Bioinformatics Analysis Of Transcriptomics Data

The transcriptome refers to a set of all RNA that can be transcribed by a cell under a certain condition.Transcriptomics is a discipline that studies the transcriptional occurrence and changes of transcriptome in biological cells at the overall level.Before the technology of transcriptome sequencing(RNA-seq),gene chip was mainly used to study gene expression.However,with the continuous development of RNA-seq and the decreasing cost of high-throughput sequencing,RNAseq is becoming more and more common in the study of transcriptional analysis.Compared with other technologies,RNA-seq has the characteristics of high sensitivity,high accuracy and a wide range of sequencing.The maturity of RNA-seq technology allows us to go deeper in the systematic study of the whole transcriptome.With the rapid development of RNA-seq,its application has covered many aspects of RNA research,such as transcriptome information of single cell,RNA translation and determination of RNA structure.At the same time,the application of RNA-seq in biological research is also expanding.At present,it mainly includes long-read sequencing technology and the use of sequencing technology to obtain the spatial specific information of gene expression,namely spatial transcriptome technology.The wide application of RNA-seq has enriched the research methods of scholars and improved the understanding of many biological issues.Based on a large amount of RNA-seq data and the application of RNA-seq in different biological problems,the work of this article mainly includes the following aspects:1.The assembly of primordial follicles in mammals represents one of the most critical processes in ovarian biology.It directly affects the number of oocytes available to a female throughout her reproductive life.To delineate the developmental trajectory of oocyte during the process,we performed RNA-seq on single germ cells from newborn(P0.5)ovaries and identified a series of genes that may function between stage transitions.The significant decrease of meiosis-related genes and the dramatic increase of oocyte-specific genes marked the transition of germ cell to a functional oocyte.Our data highlighted the complexity of transcriptional control and depicted the regulons and their regulatory networks in oocyte development.Besides that,our data first characterized patterns of alternative splicing events and linked isform usage differences to cellular stage transitions of folliculogenesis.In summary,this study reconstructed molecular cascades in oocytes and revealed the orchestration of transcription-splicing coupling regulation on follicle formation.2.Gene editing is the editing of target genes by inserting and knocking out specific DNA fragments.With the in-depth research of gene editing and the emergence of gene editing technology CRISPR/Cas(Clustered regularly interspaced short palindromic repeats/Cas,CRISPR/Cas)system,gene editing also provides more possibilities for the treatment of diseases.At present,one of the problems faced by gene editing is the large number of off target effects caused by gene editing and the resulting side effects including cancer.Therefore,in view of the problems of gene editing,this study compared endogenous RNA editing and off-target RNA single nucleotide variation(SNV)caused by gene editing to explore the qualitative differences.3.In the past few years of research,many RNA editing sites have been identified by high-throughput RNA sequencing.However,the exploration of RNA editing events in humans and other species is still not comprehensive.As a result,we developed db RED(RNA Editing Database),which provides a database with rigorous annotation for A-to-I RNA editing events.db RED(https://dbred.bioinfotech.org)collected more than 2.3million RNA editing sites identified in seven species from nine projects using multiple methods.While integrating genome and epigenome annotations,it can also analyze RNA editing sites across tissues/cell lines/species.Besides,db RED allows users to explore annotations of interested A-to-I editing sites in an interactive and user-friendly visualization interface.db RED will be a useful resource for exploring the functional consequence of A-to-I changes with their genomic and epigenomic context.