<p>I'd also cross-reference <a href="https://www.genome.jp/kegg/" rel="nofollow noreferrer">KEGG</a> but its focus is quite different.</p>
<p><strong>Uniprot</strong></p>
<p>UniProt Annotations are manually curated using strong experimental evidence or (possibly) solid <em>in silico</em> evidence. Overwhelmingly, UniProt curators use well-supported experimentally validated subcellular localisations. For example, UniProt annotations require evidence from microscopy or subcellular fractionation. UniProt curators in aiming for higher confidence may filter out locations that are less certain or inferred from indirect evidence (such as sequence-based predictions).</p>
<p><strong>GO</strong></p>
<p>GO (Gene Ontology) annotations use data pipelines, incorporating <em>in silico</em> predictions, but are also manually curated with various sources of experimental data. GO annotations are extensive because they were designed to provide a standardised way to describe cellular biology across the tree of life through a hierarchical ontology. They will include a wide range of potential locations using for example sequence homology or structural predictions. Obviously this can be shaky, but for example membrane proteins can be predicted at a VERY high level of accuracy across the tree of life and this has always been the case.</p>
<p>Basically with GO terms because proteins can be found in multiple subcellular compartments under different conditions or stages of the cell cycle, GO annotations tend to include all possible locations associated with a protein's biological functions.</p>
<p>GO annotations accuracy ... may not be incorrect, e.g. membrane proteins, but are not as accurate as UniProt, i.e. GO can get it wrong. GO tends towards more speculative or inferred localisations, e.g. just because two proteins show reasonable homology doesn't mean they'll have the same localisation. Thus, just because GO describes a locatisation that does not always mean that the protein is definitively localised there under all conditions.</p>
<p><strong>Summary</strong></p>
<p>Thus for NR1H2 gene, I'd focus on, in order of priority:</p>
<ol>
<li>the UniProt annotations for the most experimentally verified localisations.</li>
<li>GO annotations for hypothesis building and future experiments, i.e. the Discussion.</li>
</ol>
<p>Thus in this way you can get the best of both worlds. GO curators (and others) may challenge this viewpoint however, for example pointing to the increased power of <em>in silico</em> prediction.</p>

CC BY-SA 4.0
2024-12-16T10:09:27.680Z
2024-12-16T10:15:56.077Z
2024-12-16T10:15:56.077Z
M__
<p>UniProtKB/Swiss-Prot is expertly curated by biocurators who, among many other aspects, assign <a href="https://www.uniprot.org/locations/?query=*" rel="nofollow noreferrer">subcellular location</a> terms.
UniProtKB/TrEMBL is enriched by <a href="https://www.uniprot.org/help/automatic_annotation" rel="nofollow noreferrer">automatic annotation procedures</a>.</p>
<p>While UniProt's subcellular location terms are directly mapped to Gene Ontology terms from the Cellular Component subsection (see <a href="https://www.uniprot.org/locations/?query=*" rel="nofollow noreferrer">https://www.uniprot.org/locations/?query=*</a>), these are not the only sources of GO cellular component annotation. In addition to UniProt curators, biocurators from model organism databases (MODs) contribute GO annotations as described in the <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC9216577/" rel="nofollow noreferrer">SwissBioPics publication</a> , and GO terms added by automatic procedures are also included.</p>
<p>The source and evidence for each GO term (from all 3 GO sections) and provided in the <a href="https://www.uniprot.org/uniprotkb/P55055/entry#function" rel="nofollow noreferrer">Function section of NR1H2</a>.</p>
<p>Please do not hesitate to contact the <a href="https://www.uniprot.org/contact" rel="nofollow noreferrer">UniProt helpdesk</a> if you have any additional questions.</p>

CC BY-SA 4.0
2024-12-17T17:47:08.300Z
2024-12-20T10:57:55.757Z
2024-12-20T10:57:55.757Z
Elisabeth.Gasteiger
<p>I'm looking for information on a protein P55055 (NR1H2 gene).</p>
<p>In <strong>Uniprot</strong> at protein entries at  <strong>Subcellular location</strong> section you can see two different information sources: Uniprot annotations and GO annotations.
The <strong>GO annotations includes much more locations</strong>. If I know well the GO annotations  annotation filtering is applied here and therefore cant see all of the locations.
<a href="https://www.uniprot.org/uniprotkb/P55055/entry#subcellular_location" rel="nofollow noreferrer">link to the subcellular location of the concerned protein</a>
<a href="https://i.sstatic.net/XIpxyxAc.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/XIpxyxAc.png" alt="enter image description here" /></a> <a href="https://i.sstatic.net/8MPG2iwT.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/8MPG2iwT.png" alt="enter image description here" /></a></p>
<p>My question:</p>
<ol>
<li>Is it true?</li>
<li>Why have the Go annotations have much more location items? And are these correct?</li>
</ol>

CC BY-SA 4.0
2024-12-15T04:45:47.133Z
This doesn't seem like a bioinformatics problem, unless there is additional data / algorithm context that you haven't provided; have you tried asking on [biology.stackexchange.com](https://biology.stackexchange.com)? Here is a similar question, with an answer from Uniprot: https://biology.stackexchange.com/questions/40784/what-does-uniprot-consider-unambiguous-evidence-for-the-subcellular-domain-of
gringer
<uniprot>
Which source is correct in Uniprot at subcellular location info?
# Which source is correct in Uniprot at subcellular location info?

