MicroRNA expression and function in neonatal hypoxic ischaemic encephalopathy

Hypoxic ischaemic encephalopathy (HIE) is a devastating neonatal condition which affects 2-3 per 1000 infants annually. The current gold standard of treatment - induced hypothermia, has the ability to reduce neonatal mortality and improve neonatal morbidity. However, to be effective it needs to be initiated within the therapeutic window which exists following initial insult until approximately 6 hours after birth. Current methods of assessment which are relied upon to identify infants with HIE are subjective and unreliable. To overcome this issue, an early and reliable biomarker of HIE severity must be identified. MicroRNA (miRNA) are a class of small non-coding RNA molecules which have potential as biomarkers of disease state and potential therapeutic targets. These tiny molecules can modulate gene expression by inhibiting translation of messenger RNA (mRNA) and as a result, can regulate protein synthesis. These miRNA are understood to be released into the circulation during cellular stress, where they are highly stable and relatively easy to quantify. Therefore, these miRNAs may be ideal candidates for biomarkers of HIE severity and may aid in directing the clinical management of these infants. By using both transcriptomic and proteomic approaches to analyse the expression of miRNAs and their potential targets in the umbilical cord blood, I have confirmed that infants with perinatal asphyxia and HIE have a significantly different UCB miRNA signature compared to UCB samples from healthy controls. Finally, I have identified and investigated 2 individual miRNAs; both of which show some potential as classifiers of HIE severity and predictors of long term outcome, particularly when coupled with their downstream targets. While this work will need to be validated and expanded in a new and larger cohort of infants, it suggests the potential of miRNA as biomarkers of neonatal pathological conditions such as HIE.

Identification of RNA editing in the human exome and development of DARNED DatabaseSF

RNA editing is a biological phenomena that alters nascent RNA transcripts by insertion, deletion and/or substitution of one or a few nucleotides. It is ubiquitous in all kingdoms of life and in viruses. The predominant editing event in organisms with a developed central nervous system is Adenosine to Inosine deamination. Inosine is recognized as Guanosine by the translational machinery and reverse-transcriptase. In primates, RNA editing occurs frequently in transcripts from repetitive regions of the genome. In humans, more than 500,000 editing instances have been identified, by applying computational pipelines on available ESTs and high-throughput sequencing data, and by using chemical methods. However, the functions of only a small number of cases have been studied thoroughly. RNA editing instances have been found to have roles in peptide variants synthesis by non-synonymous codon substitutions, transcript variants by alterations in splicing sites and gene silencing by miRNAs sequence modifications. We established the Database of RNA EDiting (DARNED) to accommo-date the reference genomic coordinates of substitution editing in human, mouse and fly transcripts from published literatures, with additional information on edited genomic coordinates collected from various databases e.g. UCSC, NCBI. DARNED contains mostly Adenosine to Inosine editing and allows searches based on genomic region, gene ID, and user provided sequence. The Database is accessible at http://darned.ucc.ie RNA editing instances in coding region are likely to result in recoding in protein synthesis. This encouraged me to focus my research on the occurrences of RNA editing specific CDS and non-Alu exonic regions. By applying various filters on discrepancies between available ESTs and their corresponding reference genomic sequences, putative RNA editing candidates were identified. High-throughput sequencing was used to validate these candidates. All predicted coordinates appeared to be either SNPs or unedited.