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

doi:10.21203/rs.3.rs-4718000/v1

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

https://doi.org/10.21203/rs.3.rs-4718000/v1

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published 04 Sep, 2024

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The polyploid genome of cotton greatly increased the transcript complexity. Recent advances in full-length transcript sequencing are now widely used to characterize the complete landscape of transcriptional events. Such circumstances in cotton can help us explore the genetic mechanisms of the early seedling growth dynamics of cotton. This study, through long-read single-molecule sequencing, compared the transcriptomes of three yield-contrasting genotypes of upland cotton. Our analysis identified a diversity of spliced isoforms in each genotype, of which most were novel compared to previous cotton reference transcriptomes and had significant differences in the number of exon structures and coding sequence length due to intron retention. Quantification of isoform expression revealed significant expression differences in the root and leaf of each genotype. An array of core isoform target genes showed protein kinase or phosphorylation functions, and their protein interaction network contained most of the circadian oscillator proteins. Divergent spliced isoforms with differential regulation from the GIGANTEA (GI) are expected to regulate translational activities, including the sequence and function of target proteins. In addition, these spliced isoforms generate rhythmic expression profiles in cotton leaves, which may change the transcriptional regulatory network. Silencing of GI novel spliced isoforms Gh_A02G0645_N17 significantly impacts biomass traits in cotton and contributes to variability in growth and development. Our high-throughput hybrid sequencing results will be useful to dissect functional differences among spliced isoforms in the polyploid genome of cotton.

Spliced isoforms

Seedling growth

GIGANTEA

Circadian oscillator

Polyploid cotton

Transcriptome sequencing is an important platform to detect transcriptional events and provides knowledge on gene expression quantification, their architecture, function, and genetic variations (Hoang, et al. 2017). In agronomic crops, transcriptome analysis has extensively been performed to identify gene expression changes that enable us to understand functional aspects of growth and development (Nie, et al. 2015; Shahzad, et al. 2020; Zhang, et al. 2022). Until now, second generation sequencing technology platform with the advantages of high throughput, high accuracy, and low cost was largely adopted by researchers to acquire transcriptomic data for complex biological problems (Lan, et al. 2012; Levy and Myers 2016). However, sometimes short reads result in low quality transcript profiling, read gaps, and incorrect gene annotations (Goodwin, et al. 2016; Imelfort and Edwards 2009). In addition, the short read length complicates the efficient identification of post-transcriptional regulatory mechanisms retrieved from precursor mRNA. In plants, the functional significance of post-transcriptional events such as splicing isoforms, polyadenylation, and long non-coding RNA have not yet been fully understood (Aghamirzaie, et al. 2013; Chen, et al. 2017; Yadav, et al. 2024). Recent evidence shows that these events produce transcript complexity and synthesized proteins with diverse functions, which play an important role in molecular, cellular, biochemical, physiological, and developmental processes in plants (Baralle and Giudice 2017; Carvalho, et al. 2013; Seo, et al. 2013). In plants, splicing isoforms along with other post-transcriptional processes modify signal transduction (Hoang, et al. 2017), grain size (Ren, et al. 2021), circadian rhythms (Zhang, et al. 2021), flowering time (Marquardt, et al. 2014), light responses (Zhang, et al. 2017), and adaptation to various biotic and abiotic stresses (Mastrangelo, et al. 2012; Shang, et al. 2017). Previous transcriptional landscapes in plants have shown that almost 60–80% of multi-exon containing genes form splicing isoforms, which ultimately contribute to the functional variability of coding proteins (Chen, et al. 2019; Thatcher, et al. 2016; Zhu, et al. 2017). Although short read sequencing is powerful for analyzing gene expression profiles in various crop species, it is very difficult to accurately reconstruct, identify, and quantify the expression of splicing isoforms with second generation sequencing tools (Chen, et al. 2017; Jiang and Wong 2009). The better and more realiable discovery of isoforms has large significance, thereby most likely providing novel insights into transcriptional mechanisms that significantly contribute to growth and development.

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 (Xie, et al. 2022), sorghum (Abdel-Ghany, et al. 2016), wheat (Aury, et al. 2022) and cotton (Wang, et al. 2018) to provide global overview of full-length transcripts. These previous studies uncovered that the landscape of transcripts is still incomplete for crop species. Only error-free analysis of novel transcripts, alternative splicing modes, gene fusions, open reading frames, polyadenylation, long non-coding RNA, and differential isoform expression can open new avenues to discove genetic architecture of genotype to phenotype variations. However, the ambiguities of lower sequencing depth and higher error rates of PacBio sequencing demand integration with second-generation sequencing, which makes them more suitable to study perturb biological and physiological probelems (Liu, et al. 2022; Shen, et al. 2020). In addition, this hybrid sequencing methodology can efficiently identify the landsacpe of spliced isoforms from each gene, which can change the coding sequence and functions of target proteins. In recent years, comprehensive characterization of the full-length spliced isoforms has been performed to identify cell lines, tissues, and disease-specific transcripts in humans (Au, et al. 2013). These advancements strongly suggest that quantification of full-length spliced isoforms reveals transcriptomic differences at the isoform level, which can provide an excellent opportunity to explore the functional role of potentially important spliced isoforms. In upland cotton, the genome polyploidization increases even more complexity in transcriptional events. A comprehensive analysis of spliced isoforms will therefore expedite the functional genomics of favorable traits in upland cotton.

Cotton is an important cash crop. It contains almost 50 species, and upland cotton is the most important allotetraploid species in the cotton genus that is cultivated in significant areas, mainly for textile-based industrial drives (Shahzad, et al. 2022). In cotton, seedling vigor is positively associated with plant establishment, plant growth, and various devolomental stages. It is essential to stabilize crop yield and stress management under various stress adversities. However, the regulatory mechanism underlying seedling growth remains unclear. With progress in technology, reference genomes of various cotton species have been sequenced in recent years (Li, et al. 2015; Wang, et al. 2019; Zhang, et al. 2015). Researchers are extensively utilizing these reference genomes not only to invetigate the functional transcripts for yield (Shahzad, et al. 2020) fiber quality (Wang, et al. 2020) and oil traits (Song, et al. 2022) but also performing research to understand biotic and abiotic stress-responsive transcription events in various cotton species (Naqvi, et al. 2017; Zhu, et al. 2013). Numerous transcript sequenced data enable us to understand that homoeologous genes in polyploid cotton have significantly complex mechanisms of transcriptional and post-transcriptional regulation (Shahzad, et al. 2022; Wang, et al. 2018). At the same time, differential regulation of spliced isoforms driven by homoeologous genes can further disorder the regulatory network of functional proteins. These evidences strongly suggest functional differences in transcripts at the isoform level can serve as a driving force to fully understand the genetic control of favorable traits, especially in highly sequence similar subgenomes of upland cotton. In particular, identification of new spliced isoforms can play a role in exploring the functional mechanism of cotton seedling growth related traits. Here, we first performed a comprehensive analysis of full-length spliced isoforms of contrasting genotypes of upland cotton, characterized the diversity of full-length spliced isoforms in upland cotton, quantified the expression profiles of novel spliced isoforms with hybrid sequancing protocols, and identified important novel spliced isoforms that potentially play a role in vegetative and reproductive growth dynamics in cotton. Our study provides rich datasets of novel spliced isoforms, and their functional characterization will enable us to understand the functional mechanisms underlying cotton seedling growth.

Plant materials, RNA extraction, and library construction for Iso-Seq

This study was performed by using three yield-converting genotypes of cotton, including SJ48 (labeled as A), Z98 (B), and DT8 (D). The brief details of field trials and genotype performances for yield-contributing traits are presented in our study (Shahzad, et al. 2019). These plant materials were planted in the experimental lab at the Cotton Research Institute of the Chinese Academy of Agricultural Science, Anyang, China. When seedlings first true leaves were fully expended, the roots were scanned and analyzed with the WinRHIZO root analyzer system (WinRHIZO version 2007b, Regent Instruments Canada, Montreal, QC, Canada). The fresh and dry biomass for root, shoot, and total plant were determined with an electronic balance. For RNA extraction, root and leaf tissue of the same plant was harvested in three bioilogical replicates from these genotypes seedlings raised in standard Hoagland solution in the green house. The Sigma Spectrum Plant Total RNA Kit (Sigma-Aldrich, USA) was used to isolate high-quality total RNA, and genomic DNA contamination was removed and validated with gel electrophoresis in order to ensure the accuracy of sequencing data. In addition, RNA purity (OD 260/280), concentration, and nucleic acid absorption peak were tested with a Nanodrop 2000 spectrophotometer (NanoDrop Technologies Inc., USA). RNA integrity was confirmed with the Agilent 2100 Bioanalyzer (Agilent Technologies, USA). Equimolar ratios of the root and leaf purified poly-A (+) mRNA were pooled, and then 1µg RNA was used to synthesize full-length cDNA with the SMARTer PCR cDNA Synthesis Kit (Takara Biotechnology, China) and screened for size selection with the BluePippin™ system. Then, we performed PCR amplification, end repair, SMRT connector ligation, exonuclease digestion, and secondary screening with the BluePippin™ system to construct high quality SMRTbell sequence libraries for each cotton genotype. After Iso-seq libraries were prepared, quantified, and their insert sizes measured, the PacBio Sequel sequencing with RSII platform with P6-C4 reagent was used to perform Iso-Seq.

