HC 4.2 Omics and Gene Expression: Transcript Level Analysis

Question 1

Transcription involves which omes?

Answer 1

genome and transcriptome

Question 2

Types of genes

Answer 2

-Protein coding
-Non coding

Question 3

Principal step of RNA seq is selecting RNA molecules. Which selections are possible?

Answer 3

-Size selection
-Type selection with Ribodepletion and poly(A)selection

Question 4

The details of the RNA seq analysis depend on …

Answer 4

the experimental context and RNA molecules measured

Question 5

Data analysis workflow for gene expression

Answer 5

-Selection
-Fragmentation and reverse transcription
-sequence and mapping
-quantitate

Question 6

Goals mRNAseq

Answer 6

Taking complexity and analyse isoforms of genes (transcripts) or working with non-model organism with poorly characterized genome

Question 7

4 options for mRNAseq analysis via transcriptome

Answer 7

1. De novo assembly of transcriptome
2. Well characterized genome: reference-based transcriptome assembly
3. Combined reference based and de novo assembly
4. model organism: download transcriptome from ENSEMBL or NCBI and use those for mapping

Question 8

Principle of assembly

Answer 8

Reconstructing long sequences from overlapping sequence fragments.

Question 9

Big challenge with de novo assembly

Answer 9

How to find the overlaps with millions of reads generated

Question 10

How are De Bruijn graphs made?

Answer 10

-Sequence reads to k-mers of length k (nucleotide sequence from the reads)
-Order k-mers based on the overlaps > graph with arrows (de Bruijn)

Question 11

Problem with de novo assembly and isoforms

Answer 11

Due to multiple k-mers with enough overlap for connecting to the previous one, multiple isoforms of assembled transcriptome are made, and the actual transcriptome is therefore not completely constructed.

Question 12

How are long assembled sequences called?

Answer 12

Contigs

Question 13

Purpose De Bruijn graph

Answer 13

Method to construct long sequences from short sequences

Question 14

What is the result of an assembly?

Answer 14

A contig

Question 15

Question with complexity of isoforms in gene expression quantitation

Answer 15

Is it a isoform or an assembly (next different piece

Question 16

Which regions should be searched for in contigs for more biological relevance?

Answer 16

ORFs

Question 17

How to identify ORFs (open reading frames) from contigs

Answer 17

-Identify ORF by searching start codons (methionine) and stop codons in each frame
-Longest potential ORFs could be candidates for a protein > more biological relevance

Question 18

Gene prediction models

Answer 18

-Abinitio: based on gene signals like intron splice site, TF binding site and codon structure
-Homology: significant matches query with known genes
-Probabilitistic: Markov models: translate AA sequence to probable location/function

Question 19

Methods for transcriptome functional annotation

Answer 19

1. searching for homologs based on sequence similarities and identifying assembled sequences
2. domain and other sequence feature identification (sequence feature annotation)
3. assigning standardized descriptions for sequence biological properties (GO terms)

Question 20

mRNAseq analysis 2. Reference-based transcriptome assembly

Answer 20

-Reads are first splice-aware mapped against reference genome
> connectivity or splice graph is constructed to represent all possible splicing events at a locus
> alternative paths through the graph are followed to join compatible reads together to isoforms
> biological reference

Question 21

mRNAseq analysis 3. Combined reference-based and de novo assembly

Answer 21

First: de novo assembly, then alignment
> are the contigs found on the reference genome
> scaffold contigs are mapped
> unassembled reads are mapped and the scaffold contigs which were mapped are extended
Or: First alignment and then assembly
> de novo assembly of unmapped reads
> Reference-based assemby of aligned reads

Question 22

mRNAseq analysis 4. Model organisms download transcriptome using ENSEMBL/NCBi for mapping

Answer 22

-Download fasta files online
-Alignment of reads to the transcripts to calculate expression levels

Question 23

After alignment of reads to downloaded transcriptome: the gene expression =

Answer 23

The isoform expression

Question 24

Disadvantage download of transcriptome

Answer 24

You cannot discover new transcripts
> no characterization, which is already done by the community

Question 25

Why is splice-aware mapping not needed when download based mapping?

Answer 25

The transcriptome is downloaded, which does not contain introns
> introns are removed from the isoforms

Question 26

Issues download based mapping

Answer 26

-Isoforms are often very similar, so many reads do not align uniquely
> try to calculate the right gene expression levels when there are reads which multi-map (mapping on two transcripts) > the problem should be taken into account
-Numbers of reads depend on transcript lengths
> longer transcripts generate more reads: bias
> Correction is needed

Question 27

Approaches for multi-mapping reads

Answer 27

-Ignore the reads: remove them from quantification
-Count once per alignment: count those reads for both alignments
-Split them equally: divide multi-mapping reads and split among the transcripts
-Rescue based on uniquely mapped reads
-and more; the essence; take multi-mapping reads into account

Question 28

Differential gene expression analysis

Answer 28

-Differences between control cells and treated cells
-Combine various approaches

Question 29

How can mRNAseq reads be used to characterize and quantify transcriptome?

Answer 29

Characterize 4 options:
-De novo assembly
-Reference-based assembly
-Combined reference-based and de novo assembly
-Model organism download
Quantification by mapping reads on the transcripts