L8 - Transcriptomics Flashcards
1
Q
What are the two main ‘omics techniques?
A
Transcriptomics (RNA-Seq) and Proteomics.
2
Q
What does RNA-Seq analyze?
A
RNA-Seq quantifies mRNA expression levels and identifies transcript variants.
3
Q
What is proteomics?
A
The study of proteins, including their identification and quantification, often using mass spectrometry.
4
Q
Why is RNA-Seq considered an ‘open system’?
A
It sequences RNA without predefined limits, allowing discovery of unknown genes and variants.
5
Q
What is a ‘closed system’ in transcriptomics?
A
Techniques like microarrays that only detect predefined genes.
6
Q
What are the three main steps of RNA-Seq?
A
RNA extraction and enrichment, sequencing, and data analysis.
7
Q
How is RNA converted into a form suitable for sequencing?
A
It is converted into complementary DNA (cDNA).
8
Q
What sequencing method is typically used in RNA-Seq?
A
Paired-end sequencing.
9
Q
What is a FASTQ file?
A
A file format containing sequence data and quality scores for each read.
10
Q
What computational challenges does RNA-Seq pose?
A
Large dataset handling, read mapping, and sequencing bias correction.
11
Q
What software tools assist in RNA-Seq analysis?
A
TopHat and Cufflinks.
12
Q
What virus was studied using RNA-Seq in Bristol?
A
Adenovirus.
13
Q
How did adenovirus affect human gene expression in RNA-Seq studies?
A
Viral transcripts dominated human gene expression over time.
14
Q
What is the advantage of using RNA-Seq in virology?
A
It can detect both viral and host responses simultaneously.
15
Q
What sequencing technology preceded RNA-Seq?
A
Microarrays.
16
Q
What is the key limitation of microarrays?
A
They can only detect known genes and do not identify novel transcripts.
17
Q
What are the basic steps in viral RNA-Seq experiments?
A
Infecting cells, extracting RNA, sequencing, and mapping reads.
18
Q
What was the main finding from adenovirus transcriptomics?
A
A rapid increase in viral mRNA dominance over human mRNA.
19
Q
How does RNA-Seq contribute to systems biology?
A
It provides a holistic view of gene expression interactions.
20
Q
What does proteomics help determine in infectious disease research?
A
Functional aspects of gene expression at the protein level.
21
Q
What is deep sequencing?
A
High-throughput sequencing providing detailed transcriptomic data.
22
Q
How does deep sequencing benefit virology?
A
It reveals viral genetic diversity and host interactions.
23
Q
What is the significance of FPKM in RNA-Seq?
A
It normalizes gene expression levels for comparison.
24
Q
How does nanopore sequencing differ from RNA-Seq?
A
It sequences RNA directly without converting to cDNA.
25
What major drawback does nanopore sequencing have?
Higher error rates, particularly insertions and deletions.
26
What breakthrough did nanopore sequencing achieve for adenovirus?
It revealed over 11,000 transcript variants.
27
How has RNA-Seq improved over microarrays?
It provides unbiased, quantitative, and variant-specific data.
28
What is CHiP-Seq used for?
Identifying DNA-protein interactions.
29
How does whole exome sequencing differ from whole genome sequencing?
It selectively sequences only coding regions.
30
What is the role of paired-end sequencing?
It sequences both ends of DNA fragments to improve accuracy.
31
What is the purpose of poly-A selection in RNA-Seq?
To enrich for messenger RNA.
32
Why is RNA fragmented in RNA-Seq?
To create manageable short reads for sequencing.
33
How do viruses benefit from alternative splicing?
It allows them to generate diverse protein products.
34
What is the main advantage of third-generation sequencing?
Long read lengths and direct RNA sequencing capability.
35
What device enables portable third-generation sequencing?
Nanopore sequencing via a USB-powered device.
36
What major pandemic virus was analyzed using nanopore sequencing?
SARS-CoV-2.