Bioinformatic pipeline for Iso-seq data analysis

The raw sequencing output data was filtered and processed with SMRT link platform standard protocols as previously described (Li, et al. 2021). In brief, subreads and reads of inserts were obtained with a minimum read length of 50, a predicted accuracy of 0.8, a readscore of 0.65, and a number of full passes of 1. After self-error correction, single-molecule multiple sequencing sequences were merged to form CCS reads, of which those contained a 5′ adapter, a 3′ adapter, and a poly (A) tail were classified as full-length and non-chimeric (FLNC) and non-full-length (FL) reads. Then, clustering for error correction was used to cluster the full-length sequences to obtain cluster consensus sequences, and finally, the resulting full-length sequences were polished using non-full-length sequences to obtain high-quality consensus sequences for subsequent analysis. Sequencing error of high-quality FL reads was corrected with previously pulished high coverage second-generation sequanced datasets of the same root and leaf samples of each cotton genotype. Alignment of FL reads to the reference genome of upland cotton (Zhang, et al. 2015) were performed with GMAP software (Zhang, et al. 2015). Functional annotations of mapped and unmapped transcript sequences were retrieved from NR, SwissProt, KEGG, KOG, GO, NT, and PFAM. The TAPIS pipeline was used to investigate structural variations in mapped transcripts. The deletion of redundant transcripts and the filtration of low-reliability transcripts were further performed, and only high-quality spliced isoforms were selected for subsequent analysis, which was supported by at least two FLNC reads or Illumina RNA-Seq data. Then, only high-quality isoforms were classified with reference annotations to discriminate between known genes and isoforms along with novel genes and isoforms. Novel isoforms were then grouped into novel in catalog (NIC) due to their non-full coverage and corresponding with novel isoforms from known genes, and novel not in catalog (NNC), which corresponded to novel isoforms from novel genes. Subsequently, various alternative splicing events, including exon skipping, intron retention, alternative first exons, mutually exclusive exons, alternative last exons, an alternative 3' splice site, and an alternative 5' splice site, were identified with ASprofile software (Foissac and Sammeth 2007).

Expression analysis, and identification of novel isofrms with differential regualtion

Transcript-level expression quantification algorithms are more difficult to implement than gene-level quantification. Similar to previous studies (Feng, et al. 2022; Li, et al. 2021), we applied short-read sequencing data to quantify the expression of each isoform identified in Iso-seq data analysis. The llumina RNA-seq data of the same root and leaf tissues of these genotypes was previously published (Shahzad, et al. 2020). HISAT2 (Kim, et al. 2015) was used to align the second-generation reads to the reference genome, and the mapping of each sample was counted. At the same time, all clean reads were mapped to FL transcripts obtained on the PacBio platform by applying Bowtie2 software (Langmead 2010) to acquire information about novel isoforms. When the sequencing depth and exon length were constant, the number of reads was directly proportional to the corresponding transcript expression level. Then, Cufflinks included Cuffdiff (Ghosh and Chan 2016) that was based on a maximum-expected algorithm for transcript quantification was utilized for expression quantification and to merge the FPKM values of novel isoforms. It was further used to estimate differential expression of isoforms and post-transcriptional regulation among different target groups. A false discovery rate (FDR) < 0.05 and log2fold change (FC) > 1 were standard values for a significant difference. The molecular, biological, and cellular functional categories of novel isoform target genes were obtained with BLAST2GO v2.3.5 (Conesa, et al. 2005). KOBAS v2.0 was applied to perform pathway enrichment analysis of novel isoform target gene (Xie, et al. 2011).

Prediction of the protein network, qRT-PCR analysis, and functional analysis of

The predicted protein-protein interaction network of isoform target genes was retrieved from the ccNET database of polyploid Gossypium (You, et al. 2017). Only core novel isoform target genes with significant positive and negative interacting proteins in root and leaf tissue were screened. Then, core novel isoforms identified for these target genes were also added for a comprehensive overview, and the final network was constructed with Cytoscape v. 3.7.1(Shannon, et al. 2003). For qRT-PCR validation of novel soforms, the PrimerScriptTM RT Reagent Kit for Perfect Real Time (RR037A, TaKaRa,Japan) was used to prepare cDNA from the roots and leaves of each cotton genotype. Novel isoform specific primers were designed with Oligo7 software (Table S1). The qRT-PCR reaction mixture was prepared with TransSart Top Green qPCR SuperMix (AQ131, TransGen Biotech, China), and data was obtained from the Mastercycler ep realplex instrument (Eppendorf, Germany). The brief details of the qRT-PCR reaction mixture and running protocol are present in our previous study (Wu, et al. 2017). The G. hirsutum Histone3 gene was used as an internal control to normalize expression levels. The relative expression level of each isoform was calculated with the 2^−ΔΔCt method (Livak and Schmittgen 2001), and the final expression was obtained from three biological replicates. The significant expression differences were determined with a two-way ANOVA and least significant difference (LSD) test, and the significant difference (P-value < 0.05) is presented with different superscript alphabatical letters. For the diurnal expression experiment, the cotton seeds were grown under 16-hour light and 8-hour dark conditions in the lab. The leaf samples were harvested every 6 hours to extract RNA and perform qRT-PCR. For the virus-induced gene silencing (VIGS) experiment, specific primers were designed with Oligo7 software (Table S1), a specific region of 300 bp from the coding sequence was cloned into the CLCrV binary vector with an in-fusion reaction, and the plasmid was transformed into GV3101. Inoculation of cotton seedlings was performed with a 1 mL medical syringe at the time when two cotyledons were fully expanded. All the plants were placed in the dark for the dark for 24 hours, followed by a normal growth period of no less than thirty plants. The relative expression, plant height, and biomass-related traits were measured after 40 days of inoculation of cotton seedlings. For 3D protein structure prediction, the amino acid sequence of reference protein GIGANTEA was obtained from the cotton functional genomics database. For novel isoforms, the tool ORFfinder (https://www.ncbi.nlm.nih.gov/orffinder/) was first used to search for open reading frames. The ORFs with the longest aminoacid length were then selected, and 3D protein structure was predicted and compared in SWISS-MODEL. The statistical significance (P-value < 0.0001) for the number of exon structures, total isoform length, and fold change ratio of novel isoforms was analyzed with one sample t test and a Wicoxon test for each genotype and novel isoform type. Isoform heatmaps and enrichment plots were made with SRplot (Tang, et al. 2023). In addition, some data visualization and graphing were performed with GraphPad Prism 8.

Contrasting genotypes of cotton, an overview of full-length sequencing, and a bioinformatics pipeline for FL transcript analysis

Three yield-contrasting cotton genotypes, including SJ48, Z98, and DT, were selected from prevoius field studies of various genotypes conducted at three main cotton belts in China for two years. The genotype SJ48 is from the Yellow River cotton belt of China, while both other genotypes are from the Yangze River. The genotype SJ48 displayed a higher cotton yield and stable performance across all environments. In contrast, both other genotypes had diverse performance across all environments. Specifically, Z98 showed the lowest yield than SJ48. Their analysis of the yield trajectory showed significant variation in yield and fiber quality traits among these genotypes (Shahzad, et al. 2019). Meanwhile, these geneotypes showed distinct root morpohlogical and biomass mass trait variability at the early seedling stage (Fig. 1). The root phenotype, length, surface area, diameter, and volume were significantly different among these genotypes (Fig. 1a-f). The variability in fresh and dry biomass showed significant differences (Fig. 1g-h). However, above ground traits such as shoot length and leaf size had significantly less variance among these genotypes (Fig. 1i). Variability in seedling growth stages will probably disrupt the substantial energy biomass resources for yield enhancement as well as to mitigate various stresses.Thus, their transcript profiling can enable us to understand the phenomenon of important economic traits. To construct SMRT bell libraries, the high-quality total mRNAs from the root and first true leaf were pooled equally for every cotton genotype. A total of 14.48G raw bases were generated for ARL (SJ48), which yielded 12751616 filtered subreads with a mean length of 1136 bp and an N50 of 2118 bp (Table S2). The 14.54G raw bases in BRL (Z98) yielded 15577536 filtered subreads with a mean length of 934 bp and an N50 of 2194 bp. Whereas 13.3G raw bases in DRL (DT8) yielded 6222044 filtered subreads with a mean length of 2137 bp and an N50 of 2591 bp (Table S2). The length distribution of subreads revealed DRL had a large difference in read length compared to ARL and BRL inbred parents (Fig. S1a–c). After subreads integration and error correction, a total of 623730 circular consensus sequences (CCSs) reads of ARL were divided into 452708 full-length (FL) and 373468 full-length non-chimeric (FLNC) reads (Table S3). In BRL, 615287 CCS reads were divided into 444750 FL reads and 354876 FLNC reads. The 560143 CCS reads of DRL were divided into 413090 FL and 397153 FLNC reads. The mean length of FLNC reads was almost similar in ARL and BRL but higher in DRL (Fig. S2a-c). Further clustering and polishing yielded 226272 high-quality FL consensus reads with a mean length of 2112 bp in AR, whereas high quality FL consensus reads were 211904 in BRL with a mean length of 2273 bp. In DRL, the number of high-quality FL consensus reads was 212885, with a mean length of 2696 bp (Table S4). The high-quality FL consensus reads had significantly improved length distribution, and all sequenced libraries showed similar trends as compared with filtered subreads (Fig. S1d–f). In addition, comparison with high-quality Illumina HiSeq transcripts further confirmed the accuracy of constructed FL transcripts (Table S5). The total reads mapped to the TM-1 reference genome were almost 82%, while the mean percentage of unmapped, multi-mapped, and uniquely mapped reads was approximately 17, 50, and 32, respectively, in this sequencing (Table S6).