(Asked by: username_0 on 2024-12-14)

I'm looking for information on a protein P55055 (NR1H2 gene).

In **Uniprot** at protein entries at **Subcellular location** section you can see two different information sources: Uniprot annotations and GO annotations.
The **GO annotations includes much more locations**. If I know well the GO annotations annotation filtering is applied here and therefore cant see all of the locations.
[link to the subcellular location of the concerned protein](https://www.uniprot.org/uniprotkb/P55055/entry#subcellular_location)
[![enter image description here](https://i.sstatic.net/XIpxyxAc.png)](https://i.sstatic.net/XIpxyxAc.png) [![enter image description here](https://i.sstatic.net/8MPG2iwT.png)](https://i.sstatic.net/8MPG2iwT.png)

My question:

1. Is it true?
2. Why have the Go annotations have much more location items? And are these correct?

**Tags:** uniprot
> **Comments:**
> **username_1**: This doesn't seem like a bioinformatics problem, unless there is additional data / algorithm context that you haven't provided; have you tried asking on [biology.stackexchange.com](https://biology.stackexchange.com)? Here is a similar question, with an answer from Uniprot: https://biology.stackexchange.com/questions/40784/what-does-uniprot-consider-unambiguous-evidence-for-the-subcellular-domain-of  

---

## 2 answers

### Answer by username_2 on 2024-12-16. Score: 0 | Accepted answer

I'd also cross-reference [KEGG](https://www.genome.jp/kegg/) but its focus is quite different.

**Uniprot**

UniProt Annotations are manually curated using strong experimental evidence or (possibly) solid *in silico* evidence. Overwhelmingly, UniProt curators use well-supported experimentally validated subcellular localisations. For example, UniProt annotations require evidence from microscopy or subcellular fractionation. UniProt curators in aiming for higher confidence may filter out locations that are less certain or inferred from indirect evidence (such as sequence-based predictions).

**GO**

GO (Gene Ontology) annotations use data pipelines, incorporating *in silico* predictions, but are also manually curated with various sources of experimental data. GO annotations are extensive because they were designed to provide a standardised way to describe cellular biology across the tree of life through a hierarchical ontology. They will include a wide range of potential locations using for example sequence homology or structural predictions. Obviously this can be shaky, but for example membrane proteins can be predicted at a VERY high level of accuracy across the tree of life and this has always been the case.

Basically with GO terms because proteins can be found in multiple subcellular compartments under different conditions or stages of the cell cycle, GO annotations tend to include all possible locations associated with a protein's biological functions.

GO annotations accuracy ... may not be incorrect, e.g. membrane proteins, but are not as accurate as UniProt, i.e. GO can get it wrong. GO tends towards more speculative or inferred localisations, e.g. just because two proteins show reasonable homology doesn't mean they'll have the same localisation. Thus, just because GO describes a locatisation that does not always mean that the protein is definitively localised there under all conditions.

**Summary**

Thus for NR1H2 gene, I'd focus on, in order of priority:

1. the UniProt annotations for the most experimentally verified localisations.
2. GO annotations for hypothesis building and future experiments, i.e. the Discussion.

Thus in this way you can get the best of both worlds. GO curators (and others) may challenge this viewpoint however, for example pointing to the increased power of *in silico* prediction.


---

### Answer by username_3 on 2024-12-17. Score: 2

UniProtKB/Swiss-Prot is expertly curated by biocurators who, among many other aspects, assign [subcellular location](https://www.uniprot.org/locations/?query=*) terms.
UniProtKB/TrEMBL is enriched by [automatic annotation procedures](https://www.uniprot.org/help/automatic_annotation).

While UniProt's subcellular location terms are directly mapped to Gene Ontology terms from the Cellular Component subsection (see [https://www.uniprot.org/locations/?query=\*](https://www.uniprot.org/locations/?query=*)), these are not the only sources of GO cellular component annotation. In addition to UniProt curators, biocurators from model organism databases (MODs) contribute GO annotations as described in the [SwissBioPics publication](https://pmc.ncbi.nlm.nih.gov/articles/PMC9216577/) , and GO terms added by automatic procedures are also included.

The source and evidence for each GO term (from all 3 GO sections) and provided in the [Function section of NR1H2](https://www.uniprot.org/uniprotkb/P55055/entry#function).

Please do not hesitate to contact the [UniProt helpdesk](https://www.uniprot.org/contact) if you have any additional questions.


---