37
What is the main computational challenge in RNA-Seq analysis?
Reconstructing full transcripts from short reads.
38
How does sequencing help detect antiviral drug resistance?
By identifying genetic mutations associated with resistance.
39
Why is RNA-Seq useful for studying emerging viruses?
It allows unbiased detection of novel viral sequences.
40
What is de novo assembly in RNA-Seq?
Reconstructing transcripts without a reference genome.
41
What was a key finding of deep sequencing in HIV studies?
Detection of rare drug-resistant variants.
42
What type of cells were used in the adenovirus RNA-Seq study?
HeLa cells.
43
What time points were examined in the adenovirus RNA-Seq study?
0, 8, and 24 hours post-infection.
44
How many reads were generated per sample in the adenovirus study?
Around 30 million paired-end reads.
45
What proportion of reads were adenoviral at 24 hours post-infection?
About 80% of mapped reads.
46
What is the function of TopHat software?
It maps short reads to genomes, considering introns.
47
What does Cufflinks software do?
It quantifies gene expression levels from RNA-Seq data.
48
How has RNA-Seq revolutionized virology?
It provides a comprehensive view of viral and host transcriptomes.
49
What sequencing technology is often used for clinical virus detection?
Nanopore sequencing.
50
How can sequencing data inform proteomics?
By predicting protein expression from RNA levels.
51
Why is systems biology important in infectious disease research?
It integrates multiple data types to understand host-pathogen interactions.
52
How has the cost of sequencing changed over time?
It has drastically decreased, enabling broader use.
53
What is a key limitation of PCR-based viral genome studies?
It does not provide full transcriptome information.
54
How do sequencing technologies aid vaccine development?
By identifying viral genetic variation and immune targets.
55
What challenge does massive sequencing throughput present?
Large computational and storage demands.
56
What sequencing approach allows rapid identification of new pathogens?
Random deep sequencing of clinical samples.
57
What technology was crucial for SARS-CoV-2 surveillance?
Third-generation sequencing.
58
How does transcriptomics aid in understanding viral evolution?
By revealing mutation patterns and splicing diversity.
59
What type of sequencing does not require prior knowledge of the genome?
De novo sequencing.
60
How does RNA-Seq contribute to personalized medicine?
By profiling individual gene expression patterns.
61
What sequencing method can detect epigenetic modifications?
Nanopore sequencing.
62
What is the purpose of quality scores in FASTQ files?
To assess sequencing accuracy.
63
How do viruses manipulate host transcription?
By hijacking cellular machinery for their own gene expression.
64
What does 'omics integration' refer to?
Combining transcriptomics, proteomics, and other data.
65
What is the main advantage of high-throughput sequencing?
Rapid, large-scale genetic analysis.
66
What biological insight does RNA-Seq provide in infectious diseases?
Host and viral transcriptome interactions.
67
What is the function of mRNA splicing?
To generate different protein isoforms from the same gene.
68
Why are sequencing errors a concern in third-generation sequencing?
They can affect variant calling and transcript identification.
69
What virus family does adenovirus belong to?
Adenoviridae.
70
What is the primary function of the viral core proteins?
To package and protect the viral genome.
71
What method is used to analyze viral transcriptomes in great detail?
Nanopore sequencing.
72
How does sequencing contribute to epidemiology?
By tracking viral mutations and outbreaks.
73
What makes proteomics essential alongside transcriptomics?
RNA levels do not always correlate directly with protein abundance.
74
What does 'fragments per kilobase per million' (FPKM) measure?
Normalized gene expression in RNA-Seq.
75
What does 'deep sequencing' refer to?
Sequencing at high coverage for detailed analysis.
76
What is the role of bioinformatics in RNA-Seq?
To process, analyze, and interpret sequencing data.
77
What major challenge remains in omics research?
Integrating large datasets for meaningful insights.
78
What are the limitations of proteomics compared to transcriptomics in virus-infected cells?
