Large-scale translatome profiling annotates the functional genome and reveals the key role of genic 3′ untranslated regions in translatomic variation in plants

Abstract

The translatome, a profile of the translational status of genetic information within cells, provides a new perspective on gene expression. Although many plant genomes have been sequenced, comprehensive translatomic annotations are not available for plants due to a lack of efficient translatome profiling techniques. Here, we developed a new technique termed 3′ ribosome-profiling sequencing (3′Ribo-seq) for reliable, robust translatomic profiling. 3′Ribo-seq combines polysome profiling and 3′ selection with a barcoding and pooling strategy. Systematic translatome profiling of different tissues of Arabidopsis , rice, and maize using conventional ribosome profiling (Ribo-seq) and 3′Ribo-seq revealed many novel translational genomic loci, thereby complementing functional genome annotation in plants. Using the low-cost, efficient 3′Ribo-seq technique and genome-wide association mapping of translatome expression (eGWAS), we performed a population-level dissection of the translatomes of 159 diverse maize inbred lines and identified 1,777 translational expression quantitative trait loci (eQTLs). Notably, local eQTLs are significantly enriched in the 3′ untranslated regions of genes. Detailed eQTL analysis suggested that sequence variation around the polyadenylation (polyA) signal motif plays a key role in translatomic variation. Our study provides a comprehensive translatome annotation of plant functional genomes and introduces 3′Ribo-seq, which paves the way for deep translatomic analysis at the population level.

Variation in upstream open reading frames contributes to allelic diversity in protein abundance

“…Rare alleles in the promoter and 5' UTR were associated with more variable protein abundance, with rare alleles in the 5' UTR showing the strongest effect (Figure 1a,c, Supplemental Figure 2). This finding reinforces previous implication of the 5' UTR in post-transcriptional regulation (10, 12, 13, 16-18, 33, 34), and the lack of any significant effect from variants in the 3' UTR contrasts with recent work focused on the role of the 3' UTR in translational regulation in maize (35). The 5' UTR can contribute to post-transcriptional regulation of gene expression, and machine learning models have been successful at predicting protein abundance from sequence.…”

Genome-Wide Identification and Characterization of Small Peptides in Maize

“…In a previous study by authors, we sampled whole seedlings, roots, stems, and leaves of 14-day-old maize plants, as well as ears and tassels at the V12 stage with two replicates each and used these to perform RNA sequencing (RNA-seq), Ribo-seq, and MS analysis (MS only for leaf samples) ( Figures 1A,B and Supplementary Table 1 ) (Zhu et al, 2021 ). We obtained a total of 236 million RNA-seq reads to quantify transcript abundance.…”

“…The RNA-seq and Ribo-seq data of these plant samples were collected from study (Zhu et al 2021 ). A non-coding RNA data set including rRNA, tRNA, and snoRNA sequences were downloaded from the database Rfam ( http://rfam.xfam.org/ ).…”

“…The MS data of maize leaves sampled from the 14-day-old seedlings were collected from study (Zhu et al 2021 ).…”

A New Year's spotlight on two years of publication

“…Among the five original articles in this issue, two reported on the development of new CRISPR-based genome editing tools ( Grutzner et al., 2021 ; Sretenovic et al., 2021 ); the other three reported an anther culture-based system that enables highly efficient and genotype-independent creation of transgenic and gene-edited plants from commercial barley varieties ( Han et al., 2021 ), a high-throughput micro-computed tomography (micro-CT) imaging system integrated with deep learning for extracting and analyzing rice morphological traits ( Wu et al., 2021a ), and a nanopore-based single-molecule approach for characterizing plant polysaccharides ( Cai et al., 2021 ), respectively. Apart from those in the special issue, we also published several other methods and tools, including a technique for quantifying the total and individual abundance of root-colonizing microbes ( Guo et al., 2020 ), a 3′ ribosome-profiling sequencing (3′Ribo-Seq) method for translatome profiling and genome annotation ( Zhu et al., 2021 ), a novel genotyping approach based on high-resolution multiple-single nucleotide polymorphism (SNP) arrays that combines improved genotyping by target sequencing with liquid chip technology ( Guo et al., 2021 ), and a Split-HaloTag imaging assay for studying protein-protein interactions in planta ( Minner-Meinen et al., 2021 ).…”