Richard Emes is Professor of Bioinformatics at Nottingham School of Veterinary Medicine and Science and Director of the University of Nottingham Advanced Data Analysis Centre ADAC.
Richard is Associate Faculty PVC for Research and Knowledge Exchange, Faculty of Medicine and Health Sciences and Enabling Digital Infrastructure Lead for the Future Food Research Beacon
Richard is a scientist with over 15 years of specialism in bioinformatics. He has extensive experience in genomics/evolution and development of novel solutions to complex biological problems. He initially trained at the MRC Functional Genomics Unit Oxford University where he was a central to the analysis, interpretation and writing of the mouse and rat international genome sequencing projects (Waterston et. al. Nature 2002, Weinstock et. al. Nature 2004) and related reviews (Emes et.al. Hum Mol Genet 2003 and Emes et. al. Genome Research 2004). He later built on this experience through research positions at the Sanger Institute Cambridge and later held an MRC Fellowship in Bioinformatics at University College London.
Research in the Emes lab focuses on the integration of genetic/genomic data and the development of methodologies to analyse these data. Recent interests of the group are comparative genomics to understand gene function and evolution (e.g. Bayes et al Nature Communications 2017, Nithianantharajah et al Nature Neuroscience 2013, Emes and Grant Annual Reviews in Neuroscience 2012, Emes et al. Nature Neuroscience 2008) and functional genomics (e.g. Olcese et al Nature Communications 2017, Sulak et al eLife 2016).
Significance and impact of his research have been through the creation of original software and comprehensive interpretation of complex biological data enabling challenging research to be undertaken. In 2012, he founded the University of Nottingham Advanced Data Analysis Centre (ADAC). Under his co-direction ADAC has since secured self-sustaining funding from sources including MRC, BBSRC, NERC, EU and industrial collaborators.
Emes Group Webpages and links to software
Advanced Data Analyis Centre (ADAC)
Impact and Outputs:
Google Scholar Profile
- Dr Philip Quinlan (ADAC Chief Technical Officer)
- Dr Tom Giles (ADAC Analyst)
- Dr Jo Moreton (ADAC Analyst)
- Andrew Warry (ADAC Analyst)
- Dr Michael Wilson (ADAC Analyst, Future Food Beacon)
- Daniel Lea (ADAC Analyst)
- Abril Izquierdo (PhD Student 2015-2018) - comparative transcriptomics and molecular evolution.
- Necati Esener (PhD Student 2017-2020) - Implementation of new approaches for the understanding and diagnosis of infectious diseases in livestock.
- Colman O'Cathail (BBSRC PhD Student 2017-2020) - Using genomics to elucidate transmission of Mycobacteria between badgers and cattle.
Previous Group Members
- Dr Adam Blanchard Understanding inflammatory processes in ovine footrot to inform rational vaccine design. (BBSRC). Currently Lecturer Nottingham Trent University.
- Maqsud Hossain (PhD Student 2011-2015) - Bioinformatic analysis of pathogen genes and genomes. Currently Director, NSU Genome Research Institute (NGRI)
- Dr Juan Xu Genetics of one-carbon metabolism in sheep in relation to productivity, fertility and health (BBSRC)
- Kameswara Venkata Rama (MSc Student 2016) - De novo transcriptome assembly and annotation of the brain of common pipistrelle bat (Pipistrellus pipistrellus).
- Dr Tania Dottorini Molecular Basis of mating and reproduction in Anopheles species. (Independent Research Fellow) Now Assistant Prof in Bioinformatics SVMS.
- Dr Adam Blanchard (PhD Student 2012-2015) co-supervised with Prof Jamie Leigh SVMS - The use of random mutagenesis in the functional annotation of the genome of Streptococcus uberis.
- Dr Sandie Choong Siew Shean (PhD Student 2012-2015) co supervised with Dr Nigel Mongan and Dr Lisa Yon SVMS - Comparative transcriptomics of adipose tissue.
- Frank Wessely (PhD Student 2010-2013). Currently Post Doc University of Oxford.
- Ornampai Japa (PhD Student 2010-2013). Currently lecturer University of Phayao, Thailand.
- Dr Tom Giles (Bioinformatics Intern 2012). Currently ADAC analyst.
- Ishan Ajmera (Bioinformatics Intern 2012). Currently PhD student University of Nottingham.
