Case study: RNA-seq differential expression in Arabidopsis (PRJNA871280)

Worked example

RNA-seq differential expression, start to finish — no code

To show what Liragen Insights does, we ran a published plant-biology study through it end to end: an Arabidopsis investigation of age-related disease resistance and the auxin-signaling gene IAA26 (NCBI BioProject PRJNA871280, GEO GSE211670). Here is the whole workflow, from accession to interpreted results, in the browser.

The dataset

PRJNA871280 — IAA26 and age-related resistance

Accession

NCBI BioProject PRJNA871280 (GEO GSE211670)

Organism

Arabidopsis thaliana — thale cress

Focus

IAA26 (auxin signaling) & age-related disease resistance

Design

iaa26 knockout & IAA26-stabilised lines vs. wild-type (Shahdara)

Samples

9 bulk RNA-seq libraries across the genotypes

Source

University of Maryland · NCBI (2022)

Step 1 · Load

Start from the accession

Paste PRJNA871280 (or GSE211670) — or upload your own counts or FASTQ. Insights pulls the data and sample metadata and lays out the project, with no downloading or file wrangling.

Project summary for the loaded dataset in Liragen Insights — The project summary once the dataset is loaded.

Step 2 · Differential expression

One click runs DESeq2

Insights fits the genotype contrasts with DESeq2 — for example iaa26 knockout vs. wild-type — and returns an interactive Volcano plot: every gene by fold-change and significance, up- and down-regulated genes separating at a glance.

Volcano plot of differential expression — Volcano report — DESeq2 differential expression.

Step 3 · Explore

See the structure in your data

PCA separates the genotypes; linked heatmaps show the genes driving each contrast, clustered across all nine libraries. Click any gene to trace it through every report.

Gene expression heatmap across samples — A gene heatmap across the eight samples.

Step 4 · Interpret

Every report explains itself

Each report ships with an AI-written interpretation that names the top genes and recalculates the moment you change a threshold — turning a plot into a conclusion you can act on.

Volcano report with an AI-written interpretation — A Volcano report with its AI-written interpretation.

The result

The biology, surfaced automatically

The study centers on IAA26 — an auxin-signaling gene — and how it shapes disease resistance as the plant ages. Insights puts exactly this kind of signal front and center.

Genes behind the phenotype

Differential expression between the knockout, stabilised, and wild-type lines highlights the transcripts that move with IAA26.

Auxin & defense pathways

Because the study centers on auxin signaling and age-related resistance, the GO and KEGG reports surface hormone-response and plant-defense pathways.

Contrasts side by side

Multi-contrast reports (Venn and UpSet) show which genes are shared or unique across the genotype comparisons.

Reproducible

PRJNA871280 is public, so anyone can load it and reproduce the analysis in Insights — a shared reference for what the platform does.

Dataset: NCBI BioProject PRJNA871280 (GEO GSE211670), “IAA26: a key component in the regulation of age-related resistance in Arabidopsis” (University of Maryland, 2022). Figures above show Liragen Insights report types; the dataset is public and reproducible in the app.

Run this dataset yourself

Load PRJNA871280 — or your own RNA-seq — and get decision-ready reports in minutes. No code, no installs.

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