX3 is linked with obesity and determines body mass and composition. This is further supported by the fact that obesity-associated single nucleotide polymorphisms are involved in the expression of IRX3 (not FTO) in human brains.
Association with Alzheimer's disease
Recent studies revealed that carriers of common FTO gene polymorphisms show both a reduction in frontal lobe volume of the brain and an impaired verbal fluency performance. Fittingly, a population-based study from Sweden found that carriers of the FTO rs9939609 A allele have an increased risk for incident Alzheimer disease.
Association with other diseases
The presence of the FTO rs9939609 A allele was also found to be positively correlated with other symptoms of the metabolic syndrome, including higher fasting insulin, glucose, and triglycerides, and lower HDL cholesterol. However all these effects appear to be secondary to weight increase since no association was found after correcting for increases in body mass index. Similarly, the association of rs11076008 G allele with the increased risk for degenerative disc disease was reported. 
Model organisms have been used in the study of FTO function. In contrast to the findings in humans deletion, analysis of the Fto gene in mice showed loss of function is associated with no differences in energy intake but greater energy expenditure and this results in a reduction of body weight and fatness.
|Glucose tolerance test||Normal|
|Auditory brainstem response||Normal|
|All tests and analysis from|
Another conditional knockout mouse line, called Ftotm1a(EUCOMM)Wtsi was generated as part of the International Knockout Mouse Consortium program — a high-throughput mutagenesis project to generate and distribute animal models of disease to interested scientists. Male and female animals from this line underwent a standardized phenotypic screen to determine the effects of deletion. Twenty five tests were carried out on mutant mice and only significant skeletal abnormalities were observed, including kyphosis and abnormal vertebral transverse processes, and only in female homozygous mutant animals. 
The reasons for the differences in FTO phenotype between humans and different lines of mice is presently uncertain. However, many other genes involved in regulation of energy balance exert effects on both intake and expenditure.
Origin of name
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This tab holds the annotation information that is stored in the Pfam database. As we move to using Wikipedia as our main source of annotation, the contents of this tab will be gradually replaced by the Wikipedia tab.
FTO catalytic domain Provide feedback
This domain is the catalytic AlkB-like domain from the FTO protein . This domain catalyses a demethylase activity with a preference for 3-methylthymidine.
Han Z, Niu T, Chang J, Lei X, Zhao M, Wang Q, Cheng W, Wang J, Feng Y, Chai J;, Nature. 2010; [Epub ahead of print]: Crystal structure of the FTO protein reveals basis for its substrate specificity. PUBMED:20376003 EPMC:20376003
This tab holds annotation information from the InterPro database.
InterPro entry IPR024367Alpha-ketoglutarate-dependent dioxygenase FTO, also known as Fat mass and obesity-associated protein, is a nucleus protein which belongs to the FTO family. This enzyme is a dioxygenase that repairs alkylated DNA and RNA by oxidative demethylation [PUBMED:17991826]. FTO activity is highest towards single-stranded RNA containing 3-methyluracil, followed by single-stranded DNA containing 3-methylthymine. FTO has low demethylase activity towards single-stranded DNA containing 1-methyladenine or 3-methylcytosine [PUBMED:18775698]. FTO has no activity towards 1-methylguanine. It has no detectable activity towards double-stranded DNA. FTO requires molecular oxygen, alpha-ketoglutarate and iron. FTO contributes to the regulation of the global metabolic rate, energy expenditure and energy homeostasis. It contributes to the regulation of body size and body fat accumulation as well [PUBMED:19234441].
This domain is the catalytic AlkB-like domain from the FTO protein [PUBMED:20376003]. This domain catalyses a demethylase activity with a preference for 3-methylthymidine.
Below is a listing of the unique domain organisations or architectures in which this domain is found. More...
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This clan represents the conserved barrel domain of the 'cupin' superfamily  ('cupa' is the Latin term for a small barrel). The cupin fold is found in a wide variety of enzymes, but notably contains the non-enzymatic seed storage proteins also.
