RNA Seq: Principle and Workflow of RNA Sequencing
Summary
TLDRThis video delves into RNA-Seq, a next-generation sequencing technique that uncovers RNA presence and quantity in biological samples. It traces RNA-Seq's evolution from Sanger sequencing to Illumina's dominance and emerging third-generation technologies. RNA-Seq offers high-throughput, single-base resolution profiling, overcoming microarray and Sanger sequencing limitations. The video outlines the workflow, from RNA isolation to data generation, and touches on challenges like PCR bias. It also discusses the importance of quality assessment and the technology's ability to detect sequence variations and gene regulation.
Takeaways
- 🧬 **RNA-Seq Definition**: RNA sequencing (RNA-Seq) uses next-generation sequencing (NGS) to analyze the presence and quantity of RNA in a sample at a specific developmental stage or physiological condition.
- 📈 **Development of RNA-Seq**: RNA-Seq evolved from Sanger sequencing and microarrays to become dominant with the advent of NGS technologies like Illumina and Roche 454.
- 🔎 **Advantages of RNA-Seq**: RNA-Seq offers high-throughput RNA profiling at single base resolution with low background noise, surpassing microarrays and Sanger sequencing in sensitivity and specificity.
- 🧪 **Third-Generation Sequencing**: Third-generation sequencing technologies like Pacific Biosciences provide long-read sequencing, useful for identifying new transcripts and isoforms without fragmentation.
- 📉 **Challenges in RNA-Seq**: Challenges include short read biases and PCR amplification biases that can affect gene expression quantitation.
- 🧪 **Workflow of RNA-Seq**: The workflow involves converting RNA into cDNA fragments, attaching sequencing adapters, generating sequence data, and aligning reads to a reference genome or transcriptome.
- 🌟 **Types of Reads**: RNA-Seq classifies reads into exonic, junction, and poly-A reads to generate a base resolution expression profile.
- 🧪 **Sample Collection**: Total RNA is isolated and processed, often involving ribosomal RNA depletion to enrich non-ribosomal RNA species.
- 🔬 **Fragmentation**: RNA molecules are fragmented into smaller pieces for sequencing, with cDNA fragmentation providing information about the 3' ends and RNA fragmentation accessing the transcript body.
- 📊 **Bioinformatics Analysis**: The first step in RNA-Seq analysis is quality assessment, followed by read mapping or assembly, and gene expression level inference.
- 🔍 **Applications**: RNA-Seq is used to detect differential expression, SNPs, fusion genes, and post-transcriptional gene regulation.
Q & A
What is RNA-seq and what does it reveal about biological samples?
-RNA-seq, short for RNA sequencing, uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample at a specific developmental stage or physiological condition. It is a powerful tool for analyzing the dynamic cellular transcriptome, which is essential for interpreting the functional elements of the genome, revealing molecular constituents of cells and tissues, and understanding development and disease.
What technological advancements have influenced the development of RNA-seq?
-The development of RNA-seq has been influenced by several technological advancements, including Sanger sequencing technology, microarrays, and the advent of next-generation sequencing technologies. The first RNA-seq paper was published in 2006 using Roche 454 technology, and the technology matured with the advent of Illumina technology in 2008. Third-generation sequencing technologies, such as Pacific Biosciences' long-read sequencing, are also emerging in RNA-seq.
How does third-generation sequencing technology impact RNA-seq?
-Third-generation sequencing technology, such as Pacific Biosciences' long-read sequencing, allows for full-length transcript sequencing without the need for fragmentation. This is useful for identifying new transcripts and novel isoforms, alternative splicing sites, fusion gene expression, and allelic expression more accurately.
What are the advantages of RNA-seq over traditional microarray and Sanger sequencing?
-RNA-seq has several advantages over traditional microarray and Sanger sequencing, including high throughput RNA profiling at single base resolution, low background noise, the ability to map transcribed regions and gene expression simultaneously, and the capability to distinguish different isoforms and allelic expression. It also requires a lower amount of RNA and is less costly.
What are the challenges faced by RNA-seq?
-RNA-seq faces challenges such as short read biases and PCR biases. Short read lengths were a concern, but Illumina sequencing technology has increased read length and throughput. PCR amplification can impact the accuracy of gene expression quantitation, but amplification-free technologies and PCR-free methods for Illumina sequencing have been developed to address this.
What is the workflow of RNA-seq using high-throughput sequencing technology?
-The workflow of RNA-seq involves converting long RNAs into a library of cDNA fragments through RNA or DNA fragmentation, attaching sequencing adapters to each cDNA fragment, and generating sequence data from both ends in a high-throughput manner. The resulting sequence reads are aligned with the reference genome or transcriptome and classified into exonic, junction, and poly-A reads to generate a base resolution expression profile.
