Transcriptomic profiling of developing fiber in levant cotton (Gossypium herbaceum L.)

Genome-wide identification and expression analysis of terpene synthases in Gossypium species in response to gossypol biosynthesis

Cottonseed is an invaluable resource, providing protein, oil, and abundant minerals that significantly contribute to the well-being and nutritional needs of both humans and livestock. However, cottonseed also contains a toxic substance called gossypol, a secondary metabolite in Gossypium species that plays an important role in cotton plant development and self-protection. Herein, genome-wide analysis and characterization of the terpene synthase (TPS) gene family identified 304 TPS genes in Gossypium. Bioinformatics analysis revealed that the gene family was grouped into six subgroups TPS-a, TPS-b, TPS-c, TPS-e, TPS-f, and TPS-g. Whole-genome, segmental, and tandem duplication contributed to the evolution of TPS genes. According to the analysis of selection pressure, it was predicted that TPS genes experience predominantly negative selection, with positive selection occurring subsequently. RT-qPCR analysis in TM-1 and CRI-12 lines revealed GhTPS48 gene as the candidate gene for silencing experiments. To summarize, comprehensive genome-wide studies, RT-qPCR, and gene silencing experiments have collectively demonstrated the involvement of the TPS gene family in the biosynthesis of gossypol in cotton.

Transcriptional Landscape of Cotton Fiber Development and Its Alliance With Fiber-Associated Traits

Cotton fiber development is still an intriguing question to understand fiber commitment and development. At different fiber developmental stages, many genes change their expression pattern and have a pivotal role in fiber quality and yield. Recently, numerous studies have been conducted for transcriptional regulation of fiber, and raw data were deposited to the public repository for comprehensive integrative analysis. Here, we remapped > 380 cotton RNAseq data with uniform mapping strategies that span ∼400 fold coverage to the genome. We identified stage-specific features related to fiber cell commitment, initiation, elongation, and Secondary Cell Wall (SCW) synthesis and their putative cis-regulatory elements for the specific regulation in fiber development. We also mined Exclusively Expressed Transcripts (EETs) that were positively selected during cotton fiber evolution and domestication. Furthermore, the expression of EETs was validated in 100 cotton genotypes through the nCounter assay and correlated with different fiber-related traits. Thus, our data mining study reveals several important features related to cotton fiber development and improvement, which were consolidated in the "CottonExpress-omics" database.

Comparative transcriptome analysis of fiber and nonfiber tissues to identify the genes preferentially expressed in fiber development in Gossypium hirsutum

Cotton is an important natural fiber crop and economic crop worldwide. The quality of cotton fiber directly determines the quality of cotton textiles. Identifying cotton fiber development-related genes and exploring their biological functions will not only help to better understand the elongation and development mechanisms of cotton fibers but also provide a theoretical basis for the cultivation of new cotton varieties with excellent fiber quality. In this study, RNA sequencing technology was used to construct transcriptome databases for different nonfiber tissues (root, leaf, anther and stigma) and fiber developmental stages (7 days post-anthesis (DPA), 14 DPA, and 26 DPA) of upland cotton Coker 312. The sizes of the seven transcriptome databases constructed ranged from 4.43 to 5.20 Gb, corresponding to approximately twice the genome size of Gossypium hirsutum (2.5 Gb). Among the obtained clean reads, 83.32% to 88.22% could be compared to the upland cotton TM-1 reference genome. By analyzing the differential gene expression profiles of the transcriptome libraries of fiber and nonfiber tissues, we obtained 1205, 1135 and 937 genes with significantly upregulated expression at 7 DPA, 14 DPA and 26 DPA, respectively, and 124, 179 and 213 genes with significantly downregulated expression. Subsequently, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analyses were performed, which revealed that these genes were mainly involved in catalytic activity, carbohydrate metabolism, the cell membrane and organelles, signal transduction and other functions and metabolic pathways. Through gene annotation analysis, many transcription factors and genes related to fiber development were screened. Thirty-six genes were randomly selected from the significantly upregulated genes in fiber, and expression profile analysis was performed using qRT-PCR. The results were highly consistent with the gene expression profile analyzed by RNA-seq, and all of the genes were specifically or predominantly expressed in fiber. Therefore, our RNA sequencing-based comparative transcriptome analysis will lay a foundation for future research to provide new genetic resources for the genetic engineering of improved cotton fiber quality and for cultivating new transgenic cotton germplasms for fiber quality improvement.

