Development of ultra-low-input nanoRibo-seq enables quantification of translational control, revealing broad uORF translation by subtype-specific neurons

Author:

Froberg John E.,Durak Omer,Macklis Jeffrey D.

Abstract

ABSTRACTWhile increasingly powerful approaches enable investigation of transcription using small samples of RNA, approaches to investigate translational regulation in small populations of specific cell types, and/or (sub)-cellular contexts are lacking. Comprehensive investigation of mRNAs actively translated into proteins from ultra-low input material would provide important insight into molecular machinery and mechanisms underlying many cellular, developmental, and disease processes in vivo. Such investigations are limited by the large input required for current state-of-the-art Ribo-seq. Here, we present an optimized, ultra-low input “nanoRibo-seq” approach using 102 – 103-fold less input material than standard approaches, demonstrated here in subtype-specific neurons. nanoRibo-seq requires as few as 2.5K neurons, and exhibits rigorous quality control features: 1) strong enrichment for CDS versus UTRs and non-CDS; 2) narrow, distinct length distributions over CDS; 3) ribosome P-sites predominantly in-frame to annotated CDS; and 4) sufficient ribosome-protected fragment (RPF) coverage across thousands of mRNAs. As proof-of-concept, we calculate translation efficiencies from paired Ribo-seq and alkaline fragmented control libraries from “callosal projection neurons” (CPN), revealing divergence between mRNA abundance and RPF abundance for hundreds of genes. Intriguingly, we identify substantial translation of upstream ORFs in the 5’ UTRs of genes involved in axon guidance and synapse assembly. nanoRibo-seq enables previously inaccessible investigation of translational regulation by small, specific cell populations in normal or perturbed contexts.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3