Zhou Lab

Translational genomics is a new emerging science combining translational and clinical research with statistics, genomics, clinical informatics, bioinformatics, medical informatics, information technology, and mathematics together. One of our current research goals is to develop appropriate computational tool to analyze the high-throughput genomic and genetic data obtained from animal models or human patients to optimize the development of disease-specific biomarkers, aid medical decision-making, and supervise drug target identification and clinical validation. We are currently working with Dr. Qi Chen's Lab to identify the “disease RNA code” composed of non-canonical small non-coding RNAs (e.g. tRNA-derived small RNAs [tsRNAs], rRNA-derived small RNAs [rsRNAs], and YRNA-derived small RNAs [ysRNAs]), which potentially paves a new avenue for future molecular diagnosis/prognosis in precision medicine.

With the development of high-throughput sequencing technology, it has been revealed that, in eukaryotes, only a small proportion of transcripts carry protein-coding potential, while the majority of the genome is transcribed to produce non-coding RNAs. Non-coding RNAs are often involved in regulating gene expression at the transcriptional and/or post-transcriptional levels. It is my research interest to investigate the non-canonical small non-coding RNAs, including tRNA-derived small RNAs (tsRNAs), rRNA-derived small RNAs (rsRNAs), YRNA-derived small RNAs (ysRNAs), and so on, which are markedly under investigated but miraculously involved in transgenerational epigenetic inheritance and post-transcriptional regulation.

Synonymous mutations (so called silent mutations) are the change of one base for another in an exon of a gene, such that the produced protein primary sequence is not modified. When a synonymous or silent mutation occurs, the change is often assumed to be neutral, meaning that it does not affect the fitness of the individual carrying the new gene to survive and reproduce. However, increasing evidence indicates that synonymous mutations have significant consequences for cellular processes in all taxa. Evolutionary research on synonymous sites is becoming increasingly important as these analyses make their way into clinical utilizations of academic results, which has numerous implications not only for the understanding of basic biology but also for methods development in bioengineering and for the diagnosis and treatment of genetic disease.