Small noncoding RNAs (sncRNAs), such as microRNAs (miRNAs), are ubiquitous and play an important role in the control of cellular processes, making them suitable targets for the investigation of human disease. But before we can fully understand their function, we must distinguish between valid miRNAs and false positives – a task with which machine learning methods often struggle. In an attempt to elucidate the most resilient miRNA biomarkers, a team from Saarland University took an unusual approach by sequencing the blood of different animals (1). We spoke to lead researcher Andreas Keller to find out more.
Why analyze the blood of animals?
When we collect sncRNA data from humans, there can be up to 20 million data points per patient, which leaves us with numerous miRNA features. But because patient cohorts are typically small, machine learning methods have difficulty recognizing true biomarker signatures without overtraining the models. Confounding patient factors, such as age, gender, and ethnicity, add to the diversity of miRNA profiles and increase this complexity. Our aim is to exclude miRNA signatures that are likely artifacts.
Evolutionarily conserved biomarkers that occur in different species in similar form and function are much more likely to be resilient. And that’s where the animals come in. We took 21 blood samples from 19 different species – including a coati and a Humboldt penguin – and performed next-generation sequencing of the miRNAs expressed in their blood cells.
How does the conservation of miRNA expression between different species help with human disease biomarkers?
Studies on sncRNAs often rely on genomic sequence similarity rather than expression data. We realized that, for many conserved animal miRNAs, there was no actual expression data available. When we evaluated and compared the data across species, we found that miRNA sequences and expression were even more conserved than previously thought. Now, we can incorporate our findings into computer models to improve our ability to find reliable biomarkers in the future.
How many animals do you aim to analyze?
The more animals we sequence, the better! There are currently 40 different animals in the database and we continue to make discoveries with each new species. But we don’t just want more species; it will also be beneficial to sequence a number of different animals of the same species to build on the data. Finally, we want to apply a variety of technologies alongside bulk sequencing, such as single-cell RNA sequencing of animal blood cells.
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References
- T Fehlmann et al., “The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals”, Nucleic Acids Res, 47, 4431–4441 (2019). PMID: 30937442.