How is total RNA isolated for RNA-seq?
-Total RNA is usually isolated via organic extraction or silica membranes of spin columns. The total RNA sample is then processed either by direct selection of polyA RNA or by selective removal of ribosomal RNA, as ribosomal RNA is often not the research focus and can greatly reduce the coverage of useful transcripts.
Why is ribosomal RNA depletion preferred over polyA RNA selection?
-Ribosomal RNA depletion is preferred over polyA RNA selection because it enriches all non-ribosomal RNA species, including tRNA, ncRNA, non-polyA mRNA, and pre-processed RNA. This approach captures a broader range of RNA species compared to polyA RNA selection, which may miss some RNA transcripts that lack polyA tails.
How are larger RNA molecules prepared for deep sequencing technologies?
-Larger RNA molecules need to be fragmented into smaller pieces (200 to 500 nt) before deep sequencing technologies. cDNA fragmentation is biased towards the identification of sequences from the 3' ends of transcripts, while RNA fragmentation provides access to the precise identity of the transcript body.
What are the different platforms that dominate RNA-seq?
-RNA-seq is currently dominated by three different platforms: Illumina, Ion Torrent (Thermo Fisher Scientific), and Pacific Biosciences' SMRT. These platforms offer varying read lengths and technologies for sequencing.
How does RNA-seq enable the detection of differential expression and other genomic features?
-RNA-seq allows for the detection of differential expression across treatments or conditions by normalizing the differences between samples. It also enables the identification of SNPs, fusion genes, and post-transcriptional gene regulation, such as RNA editing, degradation, and translation.
Outlines
🔬 Introduction to RNA Sequencing (RNA-seq) and its Evolution
This paragraph introduces RNA sequencing (RNA-seq), explaining its role in using next-generation sequencing (NGS) to detect the presence and quantity of RNA in biological samples. RNA-seq helps analyze the dynamic transcriptome of cells, crucial for understanding gene functions, cell composition, and disease mechanisms. The paragraph also discusses the historical development of RNA-seq, starting from early transcriptomics methods like SAGE and microarrays, and how NGS surpassed microarrays. The first RNA-seq paper was published in 2006, with the technology becoming dominant by 2008, driven by advancements in Illumina technology and the promise of third-generation sequencing technologies like Pacific Biosciences for more comprehensive transcript identification.
🧬 RNA-seq’s Advantages and Challenges
Here, the technological advantages of RNA-seq over older methods like microarray and Sanger sequencing are discussed. RNA-seq offers high throughput, single-base resolution, low background noise, and cost efficiency. It enables accurate mapping of gene expression and identification of different isoforms and allelic expressions. However, challenges like short read lengths and PCR biases are mentioned, though improvements in sequencing technology, such as longer reads and amplification-free techniques, are mitigating these issues. Third-generation sequencing is highlighted for full-length transcript sequencing, further improving RNA-seq's accuracy.
📊 RNA-seq Workflow Overview
This section details the typical RNA-seq workflow, starting from the conversion of long RNAs into cDNA fragments. The cDNA fragments are then sequenced, and the sequence reads are aligned with reference genomes or transcriptomes. The paragraph outlines the different types of reads generated—exonic, junction, and poly(A)—which help create a base-resolution gene expression profile. The workflow includes RNA extraction methods like organic extraction or silica membranes and highlights the importance of isolating non-ribosomal RNA to improve coverage of relevant transcripts. Challenges with fragmentation and bias are also mentioned, alongside the benefits of using RNA fragmentation for more even coverage across transcripts.
🧪 Ribosomal RNA Depletion and Fragmentation Methods
This paragraph focuses on ribosomal RNA depletion, a key step in RNA-seq for enriching non-ribosomal RNA species like tRNA, non-coding RNA, and mRNA. It explains two popular depletion methods: hybridization with biotin-labeled anti-rRNA probes, followed by removal with magnetic beads, and selective degradation of rRNA by exonucleases. The paragraph also discusses the importance of fragmentation, which breaks down larger RNA molecules into smaller pieces for sequencing. Different methods of fragmentation provide varying biases, with RNA fragmentation covering more of the transcript body, while cDNA fragmentation focuses on transcript ends.
🧬 Preserving Strand-Specific Information and RNA-seq Platforms
This section explains how strand-specific information, crucial for understanding transcriptional direction, is often lost in classic NGS protocols. To counter this, methods such as pre-treating RNA samples with sodium bisulfite or directly ligating RNA adapters have been developed. The paragraph also reviews the major RNA-seq platforms, including Illumina, Ion Torrent, Roche 454, and Pacific Biosciences, comparing their read lengths. Longer reads are valuable for studying complex transcriptomes, revealing exon connectivity and sequence variations, which helps in understanding gene expression and regulation more comprehensively.
🖥️ Bioinformatics and Data Analysis in RNA-seq
This paragraph emphasizes the bioinformatics analysis required for RNA-seq. The first step involves quality assessment, where low-quality and adapter sequences are removed to ensure accurate results. Once the sequence reads are filtered and mapped to the reference genome, gene expression levels are inferred. The data can be used to generate a transcriptome map on a genome-wide scale, allowing the detection of differential gene expression across different treatments or conditions. Additional RNA-seq capabilities include identifying SNPs, fusion genes, and post-transcriptional gene regulation mechanisms like RNA editing and degradation.
Mindmap
Keywords
💡RNA-Seq
💡Next Generation Sequencing (NGS)
💡Transcriptome
💡Sanger Sequencing
💡Microarrays
💡Illumina Technology
💡Third Generation Sequencing
💡Isoforms
💡Allelic Expression
💡PolyA RNA
💡Ribosomal RNA Depletion
Highlights
RNA-Seq is a powerful tool to analyze the cellular transcriptome, essential for understanding development and disease.
Sanger sequencing and microarrays were early methods for transcriptomics, but have been surpassed by next-generation sequencing.
The first RNA-Seq paper using Roche 454 technology was published in 2006, marking the beginning of RNA-Seq dominance.
Illumina technology matured in 2008, further advancing RNA-Seq capabilities.
Third-generation sequencing technologies like Pacific Biosciences offer long-read sequencing, useful for identifying new transcripts and isoforms.
RNA-Seq provides high throughput RNA profiling at single base resolution with low background noise.
Compared to microarray and Sanger sequencing, RNA-Seq requires less RNA and is less costly.
Challenges for RNA-Seq include short read and PCR biases, which newer technologies are addressing.
Long paired and strand-specific reads are used for higher map ability and de novo assembly of transcriptomes.
The workflow of RNA-Seq involves converting long RNAs into cDNA fragments, attaching sequencing adapters, and generating sequence data.
RNA samples are processed by direct selection of polyA RNA or by selective removal of ribosomal RNA.
Ribosomal RNA depletion is preferred for enriching all non-ribosomal RNA species.
RNA fragmentation is crucial for sequencing larger RNA molecules into smaller pieces suitable for deep sequencing technologies.
Strand specificity can be maintained through various methods, including sodium bisulfite treatment and direct ligation of RNA adapters.
RNA-Seq platforms include Illumina, Ion Torrent, Roche 454, and Pacific Biosciences, each with different read lengths and capabilities.
RNA-Seq allows for the detection of differential expression across treatments or conditions.
Quality assessment is a critical first step in RNA-Seq bioinformatics analysis, ensuring accurate results.
RNA-Seq enables the identification of SNPs, fusion genes, and post-transcriptional gene regulation.
For more information on RNA-Seq services, visit the website www.cdgenomics.com.
Transcripts
welcome back to the cd genomics's next
generation sequencing video series the
topic here is the development and
workflow of rna sec
we will give you a detailed introduction
to rna sec including what rna sec is the
development of it and the workflow of it
rna sec the abbreviation of rna
sequencing utilizes next generation
sequencing ngs to reveal the presence
and quantity of rna in a biological
sample at a specific developmental stage
or physiological condition rna sec is a
powerful tool to analyze the
continuously changing cellular
transcriptome which is essential for
interpreting the functional elements of
the genome revealing the molecular
constituents of cells and tissues and
understanding development and disease
sanger sequencing technology was first
used for transcriptomics which enabled
methods such as sage serial analysis of
gene expression
sage was one of the first attempts to
quantify gene expression on a global
basis
almost simultaneously microarrays
utilizing complementary probe
hybridization quickly emerged and came
to dominate the field of transcriptomics
profiling for the next decade
the advent of next generation
technologies has enabled the sequencing
approach to surpass microarray approach
in 2006 the first rna sec paper was
published by utilizing roche 454
technology the era of rna sect dominance
began in 2008 with the maturity of
illuminate technology
despite the popularization of the ngs
technologies the application of third
generation sequencing in rna sec is on
its way
pacific biosciences long read sequencing
technology can easily cover complete
transcript without the need of
fragmentation which is useful to
identify new transcripts and new
entrants thereby accurately identifying
isoforms alternative splicing sites
fusion gene expression and allelic
expression
rna sec is often referred to as rna
profiling using the next or third
generation sequencing technologies
compared to traditional microarray and
sanger sequencing it has multiple
advantages in technology specifications
applications and practical issues rna
sec is a high throughput rna profiling
technology at single base resolution
with low background noise
it can be used to simultaneously map
transcribed regions and gene expression
as well as distinguish different
isoforms and allelic expression
compared to microarray and sanger
sequencing it requires a lower amount of
rna and cost less
however rna sec is faced with several
challenges such as short read and pcr
biases
short read used to be one concern
but illumina sequencing technology has
steadily increased read length and
throughput since its introduction in
2007.
long paired and strand specific reads
are commonly used for higher levels of
map ability and de novo assembly of
transcriptomes
furthermore the third generation
sequencing technology such as pacific
biosciences smart enables full-length
transcripts sequencing
another concern is the impact of pcr
amplification on the accuracy of gene
expression quantitation via rna sec
helicos and some of the third sequencer
use an amplification free technology
there are also pcr-free methods for
illumina sequencing
the workflow of rna sec by utilizing
high-throughput sequencing technology is
illustrated in the left figure
briefly long rnas are first converted
into a library of cdna fragments through
rna or dna fragmentation
sequencing adapters are then attached to
each cdna fragment and sequence data are
generated in a high throughput manner
from both ends the resulting sequence
reads are subsequently aligned with the
reference genome or transcriptome and
are classified into three types exonic
reads junction reads and polio and reads
a base resolution expression profile can
be generated by using these three types
of sequence reads
following sample collection total rna is
usually isolated via organic extraction
or silica membranes of spin columns
total rna sample is subsequently
processed either by direct selection of
polya rna or by selective removal of
ribosomal rna because the abundant
ribosomal rna is usually not the
research focus and greatly reduces the
coverage of the useful transcript
oligodt based mrna purification
procedure is widely used in eukaryotes
however some rna transcripts that lack
the polya tails are missed compared to
the polya rna selection ribosomal rna
depletion approach is preferred because
it enriches all non-ribosomal rna
species
including trna ncrna nonpolio mrna and
pre-processed rna
there are two popular ribosomal rna
depletion methods one is the
hybridization of ribosomal rna with
biotin labeled anti-ribosomal rna probes
followed by removal with streptavid and
counted magnetic beads
the other is the selective degradation
of ribosomal rna by a5 prime to three
prime exonuclease that specifically
recognizes ribosomal rna with a five
prime phosphate
fragmentation is subsequently conducted
to reach the desired length for
different ngs technologies some small
rnas such as micrornas pee-wee
interacting rnas and short interfering
rnas can be directly sequenced without
fragmentation
larger rna molecules need to be
fragmented into smaller pieces 200 to
500 nt
before deep sequencing technologies
cdna fragmentation is usually strongly
biased towards the identification of
sequences from the three prime ends of
transcripts while rna fragmentation has
little bias over the transcript but is
depleted for transcript ends
therefore cdna fragmentation provides
valuable information about the precise
identity of these ends and rna
fragmentation provides access to precise
identity of the transcript body
in the classic ngs protocols adapters
are ligated on to share double-stranded
dna fragments however a major drawback
of this approach is the loss of
information on transcriptional direction
the pre-treatment of the rna samples
with sodium bisulfate can convert the
citrine into uridine widespread c to t
transition thereby marks the coding
stand of each transcript
some other methods that maintain strand
specificity have been proposed such as
direct ligation of rna adapters to the
rna sample before reverse transcription
the rna sec is currently dominated by
three different platforms alumina ion
torrid roche 454 and pacific biosciences
smart
read lengths range from 200 to 600 bp
for illumina 400 bp for ion torrent 400
to 700 bp for four five four pyro
sequencing system and 15 to 20 kilobits
for pacific biosciences smart platforms
longer reads or paired and short reads
can reveal connectivity between multiple
exons rna sec is a powerful method to
study complex transcriptomes and reveal
sequence variations in the transcribed
regions
quality assessment is the first step for
the bioinformatics analysis of rna sec
which ensures a coherent final result by
removal of low-quality sequences
over-represented sequences and adapter
sequences once all reads have been
filtered and mapped or assembled gene
expression levels can thus be inferred
leading to a genome-scale transcriptome
map in terms of quality and quantity
rna sec also allows detecting
differential expression across
treatments of conditions
normalization has to be conducted to
adjust the differences between samples
such as library size and gene-specific
features
furthermore rna sec enables us to
identify snps fusion genes and
post-transcriptional gene regulation
such as rna editing degradation and
translation
in the end if you want more information
about accurate and reliable rna sex
service please visit our website www
cd
we are more than happy to be of
assistance
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