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8,068 results for “Transcriptome analysis”
Ice recrystallization inhibitors enable efficient cryopreservation of induced pluripotent stem cells: A functional and transcriptomic analysis
<p><span>The successful use of human induced pluripotent stem cells (iPSCs) for research or clinical applications requires the development of robust, efficient, and reproducible cryopreservation protocols. After cryopreservation, the survival rate of iPSCs is suboptimal and cell line dependent. We assessed the use of ice recrystallization inhibitors (IRIs) for cryopreservation of human iPSCs<span>. A toxicity screening study was performed to assess specific small-molecule carbohydrate-based IRI and concentrations for further evaluation.</span> Then, a cryopreservation study compared the cryoprotective efficiency of 15 mM IRIs in 5 % or 10 % DMSO-containing solutions and with CryoStor® CS10. Three iPSC lines were cryopreserved as single-cell suspensions in the cryopreservation solutions and post-thaw characteristics, including pluripotency and differential gene expression, were assessed. </span><span>W</span><span>e demonstrate the fitness-for-purpose of 15 mM IRI in 5 % DMSO as an efficient cryoprotective solution for iPSCs in terms of post-thaw recovery, viability, pluripotency, and transcriptomic changes. Given that this dataset is the first report where mRNA sequencing has been used to identify expression changes resulting from iPSCs cryopreservation, it has the potential to be used for molecular mechanism analysis relating to cryopreservation. IRIs can reduce DMSO concentrations, thereby improving the utility, effectiveness, and efficiency of cryopreservation. </span></p>
Ulkenia visurgenis Lng2 transcriptomic analysis
<p><span>Programming codes, intermediates files, transcript annotation spreadsheets and the final version of the assembled transcriptome developed for a transcriptional anaylisis of the thraustochytrid <em>Ulkenia visurgensis</em> Lng2.</span></p>
Data from: Combined transcriptome and metabolome analysis identifies defence responses in spider-mite infested pepper
<p>Plants regulate responses towards herbivory through fine-tuning of defence-related hormone production, expression of defence genes and production of secondary metabolites. Jasmonic acid (JA) plays a key role in plant-herbivorous arthropod interactions. To understand how pepper responds to herbivory, leaf transcriptomes and metabolomes of two genotypes different in their susceptibility to spider mites, were studied. Mites induced both JA and salicylic acid (SA) signalling. However, mite infestation and exogenous JA resulted in distinct transcriptome profiles. Compared with JA, mites induced less differentially expressed genes involved in metabolic processes (except for genes involved in the phenylpropanoid pathway) and lipid metabolic processes. Furthermore, pathogen-related defence responses including WRKY transcription factors, were stronger induced upon mite infestation, likely as result of induced SA signalling. Untargeted analysis of secondary metabolites confirmed that JA treatment induced larger changes in metabolism than spider-mite infestation, resulting in a higher terpenoid and flavonoid production. The more resistant genotype exhibited a larger increase in endogenous JA and volatile and non-volatile secondary metabolites upon infestation, which could explain its stronger defence. Reasoning that in JA-SA antagonizing crosstalk, SA-defences are prioritized over JA-defences, we hypothesize that lack of SA-mediated repression of JA-induced defences could result in gain-of-resistance towards spider mites in pepper.</p>
Data from: De novo assembly of a tadpole shrimp (Triops newberryi) transcriptome and preliminary differential gene expression analysis
Next-generation sequencing techniques, such as RNA sequencing, have provided a wealth of genomic information for nonmodel species. Transcriptomic information can be used to quantify the patterns of gene expression, which can identify how environmental differences invoke organismal stress responses and provide a gauge in predicting species adaptability. In our study, we used RNA sequencing to characterize the first transcriptome from a naupliar tadpole shrimp (Triops newberryi) to identify the genes expressed during the early life history stages and which could be important for future genomic studies. RNA was extracted from naupliar T. newberryi that were reared in a laboratory-controlled setting and in two different water types, a native and a non-native condition. A total of six replicates, three per condition, were sequenced with the Illumina Hi-Seq 2000 achieving 365 M 50-nt reads. High-quality reads were produced and de novo assembly was used to construct a T. newberryi transcriptome that was approximately 24.8 M base pairs. More than 10 000 peptides were predicted from the assembly, and genes were sorted into gene ontology categories. The use of different water conditions allowed for a preliminary differential gene expression analysis in order to compare the changes in gene expression between conditions. There were 299 differentially expressed genes between water conditions that might serve as a focal point for future genomic studies of Triops acclimation to different environments. The Triops transcriptome could serve as vital genomic information for additional studies on Branchiopod crustaceans.