Transcriptome analysis for molecular landscaping of genes controlling diterpene andrographolide biosynthesis in Andrographis paniculata (Burm . f.) Nees

Kalmegh [Andrographis paniculata (Burm. f.) Nees.] is one of the essential medicinal plants due to an important terpenoid, i.e. andrographolide possesses immense therapeutic and pharmacological uses. The experiment was performed to elucidate the expression of candidate genes associated with andrographolide biosynthesis. Based on results obtained in chromatography for andrographolide content analysis of six genotypes, two contrast genotypes, i.e. IC-520361 (maximum andrographolide content-2.33%) and Anand Local (lowest andrographolide content-1.01%) were selected for the transcriptome analysis. A total of 1.04 Gb of raw data were produced using MiSeq Illumina platform, in which IC 520361 generated 645 million base pairs sequence along with 4,524,251 raw reads and Anand Local produced 419 million base pairs sequence along with 3,021,316 raw reads. The combined assembly of high quality reads generated for both the samples had 33,247,454 bp of total assembled bases and 38,292 of transcripts. The GC percent of assembled transcripts was 44.79%, an average read length was 800 bp and N50 value was 1186 bp. Species-specific distribution using BLAST X (Nr), showed the highest Blast hits with Sesamum indicum. Out of 23,346 transcripts, 87% of transcripts annotated in UniProt KB (Universal Protein Resource KnowledgeBase) database and only 0.21% of transcripts were annotated in TAIR (The Arabidopsis Information Resources). Biological processes gene ontology classified based on Blast2GO showed, out of 6853 transcripts, 1370 of transcripts were represented by terpenoid biosynthetic pathway, which involved in secondary metabolite andrographolide biosynthesis. The heat map showed 1016 transcripts were differentially expressed between two kalmegh genotypes, in which nine important differentially expressed transcripts related to MEP (2C methyl-d-erythritol 4-phosphate) and MVA (Mevalonic acid) andrographolide biosynthesis pathways such as, geranyl diphosphate synthase small subunit, Isopentenyl-diphosphate delta-isomerase i-like, 4, 13-hydroxy-3-methylglutaryl-coenzyme a reductase etc. were upregulated in IC 520361 as compared to Anand Local, which were validated through RT-qPCR. The highest expression of gene 13-hydroxy-3-methylglutaryl-coenzyme a reductase (HMGR) was reported, which is responsible for accumulation of andrographolide in leaf. This comparative transcriptome analysis confirmed the expression level of genes were higher in accession IC 520361 as compare to Anand Local related to andrographolide biosynthesis pathways i.e. MEP and MVA. These up-regulated genes could be over-expressed to enhance the andrographolide content using genetic engineering of these metabolic pathways. It will also give an idea to the breeder for development of molecular markers for direct screening of the genotypes.

Tumorous Stem Development of Brassica Juncea: A Complex Regulatory Network of Stem Formation and Identification of Key Genes in Glucosinolate Biosynthesis

Stem mustard is a stem variety of mustard, an important Brassica vegetable. The formation and development of the tumorous stem, which is the key organ for the direct yield and quality, is a complex biological process involving morphogenesis, material accumulation and gene regulation. In this study, we demonstrated through anatomical studies that stem swelling is mainly dependent on the increase in the number of cells and the volume of parenchyma cells in the cortex and pith. To further understand transcript and metabolic changes during stem swelling, we obtained 27,901 differentially expressed genes, of which 671 were specifically detected using transcriptome sequencing technology in all four stages of stem swelling. Functional annotation identified enrichment for genes involved in photosynthesis, energy metabolism, cell growth, sulfur metabolism and glucosinolate biosynthesis. Glucosinolates are a group of nitrogen- and sulfur-containing secondary metabolites, which largely exist in the Cruciferous vegetables. HPLC analysis of the contents and components of glucosinolates in four different stem development stages revealed eight glucosinolates, namely, three aliphatic glucosinolates (sinigrin, glucoalyssin and gluconapin), four indole glucosinolates (4-hydroxyglucobrassicin, glucobrassicin, 4-methoxyglucobrassicin and neoglucobrassicin) and one aromatic glucosinolate (gluconasturtiin). All these types of glucosinolates showed a significant downward trend during the stem swelling period. The content of aliphatic glucosinolates was the highest, with sinigrin being the main component. In addition, qPCR was used to validate the expression of nine genes involved in glucosinolate biosynthesis. Most of these genes were down-regulated during stem swelling in qPCR, which is consistent with transcriptome data. These data provide a basic resource for further molecular and genetic research on Brassica juncea.

Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton

Cotton is an important natural fiber crop, however, its comprehensive and high-resolution gene map is lacking. 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. We devise a computational pipeline, named IGIA, to reconstruct accurate gene structures from the integrated data. 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. 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. The methods and findings provide valuable resources for further functional genomic studies such as understanding natural SNP variations for plant community.