Question 1

What is RNA-seq and how does it differ from microarrays?

Accepted Answer

RNA-seq is a high-throughput sequencing technique that measures the sequence and quantity of all RNA expressed in a cell population, called the transcriptome. Unlike microarrays, which probe for known RNA sequences, RNA-seq can profile gene expression from organisms with unsequenced genomes and accurately measure a larger range of transcript expression levels, especially at very low or very high levels.

Question 2

Why is rRNA removed before RNA-seq library preparation?

Accepted Answer

Most RNA in cells is ribosomal RNA (rRNA), which is the central component of the cell's protein-production machinery. Removing rRNA facilitates recovery of other transcript types for accurate measurement. rRNA is typically removed by hybridizing the sample to complementary oligonucleotides attached to magnetic beads, then using a magnet to separate rRNA from the rest of the sample.

Question 3

How are RNA samples converted to DNA for sequencing?

Accepted Answer

Because RNA is inherently prone to degradation, it is first reverse transcribed to double-stranded DNA. Oligonucleotide sequences called adaptors are then ligated onto the DNA fragments. These adaptors contain constant regions that serve as primer-binding sites for PCR amplification and unique sequences called barcodes that identify fragments from each sample.

Question 4

What role do barcodes play in RNA-seq library preparation?

Accepted Answer

Barcodes are unique oligonucleotide sequences contained within adaptors that identify all DNA fragments originating from a single sample. This allows libraries from different samples to be mixed together and sequenced simultaneously. After sequencing, the barcodes enable researchers to sort and analyze reads by their source sample.

Question 5

How is RNA-seq data quality assessed during sequencing?

Accepted Answer

The quality of sequencing is indicated by the Q score, which reflects the likelihood of an incorrect base being identified. Q scores greater than 30 correspond to less than a 1 in 1,000 chance of an incorrect read. Additionally, reference DNA sequences added at low concentration serve as quality control, and their recovery at the expected rate indicates that all library sequences are evenly represented.

Question 6

What can RNA-seq reveal about gene expression differences between samples?

Accepted Answer

RNA-seq can identify genes that are differentially expressed under different conditions by comparing transcriptomes between samples. Researchers can count the number of reads per transcript to measure RNA abundance. Even for organisms without sequenced genomes, transcriptome information can be compared to other sequenced species to identify genes with increased or decreased expression levels.

Question 7

How is RNA-seq used to study RNA-protein interactions?

Accepted Answer

RNA-seq can be adapted to identify transcripts that a protein of interest binds to by immunoprecipitating the protein with antibodies and defining the bound RNAs through sequencing. When RNA-protein complexes are crosslinked at the beginning, sequencing analysis can map the crosslink site and identify the protein-binding site on the RNA down to the nucleotide level.

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