Transcript Complexity and New Insights of Restorer Line in CMS-D8 Cotton Through Full-Length Transcriptomic Analysis

Abstract

Hybrid utilization has proficiently increased crop production worldwide. The cytoplasmic male sterility (CMS) system has emerged as an efficient tool for commercial hybrid cotton seed production. The restorer line with dominant Rf2 gene can restore the fertility of the CMS-D8 sterile line. However, the molecular mechanism of fertility restoration remains unclear in CMS-D8 cotton that limits wider utilization of three-line hybrid breeding. In our study, the Pacific Biosciences (PacBio) Iso-Seq technology was applied to understand fertility restoration mechanism of CMS-D8 cotton. In total, 228,106 full-length non-chimeric transcriptome sequences were obtained from anthers of developing flowering buds. The analysis results identified 3,174 novel isoforms, 2,597 novel gene loci, 652 long non-coding RNAs predicted from novel isoforms, 7,234 alternative splicing events, 114 fusion transcripts, and 1,667 genes with alternative polyadenylation. Specially, two novel genes associated with restoration function, Ghir_D05.742.1 and m64033_190821_201011/21103726/ccs were identified and showed significant higher levels of expression in restorer line than sterile and maintainer lines. Our comparative full-length transcriptome analysis provides new insights into the molecular function of Rf2 fertility restorer gene. The results of this study offer a platform for fertility restoration candidate gene discovery in CMS-D8 cotton.

Comparative Transcriptome Profiling of CMS-D2 and CMS-D8 Systems Characterizes Fertility Restoration Genes Network in Upland Cotton

“…2.1. Differentially Expressed Genes (DEGs) Analysis in Both CMS-D2 and CMS-D8 Systems Our group previously characterized full-length anther transcripts in both CMS-D2 and CMS-D8 systems [40,41]. Here, a comprehensive analysis was performed to analyze the similarities and differences of DEGs among A, B, and R lines between the two cotton CMS systems.…”

“…Hamid et al [ 43 ] found that DYT1 and AMS were aberrantly expressed in pollen developmental pathways of CGMS in cotton through transcriptome analysis. Our previous studies have also characterized the full-length transcripts in the anthers of both CMS-D2 and CMS-D8 systems [ 40 , 41 ]. In addition, Gh_D05G3427 has been identified as a potential candidate restorer gene for CMS-D2 cotton by transcriptome analysis [ 27 ].…”

“…The Sigma Spectrum Plant Total RNA Kit (Sigma-Aldrich, Saint Louis, MO, USA) was used to extract high-quality total RNA for each sample following the manufacturer’s procedure. The brief details on RNA-Seq library construction, PacBio sequencing, and workflow of quality data analysis can be seen for CMS-D2 and CMS-D8 in our previously published research results [ 40 , 41 ].…”

Integrative analyses of long and short-read RNA sequencing reveal the spliced isoform regulatory network of seedling growth dynamics in upland cotton

“…Transcript-level expression quanti cation algorithms are more di cult to implement than gene-level quanti cation. Similar to previous studies (Feng, et al 2022;), we applied short-read sequencing data to quantify the expression of each isoform identi ed in Iso-seq data analysis. The llumina RNA-seq data of the same root and leaf tissues of these genotypes was previously published ).…”

“…With recent developments in long read sequencing protocols, single-molecule real-time (SMRT) isoform sequencing (Iso-Seq) using the PacBio platform has emerged as a powerful tool for the direct synthesis of long read transcripts up to > 15kb (Rhoads and Au 2015). Such circumstances enable accurate prediction of full transcripts, novel genes, isoforms, alternative splicing varients, long non-coding RNAs, polyadenylation, fusion transcripts, and gene annotations (Feng, et al 2022;Roberts, et al 2013). Since Iso-Seq not only enriches comprehensive analysis of isoforms but also improves the accuracy of novel genes, This sequential protocol has recently been widely utilized in maize (Wang, et al 2016), rice , sorghum (Abdel-Ghany, et al 2016), wheat (Aury, et al 2022) and cotton to provide global overview of full-length transcripts.…”