Diversity of long-length isoforms in contrasting genotypes of cotton

We developed a brief bioinforamtic pipeline to identify full-length isoforms, and the FL transcript was compared with the cotton reference genome to identify novel genes and novel isoforms. In addition, the functional annotations of FL transcripts were retrieved from various databases to further strengthen the reference transcriptome. It was found that most of the mapped FL transcripts were aligned to nucleotide sequences (NT), followed by non-redundant protein sequences (NR), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) (Fig. S3a). In contrast, the majority of unmapped reads had annotations retrieved for the Protein Family (Pfam), Swiss-Prot, and NR (Fig. S3b). Our comparative analysis detected a diversity of isoforms in each cotton geneotype. The 13515 transcripts were from novel genes. In total, 88423 isoforms were identified in ARL, which were classified into three different groups. 15.7% were full-splice matches (FSM) matching completely to known genes. 72.3% were novel in the catalog due to non full coverage (NIC), which corresponds to novel isoforms from known genes, and 11.9% were novel not in the catalog (NNC), which corresponds to novel isoforms from novel genes (Fig. 2a). Whereas 13514 tanscripts of BRL were identified as novel genes, the total number of isoforms was 83927, the percentage of FSM isoforms was 15.1, the percentage of NIC isoforms was 73.4, and the percentage of NNC isoforms was 11.5 (Fig. 2b). In DRL, the number of identified novel genes was 13514. The total number of detected isoforms was 8,1513. Of which, 16%, 73.4%, and 10.7%, respectively, belong to the FSM, NIC, and NNC isoform groups (Fig. 2c). These higher landscapes of novel isoforms indicate the diversity of structural transcripts in each cotton geneotype. Our comparative analysis further determined 9.3% (n = 17736) overlapped isoforms among ARL, BRL, and DRL. However, 27.5% (n = 52307) isoforms were specifically detected in ARL, whereas 25.1% (n = 44666) isoforms were specific to BRL, and 23.4% (n = 47910) isoforms were specific to DRL (Fig. 2d). The identification of large number of specific isoforms reveals variability in these genotypes. These results not only enrich the knowledge about full-length transcriptomes but also suggest that exploring novel isoforms remains an unexploited biological research area in cotton, especially in the complex allotetraploid genome of upland cotton. Thus, we further characterized novel isoforms (NIC and NNC) in this study. Their subgenomic distribution has shown that novel isoforms were equally distributed across the At and Dt subgenomes of cotton (Fig. S4). Among different groups of novel isoforms, each of the At and Dt subgenomes of cotton generated approximately 45% NIC type isoforms. However, both subgenomes combined generated 9% of NNC type isoforms, and only 1% of novel isoforms belonged to different scaffolds (Fig. 2e). In addition, novel isoforms of these cotton genotypes were widely distributed across the 26 chromosomes of cotton. The chromosomes A05 and D05, followed by chromosome D11, had a significantly higher number of novel isoforms in ARL and BRL, while chromosome A04 had the lowest proportion of novel isoforms among the others (Fig. S5). Similar statistics were observed on these chromosomes for both NIC and NNC types of isoforms in ARL, BRL, and DRL (Fig. S6).

It was detected that almost the same proportion of NIC type isoforms was associated with the antisense and sense strands in each cotton genotype. In contrast, above 80% of NNC type isoforms were associated with the sense strand (Fig. 2f). The comparative analyses of the number of exons showed NIC contained significantly higher number of exons than NNC (median 7 vs 1) in each genotype. It was further observed that both types of novel isoforms possessed significantly different median exon structures in the root and leaf. Both BRL and DRL possessed a higher median exon structure than ARL (Fig. 2g). The meadian length per isoform is significantly different for three geneotypes and novel isoforms. The meadian length of NIC was 2228, 2464, and 2313, respectively, for ARL, BRL, and DRL, wherein the median length of NCC in ARL was 2200, 2474 in BRL, and 2289 in DRL (Fig. 2h). Our computational analyses found enrichment of novel isoforms with different exon structures and lengths for each cotton genotype. For instance, Gh_A12G0099 encodes phototropin-2 and is predicted to be involved in stomata opening and photomorphogenesis stimuli in leaves. It yields a different number of novel isoforms in all genotypes. Of which, seven were overlapped, 18 specific to ARL, 20 specific to BRL, and 10 specific to DRL (Fig. S7a). These variabilities in isoforms may have a relationship with the functional diversity of genes, which ultimately results in disruption of the growth pattern of cotton. Among transcript structural variables, alternative splicing is a key post-transcriptional regulatory mechanism, yields more than one splicing isoform through various splicing models (Fig. S7b), and ultimately increases protein diversity and functional domains. Within a geneotype, a total of 21348 AS events corresponding to 33966 novel isoforms were detected in ARL, which contained 7918 intron retention (IR), 5567 alternative 3 splice sites (A3), 3234 alternative 5 splice sites (A5), 2141 skipped exons (SE), 134 mutually exclusive exons (MX), and 1354 others (Fig. S7c). Whereas, a total of 21186 AS events were escalated from 35071 novel isoforms in BRL and consisted of 7851 IR, 5510 A3, 4273 A5, 2122 SE, 128 MX, and 1302 others (Fig. S7c). A total of 37176 AS events were associated with 37176 novel isoforms in BRL, consisting of 8185 IR, 5932 A3, 4573 A5, 2382 SE, 139 MX, and 1438 others (Fig. S7c). These higher alternations of splicing events probably act as an adoptable mechanism against changing evernionement in cotton.

Expression analysis based profiling of novel long-read isoforms

To quantify the expression of long-read isoforms as fragments per kilobase of exon model per million reads mapped (FPKM), we utilized previously pulished high coverage short-read RNA sequenced datasets of the same root and leaf samples, which enabled us to determine more accurate expression profiles in each cotton genotype. The analysis results showed long-read isoform derived expressions were quite different in root compared with leaf, and root had a different FPKM distribution than leaf in each cotton geneotype (Fig. 3a). Almost 86% of novel isoforms in the root and leaf had expression levels in the range of 0–15 FPKM (Fig. 3b). The comparative analysis showed nearly 10K novel isoforms had significant differential expression among ARvsBR and ARvsDR, while the comparison of ALvsBL and ALvsDL showed almost 15K novel isoforms with differntial expression (Fig. 3c). Among differential regulation, most of the isoforms exhibited higher regulation in the A root and leaf compared with the B and D roots and leaves. Within each sample, we identified that 85% of isoforms with differential regulation were NIC type and only 15% were NNCs (Fig. 3d). This indicates that differential regulation of NIC isoforms may contribute to differential growth and performance during adverse conditions, which results in different levels of seedling growth. It was detected that most NIC isoforms exhibited differential expression specific to root or leaf, whereas a smaller number of isoforms exhibited differential regulation in pairwise comparisons of both root and leaf (Fig. 3e). Only 593 shared isoforms with differetial expression were identified among the root and leaf of these contrasting genotypes. Further plotting indicated a significant fold change difference among the NIC and NNC types of isoforms. For NIC type, the median fold change differences were 0.7340 in ARvsBR, 0.7438 in ARvsDR, -0.5403 in ALvsBL, and 0.3467 in ALvsBL. In contrast, the median fold change differences for NCC type were 0.3075, -0.4084, -0.7214, and 0.3508, respectively, in ARvsBR, ARvsDR, ALvsBL, and ALvsBL (Fig. 3f). These findings further confirmed novel isoforms relatively had higher expression level differences in root, which indicates novel isoforms in root have more diversified expression profiles in cotton.

Comprehensive characterization of the novel isoforms among contrasting genotypes of cotton

Based on the above findings, we only selected core isoforms from NIC group for further study. Analyzed results showed a dynamic expression changes specific to the root or leaf. In root, expression based cluster analysis confirmed core isoforms (n = 2000) had distinct clusters in A, while both B and D were clustered together (Fig. 4a). The majority of these isoforms had higher expression levels in A, which may contribute to better root development and may drive various mechanisms related to growth and development. Our functional analysis of root core isoform target genes revealed their association with biological processes including protein phosphorylation, oxidation-reduction processes, and various metabolic processes (Fig. 4b). Some core isoform target genes had functions in cellular processes and were enriched for membrane-related processes. In the molecular functional class, the majority of core isoform target genes showed enrichment to ATP binding and varoius activities such as catalytic and transpoter. Moreover, pathway enrichment analysis identified that root core isoform annotated genes were enriched in metabolic, biosynthesis of secondary metabolites, biosynthesis of antibiotics, and carbon metabolism related pathways (Fig. 4c). The core isoforms from root had lower mean than leaf for total exon numbers and total sequanced length (Fig. 4d-e). The functioanl regulation patterns of these core isoforms may disrupt the performance of these pathways in the root, thereby, leading to modifications of biological and biochemical processes during the reproductive growth of cotton. Among core isoforms of leaf, expression based cluster analysis identified that the expression level of core isoforms is different in A than others, and most of these isofrms expression is relatively low in leaves of B and D (Fig. 4f). The core isoforms from leaf had higher mean than root for total exon numbers as well as total sequanced length (Fig. 4d-e). The major portion of genes associated with core isoforms of leaf were enriched for protein phosphorylation, along with protein phosphorylation related biological processes. In the cellular component group, these were enriched for nucleus and cytoplasm annotated functions. At molecular functions, the mojar group of isoforms encoding genes was enriched for ATP binding, catalytic activity, and protein kinese activity (Fig. 4b). In addition, it was identified that metabolic, biosynthesis of secondary metabolites, biosynthesis of antibiotics, and carbon metabolism related pathways can be altered with differential expressions of isoforms (Fig. 4c). Together, these findings show that the dynamic regulation of isoforms can imbalance several biological and molecular processes of target proteins the root and leaf, which are indespensible during early growth and developmental stage of cotton.

