UCL Division of Biosciences



UCL Genetics Institute
The single common denominator of all the research in UGI is the analysis of big genetic data to address important questions in biology and medicine. Apart from this constraint, UGI group leaders are free to work on any topic their curiosity or passion may lead them to. This results in a diverse, yet coherent, research portfolio including evolutionary and medical human genetics, plant and animal breeding as well as human and wildlife pathogen genetics. 

An important component of our work is the development of novel software for the analysis of big genetic data. We believe in scientific open access and make all our genetic data and methodological tools available to everyone without strings attached. As such, all software we develop is deposited in publicly available repositories.

See some of the most widely used software packages members of the UGI have contributed to.

Nicholas Luscombe lab: Computational Biology and Bioinformatics / Genomics and Gene Regulation

Current Group Members

Nicholas Luscombe (group leader)Arsham Gharamani
Charlotte CapitanchikRaphaelle Luisier
Sara RohbanFederico Agostini
Mahmoud-Reza “Sina” RafieeAylin Cakiroglu
Sebastian SteinhauserAndrew Steele
Cai LiAnna Poetsch
Anob “Nobby” Chakrabarti 

We are a computational biology laboratory with a particular interest in the genome-scale analysis of gene regulation and evolution.
Our goal is to use genomic data to understand: 

  • How is gene expression regulated?
  • How do these mechanisms control interesting biological behaviours?
  • How does gene regulation affect evolution?

We use a genomic approach as it allows us to identify common principles that apply to most biological systems. Unique or unusual cases - which always occur in biology - could then be understood within this broader context.
Most of our work depends on publicly available data, but we also collaborate closely with a few experimental laboratories.

Maria Secrier lab: Computational Cancer Genetics and Immunology 

Dr Maria Secrier 

Mutational processes in cancer confer an intrinsic proliferative advantage to the malignant cell, and at the same time enable it to escape immune surveillance. My group aims to understand the evolving relation between genomic instability and responses in the tumour microenvironment during cancer progression by addressing the following questions:

1. What is the impact of large-scale genomic mechanisms (mutational signatures, catastrophic events) on immune responses in cancer? 

2. How do tumour-immune cell interactions change in time (early to later stages, primary tumours to metastases, pre-/post-therapy)?

3. Can we exploit cancer vulnerabilities (inferred from RNAi, CRISPR screens) to understand the pathway-level deregulation involved in immune signalling and identify new potential targets for treatment?

To achieve this we use machine learning and data integration methods on genomic and transcriptomic datasets (from patient samples and 2D/3D cell lines) available publicly or from collaborative efforts with experimental groups. We also develop novel computational methods that enable us to identify catastrophic events (chromothripsis, breakage-fusion-bridge cycles etc.) in cancer, evaluate immune and stromal cell activity, time developmental cancer processes, etc. We aim to utilise this knowledge to propose novel prognostic biomarkers and therapeutic strategies in the clinic. 

Aida Andres lab: Evolutionary Genomics

Current Group Members


Dr Aida Andres (group leader)Dr Felix M Key  
Dr Joshua SchmidtDr Cesare de Filippo  
David ReherDr Joao Teixeira  
Sojung HanDr Barbara Bitarello  
 Dr Romain Laurent 

Our main goal is to understand how organisms adapt to their natural environments, and how these evolutionary changes shape phenotypes. We are most interested in adaptive evolution, and study the role that natural selection has played in the phenotypically-relevant genomic diversity that exists within and between populations.  While not necessarily limited by organism, we have typically studied humans, intrigued by our recent evolution, and other primates, motivated by an urgency to understand their past evolution and current adaptive potential. To answer these questions, we analyse both modern and ancient genomes using a combination of genomics, bioinformatics, population genetics and functional approaches.

Garrett Hellenthal lab: Human Population Genetics

Current Group Members


Dr Garrett Hellenthal (group leader)Dr Saioa Lopez
Dr Louise OrmondDr Lucy van Dorp 
Juan Camilo Chacon-Duque 
Pongsakorn Wangkumhang 
Liam Quinn 

Our group works on reconstructing the demographic and selection history of human populations using genome-wide DNA. In particular, we develop and apply statistical models that can identify and date genetic intermixing among groups, and relate this intermixing to historical events such as migrations, past empires and social institutions. We are currently developing other models to identify genetic regions that show signs of conservation among human groups (i.e. due to episodes of selection), relating this to phenotypes. To do these analyses, we primarily use haplotype-based techniques, which exploit correlations among neighboring genetic markers in order to increase power over other available population genetics approaches. We are applying these models to previously sampled and novel collections of genetic variation data from hundreds of world-wide human populations.