- Avnish Kumar (Visiting Scientist from National Bureau of Animal Genetic Resources India). Detecting polymorphisms in animal genomes
- Sarah Smith: PhD student SVMS Nottingham (2008-2012). Polymorphic variants of toll-like receptors. Currently Postdoc at Sheffield University.
- Harry Clifford (Genetics Society Summer studentship 2011 and Bioinformatics Intern 2012) - Effect of anti-epileptic drugs on fetal DNA methylation. Currently Post Doctoral Scientist Cambridge University.
- Libin Joy (MSc Student 2009) - A Bioinformatics approach to detect location bias in CpG island methylation related to maternal folate intake. Currently application scientist at Strand Life Sciences.
- Satish Pendurthi (MSc Student 2011) - Clustering methods for epigenetic analysis.
- Amelia Pollard (BBSRC Research Experience Placement 2011) co-supervised with Dr Lisa Chakrabarti SVMS - Does the mitochondrial proteome change according to tissue type and age? Currently PhD student, University of Nottingham.
- Oliver Heygate (Wellcome Trust Summer studentship 2011) co-supervised with Dr Lisa Chakrabarti SVMS - Do changes occur in the mitochondrial proteome of the cerebellum as the neurons develop to maturity? Currently Year 4 Vet Med Student.
Richard Emes is an elected Fellow of the Linnean Society of London. He is Speciality Chief Editor of Frontiers in Bioinformatics and Computational Biology and is the Sutton Bonington Campus local representative of the Genetics Society of Great Britain.
University of Nottingham Expertise Guide.
Prof Emes' teaching interests are in bioinformatics, genomics, research methods and presentation of scientific data. The teaching is directly informed by the past and present research carried out by… read more
A scientist with nearly 20 years specialism in bioinformatics, I have extensive experience initially gained by working at the renowned MRC Functional Genomics Unit Oxford University where I was a… read more
BAYÉS À, COLLINS MO, REIG-VIADER R, GOU G, GOULDING D, IZQUIERDO A, CHOUDHARY JS, EMES RD and GRANT SG, 2017. Evolution of complexity in the zebrafish synapse proteome. Nature communications. 8, 14613 OLCESE C, PATEL MP, SHOEMARK A, KIVILUOTO S, LEGENDRE M, WILLIAMS HJ, VAUGHAN CK, HAYWARD J, GOLDENBERG A, EMES RD, MUNYE MM, DYER L, CAHILL T, BEVILLARD J, GEHRIG C, GUIPPONI M, CHANTOT S, DUQUESNOY P, THOMAS L, JEANSON L, COPIN B, TAMALET A, THAUVIN-ROBINET C, PAPON JF, GARIN A, PIN I, VERA G, AURORA P, FASSAD MR, JENKINS L, BOUSTRED C, CULLUP T, DIXON M, ONOUFRIADIS A, BUSH A, CHUNG EM, ANTONARAKIS SE, LOEBINGER MR, WILSON R, ARMENGOT M, ESCUDIER E, HOGG C, , AMSELEM S, SUN Z, BARTOLONI L, BLOUIN JL and MITCHISON HM, 2017. X-linked primary ciliary dyskinesia due to mutations in the cytoplasmic axonemal dynein assembly factor PIH1D3. Nature communications. 8, 14279
MORETON, JOANNA, IZQUIERDO, ABRIL and EMES, RICHARD D., 2016. Assembly, Assessment, and Availability of De novo Generated Eukaryotic Transcriptomes Frontiers in Genetics. 6, Article No.: 361
2019-20 University of Nottingham:GCRF CARE Bangladesh: Cholera Antibiotic REsistance in Bangladesh: big data mining and machine learning to improve diagnostics and treatment selection. Co-I £250,000.00
2019-22 BBSRC BB/T001933/1 Prediction of phenotype from genotype with respect to bacterial infection Co-I £655,377.00 2019-22
Innovate UK TS/S008306/1 FARM WATCH: Fight AbR with Machine learning and a Wide Array of sensing TeCHnologies Co-I £692,212
2019-22 BBSRC BB/S003908/1 Regulation of microRNA biogenesis from long noncoding RNAs Co-I £459,487
2018-23 HDR-UK (MRC, BHF, CSO, EPSRC, ESRC, NIHR, Wellcome) HDR-UK Substantive site (HDR Midlands, Universities of Nottingham, Birmingham, Leicester, Warwick) Co-I ~ £3.6m
2018-21 MRC, BHF, CSO, EPSRC, ESRC, NIHR, Wellcome. Tissue Directory and Coordination centre phase II. Co-I £1.2m.