Identification of novel isoforms target protein networks in contrasting genotypes of cotton

The long-read isoforms enable us to understand the total diversity of transcript structural variables and, therefore, can provide novel insight into the physiological, biochemical, and molecular processes of target traits. In cotton, the identification of potentially important novel isoforms can address the gap in the genetic mechanism of yield traits. Our analysis identified 647 key novel isofrms that had differential regulation both in the root and leaf of yield cotrasting genotypes of cotton (Fig. 5a). Of which, we considered potential isoforms those that have a higher length (~ 1500 bp), have at least two exon structures, and must be annotated with one target gene. With this advancement, we identified 26 potentially important novel isoforms that had shown significant fold change differences in the range of -4 to 3 among the comaprsions of ARvsBR, ARvsDR, ALvsBL, and ALvsDL (Fig. S7). Novel isoforms Gh_A01G1792_N11 and Gh_A01G1792_N14 annoated with target protein enolase 2 had the highest expression level in B compared to A and D cotton geneotypes (Fig. 5b). Circadian pathway and light depend pathway enriched GIGANTEA (GI) encoding Gh_A02G0645_N17 and Gh_A02G0645_N39 isoforms were identified with lower expression in the roots and leaves of A, B, and D cotton geneotypes (Fig. 5b). In contrast, carbon metabolism pathway enriched D-glycerate 3-kinase annoated isoforms Gh_D05G1215_N12 and Gh_D05G1215_N25 showed higher regulation in A compared with B and D cotton geneotypes. Furthermore, Gh_A05G0536_N03 encodes myosin heavy chain-related, organic cation/carnitine transporter 7 and annotates Gh_D08G0875_N23, Gh_D08G0875_N36, selenium-binding protein 2 related Gh_A10G1144_N02, Gh_A10G1144_N03, and bifunctional nuclease 1 Gh_D02G0956_N01 and Gh_D02G0956_N06 were identified with higher expression levels both in the root and leaves of A as compared with B and D cotton geneotypes. Among others potentially important novel isoforms, calcium-transporting ATPase 12 is related. Gh_A08G0581_N06, Gh_A08G0581_N10, pirin-like protein related Gh_D10G1286_N01, Gh_D10G1286_N02, and CTP synthase related Gh_D12G0472_N08, Gh_D12G0472_N13 had significant differential variation in root and leaf of all these yield contrasting genotypes of cotton (Fig. 5b). The isoforms are compulsory for functional activity of traget proteins, and spliced isoforms cause proteome diversity, therefore, we assumed a protin-protein interaction (PPI) network of traget genes accompanying potentially important novel isoforms might help to understand the complexity of transcriptional events that can influence the molecular mechanisms underlying cotton seedling growth contributing traits. In particular, it was observed that novel isoform target genes displayed protein interaction with 691 other genes (Table S7), some of which had novel isoforms with differntial expression in the root or leaf of these contrasting genotypes of cotton. In this network, most genes showed function enrichment in the circadian rhythm plant, plant pathogen interaction, and signaling pathways. In particular, the predicted PPI network of Gh_A02G0645 was relatively higher (Fig. 5c), and it was proposed to have PPI with many circadian rhythm enriched genes, including the same GIGANTEA encoding related Gh_A09G0775, Gh_D02G0690, CCT motif containing response regulator protein annotated Gh_A03G0597, Gh_D11G2916, protein REVEILLE8s annotated Gh_A09G1504, Gh_D09G1515, and protein LHY annotated Gh_A11G0926, Gh_A12G1061, Gh_D11G1068, Gh_D12G1184. From these gene networks, our analysis identified novel isoforms Gh_D02G0690_N50, Gh_A11G0926_N23, together with Gh_D11G1068 related novel isoforms Gh_D11G1068_N03, Gh_D11G1068_N7, Gh_D11G1068_N20, and Gh_D11G1068_N54, which showed dynamic expression regulation either in roots or leaves of yield contrasting cotton genotypes (Fig. 5b). In agronomic crops, most recent studies confirm that circadian rhythm is an endogenous time keeping mechanism in crops that contributes to growth, photosynthetic, leaf senescence, photoperiodic flowering, biomass, heterosis, biotic and abiotic stress resistance, and other agronomic traits by regulating target gene transcription, protein activity, and biochemical metabolism (Steed, et al. 2021). Thus, the differential regulation of novel isoforms, especially those annotated with circadian oscillator target genes, may disrupt the PPI network, which in turn may modulate transcriptional regulation crucial for growth changes in cotton.

Functional analysis of Gh_A02G0645_N17 in contrasting genotypes of cotton

Three novel isoforms of Gh_A02G0645 were selected for validation with real-time qRT-PCR analysis. Their relative expression showed significant differences among roots and leaves of the A, B, and D geneotypes of cotton (Fig. 6a-c). Their expression trends were similar to those determined with long-read single-molecule RNA sequencing (Fig. 5b). The RT-PCR analysis quantified that three novel isoforms related to the GI had higher expression levels in leaves than roots (Fig. S9). Hence, we selected leaves and further validated the diurnal expression of three novel isoforms related to the GI (Fig. 6d-e). It was observed that all these isoforms showed significantly higher expression peaks around Zeitlupe (ZT) 12 hours in each genotype. Noteably, these isoforms respond significantly differently to day light in each cotton genotype (Fig. 6d-e). This result suggests rhythmic expression of GI related isoforms probely maintian light depend endogenous biological rhythms important for development of cotton. To determine the role of Gh_A02G0645 isoforms for cotton seedling, we conducted a VIGS experiment of Gh_A02G0645_N17 in SJ48 (A) and Z98 (B) genotypes of cotton. The relative expression levels of CLCrV:00 and CLCrV:Gh_A02G0645_N17 confirmed the silenced expression of Gh_A02G0645_N17 in both cotton geneotypes (Fig. 7a). Phenotypically, CLCrV:Gh_A02G0645_N17 plants showed improved growth as compared with the control plant in both cotton genotypes. In addition, the silenced expression of CLCrV:Gh_A02G0645_N17 significantly improved plant height, fresh and dry biomass in each cotton genotype (Fig. 7d-f). These results revealed that Gh_A02G0645 mediates seedling growth in cotton (Fig. 7b-d). Functions of isoforms depend on amino acid sequence structure, which explains how isoforms with a certain degree of sequence homology perform different functions. The varoius protein deep learning based approaches now can predict accurate 3D structures of proteins, thereby, we predicted the 3D structures of protein GI (Fig. S10a) and its three novel isoforms, Gh_A02G0645_N17 (Fig. S10b), Gh_A02G0645_N39 (Fig. S10c), and Gh_A02G0645_N42 (Fig. S10d), and compared the structural differences between novel isoforms and reference protein GI. These novel isoforms showed random or less structural similarities with the reference protein GI (Fig. S11). Gh_A02G0645_N17 amino acid showed very less consistancy score (Fig. S11a) than other isoforms (Fig. S11b-c) Hypothetically, structural differences are expected to generate functional diversity. However, these structure based predictions need experimental validation.

Iso-Seq increases the accuracy of isoform quantification in cotton

In agronomic crops, transcriptomic analysis is commonly performed at the gene level, short-length transcripts, as compared to full-length transcripts, have proved less efficient at identifying transcript structural variants such as isoforms, alternative splicing, polyadenylation, long non-coding RNAs, etc. Achieving a full molecular understanding of the transcriptomic landscape of traget traits thereby demands a comprehensive analysis of transcriptional and posttranscriptional changes. In this study, we have generated a genome-wide full-length transcriptome in yield contrasting genotypes of cotton by employing the PacBio platform and established Iso-seq protocol. In addition, identify considerable RNA isoform diversity in cotton. Of which, 85% were novel isoforms, and approximately 13,0000 novel genes were identified that were not present in existing genome annotations of cotton. A previous survey of the sorghum full length transcriptome analysis reported 11,000 novel spliced isoformsand 2,100 novel genes (Abdel-Ghany, et al. 2016) while full length transcriptome analyis identified 57% novel spliced isoformsin maize (Wang, et al. 2016). In addition, full-length transcriptome analysis of the complex hexaploid genome of common wheat discovered 9591 new transcripts and 3026 new genes (Dong, et al. 2015). These results enabled us to understand that full-length transcriptome analysis can be useful to refine previous gene models and have large implications for studying the structural genomics of economically important traits such as yield and fiber quality. However, comparative analysis of spliced isoformsin diploid species is not as difficult as in polyploid crop species, including upland cotton, wheat, and sugarcane (Osborn, et al. 2003; Wang, et al. 2018). In several crop species, the merging of two diverged genomes forms polyploids that result in diverse phenotypes, including more vigorous growth, fitness against various stresses, and elcological adaptation (Comai 2005; Wood, et al. 2009). At the same time, plant polyploids reflect dynamic changes in gene expression, gene regulatory interactions, gene structure, and epigenetic mechanisms in a tissue-specific manner (Jackson and Chen 2010) that results from a large number of identical homoeologous gene sets. At the transcriptional level, homoeologous genes are often transcribed alternatively to highly identical spliced isoformswith divergent structures, and spliced isoformsthat are expressed differentially at various levels can provide additional mechanisms for transcriptional regulation of favorite traits.

