Transcriptional and translational landscape fine-tune genome annotation and explores translation control in cotton

The unavailability of intergenic region annotation in whole genome sequencing and pan-genomics hinders efforts to enhance crop improvement.

Despite advances in research, the impact of post-transcriptional regulation on fiber development and translatome profiling at different stages of fiber growth in cotton (G. hirsutum) remains unexplored.

We utilized a combination of reference-guided de novo transcriptome assembly and ribosome profiling techniques to uncover the hidden mechanisms of translational control in eight distinct tissues of upland cotton.

Our study identified P-site distribution at three-nucleotide periodicity and dominant ribosome footprint at 27 nucleotides. Specifically, we have detected 1,589 small open reading frames (sORFs), including 1,376 upstream ORFs (uORFs) and 213 downstream ORFs (dORFs), as well as 552 long non-coding RNAs (lncRNAs) with potential coding functions, which fine-tune the annotation of the cotton genome. Further, we have identified novel genes and lncRNAs with strong translation efficiency (TE), while sORFs were found to affect mRNA transcription levels during fiber elongation. The reliability of these findings was confirmed by the high consistency in correlation and synergetic fold change between RNA-sequencing (RNA-seq) and Ribosome-sequencing (Ribo-seq) analyses. Additionally, integrated omics analysis of the normal fiber ZM24 and short fiber pag1 cotton mutant revealed several differentially expressed genes (DEGs), and fiber-specific expressed (high/low) genes associated with sORFs (uORFs and dORFs). These findings were further supported by the overexpression and knockdown of GhKCS6, a gene associated with sORFs in cotton, and demonstrated the potential regulation of the mechanism governing fiber elongation on both the transcriptional and post-transcriptional levels.

Reference-guided transcriptome assembly and the identification of novel transcripts fine-tune the annotation of the cotton genome and predicted the landscape of fiber development. Our approach provided a high-throughput method, based on multi-omics, for discovering unannotated ORFs, hidden translational control, and complex regulatory mechanisms in crop plants.