Home › Genetics / Genomics › RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
Genetics / Genomics JoVE (Open Access) Citable · DOI

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

DOI: 10.3791/59771-v
What you'll learn
  • ✓ Apply RNA-seq read alignment pipeline to detect expressed LINE-1 elements
  • ✓ Perform manual curation of LINE-1 loci from sequencing data
  • ✓ Calculate mappability-corrected transcription level scores for L1s
  • ✓ Identify full-length L1 retroelements in cancer cell lines
Protocol

Here, we present a bioinformatic approach and analyses to identify LINE-1 expression at the locus specific level.

Difficulty
advanced
Total time
~3–5 days (RNA extraction, library prep, sequencing, + bioinformatic analysis per sample)
Model organism
HEK293-derived DU145 (human prostate cancer cell line)
Biosafety
BSL-1

Steps

1
Execute read alignment pipeline for L1 identification

Apply bioinformatic alignment pipeline to RNA-seq data to map reads and identify expressed LINE-1 loci genome-wide. This establishes the foundation for locus-specific expression profiling.

▶ 00:52
2
Manually curate aligned L1 sequences and annotations

Review and validate automatically identified L1 loci through manual inspection to remove false positives and confirm biological accuracy of detected retroelements.

▶ 02:48
3
Calculate mappability correction scores per locus

Assess sequence mappability at each L1 locus and apply correction factors to normalize transcription level estimates and account for mapping ambiguity artifacts.

▶ 07:48
4
Identify full-length L1s in prostate cancer cells

Apply the complete pipeline to DU145 prostate tumor cell line data to demonstrate detection and characterization of functional full-length LINE-1 retroelements.

▶ 08:42
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