Genomic study suggests ‘jumping genes’ are associated with severity of Influenza A viral infections
- Influenza A viral infection varies in severity from person to person. What causes this variability is not fully understood.
- Different individuals infected by the same virus show variations in severity of infection. This suggests that host (patient) factors contribute to severity of infection.
- One of the first responses to Influenza A virus infection is the immune-system mediated modulation of gene expression via transcription factors.
- Transposable elements (TE), also known as ‘jumping genes’ also regulate transcription at various times, including during viral infections.
- In a new genomics study, researchers discovered that some ‘jumping genes’ were predictive of viral load or severity of infection.
Researchers have long been puzzled by the varying degrees of illness experienced by individuals infected with the same virus. While viral characteristics, like different strains, contribute to this variability, they don’t fully explain the range of responses observed. Host (patient) related factors, such as pre-existing immunity, age, gender, body mass, and the body’s microorganism community, are being examined to understand this phenomenon.
The molecular biology within your cells is crucial. DNA is a long double-helical strand. You might think that genetic information is always read in order from one end to the other. However, that’s not true. DNA has regions that have been commonly referred to as ‘junk DNA’. This is by no means junk as these regions of DNA are important for the regulation of gene expression. For instance, transposable elements, which are popularly known as ‘jumping genes’ are known to regulate gene expression 1.
Do transposable elements play a role in Influenza A viral infection severity
Recently, researchers examined the contribution of TEs to variations in severity of illness after influenza A virus infection 2.
The researchers conducted a study involving 39 individuals who were monitored both before and after being infected with the influenza A virus.
Through their analysis, they discovered notable alterations in the accessibility, or “readability,” of transposable elements. To achieve this, the researchers employed a comprehensive approach that integrated multiple sets of multiomics (putting together data from all parts of the cell)) data. These datasets encompassed a range of biomolecules within cells or organisms and allowed for characterising and quantifying their presence. Specifically, they focused on two key types of data: the transcriptome and the epigenome.
The transcriptome encompasses all RNA copies transcribed from the DNA within a cell. By examining changes in the transcriptome, the researchers gained insights into the activity and expression of genes.
The epigenome represents the chemical modifications to DNA that can impact gene expression. By analyzing alterations in the epigenome, the researchers could assess changes in the regulation of genes.
One notable advantage of employing this multiomics approach is the ability to identify families of transposable elements that exhibit changes in accessibility. This is a crucial finding, as previous approaches might have missed these specific patterns. By utilizing a combination of transcriptomic and epigenomic data, the researchers were able to gain a more comprehensive understanding of the impact of influenza A virus infection on transposable elements and their potential role in disease progression.
TEs predict influenza A viral load
By examining the alterations in TEs following viral infection, the researchers were able to discern various transcription factors. Transcription factors are proteins responsible for activating or deactivating specific genes.
These transcription factors were found to play a probable role in shaping an individual’s response to influenza A infection. Building upon these discoveries, the researchers developed a model capable of predicting an individual’s viral load following influenza A infection.
The researchers claim that this model provides valuable insights into the potential severity and progression of influenza A infection in a given individual. Future research will confirm or contradict this study. Nevertheless, such a model to predict viral load of influenza A infections can be very useful in the diagnosis and treatment of these infections.
- Raquel Fueyo et al., Roles of transposable elements in the regulation of mammalian transcription. Nature Reviews Molecular Cell Biology. 23, 481-497 (2022).
- Xun Chen et al., Transposable elements are associated with the variable response to influenza infection. Cell Genomics. 3, 100292 (2023).