![]() ![]() e Statistics of effect on RNA (pie chart) and the distribution of change of CDS length due to the use of an alternative TES. d Statistics of TES usage in genes with multiple TESs including distal- (DT), proximal- (PT) and coding-TESs (CT). c The nucleotide composition around the TES. b Cumulative curve of base resolution of the TES cluster signal from PolyA-seq. a Statistics of transcription end site (TES) per gene. Multiple transcription termination and alternative 3′UTR usage in G. The source data underlying Fig. 2b–d, 2f, and 2h are provided as a Source Data file The significance levels are indicated by asterisks (* p-value < 0.05 ** p-value < 0.01 *** p-value < 0.001), and the median values in box plots are shown. h The comparison of 15NO 3 − uptaking activity between NRT-L, NRT-S, and empty vector cell lines (two-tailed t-test, n = 3, error bar represents s.d.). The lost TM helix domains caused by alternative TSS is highlighted in red. g Predicted 3D protein structures for the long and short isoforms (top: side-view, bottom: top-view). f 5′ RACE validation of the change in the use of TSS. CAGE-seq and RNA-seq signals are shown in purple and gray, respectively. The sequence encoding the transmembrane (TM) helix domain is marked in blue. e Example of a gene with long (L) and short (S) isoforms due to alternative TSS usage (arrows). The occurrences of events and associated genes are shown. Potential functional RNA elements in alternative 5′UTR regions including RBP binding, U-rich, RG4, 2nd structure, and uORFs. d Statistics of 5′ end changes and the distribution of changes in CDS length caused by alternative TSS usage. c Statistics of TSS usage signal in genes with multiple TSSs including distal- (DT), proximal- (PT) and coding-TSS (CT). b High resolution of TSS identification from CAGE-seq. a Statistics of transcription start site (TSS) per gene. Multiple transcription initiation and alternative promoter usage in G. The source data underlying Fig. 1e are provided as a Source Data file ![]() i SNP distribution on composite gene body (top) and exon (bottom) of IGIA genes. The median lengths and significances of difference were marked (* p-value < 0.05 ** p-value < 0.01 *** p-value < 0.001). h Length distribution of the 5′UTR, CDS, 3′UTR, exon, and intron, from IGIA annotation for cotton compared with seven other species. g The number of unique splicing junctions only supported by ToFU, CGP, TACO, Cottongen, and IGIA. f The deviation between TSS (left, CAGE-seq) and TES (right, PolyA-seq) peaks compared with those assembled from IGIA and other methods. e Distribution of FPKM, gene length, and number of lowly expressed genes in subgroups of genes. d Venn diagram of gene annotations comparisons between CGP, Cottongen and IGIA. c Distribution of the number of isoforms per gene. b Schematic illustration of IGIA strategy for identifying accurate isoforms. a Experimental design and analysis workflow for Integrative Gene Isoform Annotation (IGIA). Integrative multi-strategic RNA-seq for the high-resolution RNA landscape in G. The methods and findings provide valuable resources for further functional genomic studies such as understanding natural SNP variations for plant community. These regulated events affect many genes in various aspects such as gain or loss of functional RNA motifs and protein domains, fine-tuning of DNA binding activity, and co-regulation for genes in the same complex or pathway. Our results reveal a dynamic and diverse transcriptional map in cotton: tissue-specific gene expression, alternative usage of TSSs and polyadenylation sites, hotspot of alternative splicing, and transcriptional read-through. We devise a computational pipeline, named IGIA, to reconstruct accurate gene structures from the integrated data. Here we integrate four complementary high-throughput techniques, including Pacbio long read Iso-seq, strand-specific RNA-seq, CAGE-seq, and PolyA-seq, to systematically explore the transcription landscape across 16 tissues or different organ types in Gossypium arboreum. Cotton is an important natural fiber crop, however, its comprehensive and high-resolution gene map is lacking. ![]()
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