2018-23 NERC NE/R00935X/1 Genomic responses to rapid environmental change: selection, plasticity and adaptation. Co-I £782,140
2017-2020 BBSRC BB/P010520/1 Investigating the role of phosphite in plant development Co-I £624,914
2016-20 NERC NE/N019881/1 EVAL-FARMS: Evaluating the Threat of Antimicrobial Resistance in Agricultural Manures and Slurries Co-I £1.3M
A scientist with nearly 20 years specialism in bioinformatics, I have extensive experience initially gained by working at the renowned MRC Functional Genomics Unit Oxford University where I was a central part of the analysis, interpretation and writing of the mouse and rat international genome sequencing projects (Waterston et. al. Nature 2002, Weinstock et. al. Nature 2004) and related reviews (Emes et.al. Hum Mol Genet 2003 and Emes et. al. Genome Research 2004). I built on this experience through research at the Sanger Institute Cambridge and later held an MRC Fellowship in Bioinformatics at University College London. Research in my lab focuses on the integration of genetic/ genomic data and the development of methodologies to analyse these data. Recent interests of the group are comparative genomics to understand gene function and evolution (e.g. Bayes et al Nature Communication 2017, Nithianantharajah et al Nature Neuroscience 2013, Emes and Grant Annual Reviews in Neuroscience 2012, Emes et al. Nature Neuroscience 2008) and functional genomics (e.g. Watkins et al PNAS 2018, and Olcese et al Nature communication 2017). Significance and impact of my research has been through creation of original software and comprehensive interpretation of complex biological data enabling challenging research to be undertaken (e.g. Bewley et al American Journal of Respiratory Critical Care Medicine 2018, Sulak et al Elife. 2016).
Evolution of the synapse proteome: Understanding the origins and evolution of synapses may provide insight into species diversity and the organization of the brain. We were the first to use comparative proteomics and genomics, to comprehensively study the evolution of the postsynaptic density (PSD) and membrane-associated guanylate kinase (MAGUK)-associated signalling complexes (MASCs) that underlie learning and memory (Emes et al Nature Neuroscience 2008). We were the first to describe the ancient origins of the synapse protein network of proteins (Emes and Grant Front Neurosci. 2011, Ryan et al BMC Neuroscience 2008) and propose the "Synapse first" model of brain evolution (Emes and Grant Annual Reviews Neuroscience 2012). Using this model, I led the comparative genomics component of a research programme linking evolution of the synapse to brain disorders in humans (Nithianantharajah et al Nature Neuroscience 2013) and model organisms (Bayes et al Nature Communications 2017).
1) Bayés À, Collins MO, Reig-Viader R, Gou G, Goulding D, Izquierdo A, Choudhary JS, Emes RD, Grant SG. Evolution of complexity in the zebrafish synapse proteome. Nat Commun. 2017 Mar 2;8:14613 2) Nithianantharajah J, Komiyama NH, McKechanie A, Johnstone M, Blackwood DH, St Clair D, Emes RD, van de Lagemaat LN, Saksida LM, Bussey TJ, Grant SG. Synaptic scaffold evolution generated components of vertebrate cognitive complexity. Nat Neurosci. 2013 Jan;16(1):16-24. 3) Emes RD, Grant SG. Evolution of synapse complexity and diversity. Annu Rev Neurosci. 2012;35:111-31. doi: 10.1146/annurev-neuro-062111-150433. 4) Emes RD, Grant SG. The human postsynaptic density shares conserved elements with proteomes of unicellular eukaryotes and prokaryotes. Front Neurosci. 2011 Mar 31;5:44. 5) Emes RD, Pocklington AJ, Anderson CN, Bayes A, Collins MO, Vickers CA, Croning MD, Malik BR, Choudhary JS, Armstrong JD, Grant SG. Evolutionary expansion and anatomical specialization of synapse proteome complexity. Nat Neurosci. 2008 Jul;11(7):799-806. 6) Ryan TJ, Emes RD, Grant SG, Komiyama NH. Evolution of NMDA receptor cytoplasmic interaction domains: implications for organisation of synaptic signalling complexes. BMC Neurosci. 2008 Jan 15;9:6.