Richard Mott lab: Genetic Architecture of Complex Traits

Current Group Members


Professor Richard Mott (group leader)Dr Jess Buxton
Dr Michael ScottDr Sanja Franic
Dr Thu LeLeilei Cui

Our group works on the genetics of complex traits of a wide variety of plants, animals and humans. Much of this work has a common genetical and statistical framework, based on the creation and analysis of populations descended from multiple inbred strains. The chromosomes of such individuals are mosaics of the genomes of the founders, and we exploit this fact in the analysis. This strategy is particularly effective in crop genetics, where so-called MAGIC populations are now commonplace. We are funded by the BBSRC and GCRF to investigate MAGIC populations of wheat, rice and chickpea, with collaborators NIAB (Cambridge UK), IRRI (Los Banos Philippines) and ICRISAT (Hyderabad India). We also have Wellcome Trust funding to investigate DNA-DNA interactions around imprinted loci in mice, in order to understand the mechanisms underlying parent-or-origin effects (in collaboration with Gudrun Moore, ICH). We have a collaboration with Dorret Boosma (Amsterdam) on parent-of-origin effects in human twins. We have NIH funding  to investigate the genetics of adiposity (with Leah Solberg, North Carolina USA). We are also investigating the effects of structural variation on major depressive disorder.

Karoline Kuchenbaecker lab: Genetic Architecture of Complex Traits

Current Group Members

Karoline Kuchenbaecker (group leader)
Dr Stefanie Mueller

My aim is to understand the patterns of how genetic variants influence complex traits. This involves questions such as how strong is the overall influence of genetics, and do disease subtypes differ in terms of their genetic risk factors? My current focus is to compare the genetic basis of traits across different populations, such as Africans and Europeans, using polygenic methods.

Additionally, I conduct studies to identify variants or genetic elements affecting traits and I was centrally involved in several break-through discovery studies for cancer susceptibility loci. I also work on different aspects of cancer risk prediction.

I collaborate with research groups at the Wellcome Trust Sanger Institute, the University of Cambridge, UCL and the German Cancer Research Center (DKFZ).

Jürg Bähler lab: Genome Regulation

Current Group Members

Professor Jürg Bähler (group leader)
Antonia Lock
María Rodríguez-López
Michal Malecki
Leanne Grech
Mimoza (Mimi) Hoti

The Bähler laboratory studies genome regulation during cellular quiescence, ageing and stress response using fission yeast as a model system. We apply multiple genetic, computational and genome-wide approaches for systems-level understanding of regulatory processes and complex relationships between genotype, phenotype, and environment, including roles of genome variation and evolution, transcriptome regulation, and non-coding RNAs.

Mark Thomas lab: Molecular and Cultural Evolution

Current Group Members

Professor Mark Thomas (group leader)
Dr Yoan Diekmann (Research Associate)
Adrian Timpson (PhD student / Research Associate)
Catherine Walker (PhD student)
Stuart Peters (PhD Student)

We are interested the evolutionary processes that shape patterns of modern and ancient human molecular and cultural variation. We use computer simulation and statistical modelling to make inferences from genetic data – including ancient DNA – and archaeological information, on processes such as past migrations and dispersals, natural selection – particularly in response to changes in diet and infectious disease loads – and how demographic factors shape cultural evolution.

Francois Balloux lab: Pathogen Population Genomics

Current Group Members


Dr Francois Balloux (group leader)Dr Vegard Eldholm
Dr Rhys Farrer Dr Matteo Fumagalli
Dr Stephen Price Dr Thibaut Jombart
Dr Lucy van DorpDr Florent Lassalle
Javier MendozaDr Adrien Rieux
Liam Shaw Dr Ben Sobkowiak
William LeungDr Alethea Wang
Hongbin ChenDr Lucy Weinert

Our primary interest is in the use of genomic data to reconstruct infectious disease outbreaks and epidemics in humans, domesticated and wild animals. We address a variety of question ranging from reconstructing transmission chains (i.e. who infected whom) in a hospital ward to describing global epidemics, past and present. This research is directly linked to our interest in the emergence, maintenance and control of antibiotic resistance. We also have an interest in human genetics, particularly in the context of resistance and susceptibility to infectious diseases.

Dave Curtis lab: Psychiatric and Statistical Genetics

Dr Dave Curtis

I develop and apply new methods of statistical analysis to diseases with complex modes of inheritance, in particular schizophrenia and bipolar disorder. I am focussing on methods appropriate for dealing with next generation sequence data produced from large case-control cohorts. I am especially working on techniques to apply weighted burden analysis, which seeks to detect whether rare variants with predicted functional effects are enriched among cases.

Julie Bertrand lab: Quantitative Clinical Pharmacogenetics

Current Group Members

Dr Julie Bertrand (group leader)
Camille Couffignal
Philippine Eloy
Minh Le
Dr Florence Loingeville
Francois Riglet

The increasing body of data available in biomedicine makes it crucial to develop and to use adequate biological and statistical models for their analysis. Quantitative clinical pharmacology is based on the development of semi-physiological models of drug response(s) in order to improve drug development and drug personalization. Therefore, we apply and propose a model-based approach to the analysis of genetic and drug response data, with a focus on chronic diseases such as HIV, multiple sclerosis or bipolar disorders. 

Vincent Plagnol lab: Statistical Genetics

Current Group Members

Dr Vincent Plagnol (group leader)
Claire Tkacz
Seth Jarvis
Jack Humphrey

My research group lies at the intersection between genetics, statistics and bioinformatics. We use the vast amount of data generated by high throughput, genome-wide technologies to provide insights into the mechanism of complex disorders with a particular focus on neuro-degenerative, in collaboration with the UCL Institute of Neurology. Another disease area of interest is auto-immune and inflammatory disease, for which we leverage RNA-Seq studies to understand their molecular basis.