Upland cotton is allotetraploid and formed by the merger of two diploid species from the cotton A- and D-genome groups 1–2 million years ago (Cronn, et al. 2002; Senchina, et al. 2003). Hence, accurate identification of spliced isoformsin coexisting A and D subgenomes is still challenging with full-length transcript sequencing technology. A previous study in allopolyploid cotton reported that homoeologous genes produced divergent spliced isoformsin each subgeneome through various models of alternative splicing. Further, these spliced isoformsexhibit fiber and non-fiber-specific expression, which suggests fiber development is potentially regulated by the differential expression of fiber-specific genes and fiber-specific spliced isoforms(Wang, et al. 2018). Our targeted analysis identified many genotype specific novel spliced isoformswith different numbers of exon structures and lengths due to complex alternatively spliced transcriptional changes. In addition, these exibit differences in roots and leaves of contrasting genotypes. These findings reveal that the divergence of spliced isoformsmay have changed the transcriptional regulatory mechanism, providing evidence that isoform expression may be affecting the mechanism underlying cotton seedling growth. In plants, spliced isoformsshow unexpected levels of regulation in cell, tissue, and condition-specific ways (Kalsotra and Cooper 2011). Prevoius Iso-seq analysis in maize and sorghum identified tissue-specific spliced isoforms(Abdel-Ghany, et al. 2016; Wang, et al. 2018). Deep RNA sequencing uncovered numerous new transcripts that showed very low levels of expression in eight organs of cultivated rice (Zhang, et al. 2010). Among polyploids, full-length transcriptome research in hexaploid wheat reported many novel transcripts in devolping grain and described the full-length transcripts of highly similar homoeologous and paralogue members of gluten genes (Dong, et al. 2015). However, many previous studies in polyploid cotton characterized the expression dynamics of homoeologous gene sets, and few analyzed the abundance of spliced isoformsfor temporal changes or developmental stages. For instance, a comparative expression analysis of cotton duplicate genes revealed significant differences among the A and D subgenomes in seedling, vegetative, floral tissues, and developing fibers (Chaudhary, et al. 2009). Later studies also confirmed transcriptional bias and functional divergence of homoeologous gene sets of upland cotton in different tissues (Flagel, et al. 2008; Shahzad, et al. 2022) as well as response to abiotic stress (Liu and Adams 2007). These investigations in fact tell us the functional differences of homoeologous genes in polyploid cotton and should require further in-depth investigation. By considering the importance of these advances, we can predict that novel spliced isoformsidentified in root and leaf most likely contribute to the differential growth phenomenon of the cotton genotypes utilized in this study. Thereby, subfunctionalization of spliced isoformsfrom the same genes is indispensable to explore novel perspectives on target traits. However, the mechanism of the transcriptional network interlinked with ealry seedling growth is still far more complex at this stage in cotton, with more and more high throughputs. In-depth sequancing datasets can refine the isoform landscape from the same genes and identical genes of cotton species, and this will provide a complete picture of transcriptional or posttranscriptional events that are fundamental to the understanding of the biological regulation of seedling related traits in cotton.

Analysis of differential spliced isoforms reveals regulatory insights into the seedling growth dynamics of cotton

Seedling growth is associated with various devolomental variations in cotton. Successful seedling establishment provides significant advantages against insects, disease, and weeds. It minimizes the negative stress adversities of high temperature, drought, salinity, and cold. In this way, seedling-related traits play a key role in cotton yield and quality. Many genomics studies have analyzed gene loci for economic traits in cotton (Fang, et al. 2017; Ma, et al. 2018; Wang, et al. 2020). In the past few years, several candidate genes with functional roles have been confirmed for fiber yield in cotton (Wu, et al. 2023; Xie, et al. 2024; Zhang, et al. 2017). Owing to the complexity of the transcript components, the regulatory mechanism of cotton seedling growth is still not widely investigated by researchers compared with fiber yield traits. Cotton growth is influenced by genetic and epigenetic changes, and little attention has been paid to transcript structural genomics research. In particular, there is increasing interest in the accurate identification of full-length isorforms in recent years because spliced spliced isoformscan synthesize proteins with different functions. The updated reference genome sequences of cotton with single-molecule long-read sequencing provide a great platform for comprehensive analysis of complex transcriptional changes, including differential expression of isoforms. This helps us identify well-annotated transcript spliced isoformsat the whole genome level. In this way, we can systematically quantify the functions of transcripts, isoforms, and proteins. Several recent validation studies from humans with full-length cDNA sequences systematically characterized RNA isoform diversity for different developmental stages of various cells or diseases (Huang, et al. 2021; Leung, et al. 2021). In Arabidopsis, zinc-induced facilitator-like 1 generates two distinct slpiced isoforms, one of which modifies root auxin transport and the other localized plasma membrane during drought stress (Remy, et al. 2013). In hexaploid bread wheat, it is reported that the viviparous1 gene mediates seed devolment, and Vp-1 homologous splicing is proposed to correlate with preharvest grian sprouting (McKibbin, et al. 2002). These findings were in parallel with our previous knowledge that spliced spliced isoformsregulate transcription, translation, and the biological functionality of target proteins in eukertoes (Kornblihtt, et al. 2013; Nilsen and Graveley 2010). With the richness of Iso-seq data, our analysis determined that most differentially expressed spliced isoformsfrom yield contrasting genotypes are novel with diverse exon structures and lengths, and their target genes are enriched with various molecular, biological, and cellular functions. However, their differential regulation may drive phenological differences in roots and leaves in contrasting genotypes of cotton. Importantly, our integrated analysis revealed circadian oscilator GI annoated spliced isoformsare core, which are regualted at different levels in both cotton roots and leaves. Their traget genes have a complex predicted protein interaction network with many other genes from the circadian octilator, including four LHY, two PRR, and two RVE genes, of which four LHY protein related spliced isoformshave shown differential regulation in roots or leaves in this study.

It is now well evident that transcriptional or translational feedback loops of carcadian oscillators maintian endogenous time-keeping mechanisms that are interlinked with yield, quality, and adaptation related traits in crops (Steed, et al. 2021; Xu, et al. 2022). The carcadian oscillators consist of proteins that, through phosphorylation, turnover, expression, and chromatin remodeling, control clock output mechanism (Schöning and Staiger 2005). The core clockwork is composed of many transcripts, such as Circadian clock-associated 1 (CCA1), LHY, RVE, Night light-inducible and clock-regulated (LNK1), and PRR9/PRR. Evening-phased genes known as Timing of cab expression1 (TOC1), including PRR5, PRR3, PRR1, Zeitlupe (ZTL), GI, and Lux arrhythmo/phytoclock1 (LUX/PCL1), and Early flowerings (ELF) (Xu, et al. 2022). Of which, LHY forms the morning complex while GI forms the evening complex in plants, and they antagonistically regulate each other's expressions (Alabadí, et al. 2001). Their transcriptional and post-transcriptional regualtions, as well as their interactions with other, caused dynamic growth changes that ultimately impact many output pathways of final yield and other agricultural traits. Despite its essential role in clock functions, GI modulates several developmental processes, including photoperiodic flowering, carbohydrate metabolism, and adaptive processes during cold stress. The transcriptional regulation of GI with Constants (CO) and Flowering locus T (FT) and their interaction with other flowering time genes influence the flowering pathway (Sawa, et al. 2007). Previous knowledge of tissue-specific circadian clocks in plants revealed long-distance signaling among roots and shoot formed rhythmicity in the root (Takahashi, et al. 2015). Imbalanced mechanisms of GI with other core oscillators disrupt seasonal growth, flowering time, photosynthesis, carbohydrate, accumulation of chlorophyll and starch, light signaling, temperature sensitivity, and defense against biotic and biotic stresses (Creux and Harmer 2019; Steed, et al. 2021). In many previous cases, the transcriptional landscape of the plant circadian oscillator generated a rhythmic transcript isoform through various splicing events. Many of them include rhythmic introns or exons that contain spliced spliced isoforms(Hazen, et al. 2009). In plants, it has been reported that central circadian clock genes produce multiple spliced isoformsin response to diurnal conditions, thereby being expected to play a key role in circadian clock functional mechanisms (Filichkin and Mockler 2012). Many previous investigations have shown that an abundance of clock pathways enriched splicing isoforms probely disrupt the growth and development processes, including flowering time, the 24-hour growth cycle, and environmental adaptation (Staiger and Brown 2013; Swift, et al. 2022). Our results identified three novel spliced isoformsfor light dependent GI protein of circadian clock pathway, and these spliced isoformsshows significantly differntial expression in cotton. These significant had differential diurnal regualtion in cotton leaf. Furthermore, we confiremd that silencing of Gh_A02G0645_N17 significantly improved plant biomass related traits in cotton. The predicted 3D structures of novel spliced isoformsdisplayed higher structural disimilarities with the reference protein GI. Gh_A02G0645_N17 amino acid sequence had the lowest consistency score. All these results indicate GI protein related spliced isoformsplay an essential role in cotton growth dynamics, possibly via influencing length, amplitude of the clock pathway, and the transcriptional regulatory network of growth periods. Under various environmental clues, GI, LHY, CCA1, and PRR7 produced non productive spliced isoformsthat reduced functional mRNAs and, therefore, impacted protein levels (James, et al. 2012). These findings indicate that the circadian oscillator is indispensable to improving the performance of agronomic crops. This advanced knowledge and our results enabled us to support the hypothesis that spliced isoformsfrom the circadian oscillator most likely modulate the transcriptional network in the root and leaf of cotton, and their functional network is indispensable for cotton biomass growth. In brief, diurnal expression levels of splicing isoforms such as GI, together with other circadian oscillators, may curtail target protein expression in cotton roots and leaves, which is expected to disrupt physiological, biochemical, and biological output pathways related to seedling growth contributing traits of cotton. In addition, these splicing isoforms are expected to play a role under environmental stress conditions, providing a clue for the better performance of cotton plants in different environments. However, functional characterization of these isoforms that remain to be uncovered in our study is still an interesting research problem. Our results provide novel insights into the transcriptional network interlinked with seedling growth of cotton. Our Iso seq datasets will provide new research directions to explore the mechanisms underlying cotton seedling growth traits.

