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microRNA annotation

Since January 2015 we have been using the Gene Ontology (GO) to describe the biological roles of microRNAs (miRNAs). To date we have provided all manual human RNA GO annotations.

selection of hsa-miR-520b-3p annotations
We have been funded to curate miRNAs involved in cardiovascular and neurological processes. At the end of 2019 we had provided over 4,600 GO annotations for over human 400 microRNAs. The prioritisation of microRNAs for curation is ongoing but we focus on human miRNAs that are relevant to disease. Currently we are the only group prioritising human miRNAs GO annotation, these can be viewed at QuickGO. In addition, we have developed very specific guidelines (Huntley et al., 2016) to ensure consistent annotation of miRNAS which we apply during the curation of these RNA. Alongside this we have curated the roles of the key human proteins involved in miRNA processing, such as Drosha and Dicer. 

The RNA annotations are available in QuickGO, miRBase, NCBIGene, RNAcentral and AmiGO2, or in the regular GOA release files. In addition, our miRNA:target mRNA binding annotations are accessible for inclusion in network analyses from the PSICQUIC web service, in the EBI-GOA-miRNA file. Information about the data included in the PSICQUIC web service is also available.

Example: View the annotations associated with hsa-miR-133a-3p

miRNA curation guidelines

As part of this project we have drawn up miRNA curation guidelines (Huntley et al., 2016) in consultation with the Gene Ontology (GO) Consortium and experts in miRNA research, which cover how a curator should translate into GO annotations the common experimental assays used to investigate miRNA function, including how to annotate experimentally verified targets of miRNAs as well as the physiological effects that silencing has on the cell or organism.

Any queries about the miRNA project should be directed to r.lovering@ucl.ac.uk.

miRNA annotation projects undertaken

Alzheimer's Research UK grant ARUK-NSG2018A-003

The ARUK funded the creation of over 1,000 GO annotations which have facilitated the detailed and high-quality annotation of 160 Alzheimer's-relevant microRNAs. A variety of focused projects were undertaken including the curation of:

  • microRNAs that regulate microglial proteins
    • The goal of this project was to annotate the microRNAs (miRNAs) that regulated the expression of the proteins with a role in microglial processes. Over 100 human miRNAs were annotated by Rachael Huntley and Barbara Kramarz, including hsa-miR-520b-3p, which we have annotated as regulating the expression of C3 and as positive regulation of complement activation, alternative pathway. In addition, 19 papers describing the experimentally verified mRNA targets of IL6 were curated, creating 90 annotations, and annotations describing 'neuron projection development' and 'gliogenesis' were contributed, yielding 41 annotations from 19 papers and 57 annotations from 13 papers, respectively.
  • Alzheimer's Disease microRNA biomarkers
    • Swarbrick S, et al., 2019, decribed a panel of 10 microRNAs suggested to be disregulated early in Alzheimer's disease. Barbara Kramarz curated 14 papers describing the microRNA target interactions for these microRNAs, when available, creating 54 annotations for 10 human microRNAs, including the potential biomarkers hsa-miR-146a-5p, hsa-miR-107, hsa-miR-26b-5p and hsa-miR-210-3p, and 9 proteins.
British Heart Foundation (BHF) grant RG/13/5/30112

The BHF funded the creation of over 3,600 GO annotations which have facilitated the detailed and high-quality annotation of almost 400 cardiovascular-relevant microRNAs. A variety of focused projects were undertaken including the curation of:

  • BHF-funded research papers
    • From 2014 to 2018, Rachael Huntley curated all BHF funded research papers describing the role of microRNAs in cardiovascular-relevant processes.
  • Regulation of cardiac physiology
    • Rachael Huntley curated 7 microRNAs, as these had been identified as modulating cardiac excitability; literature available for these miRNAs was curated up to March 2016.
  • Angiogenesis
    • Over a period of 3 months Vanessa Acquaah curated the role of microRNAs in angiogenesis. The two major cell types are involved in this process: endothelial and smooth muscle cells (SMC). During this project Vanessa annotated 114 papers that demonstrate the roles that miRNAs play in regulating endothelial and SMC cell proliferation, migration and endothelial tube formation. These papers were identified by searches in pubmed using the key terms “mirnas in angiogenesis”. GO annotations associated with a selection of these curated papers are available in QuickGO.
  • Pulmonary artery remodelling
    • Pulmonary hypertension is caused by impaired pulmonary arterial growth and remodelling. Vanessa Acquaah annotated 24 papers that describe the role of miRNAs in vascular smooth muscle cell pulmonary artery remodelling, creating 167 annotations.  These papers were identified by searches in pubmed using the key words “miRNAs and pulmonary smooth muscle cells”.
Familial hypercholesterolemia, MSc project