The clan contains the following 57 members:2OG-Fe_Oxy_2 2OG-FeII_Oxy 2OG-FeII_Oxy_2 2OG-FeII_Oxy_3 2OG-FeII_Oxy_4 2OG-FeII_Oxy_5 3-HAO AraC_binding AraC_binding_2 AraC_N ARD Asp_Arg_Hydrox Auxin_BP CDO_I CENP-C_C CsiD Cupin_1 Cupin_2 Cupin_3 Cupin_4 Cupin_5 Cupin_6 Cupin_7 Cupin_8 DMSP_lyase dTDP_sugar_isom DUF1255 DUF1479 DUF1498 DUF1637 DUF1971 DUF386 DUF4437 DUF4867 Ectoine_synth EutQ FdtA FTO_NTD GPI HgmA HutD JmjC KduI MannoseP_isomer Ofd1_CTDD Oxygenase-NA PhyH Pirin Pirin_C PMI_typeI Popeye Pox_C4_C10 TauD Tet_JBP Ureidogly_lyase VIT VIT_2
We store a range of different sequence alignments for families. As well as the seed alignment from which the family is built, we provide the full alignment, generated by searching the sequence database (reference proteomes) using the family HMM. We also generate alignments using four representative proteomes (RP) sets, the UniProtKB sequence database, the NCBI sequence database, and our metagenomics sequence database. More...
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We make a range of alignments for each Pfam-A family:
- the curated alignment from which the HMM for the family is built
- the alignment generated by searching the sequence database using the HMM
- Representative Proteomes (RPs) at 15%, 35%, 55% and 75% co-membership thresholds
- alignment generated by searching the UniProtKB sequence database using the family HMM
- alignment generated by searching the NCBI sequence database using the family HMM
- alignment generated by searching the metagenomics sequence database using the family HMM
You can see the alignments as HTML or in three different sequence viewers:
- a Java applet developed at the University of Dundee. You will need Java installed before running jalview
- an HTML page showing the whole alignment.Please note: full Pfam alignments can be very large. These HTML views are extremely large and often cause problems for browsers. Please use either jalview or the Pfam viewer if you have trouble viewing the HTML version
- an HTML-based representation of the alignment, coloured according to the posterior-probability (PP) values from the HMM. As for the standard HTML view, heatmap alignments can also be very large and slow to render.
You can download (or view in your browser) a text representation of a Pfam alignment in various formats:
You can also change the order in which sequences are listed in the alignment, change how insertions are represented, alter the characters that are used to represent gaps in sequences and, finally, choose whether to download the alignment or to view it in your browser directly.
You may find that large alignments cause problems for the viewers and the reformatting tool, so we also provide all alignments in Stockholm format. You can download either the plain text alignment, or a gzipped version of it.
We make a range of alignments for each Pfam-A family. You can see a description of each above. You can view these alignments in various ways but please note that some types of alignment are never generated while others may not be available for all families, most commonly because the alignments are too large to handle.
1Cannot generate PP/Heatmap alignments for seeds; no PP data available
Key: available, not generated, — not available.
Format an alignment
We make all of our alignments available in Stockholm format. You can download them here as raw, plain text files or as gzip-compressed files.
You can also download a FASTA format file containing the full-length sequences for all sequences in the full alignment.
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.
|Number in seed:||19|
|Number in full:||80|
|Average length of the domain:||265.10 aa|
|Average identity of full alignment:||55 %|
|Average coverage of the sequence by the domain:||59.50 %|
|HMM build commands:||
build method: hmmbuild -o /dev/null HMM SEED
search method: hmmsearch -Z 11927849 -E 1000 --cpu 4 HMM pfamseq
|Family (HMM) version:||4|
|Download:||download the raw HMM for this family|
Weight segments by...
Change the size of the sunburst
selected sequences to HMM
a FASTA-format file
- 0 sequences
- 0 species
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.
There is 1 interaction for this family. More...
We determine these interactions using iPfam, which considers the interactions between residues in three-dimensional protein structures and maps those interactions back to Pfam families. You can find more information about the iPfam algorithm in the journal article that accompanies the website.
For those sequences which have a structure in the Protein DataBank, we use the mapping between UniProt, PDB and Pfam coordinate systems from the PDBe group, to allow us to map Pfam domains onto UniProt sequences and three-dimensional protein structures. The table below shows the structures on which the FTO_NTD domain has been found. There are 12 instances of this domain found in the PDB. Note that there may be multiple copies of the domain in a single PDB structure, since many structures contain multiple copies of the same protein seqence.
Loading structure mapping...