This study with hybrid sequancing technology reveals the abundance of novel spliced spliced isoforms in upland cotton. Comparative analysis identified spliced isoforms with differnetial regualtion in roots and leaves of yield contrasting genotypes of cotton. Intron retention events predominantly generate most novel spliced isoforms with structural diversity and expression levels. This is expected to result in complex post-transcriptional and post-translational regulation of target proteins. Our further characterization of core spliced isoforms shows most of the isoform-driven proteins are predicted to interact with many other circadian oscillator proteins. In particular, G1 generates novel spliced isoforms that are differentially expressed in the roots or leaves of cotton. The rhythmic regulation of the novel isoform Gh_A02G0645_N17 is expected to have profound effects on many physiological and phenological stages of cotton seedling growth and development. Notably, the transcriptional level of GI is compulsory for photoperiodic growth changes in plants, and its rhythmic oscillations in the light pathway will need to be unraveled in cotton. Although this study predicted a full-length isoform-based novel transcription network in cotton that may influence the complex dynamics of cotton seedling development, such integrated analysis will accelerate the functional genomic research of spliced spliced isoforms in upland cotton.

Author contributions

CZX and JYW designed the experiments. LPG, TXQ, HT, XQQ constructed plant population and field evaluation. KS, XXZ MZ, and JJF performed data analysis. KS, IM, JYW, and CZX preparated and improved the various drafts of this manuscript. All authors read and approved the final manuscript.

Acknowledgment

The authors appreciate the breeding team of our group for their anonymous work. Authors also thankful to the peer reviewers for their constructive suggestions which considerably improved this manuscript

Data availability statement

All Pacbio transcript-sequenced datasets used in this study will be available online after the review process. The short-read transcripts sequenced are freely available with accession number GSE144676 at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE144676. The summary of the data presented in this study is in supplemental files.

Funding information

National Key Research and Development Program of China (SQ2022YFD1200042), the Youth Program of the Natural Science Foundation of Henan Province (232300421269), and the Zhongyuan Academician Foundation (212101510001).

