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Innovations and evolutionary constraints in societies of superorganismal insects
Project Description
The "superorganismal" societies of ants, bees, wasps, and termites dominate many terrestrial habitats because of their extreme social living: queens and males reproduce, and morphologically distinct workers do everything else. Kin-selection theory explains why natural selection can favour alleles leading to superorganismal life. However, the theory overlooks the fundamental challenge of explaining how selection for sociality manifests in the genome.
How genetic information is used and inherited can constrain natural selection: advantages of an allele for one phenotype may be offset by detrimental impacts on another phenotype, and chromosomal architectures can affect the ability of selection to act.
To overcome such constraints, selection can favour genomic innovations such as gene duplications, rewiring of regulatory networks, and supergene regions, but such innovations can in turn create new constraints on the ability of selection to act.
This project aims to uncover how innovative social phenotypes evolve, and which genomic innovations and constraints underpin them. Using modern sequencing technologies and computational approaches, we will examine either:
* How similar genomic changes occurred across independent origins of superorganismality
* How specific genomic architectures underpin major ecological traits within species
The focus will be tailored to the student's interests and skills.
Research themes
Project Specific Training
The student will receive comprehensive training across multiple areas:
Research Skills - delivered through direct supervision, hands-on training, and visits to collaborator labs:
• Field techniques for insect collection and colony maintenance
• Modern molecular methods including DNA/RNA extraction, library preparation and sequencing
• Advanced computational analysis & data visualisation
• Project management and experimental design
Scientific Communication - developed through regular supervisory meetings, lab meetings, conferences and teaching opportunities:
• Scientific writing for manuscripts and thesis
• Conference presentation skills
• Public engagement activities
• Teaching Assistant roles on MSc courses in bioinformatics and genomics
Professional Development - accessed through external courses and institutional support:
• Specialist training through e.g., EMBO, NERC EOF, Turing institute and Wellcome Trust courses
• Regular progress reviews and career development discussions
• Networking opportunities through international collaborations & conferences
• Research skills workshops offered through the graduate school
This structured training program combines direct mentorship, hands-on experience, and external opportunities to develop both technical expertise and transferable professional skills.
Potential Career Trajectory
This project combines fundamental evolutionary biology with cutting-edge data science approaches, positioning graduates for diverse career paths.
It provides the academic track record needed for a potential long-term academic career. That’s because:
• The project's innovative approach to major evolutionary questions will enable high-impact publications in leading journals
• The strong publication record combined with expertise in both biology and computation makes graduates competitive for prestigious fellowships and faculty positions
• Experience running complex research projects provides foundation for independent research careers
But many more opportunities exist outside of academia. The combination of biological insight with rigorous computational expertise is especially attractive as organisations increasingly rely on data-driven decision making because you’ll get:
• Expertise in handling complex biological datasets, including through programming and workflow
• Statistical analysis and machine learning
• Data visualization and communication
• Experience with high-performance computing, automated testing, and version control
Our focus on reproducible research and open-source/open data approaches further enhances employability by demonstrating real-world technical capabilities alongside academic excellence.
Overall, the technical, management and communication skills are highly transferable to roles in:
• Tech companies and startups, biotech/pharma industries, Conservation and biodiversity consulting, Environmental monitoring, Government agencies.
• But they’re also transferable to generalist data science and software roles in finance, established tech companies and startups
Project supervisor/s
Yannick Wurm
Centre for Biodiversity and Sustainability & Digital Environment Research Institute
QMUL
y.wurm@qmul.ac.uk
Richard Nichols
Centre for Evolutionary and Functional Genomics
QMUL
r.a.nichols@qmul.ac.uk
Supervision balance
70:30