Similar Datasets
Project description:Annotation of the draft assembly of selaginella kraussiana Total RNA obtained from the leaf, rhizophore, seedling and stem.
2016-02-09 | E-GEOD-69388 | biostudies-arrayexpress
Project description:Background: For many years, increasing demands for fossil fuels have met with limited supply. As a potential substitute and renewable source of biofuel feedstock, microalgae have received significant attention. However, few of the current algal species produce high lipid yields to be commercially viable. To discover more high yielding strains, next-generation sequencing technology is used to elucidate lipid synthetic pathways and energy metabolism involved in lipid yield. When subjected to manipulation by genetic and metabolic engineering, enhancement of such pathways may further enhance lipid yield. Results: In this study, transcriptome profiling of a random insertional mutant with enhanced lipid production generated from a non-model marine microalga Dunaliella tertiolecta is presented. D9 mutant has a lipid yield that is 2-4 fold higher than that of wild type. Using novel Bag2D-workflow scripts developed and reported here, the non-redundant transcripts from de novo assembly were annotated based on the best hits in five model microalgae, namely Chlamydomonas reinhardtii, Coccomyxa subellipsoidea C-169, Ostreococcus lucimarinus, Volvox carteri, and Chlorella variabilis NC64A. The assembled contigs (~181 Mb) includes 481,381 transcripts, covering 10,185 genes. Pathway analysis showed that a pathway from inositol phosphate metabolism to fatty acid biosynthesis is the most significantly correlated with higher lipid yield in this mutant. Conclusion: Herein, we described a pipeline to analyze RNA-Seq data without pre-existing transcriptomic information. The draft transcriptome of D. tertiolecta was constructed and annotated, which offered useful information for characterizing high lipid-producing mutants. D. tertiolecta mutant was generated with an enhanced photosynthetic efficiency and lipid production. RNA-Seq data of the mutant and wild type were compared, providing biological insights into the expression patterns of contigs associated with energy metabolism and carbon flow pathways. Comparison of D. tertiolecta genes with homologs of five other green algae can facilitate the annotation of D. tertiolecta, and lead to a more complete annotation of its sequence database, thus laying the groundwork for optimization of lipid production pathways based on genetic manipulation. Examine two sets of RNA-Seq data from high lipid-producing mutant and wild-type sample Dt_v1*: the FASTA and annotation files used for D9_1, WT_1 samples Dt_v10*: the FASTA and annotation files used for D9_2, WT_2 samples Dt_v10-hit*: the FASTA and annotation files only including the contigs that can be annotated in Dt_v10 Additional file 1.xls: processed data for sample 1,2 Additional file 4.xls: processed data for sample 3-6
2015-07-23 | E-GEOD-70876 | biostudies-arrayexpress
Project description:RNA-Seq analysis carried out in three different backcrosses based on Iberian breed with Landrace, Pietrain and Duroc breeds
2017-10-31 | PRJEB23068 | EVA
Project description:STAR aligned RNA-seq reads were used as one of many guides informing gene model annotation of the Valley Oak genome sequence.
2021-05-22 | GSE174828 | GEO
Project description:Leaf senescence is an important developmental programmed degeneration process that dramatically affects crop quality and yield. The regulation of senescence is highly complex. Although senescence regulatory genes have been well characterized in model species such as Arabidopsis and rice, there is little information on the control of this process in cotton. Here, the senescence process in cotton (Gossypium hirsutum L.) leaves was investigated over a time course including young leaf, mature leaf and leaf samples from different senescence stages using RNA-Seq.Of 24,846 genes detected by mapping the tags to Gossypium genomes, 3,624 genes were identified as differentially expressed during leaf senescence. There was some overlap between the genes identified here and senescence-associated genes previously identified in other species. Most of the genes related to photosynthesis, chlorophyll metabolism and carbon fixation were downregulated; whereas those for plant hormone signal transduction were upregulated. Quantitative real-time PCR was used to evaluate the results of RNA-Seq for gene expression profiles. Furthermore, 519 differentially expressed transcription factors were identified, notably WRKY, bHLH and C3H. In addition, 960 genes involved in the metabolism and regulation of eight hormones were identified, of which many genes involved in the abscisic acid, brassinosteroid, jasmonic acid, salicylic acid and ethylene pathways were upregulated, indicating that these hormone-related genes might play crucial roles in cotton leaf development and senescence. However, most auxin, cytokinin and gibberellin pathway-related genes were downregulated, suggesting that these three hormones may act as negative regulators of senescence.This is the first high-resolution, multiple time-course, genome-wide comprehensive analysis of gene expression in cotton. These data are the most comprehensive dataset currently available for cotton leaf senescence, and will serve as a useful resource for unraveling the functions of many specific genes involved in cotton leaf development and senescence.