Ethics declarations

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests

Abdel-Ghany SE, Hamilton M, Jacobi JL, Ngam P, Devitt N, Schilkey F, Ben-Hur A, Reddy AS (2016) A survey of the sorghum transcriptome using single-molecule long reads. Nature communications 7:11706
Aghamirzaie D, Nabiyouni M, Fang Y, Klumas C, Heath LS, Grene R, Collakova E (2013) Changes in RNA Splicing in Developing Soybean (Glycine max) Embryos. Biology 2:1311-1337
Alabadí D, Oyama T, Yanovsky MJ, Harmon FG, Más P, Kay SA (2001) Reciprocal regulation between TOC1 and LHY/CCA1 within the Arabidopsis circadian clock. Science 293:880-883
Au KF, Sebastiano V, Afshar PT, Durruthy JD, Lee L, Williams BA, van Bakel H, Schadt EE, Reijo-Pera RA, Underwood JG, Wong WH (2013) Characterization of the human ESC transcriptome by hybrid sequencing. Proc Natl Acad Sci U S A 110:E4821-4830
Aury JM, Engelen S, Istace B, Monat C, Lasserre-Zuber P, Belser C, Cruaud C, Rimbert H, Leroy P, Arribat S, Dufau I, Bellec A, Grimbichler D, Papon N, Paux E, Ranoux M, Alberti A, Wincker P, Choulet F (2022) Long-read and chromosome-scale assembly of the hexaploid wheat genome achieves high resolution for research and breeding. GigaScience 11:
Baralle FE, Giudice J (2017) Alternative splicing as a regulator of development and tissue identity. Nature reviews Molecular cell biology 18:437-451
Carvalho RF, Feijão CV, Duque P (2013) On the physiological significance of alternative splicing events in higher plants. Protoplasma 250:639-650
Chaudhary B, Flagel L, Stupar RM, Udall JA, Verma N, Springer NM, Wendel JF (2009) Reciprocal silencing, transcriptional bias and functional divergence of homeologs in polyploid cotton (gossypium). Genetics 182:503-517
Chen G, Shi T, Shi L (2017) Characterizing and annotating the genome using RNA-seq data. Science China Life sciences 60:116-125
Chen MX, Zhu FY, Wang FZ, Ye NH, Gao B, Chen X, Zhao SS, Fan T, Cao YY, Liu TY, Su ZZ, Xie LJ, Hu QJ, Wu HJ, Xiao S, Zhang J, Liu YG (2019) Alternative splicing and translation play important roles in hypoxic germination in rice. Journal of experimental botany 70:817-833
Chen W, Jia Q, Song Y, Fu H, Wei G, Ni T (2017) Alternative Polyadenylation: Methods, Findings, and Impacts. Genomics, proteomics & bioinformatics 15:287-300
Comai L (2005) The advantages and disadvantages of being polyploid. Nature Reviews Genetics 6:836-846
Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M (2005) Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics (Oxford, England) 21:3674-3676
Creux N, Harmer S (2019) Circadian Rhythms in Plants. Cold Spring Harbor perspectives in biology 11:
Cronn RC, Small RL, Haselkorn TS, Wendel JFJAjob (2002) Rapid diversification of the cotton genus (Gossypium: Malvaceae) revealed by analysis of sixteen nuclear and chloroplast genes. 89 4:707-725
Dong L, Liu H, Zhang J, Yang S, Kong G, Chu JSC, Chen N, Wang D (2015) Single-molecule real-time transcript sequencing facilitates common wheat genome annotation and grain transcriptome research. BMC genomics 16:1039
Fang L, Wang Q, Hu Y, Jia Y, Chen J, Liu B, Zhang Z, Guan X, Chen S, Zhou B, Mei G, Sun J, Pan Z, He S, Xiao S, Shi W, Gong W, Liu J, Ma J, Cai C, Zhu X, Guo W, Du X, Zhang T (2017) Genomic analyses in cotton identify signatures of selection and loci associated with fiber quality and yield traits. Nature Genetics 49:1089-1098
Feng J, Li Y, Zhang J, Zhang M, Zhang X, Shahzad K, Guo L, Qi T, Tang H, Wang H, Qiao X, Lin Z, Xing C, Wu J (2022) Transcript Complexity and New Insights of Restorer Line in CMS-D8 Cotton Through Full-Length Transcriptomic Analysis. Frontiers in plant science 13:930131
Filichkin SA, Mockler TC (2012) Unproductive alternative splicing and nonsense mRNAs: a widespread phenomenon among plant circadian clock genes. Biology direct 7:20
Flagel L, Udall J, Nettleton D, Wendel J (2008) Duplicate gene expression in allopolyploid Gossypium reveals two temporally distinct phases of expression evolution. BMC biology 6:16
Foissac S, Sammeth M (2007) ASTALAVISTA: dynamic and flexible analysis of alternative splicing events in custom gene datasets. Nucleic acids research 35:W297-299
Ghosh S, Chan CK (2016) Analysis of RNA-Seq Data Using TopHat and Cufflinks. Methods in molecular biology (Clifton, NJ) 1374:339-361
Goodwin S, McPherson JD, McCombie WR (2016) Coming of age: ten years of next-generation sequencing technologies. Nature reviews Genetics 17:333-351
Hazen SP, Naef F, Quisel T, Gendron JM, Chen H, Ecker JR, Borevitz JO, Kay SA (2009) Exploring the transcriptional landscape of plant circadian rhythms using genome tiling arrays. Genome biology 10:R17. 10.1186/gb-2009-10-2-r17 10.1186/gb-2009-10-2-r17
Hoang XLT, Nhi DNH, Thu NBA, Thao NP, Tran LP (2017) Transcription Factors and Their Roles in Signal Transduction in Plants under Abiotic Stresses. Current genomics 18:483-497
Huang KK, Huang J, Wu JKL, Lee M, Tay ST, Kumar V, Ramnarayanan K, Padmanabhan N, Xu C, Tan ALK, Chan C, Kappei D, Göke J, Tan P (2021) Long-read transcriptome sequencing reveals abundant promoter diversity in distinct molecular subtypes of gastric cancer. Genome biology 22:44
Imelfort M, Edwards D (2009) De novo sequencing of plant genomes using second-generation technologies. Briefings in bioinformatics 10:609-618
Jackson S, Chen ZJ (2010) Genomic and expression plasticity of polyploidy. Current Opinion in Plant Biology 13:153-159
James AB, Syed NH, Bordage S, Marshall J, Nimmo GA, Jenkins GI, Herzyk P, Brown JWS, Nimmo HG (2012) Alternative splicing mediates responses of the Arabidopsis circadian clock to temperature changes. The Plant cell 24:961-981
Jiang H, Wong WH (2009) Statistical inferences for isoform expression in RNA-Seq. Bioinformatics (Oxford, England) 25:1026-1032
Kalsotra A, Cooper TA (2011) Functional consequences of developmentally regulated alternative splicing. Nature reviews Genetics 12:715-729
Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nature methods 12:357-360
Kornblihtt AR, Schor IE, Alló M, Dujardin G, Petrillo E, Muñoz MJ (2013) Alternative splicing: a pivotal step between eukaryotic transcription and translation. Nature reviews Molecular cell biology 14:153-165
Lan P, Li W, Schmidt W (2012) Complementary proteome and transcriptome profiling in phosphate-deficient Arabidopsis roots reveals multiple levels of gene regulation. Molecular & cellular proteomics : MCP 11:1156-1166
Langmead B (2010) Aligning short sequencing reads with Bowtie. Current protocols in bioinformatics Chapter 11:Unit 11.17
Leung SK, Jeffries AR, Castanho I, Jordan BT, Moore K, Davies JP, Dempster EL, Bray NJ, O'Neill P, Tseng E, Ahmed Z, Collier DA, Jeffery ED, Prabhakar S, Schalkwyk L, Jops C, Gandal MJ, Sheynkman GM, Hannon E, Mill J (2021) Full-length transcript sequencing of human and mouse cerebral cortex identifies widespread isoform diversity and alternative splicing. Cell reports 37:110022
Levy SE, Myers RM (2016) Advancements in Next-Generation Sequencing. Annual review of genomics and human genetics 17:95-115
Li F, Fan G, Lu C, Xiao G, Zou C, Kohel RJ, Ma Z, Shang H, Ma X, Wu J, Liang X, Huang G, Percy RG, Liu K, Yang W, Chen W, Du X, Shi C, Yuan Y, Ye W, Liu X, Zhang X, Liu W, Wei H, Wei S, Huang G, Zhang X, Zhu S, Zhang H, Sun F, Wang X, Liang J, Wang J, He Q, Huang L, Wang J, Cui J, Song G, Wang K, Xu X, Yu JZ, Zhu Y, Yu S (2015) Genome sequence of cultivated Upland cotton (Gossypium hirsutum TM-1) provides insights into genome evolution. Nature Biotechnology 33:524-530
Li T, Zhang X, Guo L, Qi T, Tang H, Wang H, Qiao X, Zhang M, Zhang B, Feng J, Zuo Z, Zhang Y, Xing C, Wu J (2021) Single-molecule real-time transcript sequencing of developing cotton anthers facilitates genome annotation and fertility restoration candidate gene discovery. Genomics 113:4245-4253
Liu L, Teng K, Fan X, Han C, Zhang H, Wu J, Chang Z (2022) Combination analysis of single-molecule long-read and Illumina sequencing provides insights into the anthocyanin accumulation mechanism in an ornamental grass, Pennisetum setaceum cv. Rubrum. Plant molecular biology 109:159-175
Liu Z, Adams KL (2007) Expression partitioning between genes duplicated by polyploidy under abiotic stress and during organ development. Curr Biol 17:1669-1674
Livak KJ, Schmittgen TD (2001) Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method. Methods 25:402-408
Ma Z, He S, Wang X, Sun J, Zhang Y, Zhang G, Wu L, Li Z, Liu Z, Sun G, Yan Y, Jia Y, Yang J, Pan Z, Gu Q, Li X, Sun Z, Dai P, Liu Z, Gong W, Wu J, Wang M, Liu H, Feng K, Ke H, Wang J, Lan H, Wang G, Peng J, Wang N, Wang L, Pang B, Peng Z, Li R, Tian S, Du X (2018) Resequencing a core collection of upland cotton identifies genomic variation and loci influencing fiber quality and yield. Nature Genetics 50:803-813
Marquardt S, Raitskin O, Wu Z, Liu F, Sun Q, Dean C (2014) Functional consequences of splicing of the antisense transcript COOLAIR on FLC transcription. Molecular cell 54:156-165
Mastrangelo AM, Marone D, Laidò G, De Leonardis AM, De Vita P (2012) Alternative splicing: enhancing ability to cope with stress via transcriptome plasticity. Plant science : an international journal of experimental plant biology 185-186:40-49
McKibbin RS, Wilkinson MD, Bailey PC, Flintham JE, Andrew LM, Lazzeri PA, Gale MD, Lenton JR, Holdsworth MJ (2002) Transcripts of Vp-1 homeologues are misspliced in modern wheat and ancestral species. Proc Natl Acad Sci U S A 99:10203-10208
Naqvi RZ, Zaidi SS-e-A, Akhtar KP, Strickler S, Woldemariam M, Mishra B, Mukhtar MS, Scheffler BE, Scheffler JA, Jander G, Mueller LA, Asif M, Mansoor S (2017) Transcriptomics reveals multiple resistance mechanisms against cotton leaf curl disease in a naturally immune cotton species, Gossypium arboreum. Scientific Reports 7:15880
Nie HS, Li SP, Shan XH, Wu Y, Su SZ, Liu HK, Han JY, Yuan YP (2015) Analysis of gene expression patterns and levels in maize hybrids and their parents. Genetics and molecular research : GMR 14:15399-15411
Nilsen TW, Graveley BR (2010) Expansion of the eukaryotic proteome by alternative splicing. Nature 463:457-463
Osborn TC, Pires JC, Birchler JA, Auger DL, Chen ZJ, Lee HS, Comai L, Madlung A, Doerge RW, Colot V, Martienssen RA (2003) Understanding mechanisms of novel gene expression in polyploids. Trends in genetics : TIG 19:141-147
