RNA sequencing¶

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Final Project/Exam¶

  • Dates: December 2 and 4, 2025 (During class hours)
  • Duration: Approximately 10 mins
  • Topics: Homeworks

What is RNA¶

  • RNA: Ribonucleic acid
  • Single stranded molecule
  • Assembled as a chain of nucleotides
  • Each nucleotide contains: ribose sugar, phosphate group, base (Adenine, Cytosine, Guanine, Uracil) RNA_DNA.png

Library Preparation¶

  • RNA is harvested from the source material. This could be cells, tissue, etc.
  • RNA is fragmented into smaller pieces.
  • RNA fragments are reverse-transcribed to produce complementary DNA (cDNA) fragments, whose ends contain adapter sequences.

Amplification and Sequencing by Synthesis¶

  • cDNA library is loaded into a flow cell, where it is anchored by the adapters.

  • cDNA is amplified so that identical sequences are located in the same position on the flow cell

  • New DNA is synthesized with fluorescently labeled nucleotides−A, T, C, and G have a unique fluorescence signal.

  • The sequencing machine reads the fluorescence signal for each cluster at each cycle of synthesis.

Data processing¶

  • The sequence of fluorescence signals at each cluster is converted into an RNA sequence.The full sequence for each fragment is called a “read.”
  • Sequencing adapters are trimmed, the reads are filtered according to a set quality thresholds
  • The reads are mapped to a reference genome to determine which gene a fragment belongs to. (Alignment)
  • Gene expression is quantified by counting the number of reads per gene.

FASTA¶

fast_znf398_example.png

FASTA¶

  • Contains only the sequence information (nucleotide or amino acids)
  • Commonly used for reference genomes, gene libraries, or protein sequences
  • Use Biopython library to read fasta files
In [ ]:
from Bio import SeqIO

fasta_file = "znf398.fasta"

# Iterate over each record in the FASTA file
for record in SeqIO.parse(fasta_file, "fasta"):
    print("ID:", record.id)
    print("Sequence:", str(record.seq))
    print()

FASTQ¶

  • Used for raw sequencing data produced by next-generation sequencing platforms
  • Contains the sequence information and base-by-base quality scores for each read
  • Each record consists of four lines:
    • a header (starting with "@"),
    • the sequence,
    • a separator line ("+"),
    • and a quality score line

FASTQ¶

fastq_example.png

Phread quality score (Q)¶

  • Indicated (per base) by the quality score line
  • Phred Quality Score (Q): Represents the probability that a base was incorrectly identified by the sequencer
  • Q = -10$\mathbf{\log_{10}}$(P)

QUIZ¶

Two bases have a Q score of 20 and 50 respectively. Which one has better quality?¶

Phread+33 encoding¶

  • Phred+33 encoding: encodes quality scores by adding 33 to each Phred quality score and converting to an ASCII character
  • For example,
  • Phred score of 35 is encoded as the ASCII character “D” (68 = 35+33)
  • F = ASCII 70 → Q = 37 (very high quality, very low error probability)
  • : = ASCII 58 → Q = 25 (medium quality)
  • , = ASCII 44 → Q = 11 (low quality)
  • ! = ASCII 30 → Q = 0 (yikes!!)

FASTQC¶

  • Not a sequence file
  • Report generated by the fastqc command/software after it has analyzes the fastq file
  • Contains visual summaries, tables, and graphs for QC metrics (read quality, GC content, adapter contamination, etc.) fastqc1.png

FASTQC¶

  • Basic Statistics - Basic fastq file properties (number of reads, length, encoding).
  • Per base sequence quality - Quality score for each base position across all reads
  • Per tile sequence quality - Quality across different areas (tiles) of the sequencing flow cell
  • Per sequence quality scores - Distribution of overall quality for all reads
  • Per base sequence content - Nucleotide proportions (A/T/G/C) at each position in the read. [A fail often means strong bias at some positions. Could be due to primer/adaptor contamination, PCR artifacts, or poor library prep.]
  • Per sequence GC content - Distribution of GC percentages for all reads. [A pass if the %GC is in the expected range for the target organism/library.]
  • Per base N content - Proportion of ambiguous (‘N’) base calls per position. [A pass means few or no positions with high frequency of ‘N’s.]
  • Sequence Length Distribution - Distribution of read lengths
  • Percentage of duplicated reads detected - High duplication can happen, for example, when there is no low-input RNA or there are highly expressed genes. However, if duplication is moderate to high, it could suggest PCR bias, over-amplification, or technical repetition.
  • Overrepresented sequences - Percent of sequences representing the same motif/sequence far more than expected by chance. Captures possible contamination, strong PCR artifacts.
  • Adapter Content - Presence of known adapter sequences used in library prep. [A pass means the sequences are clean of adapter context]

FASTQC¶

fastqc3.png

FASTQC¶

fastqc4.png

QUIZ¶

  • Download the fastq file from here: 'https://download.cncb.ac.cn/gsa4/CRA024763/CRR1756889/CRR1756889_r1.fastq.gz'
  • Perform fastqc and look at the report.
  • Command: fastqc -o output-directory fastq-file
In [ ]: