Analyzing the Translatome of Lymphatic and Venous Endothelial Cells In Vivo via Translating Ribosome Affinity Purification (TRAP)

Zebrafish are a powerful model for investigating vascular and lymphatic biology due to their genetic tractability and optical transparency. While translating ribosome affinity purification (TRAP) has been widely applied in other systems, its application in zebrafish has remained limited. Here, we present an optimized TRAP protocol for isolating ribosome-associated mRNAs from endothelial cells in vivo, without the need for cell dissociation or sorting. Using a novel transgenic zebrafish line, which expresses HA-tagged Rpl10a under the <i>mrc1a</i> promoter, we enriched actively translating endothelial transcripts. Differential expression analysis revealed robust upregulation of vascular and lymphatic genes including <i>flt4, kdrl</i>, and <i>lyve1b</i>. This approach captures the endothelial cell translatome with high specificity and offers a robust platform for investigating the molecular mechanisms of endothelial biology under genetic, environmental, or toxicological perturbations. Key features • Permits in vivo isolation of the endothelial ribosome without cell sorting. • Optimized TRAP protocol to analyze lymphatic and venous endothelial gene expression in zebrafish. • Utilizes a stable transgenic zebrafish line. • Compatible with real-time quantitative PCR (qPCR) and next-generation sequencing (RNA-seq).

Authors

Institutions

Publication Details

Journal
BIO-PROTOCOL
Published
2025-01-01
DOI
https://doi.org/10.21769/bioprotoc.5516
Primary Topic
Zebrafish Biomedical Research Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analyzing the Translatome of Lymphatic and Venous Endothelial Cells In Vivo via Translating Ribosome Affinity Purification (TRAP)

Olamide Olayinka, Hyun Min Jung, Leia Zarinebaf
BIO-PROTOCOL
Zebrafish Biomedical Research Applications
article

Analyzing the Translatome of Lymphatic and Venous Endothelial Cells In Vivo via Translating Ribosome Affinity Purification (TRAP)

Olamide Olayinka, Hyun Min Jung, Leia Zarinebaf
article en

Abstract

Zebrafish are a powerful model for investigating vascular and lymphatic biology due to their genetic tractability and optical transparency. While translating ribosome affinity purification (TRAP) has been widely applied in other systems, its application in zebrafish has remained limited. Here, we present an optimized TRAP protocol for isolating ribosome-associated mRNAs from endothelial cells in vivo, without the need for cell dissociation or sorting. Using a novel transgenic zebrafish line, which expresses HA-tagged Rpl10a under the <i>mrc1a</i> promoter, we enriched actively translating endothelial transcripts. Differential expression analysis revealed robust upregulation of vascular and lymphatic genes including <i>flt4, kdrl</i>, and <i>lyve1b</i>. This approach captures the endothelial cell translatome with high specificity and offers a robust platform for investigating the molecular mechanisms of endothelial biology under genetic, environmental, or toxicological perturbations. Key features • Permits in vivo isolation of the endothelial ribosome without cell sorting. • Optimized TRAP protocol to analyze lymphatic and venous endothelial gene expression in zebrafish. • Utilizes a stable transgenic zebrafish line. • Compatible with real-time quantitative PCR (qPCR) and next-generation sequencing (RNA-seq).

BIO-PROTOCOLVol. 15(1386)
University of Illinois Chicago (US)
Openalex Percentile: Top 67%
Zebrafish Biomedical Research Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.