Network analysis of pseudogene-gene relationships: from pseudogene evolution to their functional potentials

Abstract

Pseudogenes are fossil relatives of genes. Pseudogenes have long been thought of as "junk DNAs", since they do not code proteins in normal tissues. Although most of the human pseudogenes do not have noticeable functions, ~20% of them exhibit transcriptional activity. There has been evidence showing that some pseudogenes adopted functions as lncRNAs and work as regulators of gene expression. Furthermore, pseudogenes can even be "reactivated" in some conditions, such as cancer initiation. Some pseudogenes are transcribed in specific cancer types, and some are even translated into proteins as observed in several cancer cell lines. All the above have shown that pseudogenes could have functional roles or potentials in the genome. Evaluating the relationships between pseudogenes and their gene counterparts could help us reveal the evolutionary path of pseudogenes and associate pseudogenes with functional potentials. It also provides an insight into the regulatory networks involving pseudogenes with transcriptional and even translational activities.In this study, we develop a novel approach integrating graph analysis, sequence alignment and functional analysis to evaluate pseudogene-gene relationships, and apply it to human gene homologs and pseudogenes. We generated a comprehensive set of 445 pseudogene-gene (PGG) families from the original 3,281 gene families (13.56%). Of these 438 (98.4% PGG, 13.3% total) were non-trivial (containing more than one pseudogene). Each PGG family contains multiple genes and pseudogenes with high sequence similarity. For each family, we generate a sequence alignment network and phylogenetic trees recapitulating the evolutionary paths. We find evidence supporting the evolution history of olfactory family (both genes and pseudogenes) in human, which also supports the validity of our analysis method. Next, we evaluate these networks in respect to the gene ontology from which we identify functions enriched in these pseudogene-gene families and infer functional impact of pseudogenes involved in the networks. This demonstrates the application of our PGG network database in the study of pseudogene function in disease context.

PseudoFuN: Deriving functional potentials of pseudogenes from integrative relationships with genes and microRNAs across 32 cancers

“…Theoretically unprocessed pseudogenes can align to both exonic and intronic regions of DNA, while processed pseudogenes can only align to exonic regions. In our previous database we did not perform this two-procedure strategy in part to reduce the runtime of the problem [48]. These changes make the database much more complete and biologically relevant.…”

The Unforeseen Non-Coding RNAs in Head and Neck Cancer

“…The pseudogenes are transcribed in approximately 20% of cases. Some pseudogene transcripts were even found to be translated into peptides [ 52 , 59 , 60 ]. Whether these peptides have a functional role inside the cell remains to be studied [ 60 , 61 ].…”

Pseudogene-gene functional networks are prognostic of patient survival in breast cancer

“…Candidate interactions can be uncovered using direct 1:1 pseudogene to gene parent mappings; however, these interactions do not take into account the wider array of sequence homology relationships that may cause regulation. For this purpose, we use the idea of pseudogenegene networks, which are networks of pseudogenes and genes that have high sequence homology and as a result may be functionally related [20]. These functional relationships are taken from the Pseudogene Functional Network (PseudoFuN) database [21] so that pseudogenes and genes could be mapped back to prospective regulatory partners.…”