Molecular adaptation in pancreatic islets associated with diet specialization: using bats to understand human diabetes

Supervisors

Emma Teeling
UCD, 2nd supervisor

Manuel Irimia
CRG, 2nd supervisor

Objectives

Use single-cell multiomics (RNA-seq and ATAC-seq) from pancreatic islets of bat species with contrasting diets to identify gene expression and regulatory changes associated with dietary specialization. The objective is to uncover how transcriptional programs have evolved in response to distinct metabolic demands, and to link these findings to human type 2 diabetes by integrating comparative genomics and GWAS data. This work will provide novel insights into the molecular basis of islet function across species and help elucidate the evolutionary history of human diabetes susceptibility.

Methodology

The candidate will lead the computational analysis of single-cell transcriptomic and epigenomic data from pancreatic islets of bat species with contrasting diets. This includes integration of single-cell RNA-seq data, cross-species comparisons, and identification of diet-associated regulatory programs. He/she will also contribute to comparative genomics to detect species-specific regulatory changes and integrate these findings with human genetic data—using GWAS fine-mapping and variant annotation—to explore links to type 2 diabetes. The candidate will collaborate closely with researchers at the Federal University of Viçosa (Brazil), who will provide bat islet samples and perform in vivo physiological studies of glucose metabolism, as well as with other team members conducting functional studies in human beta cell lines and primary islets.

Required Skills

Background in computational biology, bioinformatics, or related fields

Experience with programming languages (Python and/or R)

Ideally, familiarity with transcriptomic and genomic data analysis.

Interest in evolutionary biology, metabolic regulation, or endocrine systems.

Expected results

Generation of the first single-cell transcriptomic atlas of pancreatic islets across bat species with diverse diets, uncovering gene expression programs linked to metabolic adaptation. Integration with human genetic data will potentially pinpoint to genes, regulatory elements or variants associated with diabetes risk that may help better understand the evolutionary history of diabetes. It will also establish a framework for evolutionary transcriptomic analysis in non-model organisms.

Planned Secondment

UCD (Teeling) in year 2 (2 months) to acquire knowhow into bat genomics research.

IP (Berthelot) in year 3 (1.5 months) to receive training on GWAS, eQTLs, and identification of evolutionary constraints.

GIMM (Gordo) in year 3 (1 week) to learn about metagenomics research.

Enrolment in doctoral program

PhD in Biomedicine from Universitat Pompeu Fabra.

References

Juan-Mateu J, Bajew S, Miret-Cuesta M, Íñiguez LP, Lopez-Pascual A, Bonnal S, Atla G, Bonàs-Guarch S, Ferrer J, Valcárcel J, Irimia M. Pancreatic microexons regulate islet function and glucose homeostasis. Nat Metab. 2023 Feb;5(2):219-236. doi: 10.1038/s42255-022-00734-2. Epub 2023 Feb 9. PMID: 36759540.

Blumer M, Brown T, Freitas MB, Destro AL, Oliveira JA, Morales AE, Schell T, Greve C, Pippel M, Jebb D, Hecker N, Ahmed AW, Kirilenko BM, Foote M, Janke A, Lim BK, Hiller M. Gene losses in the common vampire bat illuminate molecular adaptations to blood feeding. Sci Adv. 2022 Mar 25;8(12):eabm6494. doi: 10.1126/sciadv.abm6494. Epub 2022 Mar 25. PMID: 35333583; PMCID: PMC8956264.

Wilhoit K, Yamanouchi S, Chen BJ, Yamasaki YY, Ishikawa A, Inoue J, Iwasaki W, Kitano J. Convergent Evolution and Predictability of Gene Copy Numbers Associated with Diets in Mammals. Genome Biol Evol. 2025 Feb 3;17(2):evaf008. doi: 10.1093/gbe/evaf008. PMID: 39849899; PMCID: PMC11797053.