Significance of Transcriptomics
A transcriptome is the set of all RNA molecule including mRNA, r-RNA, t-RNA and other noncoding RNA like mi-RNA, si-RNA, piwi-RNA, sn-RNA, inc-RNA etc. that produced population of cells.
The transcriptome can be applied to the total no of set of transcripts in a given organisms, or to the particular subset of transcripts present in a particular cell type under particular conditions.The transcriptome can very in different parts of the body and may also differ with external environment conditions.
Introduction
Transcriptome is the whole set of RNAs transcribed by the genome from a specific cell type in a certain physiological condition. After the genome has been sequenced, transcriptome analysis allow us to understand the expression of genome at the transcription level, which provides information on gene structure , regulation of gene expression, gene product function and genome dynamics. Transcriptome analysis is the study of transcriptome of the complete set of RNA transcript that produced circumstances using high throughput methods. transcriptome analysis is most commonly used to compare a specific pair of samples.
It is used in areas of biomedical research like diagnosis of disease, discovery of bio marker and assessment of novel drugs. RNA sequencing is transforming the study of the transcriptome. A highly penetrating and accurate tool for determining expression across the transcriptome, it is providing scientists with perceptibility into previously undetected changes occurring in disease conditions in response to therapeutics, under different conditions present in environment, and through a wide range of other strategies.
RNA Sequencing allows researchers to detect both known and unique features in a single assay, allowing the identification of transcript isoforms, single nucleotide variants, gene fusions, and other features without the limitation of earlier knowledge.Regardless of the procedure selected, four phases, alignment and assembly, quantification, normalization, differential expression analysis, are generally required to determine the differentially expressed genes between two groups of samples.
Aim of Transcriptomics
- To catalogue all species of transcript including mRNA, noncoding RNAs and small RNAs
- To determine the transcriptional structure of genes in terms of their start sites 5’ and 3’ end.
- To measure the changing expression levels of each transcript during development and under different conditions.
There are two main transcriptomic techniques
- DNA microarray
- RNA sequencing
RNA-Sequencing
- RNA Sequencing transcriptomics replaces the hybridisation of nucleotides analyses with sequencing individual cDNAs produced from target RNA.
- It is a emerging method for these fully transcriptomic analysis have the potential to m overcome the limitation of microarray technology and there are on-going discussion about sequencing approaches RNA replaces microarray in middle or even in short term.
- From next generation sequencing generates hundreds of megabites tom gigabites of nucleotide sequence output in a single run depending on the platform.
Benefits of RNA Sequencing
- Covers an extremely broad dynamic range
- Provides sensitive and accurate measurement of gene expression
- Captures both known and unique new features and does not require predesigned probes.
- Generates both qualitative and quantitative data
- Discloses the full transcriptome
- Can be applied to any species if a reference sequence is not available
What are the applications of RNA sequencing?
- RNA sequencing helps to explore and discover the transcriptome and the total cellular content of RNAs including mRNA, r-RNA and t-RNA.
- RNA sequencing can tell us which genes are turned on in a cell, what their level of transcription is, and at what times they are activated or shut off.
- This allows scientists to understand the detail study of a cell in sincerely and assess changes that may indicate disease.
- Transcriptional profiling, single nucleotide polymorphism (SNP) identification comes under RNA sequencing analysis
- RNA editing and differential gene expression analysis
Steps in transcriptome or RNA seq analysis
- Number of replicates or experimental design
- Library preparation of RNA seq which convert mRNA into cDNA library
- Sequencing cDNA library
- Bioinformatics RNA seq data analysis
Workflow of Transcriptome analysis or RNA-Sequencing
RNA sequencing technique generates hundreds of millions of short RNA reads using next generation sequencing technology. These reads can be mapped with reference genome for investigates changes occur in gene expression but improved procedures for mining large RNA seq dataset for valuable biological knowledge which are needed.
NGS TECHNOLOGY
- ROCHE 454
- Illumine genome analyser sequencing
- Applied biosystem solid sequencing
Methods of RNA-Sequencing
- Library preparation- high quality of total RNA from biological sample
- cDNA library preparation
- Analysis phases
- Raw data qc
- Alignment
- Post alignment qc
- Differential expression determination
- Annotation
TOOLS USED IN Transcriptome Analysis
| Steps | Tool | Descriptions |
| Load The Data | ||
| Check The Quality Of Data | FASTQ | Quality checkup of raw sequence data |
| Remove Technical Sequences | Trimmomatic | rimmomatic performs a variety of useful trimming tasks for illumina paired-end and single ended data. |
| Remove Replication Of Abnormal Pcr | PCR Clean | Quality check up of trimmed data |
| Mapping/Alignment Of Genome | Bowtie2 , BWA | Mapping include low divergent sequence against a large reference genome which is mm10, BWA design for illumine seq up to for 100 bp. |
| Isoform Construction | Cufflinks/isolasso | Cufflinks assembles transcripts, estimates their abundances, and tests for differential expression and regulation in RNA-Seq samples |
| Update In To GTF File | Cuff merge | Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms |
| Combined Strategy For Mapping And Isoform Construction | Top Hat/Hisat | fast splice junction mapper for RNA-Seq reads. It aligns RNA-Seq reads to mammalian-sized genomes using the ultra high-throughput short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons. |
| Alignment Free Isoform Quantification | HT seq/Sailfish | alignment file in SAM or BAM format and feature file in GFF format and calculates the number of reads mapping to each featur |
| Mapping On Transcriptome | Bowtie 2 | ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences |
| Quantification By Expectation Maximization |
What can we learn from RNA sequencing?
Gene Functions
- We don’t know the sure function of many genes looking at when and where a gene is switched on or off can help us understand what it might be doing.
Genes Associated With Diseases
- By comparing the gene expression arrangements between healthy and diseased we can look for which genes are performing differently.
- These genes could be involved in the cause of the disease where further investigation can be helpful and opening the way to techniques such as gene editing.
Splicing
- Before mRNA is used as directives to make a protein, it can be cut into small sections and re-arranged in a process.
- RNA sequencing allow us to look at this in more detail and study the different form in which mRNA can be re-arranged.
Conclusion
RNA-seq has revolutionized the transcriptomics field and new computational tools continue to play a vital role in data analysis . Single-cell analysis and long-read RNA sequencing are two areas that are quickly evolving, with future developments expected to address limitations with low-abundance starting RNA and constructing long transcripts.
To Know More About Transcriptome Analysis you can join us for a 3 Hours Short Course on Genome Analysis you can register HERE
You understood about the analysis of RNA data called as Transcriptome Analysis, same way if we talk about DNA data analysis called as Whole Genome Sequencing you can read our brief article HERE