Hao Chen, MSc project 2017. Familial hypercholesterolemia (FH) is a common inherited lipid disorder that can cause cardiovascular diseases (CVD) if untreated. Treatment on FH depend on management of plasma low-density-lipoprotein (LDL) cholesterol. High level of plasma LDL cholesterol can induce atherosclerosis and plaque buildup in the walls of the arteries. There is evidence that suggest miRNAs’ regulation of LDL-C is due to their regulation of FH-associated genes, such as LDLR, PCSK9, APOB, LDLRAP1, ABCA1 and ABCG1. This project created 290 GO annotations, of which 22 were transferred from mouse miRNAs to human miRNAs using the ISS evidence code. The prioritised mRNA targets are listed below:

#

HGNC Symbol

HGNC Name

UniProt ID

1

ABCA1

ATP binding cassette subfamily A member 1

O95477

2

ABCG1

ATP binding cassette subfamily G member 1

P45844

3

APOB

apolipoprotein B

P04114

4

LDLR

low density lipoprotein receptor

P01130

5

LDLRAP1

low density lipoprotein receptor adaptor protein 1

Q5SW96

6

PCSK9

proprotein convertase subtilisin/kexin type 9

Q8NBP7

Angiogenesis, IBSc project

Marios Makris, IBSc project 2019. Angiogenesis is the formation of blood vessels from pre-existing vasculature, involving endothelial cell migration, proliferation, survival, vascular tube formation and regulation of angiogenic growth factors. A total of 237 GO annotations were created to associate 40 distinct microRNAs to 11 pro-angiogenic growth factors. The downstream angiogenesis-relevant effects of regulating these factors were also captured. The prioritised mRNA targets are listed below:

No.

Approved gene name

Approved Gene Symbol

1

Vascular endothelial growth factor A

VEGFA

2

Kinase insert domain receptor*

KDR*

3

Fibroblast growth factor 2

FGF2

4

Fibroblast growth factor receptor 1

FGFR1

5

Fibroblast growth factor receptor 2

FGFR2

Aortic aneurysm, MSc project

Zara Umrao, MSc project 2015. Aortic aneurysm (AA) is a cardiovascular disease characterized by swelling of the aorta, the main vessel that runs from the heart to the abdomen. Recently, research has revealed the role of microRNAs (miRNA) in some diseases, including AA, which may enable a better understanding of the disease. The role of one such family of miRNAs, miRNA29, was investigated by creating annotations from existing literature. Forty papers were curated, from which 497 GO annotations were made. The annotations spanned a range of species, including human, mouse, rat, zebrafish and dog. The role of miRNA29 in regulating essential extracellular matrix proteins, such as elastin, collagen, fibrillin and matrix metalloproteinases was captured. In addition, the GO annotations also described the role of miRNA29s in activities, such as aorta morphogenesis, cell migration, cell proliferation, DNA methylation and epithelium regeneration.

Early heart development, MSc project

Vanessa Acquaah, MSc project 2016. Recent evidence has shown that miRNAs, in particular microRNA-1 (miR-1) are found in abundance within cardiac tissues and may be particularly important in early heart development. A total of 313 annotations were made through the use of experimental evidence from 49 papers using GOC curation guidelines. Annotations covered the role of miR-1 as well as other miRNAs in cardiomyocyte proliferation and cardiomyocyte differentiation. Additionally, development of cardiac neural crest cells through processes such as endothelial to mesenchymal transition (EMT) and differentiation of epithelial cells are processes regulated by miRNAs; these roles have been captured as GO annotations.