| S-EPMC4342795 | biostudies-literature
Project description:Green leaf volatiles (GLVs) consist of six-carbon volatile aldehydes, alcohols, and their esters. They are formed from polyunsaturated fatty acids and are involved in the defense of plants against herbivores and pathogens. GLVs generally have low concentrations in intact healthy plant tissues, but the biosynthetic pathway to form GLVs is quickly activated by mechanical damage to tissues, an event called the GLV-burst. Most seed plants have the ability to implement GLV-burst; however, this potential in non-seed plants has not been extensively researched. In this study, we examined the GLV-burst capacity of monilophytes, lycophytes, and bryophytes, and confirmed that monilophytes and lycophytes showed substantial GLV-burst ability, while bryophytes did not, with a few exceptions. When the genome sequence of a model lycophyte, Selaginella moellendorffii was reviewed, 10 genes were found that showed high similarity with the non-canonical cytochrome P450 enzymes, CYP74s, specialized in oxylipin formation. Recombinant proteins expressed with Escherichia coli showed that one of them had the ability to encode allene oxide synthase, and another encoded hydroperoxide lyase (HPL), preferring linolenic acid 13-hydroperoxide, and it was inferred that this gene was responsible for GLV-burst in S. moellendorffii. Based on the phylogenetic tree constructed with CYP74s of non-seed and seed plants, we hypothesized that HPL was acquired independently in the lycophyte and seed plants through diversification of CYP74 genes.
| S-EPMC8578206 | biostudies-literature
Project description:Rice (Oryza sativa L.) is a widely cultivated food crop around the world, especially in Asia. However, rice seedlings often suffer from cold stress, which affects their growth and yield. Here, RNA-seq analysis and Meta-QTLs mapping were performed to understand the molecular mechanisms underlying cold tolerance in the roots of 14-day-old seedlings of rice (RPY geng, cold-tolerant genotype). A total of 4779 of the differentially expressed genes (DEGs) were identified, including 2457 up-regulated and 2322 down-regulated DEGs. The GO, COG, KEEG, and Mapman enrichment results of DEGs revealed that DEGs are mainly involved in carbohydrate transport and metabolism, signal transduction mechanisms (plant hormone signal transduction), biosynthesis, transport and catabolism of secondary metabolites (phenylpropanoid biosynthesis), defense mechanisms, and large enzyme families mechanisms. Notably, the AP2/ERF-ERF, NAC, WRKY, MYB, C2H2, and bHLH transcription factors participated in rice's cold-stress response and tolerance. On the other hand, we mapped the identified DEGs to 44 published cold-stress-related genes and 41 cold-tolerant Meta-QTLs regions. Of them, 12 DEGs were the published cold-stress-related genes and 418 DEGs fell into the cold-tolerant Meta-QTLs regions. In this study, the identified DEGs and the putative molecular regulatory network can provide insights for understanding the mechanism of cold stress tolerance in rice. In addition, DEGs in KEGG term-enriched terms or cold-tolerant Meta-QTLs will help to secure key candidate genes for further functional studies on the molecular mechanism of cold stress response in rice.
| S-EPMC7369714 | biostudies-literature
Project description:The pathogenesis of diabetes mellitus is a complicated process involving much gene regulation. The molecular mechanism of mulberry (Morus alba L.) leaf in the treatment of diabetes is not fully understood. In this study, we used the Illumina HiSeq™ 2,500 platform to explore the liver transcriptome of normal mice, STZ-induced diabetic mice, and mulberry leaf-treated diabetic mice, and we obtained 52,542,956, 52,626,414, and 52,780,196 clean reads, respectively. We identified differentially expressed genes (DEGs) during the pathogenesis of diabetes in mice. The functional properties of DEGs were characterized by comparison with the GO and KEGG databases, and the results show that DEGs are mainly involved in the metabolic pathway. qRT-PCR was used to analyse 27 differential genes involved in liver expression in different groups of diabetic mice. Among the DEGs, the expression of Scube1, Spns3, Ly6a, Igf2, and other genes between the control (C) and diabetic control (DC) groups was significantly upregulated; the expression of Grb10, Mup2, and Fasn was significantly downregulated; the expression of the Sqle, Lss, and Irs2 genes between the C group and diabetic group treated with mulberry (DD) was significantly upregulated; the expression of Fabp2, Ly6a, and Grb10 was significantly downregulated; and the expression of Sqle and Lss was significantly upregulated in the DC and DD groups, but Tap1, Igf2, and Spns3 were significantly downregulated. The results of Western blot validation showed that dynamic changes in proteins, such as IGF2, Ly6a, Grb10, and UBD, occurred to regulate the incidence of diabetes by influencing the insulin receptor substrate (IRS) signaling pathway.
