Understanding the Role of IncRNAs in Metabolic Disease

Long non-coding RNAs (lncRNAs) constitute a large and still poorly understood fraction of the human transcriptome. Although many lncRNAs show strong tissue- and cell-type specificity and have been linked to clinical phenotypes, most remain insufficiently annotated and functionally unexplored. This research line aims to define the landscape and biological relevance of lncRNAs in metabolically active organs, including adipose tissue, liver, muscle, and kidney, with a particular focus on their role in metabolic regulation and disease.

A major challenge in lncRNA research is their incomplete and inconsistent representation in existing transcriptomic datasets. Array-based platforms often focus on protein-coding genes, while commonly used RNA-sequencing pipelines rely on reference annotations that capture only a fraction of known lncRNAs. In addition, lncRNAs frequently exhibit complex splicing patterns and long transcript structures that are poorly resolved by standard short-read sequencing. To overcome these limitations, we develop dedicated bioinformatic pipelines, integrate specialized lncRNA databases, and apply long-read sequencing technologies to improve lncRNA detection, quantification, and isoform resolution across tissues and cell types.

By combining bulk and single-cell transcriptomics with spatial in situ sequencing, we systematically map tissue- and cell-type-specific lncRNA expression in metabolic organs and validate their spatial localization in situ. Candidate lncRNAs are prioritized based on strong clinical associations in large human cohorts and are subsequently investigated using functional perturbation approaches, including RNA interference, with a particular emphasis on adipose tissue. The overarching goal is to establish a comprehensive, multimodal atlas of metabolically relevant lncRNAs and to identify a subset with high potential as novel, tissue-specific therapeutic targets.