Proteomics may miss transient or low-abundance proteins and cannot detect RNA-based regulatory events such as alternative splicing or RNA editing.
79
Why is it important to study viral proteomes as well as transcriptomes?
Because mRNA levels do not always correlate with protein abundance or activity; proteomics can reveal functional viral proteins critical to pathogenesis and immune evasion.
80
What is iTRAQ and how is it used in proteomics?
iTRAQ (Isobaric Tags for Relative and Absolute Quantitation) is a technique used to label peptides from different samples for simultaneous quantification via mass spectrometry.
81
Why might proteomics data not fully reflect changes seen in transcriptomics?
Post-transcriptional and post-translational modifications, as well as differences in mRNA stability and protein degradation, can lead to discrepancies.
82
What are some common post-translational modifications detected by proteomics?
Phosphorylation, glycosylation, ubiquitination, and acetylation.
83
What is the benefit of time-course experiments in omics studies?
They allow observation of dynamic changes in gene and protein expression over the course of infection, revealing early and late responses.
84
What is mass spectrometry's role in proteomics?
It identifies and quantifies proteins by measuring the mass-to-charge ratio of peptide fragments.
85
How do viral infections affect host cell proteomes?
They can upregulate or downregulate host proteins, degrade specific proteins, and hijack cellular pathways to favour viral replication.
86
Why is sample preparation critical in proteomics?
Poor preparation can lead to contamination, loss of low-abundance proteins, or incomplete digestion, all of which impair data quality.
87
What kind of data does shotgun proteomics generate?
It produces a complex mixture of peptide spectra that must be matched to protein databases for identification and quantification.
88
What does dynamic range mean in the context of proteomics?
It refers to the ability to detect proteins with vastly different abundances in a single experiment.
89
What are the main differences between open and closed transcriptomics systems?
Open systems (e.g., RNA-Seq) sequence data without prior assumptions, allowing discovery of unknown genes and isoforms. Closed systems (e.g., microarrays) only detect predefined sequences, limiting discovery.
90
Why do long RNAs generate more sequencing fragments in RNA-Seq?
Long RNAs yield more fragments because they span a greater length, increasing the chance of fragmentation and sequencing, which requires normalization (FPKM) to compare expression levels fairly.
91
What does a paired-end read mean in RNA-Seq?
A paired-end read refers to sequencing both ends of a cDNA fragment. It helps map the fragment more accurately and determine exon connectivity across spliced mRNA.
92
Why is RNA enrichment used instead of purification in RNA-Seq?
Messenger RNA is enriched (e.g., by poly-A selection) rather than purified because complete purification is biologically challenging due to secondary RNA associations and incomplete binding.
93
What are quality scores in FASTQ files and why are they important?
Quality scores represent the confidence of each base call during sequencing. They help assess data reliability, as errors like substitutions and indels may occur due to enzymatic limitations.
94
How does the variability in exon coverage occur in RNA-Seq data?
Exon coverage variability is caused by differences in reverse transcription efficiency, PCR amplification bias, and sequencing preferences, resulting in uneven read distribution across exons.
95
What is the purpose of de novo assembly in RNA-Seq?
De novo assembly reconstructs full-length transcripts from overlapping reads without using a reference genome, enabling study of unknown organisms or novel transcripts.
96
What are the advantages of nanopore sequencing over traditional RNA-Seq?
Nanopore sequencing can read full-length RNA directly, revealing exact exon-exon junctions and isoforms, and can detect post-transcriptional modifications. It also enables rapid, field-based sequencing.
97
What major discovery was made using nanopore sequencing on adenovirus?
Nanopore sequencing revealed over 11,000 distinct adenoviral transcripts, demonstrating that the virus generates transcript diversity through widespread alternative splicing.
98
How does adenovirus infection affect host mRNA expression over time?
Adenovirus mRNA rapidly dominates host expression: at 24 hours post-infection, ~80% of reads mapped to the adenoviral genome, suppressing host transcriptome.
