Annual Scientific Report 2015

Anton Enright
PhD in Computational Biology, University of
Cambridge, 2003. Postdoctoral research at
Memorial Sloan-Kettering Cancer Center,
New York.
At EMBL-EBI since 2008.
cortex
9
106
55
65
106
1
5
1
117
18
3
6
537
23
2529
1412 1 13
brain
5
8
2
54
100
7 1
7 1
2
161
50 6
70
4
2
49
2
33
41
2
5
1
3
4
2
547
435
2
32
1546 4 1184 122
29
1210
1019 9
cerebellum
20
141
2
77
99
6
92
8 7
5
181 8
3
41
8
4
1
92
180 1 18
49
200
1
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2434 87
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258
118
24
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101
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4
84
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3
1
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293
27
994956
11 2
heart
19
3
19
1
3
1
1
17
86
115
1
7
6
10
1
5
4
1
20
63 77
1
kidney
1
2
30
2
10
7
1
2
5
1
129
15
247431
3
52
31
38
15
21
41
9
1
2
3
118
2
405
637 10 16
liver
1
11
11
1
9
12
3
2
61
3
165
4
352
12
11
2
22
5
5
1
1
64
5
96 152
5
olfactory bulb
8
101
3
5
5
108
1
43
8
1
2
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3
14
3
4
5
20
394
1
1002
1055 20
4
testes
1
171
29
82
11
54
14
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22
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31
32 1 23
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Grk4
Htt
Different spliced isoforms detected across multiple murine tissues based
on the CaptureSeq methodology.
MicroRNA evolution and function
The detection of known miRNAs and the prediction
of novel miRNAs are important for our understanding
of the evolution of these molecules and their roles in
functional specialisation. We developed a new algorithm
for the prediction of novel miRNAs from deepsequencing
data and applied this method to the de novo
detection of miRNAs in a number of species. We worked
closely with Elia Benito-Gutierrez from the Arendt
group to define miRNAs in amphioxus species from
around the world and identify miRNAs with distinct
roles in developmental processes.
Computational methods
The epi-transcriptome is a growing area of interest
and post-transcriptional modifications of a number
of different types of RNA are becoming increasingly
important. We developed Chimera, a recently published
tool for the assessment of 3’ Uridylation of miRNAs and
other changes such as adenylation or ADAR editing.
We began to use this system in collaboration with the
O’Carroll laboratory to explore uridylation and RNA
methylation in the murine male germline. Our data
shows the many important epi-transcriptomic changes
present in both microRNAs and mRNAs and how
they respond when key proteins are conditionally
knocked out.
Future plans
In 2016 we will complete our on-going long-term
analysis on lncRNAs in the male germline and D.
melanogaster mesoderm. We will continue to work on
our project to explore the process of genomic integration
of HPV and how this virus can lead to the development
of cervical cancer through sequencing and clinical
genomics. We also plan to release our new tool for the
machine-learning-based prediction of novel microRNAs
from large-scale sequencing data of both finished
genomes and organisms for which a reference genome is
not yet available.
Our long-term goal is to combine regulatory RNA target
prediction, secondary effects and upstream regulation
into complex regulatory networks. We are extremely
interested in the evolution of regulatory RNAs and
developing phylogenetic techniques appropriate for
short, non-coding RNA and long non-coding RNAs. We
will continue to build strong links with experimental
laboratories that work on miRNAs in different systems,
as this will allow us to build better datasets with which
to train and validate our computational approaches.
The use of visualisation techniques to assist with
the interpretation and display of complex, multidimensional
data will continue to be an important
parallel aspect of our work.
2015 EMBL-EBI Annual Scientific Report 136