RNA sequencing

Use of DNA sequencing of RNA-derived material to characterize expressed products and their abundances. Tissue composition and developmental stage must be controlled when comparing gene expression across lineages.

Sequencing depth describes the amount of sequence observation obtained, but its exact convention depends on the assay. For a genome, nominal mean depth can be approximated by total sequenced bases divided by target length; in RNA sequencing, depth often means the number of reads generated. Larger depth improves sampling of rare material but does not fix systematic bias or substitute for biological replication. ^[ref]

Read coverage describes how sequencing reads overlap a target sequence. Per-base depth counts overlapping reads at each position, whereas breadth asks what fraction of target positions receives specified support. For example, high average depth can coexist with an uncovered exon if sampling is uneven. In RNA sequencing, coverage also reflects transcript abundance, processing and library preparation, so absence of reads is not automatically evidence that a genomic region is absent. ^[ref]

RNA-seq differential expression compares transcript abundance between conditions using RNA sequencing data. Counts require normalization and a model that accounts for biological variability as well as sampling. A transcript’s share of all reads can fall even when its absolute abundance is unchanged, if other transcripts increase. Replicate samples, composition effects and cell-type mixtures therefore matter when interpreting an apparent expression change. ^[ref]

Transcript assembly reconstructs transcript sequences or exon paths from RNA-derived reads. It can use a reference genome or infer sequences directly from overlaps. Alternative splicing creates shared segments, so a set of individually supported exons does not necessarily determine which full-length combinations occur. Long reads can connect distant exons, but transcript completeness and sequence errors still require evaluation. ^[ref]

Nanopore sequencing infers a nucleic-acid sequence from changes in electrical current as a strand passes through a nanometre-scale pore. The signal depends on several nearby bases rather than one perfectly isolated base at a time. It supports long reads and direct RNA measurement, but base calling and modification inference require calibrated models. Comparison of conditions can detect altered signal patterns without identifying every chemical modification uniquely. ^[ref]

A method for detecting differential RNA-modification signals using Gaussian mixture distributions of nanopore current, with condition-specific component proportions. A shifted signal requires biological interpretation as well as statistical separation.^[ref]

A nuclear run-on and capped-end mapping method for characterizing transcription initiation. It is useful for comparing nascent initiation with the surviving mature transcript molecular population.^[ref]

Cap analysis of gene expression: sequencing capped RNA ends to characterize start-site usage. Differential survival or capping of transcripts can alter the observed distribution without a matching change in nascent initiation.

Thiol-linked alkylation used with metabolic RNA labelling to identify newly synthesized RNA through characteristic sequencing changes after 4-thiouridine incorporation.^[ref]

Profiling RNA from individual isolated cell nucleus preparations. The preparation samples nuclear and often incompletely processed transcripts, so its intron counts are not interchangeable with mature cytoplasmic messenger RNA counts.

Sequencing designed to span long portions of individual RNA molecules or derived Complementary DNA. Linking distant exons on one molecule helps resolve complete transcript isoforms, while per-base errors and sampling depth still require control.