| S-EPMC6090096 | biostudies-literature
Project description:BackgroundRice plants show yellowing, stunting, withering, reduced tillering and utimately low productivity in susceptible varieties under low temperature stress. Comparative transcriptome analysis was performed to identify novel transcripts, gain new insights into different gene expression and pathways involved in cold tolerance in rice.ResultsComparative transcriptome analyses of 5 treatments based on chilling stress exposure revealed more down regulated genes in susceptible and higher up regulated genes in tolerant genotypes. A total of 13930 and 10599 differentially expressed genes (DEGs) were detected in cold susceptible variety (CSV) and cold tolerant variety (CTV), respectively. A continuous increase in DEGs at 6, 12, 24 and 48 h exposure of cold stress was detected in both the genotypes. Gene ontology (GO) analysis revealed 18 CSV and 28 CTV term significantly involved in molecular function, cellular component and biological process. GO classification showed a significant role of transcription regulation, oxygen, lipid binding, catalytic and hydrolase activity for tolerance response. Absence of photosynthesis related genes, storage products like starch and synthesis of other classes of molecules like fatty acids and terpenes during the stress were noticed in susceptible genotype. However, biological regulations, generation of precursor metabolites, signal transduction, photosynthesis, regulation of cellular process, energy and carbohydrate metabolism were seen in tolerant genotype during the stress. KEGG pathway annotation revealed more number of genes regulating different pathways resulting in more tolerant. During early response phase, 24 and 11 DEGs were enriched in CTV and CSV, respectively in energy metabolism pathways. Among the 1583 DEG transcription factors (TF) genes, 69 WRKY, 46 bZIP, 41 NAC, 40 ERF, 31/14 MYB/MYB-related, 22 bHLH, 17 Nin-like 7 HSF and 4C3H were involved during early response phase. Late response phase showed 30 bHLH, 65 NAC, 30 ERF, 26/20 MYB/MYB-related, 11 C3H, 12 HSF, 86 Nin-like, 41 AP2/ERF, 55 bZIP and 98 WRKY members TF genes. The recovery phase included 18 bHLH, 50 NAC, 31 ERF, 24/13 MYB/MYB-related, 4 C3H, 4 HSF, 14 Nin-like, 31 bZIP and 114 WRKY TF genes.ConclusionsTranscriptome analysis of contrasting genotypes for cold tolerance detected the genes, pathways and transcription factors involved in the stress tolerance.
| S-EPMC6694648 | biostudies-literature
Project description:Plants have developed complex mechanisms to respond and adapt to abiotic stresses, coupling elaborate modulation of gene expression together with the preservation of genome stability. Epigenetic mechanisms - DNA methylation, chromatin modifications and non coding RNAs - were shown to play a fundamental role in stress-induced gene regulation and may also result in genome destabilization, with the activation and/or the transcription of silenced transposons and retroelements, causing genome rearrangements and novel gene expression patterns. Maize leaf transcriptome was analyzed by total RNA-Seq in both B73 and rmr6 (PolIV mutant involved in siRNA biogenesis and in the RdDM pathway) after drought and salt stress application. Reference annotation based transcript assembly allowed the identification both of new expressed loci and splicing variants, improving the current maize transcriptome annotation. Many antisense transcripts matching on the opposite strand of annotated loci were also identified, while more than the 20% of transcripts represent non coding RNA belonging to four classes: siRNAs, shRNAs, lncRNAs and transposable elements (or their relics). Several lncRNAs are modulated by stress application while TE-related sequences are mainly expressed in rmr6 and up-regulated by the stress.
2016-01-14 | GSE71046 | GEO