Regulation of amyloid-beta 'good' receptors, MSc project

Shirin Saverimuttu, MSc project 2018. Alzheimer’s disease (AD), the most common form of dementia, is characterised by amyloid beta (Aβ) accumulation in extracellular plaques. Moreover, accumulation has been hypothesised as a primary cause of the disease, with a dysregulation to the proteins involved in clearance thought to be critical. Interestingly, hundreds of microRNAs have been found to be altered in brain tissue affected by AD and several have been experimentally proven to regulate the expression of clearance proteins. This MSc project led to a total of 258 GO annotations being created. This allowed for knowledge describing how microRNAs regulate clearance proteins to be captured, as well as the capturing the downstream effects of these microRNAs. The prioritised mRNA targets are listed below:

#

HGNC Symbol

HGNC Name

UniProt ID

1

APOE

Apolipoprotein E

P02649

2

CHRNA7*

Cholinergic receptor nicotinic alpha 7 subunit

P36544

3

CLU

Clusterin

P10909

4

FPR2

Formyl peptide receptor 2

P25090

5

HSPG2

Heparan sulfate proteoglycan 2

P98160

6

ITGA2*

Integrin subunit alpha 2

P17301

7

ITGAM*

Integrin subunit alpha M

P11215

8

LRP1

LDL receptor related protein 1

Q07954

9

LRP2

LDL receptor related protein 2

P98164

10

LDLR

Low density lipoprotein receptor

Q07954

11

MARCO*

Macrophage receptor with collagenous structure

Q9UEW3

12

MSR1*

Macrophage scavenger receptor 1

P21757

13

PICALM*

Phosphatidylinositol binding clatherin assembly protein

Q13492

14

PRNP

Prion protein

P04156

15

TLR2

Toll like receptor 2

O60603

16

TLR4

Toll like receptor 4

O00206

* there was no experimental evidence to support annotation of microRNAs regulating these proteins in July 2019

Regulation of interleukins

Shirin Saverimuttu is responsible for this project, the goal of which is to annotate microRNAs (miRNAs) that regulate the expression of interleukins with a role in Alzheimer’s-relevant processes. In order to achieve this goal, it was necessary to generating a priority list of interleukins (below) and then to identify their regulatory miRNAs. The miRNAs are identified on a target-by-target basis, firstly using mirTarBase and then with specific searches in PubMed. This project is funded from Functional Gene Annotation group’s discretionary funds. The prioritised mRNA targets are listed below:

#

HGNC Symbol

HGNC Name

UniProt ID

1

IL1A

Interleukin 1 alpha

P01583

2

IL1B

Interleukin 1 beta

P01584

3

IL1F10

Interleukin 1 family member 10

Q8WWZ1

4

IL2

Interleukin 2

P60568

5

IL3

Interleukin 3

P08700

6

IL4

Interleukin 4

P05112

7

IL5

Interleukin 5

P05113

8

IL6

Interleukin 6

P05231

9

IL7

Interleukin 7

P13232

10

CXCL8

C-X-C motif chemokine ligand 8 (alias: interleukin 8)

P10145

11

IL9

Interleukin 9

P15248

12

IL10

Interleukin 10

P22301

13

IL11

Interleukin 11

P20809

14

IL12A

Interleukin 12A

P29459

15

IL12B

Interleukin 12B

P29460

16

IL13

Interleukin 13

P35225

17

IL15

Interleukin 15

P40933

18

IL16

Interleukin 16

Q14005

19

IL17A

Interleukin 17A

Q16552

20

IL17B

Interleukin 17B

Q9UHF5

21

IL17C

Interleukin 17C

Q9P0M4

22

IL17D

Interleukin 17D

Q8TAD2

23

IL17F

Interleukin 17F

Q96PD4

24

IL18

Interleukin 18

Q14116

25

IL19

Interleukin 19

Q9UHD0

26

IL20

Interleukin 20

Q9NYY1

27

IL21

Interleukin 21

Q9HBE4

28

IL22

Interleukin 22

Q9GZX6

29

IL23A

Interleukin 23 alpha

Q9NPF7

30

IL24

Interleukin 24

Q13007

31

IL25

Interleukin 25

P01589

32

IL26

Interleukin 26

Q9NPH9

33

IL27

Interleukin 27

Q8NEV9

34

IL31

Interleukin 31

Q6EBC2

35

IL32

Interleukin 32

P24001

36

IL33

Interleukin 33

O95760

37

IL34

Interleukin 34

Q6ZMJ4

38

IL36A

Interleukin 36 alpha

Q9UHA7

39

IL36B

Interleukin 36 beta

Q9NZH7

40

IL36G

Interleukin 36 gamma

Q9NZH8

41

IL37

Interleukin 37

Q9NZH6

Endothelial connections at the Blood Brain Barrier

Katherine Thurlow, MSc project 2019. Evidence for cerebrovascular mechanisms, particularly increased breakdown and dysfunction of the blood-brain barrier (BBB), as key contributors to Alzheimer’s Disease (AD), the most common form of dementia, has grown in recent years,. The BBB is key in regulating influx and efflux of substances to the brain and as such maintains normal neuronal and cognitive function. Alterations in BBB constituent proteins could alter its ability to selectively transport molecules and result in a change in permeability to potentially toxic substances. The list of priority mRNA targets for this project was identified from Figure 2 of Sweeney et al., 2019. This MSc project led to a total of 253 GO annotations being created. This allowed for knowledge describing the role of microRNAs at the BBB to be captured. The prioritised mRNA targets are listed below:

#

UniProt ID

HGNC Symbol

HGNC Name

1

P60709 

ACTB

actin beta

2

P63261

ACTG1

actin gamma 1

3

P33151

CDH5

cadherin 5

4

O95832

CLDN1

claudin 1

5

P56749

CLDN12

claudin 12

6

O15551

CLDN3

claudin 3

7

O00501

CLDN5

claudin 5

8

P11532 

DMD

dystrophin

9

Q96AP7

ESAM

endothelial cell adhesion molecule

10

Q9Y624

F11R

F11 receptor

11

P17302

GJA1

gap junction protein alpha 1

12

O95452

GJB6

gap junction protein beta 6

13

P05556

ITGB1

Integrin subunit beta 1

14

P57087

JAM2

junctional adhesion molecule 2

15

Q9BX67

JAM3

junctional adhesion molecule 3

16

P24043

LAMA2

Laminin subunit alpha-2

17

P11047

LAMC1

Laminin subunit gamma-1

18

Q86X29

LSR

lipolysis stimulated lipoprotein receptor

19

Q16625

OCLN

occludin

20

P16284 

PECAM1

platelet and endothelial cell adhesion molecule 1

21

Q07157 

TJP1

tight junction protein 1

22

Q9UDY2

TJP2

tight junction protein 2

23

O95049

TJP3

tight junction protein 3

24

P18206 

VCL

vinculin

Regulation of key proteins involved in APP processing and Aβ formation

Sandra De Miranda Pinheiro, MSc project 2019. Accumulation of amyloid-beta (Aβ) and tau proteins in the brain is the hallmark of Alzheimer’s disease and lead to neurodegeneration. An imbalance between the production and the clearance of Aβ from the brain is thought to drive the development of the disease. Aβ derives from a larger protein, the amyloid precursor protein (APP), which is processed by different secretases in a sequential way. In the amyloidogenic pathway, β-secretase cleaves APP at the β-site and cleavage of the remaining APP fragment by γ-secretase results in the production of Aβ peptides. Increased APP expression has been associated with an increased risk of developing Alzheimer’s disease. This MSc project led to a total of 254 GO annotations being created. This allowed for knowledge describing how microRNAs regulate the processing of APP and the formation of Aβ. The prioritised mRNA targets are listed below:

#

HGNC Gene Symbol

HGNC Approved Name

Protein Group

1

APP

amyloid beta precursor protein

 

2

ADAM9

ADAM metallopeptidase domain 9

Alpha-secretase

3

ADAM10

ADAM metallopeptidase domain 10

Alpha-secretase

4

ADAM17

ADAM metallopeptidase domain 17

Alpha-secretase

5

ADAM19

ADAM metallopeptidase domain 19

Alpha-secretase

6

APH1A

aph-1 homolog A

Gamma-secretase subunit

7

APH1B

aph-1 homolog B

Gamma-secretase subunit

8

BACE1

beta-secretase 1

Beta-Secretase 1

9

NCSTN

nicastrin

Gamma-secretase

10

PSEN1

presenilin 1

Gamma-secretase

11

PSEN2

presenilin 2

Gamma-secretase

12

PSENEN

presenilin enhancer

Gamma-secretase subunit

 

tbc

miRNA annotation