Developing tools to understand gene Function related to pathogenicity in Streptococcus uberis. Many of the articles described in this biosketch use novel software developed by my group. These are made available for wider use by the research community at https://emeslab.wordpress.com/group-software/ or https://github.com/ADAC-UoN/
Streptococcus uberis is a Gram-positive, catalase-negative member of the family Streptococcaceae and is an important environmental pathogen responsible for a significant proportion of subclinical and clinical bovine intramammary infections (Davies et al J. Clin Microbiol 2016). In a comparative genomics analysis of virulent versus avirulent strains, we showed that no single or cluster of genes could be identified that simply determined virulence (Hossain et al BMC Genomics 2015). To dissect the source of S. uberis pathogenicity we developed a computational tool based on saturation mutagenesis that allowed base-pair resolution of the role of genes in pathogenicity (Blanchard et al Front Genetics 2015 and Blanchard et al Front Microbiol 2016). The close association of software development with laboratory research allows the rapid dissection of complex problems with real world applications.
1) Blanchard AM, Egan SA, Emes RD, Warry A, Leigh JA. PIMMS (Pragmatic Insertional Mutation Mapping System) Laboratory Methodology a Readily Accessible Tool for Identification of Essential Genes in Streptococcus. Front Microbiol. 2016 Oct 25;7:1645. eCollection 2016. 2) Davies PL, Leigh JA, Bradley AJ, Archer SC, Emes RD, Green MJ. Molecular Epidemiology of Streptococcus uberis Clinical Mastitis in Dairy Herds: Strain Heterogeneity and Transmission. J Clin Microbiol. 2016 Jan;54(1):68-74. 3) Blanchard AM, Leigh JA, Egan SA, Emes RD. Transposon insertion mapping with PIMMS - Pragmatic Insertional Mutation Mapping System. Front Genet. 2015 Apr 9;6:139. 4) Hossain M, Egan SA, Coffey T, Ward PN, Wilson R, Leigh JA, Emes RD. Virulence related sequences; insights provided by comparative genomics of Streptococcus uberis of differing virulence. BMC Genomics. 2015 Apr 23;16:334.
Epigenetic markers in human and animal disease. Epigenetic markers provide an early marker for disease, particularly cancers (Emes and Farrell J Mol Endocrinology 2012). We were one of the first groups to describe methylation of DNA elements and birth outcomes (Fryer et al Epigenetics 2009 and Fryer et al Epigenetics 2011, Haworth et al Epigenomics 2014). This required development of novel software tools for processing and quality control of methylation differences measured by microarray. Using our tool NIMBL (Wessely and Emes Front Genetics 2012) and later derivatives of our methods we detected methylation changes associated with bladder cancer (Kitchen et al PloS One 2015, Kitchen et al Epigenetics 2016), Rheumatoid arthritis (Glossop et al Epigenetics 2014, Glossop et al Epigenomics 2015, Glossop et al Epigenomics 2017), gestational diabetes (Wu et al Epigenetics 2018) and pituitary adenomas (Duong et al Endcr Related Cancer 2012).