Remy E, Cabrito TR, Baster P, Batista RA, Teixeira MC, Friml J, Sá-Correia I, Duque P (2013) A major facilitator superfamily transporter plays a dual role in polar auxin transport and drought stress tolerance in Arabidopsis. The Plant cell 25:901-926
Ren X, Zhi L, Liu L, Meng D, Su Q, Batool A, Ji J, Song L, Zhang N, Guo L, Liu X, Li J, Zhang W (2021) Alternative Splicing of TaGS3 Differentially Regulates Grain Weight and Size in Bread Wheat. International journal of molecular sciences 22:
Rhoads A, Au KF (2015) PacBio Sequencing and Its Applications. Genomics, proteomics & bioinformatics 13:278-289
Roberts RJ, Carneiro MO, Schatz MC (2013) The advantages of SMRT sequencing. Genome biology 14:405
Sawa M, Nusinow DA, Kay SA, Imaizumi T (2007) FKF1 and GIGANTEA complex formation is required for day-length measurement in Arabidopsis. Science 318:261-265
Schöning JC, Staiger D (2005) At the pulse of time: protein interactions determine the pace of circadian clocks. FEBS Letters 579:3246-3252
Senchina DS, Alvarez I, Cronn RC, Liu B, Rong J, Noyes RD, Paterson AH, Wing RA, Wilkins TA, Wendel JF (2003) Rate variation among nuclear genes and the age of polyploidy in Gossypium. Molecular biology and evolution 20:633-643
Seo PJ, Park MJ, Park CM (2013) Alternative splicing of transcription factors in plant responses to low temperature stress: mechanisms and functions. Planta 237:1415-1424
Shahzad K, Mubeen I, Zhang M, Zhang X, Wu J, Xing C (2022) Progress and perspective on cotton breeding in Pakistan. Journal of Cotton Research 5:29
Shahzad K, Qi T, Guo L, Tang H, Zhang X, Wang H, Qiao X, Zhang M, Zhang B, Feng J, Shahid Iqbal M, Wu J, Xing C (2019) Adaptability and Stability Comparisons of Inbred and Hybrid Cotton in Yield and Fiber Quality Traits. Agronomy 9:516
Shahzad K, Zhang X, Guo L, Qi T, Bao L, Zhang M, Zhang B, Wang H, Tang H, Qiao X, Feng J, Wu J, Xing C (2020) Comparative transcriptome analysis between inbred and hybrids reveals molecular insights into yield heterosis of upland cotton. BMC Plant Biology 20:239
Shahzad K, Zhang X, Guo L, Qi T, Tang H, Zhang M, Zhang B, Wang H, Qiao X, Feng J, Wu J, Xing C (2020) Comparative transcriptome analysis of inbred lines and contrasting hybrids reveals overdominance mediate early biomass vigor in hybrid cotton. BMC genomics 21:140
Shahzad K, Zhang X, Zhang M, Guo L, Qi T, Tang H, Wang H, Mubeen I, Qiao X, Peng R, Wu J, Xing C (2022) Homoeolog gene expression analysis reveals novel expression biases in upland hybrid cotton under intraspecific hybridization. Functional & Integrative Genomics 22:757-768
Shang X, Cao Y, Ma L (2017) Alternative Splicing in Plant Genes: A Means of Regulating the Environmental Fitness of Plants. International journal of molecular sciences 18:
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research 13:2498-2504
Shen C, Wei C, Li J, Zhang X, Wu Y (2020) Integrated single-molecule long-read sequencing and Illumina sequencing reveal the resistance mechanism of Psathyrostachys huashanica in response to barley yellow dwarf virus-GAV. Phytopathology Research 2:19
Song J, Pei W, Wang N, Ma J, Xin Y, Yang S, Wang W, Chen Q, Zhang J, Yu J, Wu M, Qu Y (2022) Transcriptome analysis and identification of genes associated with oil accumulation in upland cotton. 174:e13701
Staiger D, Brown JWS (2013) Alternative Splicing at the Intersection of Biological Timing, Development, and Stress Responses. The Plant cell 25:3640-3656
Steed G, Ramirez DC, Hannah MA, Webb AAR (2021) Chronoculture, harnessing the circadian clock to improve crop yield and sustainability. Science 372:
Swift J, Greenham K, Ecker JR, Coruzzi GM, Robertson McClung C (2022) The biology of time: dynamic responses of cell types to developmental, circadian and environmental cues. The Plant journal : for cell and molecular biology 109:764-778
Takahashi N, Hirata Y, Aihara K, Mas P (2015) A hierarchical multi-oscillator network orchestrates the Arabidopsis circadian system. Cell 163:148-159
Tang D, Chen M, Huang X, Zhang G, Zeng L, Zhang G, Wu S, Wang Y (2023) SRplot: A free online platform for data visualization and graphing. PLoS One 18:e0294236
Thatcher SR, Danilevskaya ON, Meng X, Beatty M, Zastrow-Hayes G, Harris C, Van Allen B, Habben J, Li B (2016) Genome-Wide Analysis of Alternative Splicing during Development and Drought Stress in Maize. Plant physiology 170:586-599
Wang B, Tseng E, Regulski M, Clark TA, Hon T, Jiao Y, Lu Z, Olson A, Stein JC, Ware D (2016) Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing. Nature communications 7:11708
Wang H, Zhang R, Shen C, Li X, Zhu D, Lin Z (2020) Transcriptome and QTL analyses reveal candidate genes for fiber quality in Upland cotton. The Crop Journal 8:98-106
Wang M, Tu L, Yuan D, Zhu D, Shen C, Li J, Liu F, Pei L, Wang P, Zhao G, Ye Z, Huang H, Yan F, Ma Y, Zhang L, Liu M, You J, Yang Y, Liu Z, Huang F, Li B, Qiu P, Zhang Q, Zhu L, Jin S, Yang X, Min L, Li G, Chen L-L, Zheng H, Lindsey K, Lin Z, Udall JA, Zhang X (2019) Reference genome sequences of two cultivated allotetraploid cottons, Gossypium hirsutum and Gossypium barbadense. Nature Genetics 51:224-229
Wang M, Wang P, Liang F, Ye Z, Li J, Shen C, Pei L, Wang F, Hu J, Tu L, Lindsey K, He D, Zhang X (2018) A global survey of alternative splicing in allopolyploid cotton: landscape, complexity and regulation. New Phytol 217:163-178
Wood TE, Takebayashi N, Barker MS, Mayrose I, Greenspoon PB, Rieseberg LH (2009) The frequency of polyploid speciation in vascular plants. Proc Natl Acad Sci U S A 106:13875-13879
Wu H, Fan L, Guo M, Liu L, Liu L, Hou L, Zheng L, Qanmber G, Lu L, Zhang J, Li F, Yang Z (2023) GhPRE1A promotes cotton fibre elongation by activating the DNA-binding bHLH factor GhPAS1. 21:896-898
Wu J, Zhang M, Zhang B, Zhang X, Guo L, Qi T, Wang H, Zhang J, Xing C (2017) Genome-wide comparative transcriptome analysis of CMS-D2 and its maintainer and restorer lines in upland cotton. BMC genomics 18:454
Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, Kong L, Gao G, Li CY, Wei L (2011) KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic acids research 39:W316-322
Xie D, Li J, Li W, Sun L, Dai Z, Zhou W, Su J, Sun J (2024) The NAC transcription factor LuNAC61 negatively regulates fiber development in flax (Linum usitatissimum L.). Journal of Integrative Agriculture 23:795-805
Xie J, Wang W, Yang T, Zhang Q, Zhang Z, Zhu X, Li N, Zhi L, Ma X, Zhang S, Liu Y, Wang X, Li F, Zhao Y, Jia X, Zhou J, Jiang N, Li G, Liu M, Liu S, Li L, Zeng A, Du M, Zhang Z, Li J, Zhang Z, Li Z, Zhang H (2022) Large-scale genomic and transcriptomic profiles of rice hybrids reveal a core mechanism underlying heterosis. Genome biology 23:264
Xu X, Yuan L, Yang X, Zhang X, Wang L, Xie Q (2022) Circadian clock in plants: Linking timing to fitness. Journal of integrative plant biology 64:792-811
Yadav A, Mathan J, Dubey AK, Singh A (2024) The Emerging Role of Non-Coding RNAs (ncRNAs) in Plant Growth, Development, and Stress Response Signaling. Non-coding RNA 10:
You Q, Xu W, Zhang K, Zhang L, Yi X, Yao D, Wang C, Zhang X, Zhao X, Provart NJ, Li F, Su Z (2017) ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium. Nucleic acids research 45:D1090-D1099
Zhang B, Liu G, Song J, Jia B, Yang S, Ma J, Liu J, Shahzad K, Wang W, Pei W, Wu M, Zhang J, Yu J (2022) Analysis of the MIR396 gene family and the role of MIR396b in regulating fiber length in cotton. Physiologia plantarum 174:e13801
Zhang G, Guo G, Hu X, Zhang Y, Li Q, Li R, Zhuang R, Lu Z, He Z, Fang X, Chen L, Tian W, Tao Y, Kristiansen K, Zhang X, Li S, Yang H, Wang J, Wang J (2010) Deep RNA sequencing at single base-pair resolution reveals high complexity of the rice transcriptome. Genome research 20:646-654
Zhang H, Lin C, Gu L (2017) Light Regulation of Alternative Pre-mRNA Splicing in Plants. Photochemistry and photobiology 93:159-165
Zhang M, Han LB, Wang WY, Wu SJ, Jiao GL, Su L, Xia GX, Wang HY (2017) Overexpression of GhFIM2 propels cotton fiber development by enhancing actin bundle formation. Journal of integrative plant biology 59:531-534
Zhang S, Liu H, Yuan L, Li X, Wang L, Xu X, Xie Q (2021) Recognition of CCA1 alternative protein isoforms during temperature acclimation. Plant cell reports 40:421-432
Zhang T, Hu Y, Jiang W, Fang L, Guan X, Chen J, Zhang J, Saski CA, Scheffler BE, Stelly DM, Hulse-Kemp AM, Wan Q, Liu B, Liu C, Wang S, Pan M, Wang Y, Wang D, Ye W, Chang L, Zhang W, Song Q, Kirkbride RC, Chen X, Dennis E, Llewellyn DJ, Peterson DG, Thaxton P, Jones DC, Wang Q, Xu X, Zhang H, Wu H, Zhou L, Mei G, Chen S, Tian Y, Xiang D, Li X, Ding J, Zuo Q, Tao L, Liu Y, Li J, Lin Y, Hui Y, Cao Z, Cai C, Zhu X, Jiang Z, Zhou B, Guo W, Li R, Chen ZJ (2015) Sequencing of allotetraploid cotton (Gossypium hirsutum L. acc. TM-1) provides a resource for fiber improvement. Nature Biotechnology 33:531-537
Zhu F-Y, Chen M-X, Ye N-H, Shi L, Ma K-L, Yang J-F, Cao Y-Y, Zhang Y, Yoshida T, Fernie AR, Fan G-Y, Wen B, Zhou R, Liu T-Y, Fan T, Gao B, Zhang D, Hao G-F, Xiao S, Liu Y-G, Zhang J (2017) Proteogenomic analysis reveals alternative splicing and translation as part of the abscisic acid response in Arabidopsis seedlings. 91:518-533
Zhu YN, Shi DQ, Ruan MB, Zhang LL, Meng ZH, Liu J, Yang WC (2013) Transcriptome analysis reveals crosstalk of responsive genes to multiple abiotic stresses in cotton (Gossypium hirsutum L.). PLoS One 8:e80218

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

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Journal Publication

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Abstract

Figures

Introduction

Materials and methods

Plant materials, RNA extraction, and library construction for Iso-Seq

Bioinformatic pipeline for Iso-seq data analysis

Expression analysis, and identification of novel isofrms with differential regualtion

Prediction of the protein network, qRT-PCR analysis, and functional analysis of

Results

Diversity of long-length isoforms in contrasting genotypes of cotton

Expression analysis based profiling of novel long-read isoforms

Comprehensive characterization of the novel isoforms among contrasting genotypes of cotton

Identification of novel isoforms target protein networks in contrasting genotypes of cotton

Discussion

Iso-Seq increases the accuracy of isoform quantification in cotton

Analysis of differential spliced isoforms reveals regulatory insights into the seedling growth dynamics of cotton

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1