Variable splicing of pre-mRNA is not only the major cause of proteome diversity. It can also regulate gene expression through post-transcriptional regulatory mechanisms, thus playing a necessary role in various biological processes such as abiotic environmental stress response, pathogen defense, cell differentiation fate determination, growth and development, regulation of circadian rhythm changes and control of the flowering transition. With the development of high-throughput sequencing technology, variable splicing has become one of the important research directions in life.
Lifeasible has been specializing in plant sequencing since its inception. We have a Sanger sequencing/next-generation sequencing/long-read sequencing platform and a dedicated bioinformatics analysis team to provide customizable bioinformatics analysis solutions for plant pre-mRNA variable splicing.
We performed RNA-Seq on the plants to be analyzed and then systematically analyzed their gene expression and variable splicing characteristics using bioinformatics techniques. Our service can target RNA-seq sequencing data from different tissues (such as seeds, roots, leaves, and flowers) and environmental stresses.
We first extract the RNA from the plant samples, reverse transcribe the RNA and use the Ct method to calculate expression from the data obtained. The RNA will then be used to build a sequencing library. We usually build two types of libraries, PolyA enrichment libraries and rRNA removal libraries.
We will download the genome annotation data of the plants to be analyzed from the NCBI database, RAPDB, and MSU database, then use the software to merge the data and integrate overlapping genes to obtain a complete gene annotation file. This file will be used for RNA-seq sequence alignment and transcript assembly.
The ability to use the skewer to remove splices and low-quality sequences from raw Fast Q files to produce high-quality Fast Q files. RSEQC counts the alignment information, mainly the number of aligned sequences compared to the reference genome, unique alignments, multiple position alignments, and non-contiguous clipping alignments. Transcripts are then assembled using biological software such as StringTie, gffcompare, Cufflinks, and TACO.
We will use DESeq2, the most widely used tool for differentially expressed gene analysis, for differentially expressed gene identification.
We will use various tools such as SUPPA2 and r MATs to analyze the five main types of variable splice events in annotation files: ES, IR, A3SS, A5SS, and MXE with SUPPA2 specializing in the analysis of existing variable splice events in annotation files.
This work uses the R package clusterprofiler (v3.10.1) to perform GO and KEGG enrichment analysis of identified differentially expressed genes and genes that undergo differential variable splicing events, with GO enrichment analysis focusing on three aspects: molecular function (MF), biological process (BP), and cellular composition (CC).
We can identify differentially expressed genes and differential alternative splicing events between different stress conditions and analyze the biological functions of differentially expressed genes and differential splicing events.
Lifeasible is focused on providing a one-stop shop for bioinformatics analysis of variable splicing of plant pre-mRNA. We sincerely look forward to working with you, and if you have any questions, please contact us directly.
Lifeasible has established a one-stop service platform for plants. In addition to obtaining customized solutions for plant genetic engineering, customers can also conduct follow-up analysis and research on plants through our analysis platform. The analytical services we provide include but are not limited to the following:
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