1) Glossop JR, Nixon NB, Emes RD, Sim J, Packham JC, Mattey DL, Farrell WE, Fryer AA. DNA methylation at diagnosis is associated with response to disease-modifying drugs in early rheumatoid arthritis. Epigenomics. 2017 Apr;9(4):419-428. 2) Wu P, Farrell WE, Haworth KE, Emes RD, Kitchen MO, Glossop JR, Hanna FW, Fryer AA. Maternal genome-wide DNA methylation profiling in gestational diabetes shows distinctive disease-associated changes relative to matched healthy pregnancies. Epigenetics. 2018;13(2):122-128. 3) Kitchen MO, Bryan RT, Emes RD, Glossop JR, Luscombe C, Cheng KK, Zeegers MP, James ND, Devall AJ, Mein CA, Gommersall L, Fryer AA, Farrell WE. Quantitative genome-wide methylation analysis of high-grade non-muscle invasive bladder cancer. Epigenetics. 2016 Mar 3;11(3):237-46. 4) Glossop JR, Emes RD, Nixon NB, Packham JC, Fryer AA, Mattey DL, Farrell WE. Genome-wide profiling in treatment-naive early rheumatoid arthritis reveals DNA methylome changes in T and B lymphocytes. Epigenomics. 2016 Feb;8(2):209-24. 5) Kitchen MO, Bryan RT, Haworth KE, Emes RD, Luscombe C, Gommersall L, Cheng KK, Zeegers MP, James ND, Devall AJ, Fryer AA, Farrell WE. Methylation of HOXA9 and ISL1 Predicts Patient Outcome in High-Grade Non-Invasive Bladder Cancer. PLoS One. 2015 Sep 2;10(9):e0137003. 6) Glossop JR, Haworth KE, Emes RD, Nixon NB, Packham JC, Dawes PT, Fryer AA, Mattey DL, Farrell WE. DNA methylation profiling of synovial fluid FLS in rheumatoid arthritis reveals changes common with tissue-derived FLS. Epigenomics. 2015;7(4):539-51. 7) Kitchen MO, Yacqub-Usman K, Emes RD, Richardson A, Clayton RN, Farrell WE. Epidrug mediated re-expression of miRNA targeting the HMGA transcripts in pituitary cells. Pituitary. 2015 Oct;18(5):674-84. 8) 8: Haworth KE, Farrell WE, Emes RD, Ismail KM, Carroll WD, Hubball E, Rooney A, Yates AM, Mein C, Fryer AA. Methylation of the FGFR2 gene is associated with high birth weight centile in humans. Epigenomics. 2014;6(5):477-91. 9) Glossop JR, Emes RD, Nixon NB, Haworth KE, Packham JC, Dawes PT, Fryer AA, Mattey DL, Farrell WE. Genome-wide DNA methylation profiling in rheumatoid arthritis identifies disease-associated methylation changes that are distinct to individual T- and B-lymphocyte populations. Epigenetics. 2014 Sep;9(9):1228-37. 10) Duong CV, Yacqub-Usman K, Emes RD, Clayton RN, Farrell WE. The EFEMP1 gene: a frequent target for epigenetic silencing in multiple human pituitary adenoma subtypes. Neuroendocrinology. 2013;98(3):200-11. 11) Glossop JR, Nixon NB, Emes RD, Haworth KE, Packham JC, Dawes PT, Fryer AA, Mattey DL, Farrell WE. Epigenome-wide profiling identifies significant differences in DNA methylation between matched-pairs of T- and B-lymphocytes from healthy individuals. Epigenetics. 2013 Nov;8(11):1188-97. 12) Haworth KE, Farrell WE, Emes RD, Ismail KM, Carroll WD, Borthwick HA, Yates AM, Hubball E, Rooney A, Khanam M, Aggarwal N, Jones PW, Fryer AA. Combined influence of gene-specific cord blood methylation and maternal smoking habit on birth weight. Epigenomics. 2013 Feb;5(1):37-49. 13) Duong CV, Emes RD, Wessely F, Yacqub-Usman K, Clayton RN, Farrell WE. Quantitative, genome-wide analysis of the DNA methylome in sporadic pituitary adenomas. Endocr Relat Cancer. 2012 Nov 19;19(6):805-16. 14) Emes RD, Farrell WE. Make way for the 'next generation': application and prospects for genome-wide, epigenome-specific technologies in endocrine research. J Mol Endocrinol. 2012 May 29;49(1):R19-27. 15) Wessely F, Emes RD. Identification of DNA methylation biomarkers from Infinium arrays. Front Genet. 2012 Aug 25;3:161. 16) Fryer AA, Emes RD, Ismail KM, Haworth KE, Mein C, Carroll WD, Farrell WE. Quantitative, high-resolution epigenetic profiling of CpG loci identifies associations with cord blood plasma homocysteine and birth weight in humans. Epigenetics. 2011 Jan;6(1):86-94. 17) Fryer AA, Nafee TM, Ismail KM, Carroll WD, Emes RD, Farrell WE. LINE-1 DNA methylation is inversely correlated with cord plasma homocysteine in man: a preliminary study. Epigenetics. 2009 Aug 16;4(6):394-8.
Bioinformatics is a fast changing discipline, my lab aims to be analyzing important and interesting findings using the latest technologies.