Transcriptomic analysis demonstrates the expression, origin and function of lncRNAs in multiple skin diseases
<p>Transcriptomic analysis demonstrates the expression, origin and function of lncRNAs in multiple skin diseases</p>
Datasets used in Consensus Clustering Problem in Single-cell Transcriptome Data Analysis
<p>20 benchmark scRNA-seq datasets used in Consensus Clustering Problem in Single-cell Transcriptome Data Analysis. In every datasets .zip files, it provided raw data files, the processed R code and the corresponding R objects. The datasets.xlsx file provided the detailed information of 20 datasets.</p>
Fig. 6 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis
Fig. 6. Multiple sequence alignment for the catalytic domain of V. betonicifolia protein disulfide isomerases, VbPDI1-2 with previously reported PDIs from Rubiaceae (OaPDI) and Violaceae (GbPDI). The active site residues CGHC are highlighted.
Fig. 4 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis
Fig. 4. Vibe cyclotide/acyclotide properties A. Graphical representation of net acidity, basicity and hydrophobicity of cyclotide/acyclotide* from V. betonicifolia, calculated using a peptide property calculation tool, https://www.peptide2.com/N_peptide_hydrophobicity_hydrophilicity.php (Kyte and Doolittle, 1982; Sims, 2010). B. Sequence alignment highlighting physicochemical similarity. Hydrophobic residues are highlighted in yellow, basic in red and acidic in blue. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis
Fig. 3. Vibe cyclotides identified from small scale extraction of V. betonicifolia. A. Base peak ion (BPI) chromatogram from V. betonicifolia containing deconvoluted masses for (M + H)+ of candidate cyclotides. B. Isotopic mass pattern of native, reduced/alkylated, endoproteinase GluC cleaved cyclotides exemplified by kalata S/ varv A (B), vibe 13 (C) and a new cyclotide present in the extract but absent in the transcriptome (D).
Fig. 2 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis
Fig. 2. Schematic representation of the general organisation of cyclotide precursors and multiple sequence alignment of 28 cyclotide precursor proteins obtained from the de novo transcriptome assembly of V. betonicifolia. A. ER signal domain at the start of each precursor sequence is highlighted in blue where cleavage of the signal domain is predicted to occur between blue and pink residues (Dutton et al., 2004). The precursor is organised with an N-terminal propeptide domain, NTPP (black), N-terminal repeat, NTR (green), mature cyclotide domain (red) and C-terminal propeptide domain, CTPP (purple). An AEP mediated cleavage potentially occurs at the conserved Asn/Asp adjacent to the CTPP of all cyclotide sequences; B. New cyclotides are named vibe 1–25. In varv A/kalata S and vibe 24 transcripts, two repeating mature domains are present. In acyclotides, either the conserved Asn/Asp or CTPP sequence is absent. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis
Fig. 1. Example structures and sequences from the three main cyclotide subfamilies. The structures are based on the PDB files for kalata B1 (1nb1), cycloviolacin O1 (1nbj) and Momordica cochinchinensis II (MCoTI-II) (1ib9). The unique cyclic cystine knot (CCK) topology of cyclotides arises when the ring formed by CysI-CysIV and CysII-CysV together with the backbone loops 1 and 4 are penetrated by the third disulfide between CysIII and CysVI. The cyclotide producing plant families are denoted by RRubiaceae VViolaceae, FFabaceae, SSolanaceae and CCucurbitaceae. The conserved Cys residues are highlighted in yellow and the cis-pro in loop 5 that defines the M¨obius subfamily is highlighted in blue. The conserved Asn/Asp residue at which cyclisation occurs is highlighted in red. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis
Fig. 5. Multiple sequence alignment of vibe AEPs and other functionally verified ligase- and protease-type AEPs identified in cyclic peptide producing plants. The AEP conserved catalytic triad residues Asn, Cys and His are highlighted in red. In the aligned AEPs, ligase activity determinant 1 (LAD1) containing gate keeper residue (highlighted in green/cyan, position orthologous to CYS247 in OaAEP1b (Harris et al., 2015) and ligase activity determinant 2 (LAD2) regions (highlighted in pink/blue) (Hemu et al., 2019), poly-proline region (Jackson et al., 2018) and marker of ligase activity region (MLA) (Jackson et al., 2018) are highlighted in boxes. VyPAL2 from V. yedoensis (Hemu et al., 2019), HeAEP3 from H. enneaspermus (Jackson et al., 2018), OaAEP1b from O. affinis (Harris et al., 2015) and butelase 1 from C. ternatea (Nguyen et al., 2014) are functionally verified ligases. MCoAEP2 has also shown efficient in vitro ligase activity, despite the presence of protease-type ligase activity determinant regions (Du et al., 2020). VyAEP1 from V. yedoensis and HaAEP1 from H. annus are protease-type AEPs with weaker ligase activity at high/neural pH (Haywood et al., 2018; Hemu et al., 2019). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 2. Genes involved in Paris saponin biosynthesis. (a) Genes participated in the MVA and MEP pathways. (b) Genes participated in the downstream of saponin backbone biosynthesis.
Fig. 4 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 4. An overview of DEG expression patterns and GO enrichments. (a) Heatmap of expression values for all DEGs. (b) GO enrichments of DEGs, with displaying the top fifteen subcategories for each category.
Fig. 7 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 7. QRT-PCR validation of RNA-Seq data. Expression profiles of eight selected genes were determined by transcriptome and qRT-PCR data. The left vertical axis represents the relative expression of the gene based on qRT-PCR. The right vertical axis represents the expression level of the gene based on transcriptome sequencing. The asterisk above the bar chart denotes statistical significance based on the qRT-PCR data (* denotes P value <0.05, ** denotes P value <0.01, ns denotes P value> 0.05).
Fig. 1 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 1. The bioactive compound content and transcriptome characters. (a) Total content of three typical types of Paris saponins in leaves and rhizomes during the vegetative and fruiting stages. VL: leaves at vegetative stage, VR: rhizomes at vegetative stage, FL: leaves at fruiting stage, and FR: rhizomes at fruiting stage. (b) Proportion of three types of Paris saponins in leaves and rhizomes. (c) Distribution of the expressed unigenes in tissues during the two stages (log2 (TPMþ1)> 0). (d) Boxplot of unigene expression profiles.
Fig. 3 in Transcriptome analysis of Paris polyphylla var. yunnanensis illuminates the biosynthesis and accumulation of steroidal saponins in rhizomes and leaves
Fig. 3. DEG statistics. (a) Venn diagram of DEGs from the four paired comparisons. (b) The number of up-down regulated DEGs of the four paired comparisons.
Fig. 2 in Comparative transcriptome analysis infers bulb derived in vitro cultures as a promising source for sipeimine biosynthesis in Fritillaria cirrhosa D. Don (Liliaceae, syn. Fritillaria roylei Hook.) - High value Himalayan medicinal herb
Fig. 2. (A–E) Differential gene expression analysis in comparative F. roylei transcriptome: (A) Heat-map showing differential gene expression in the bulb (PKW) vs callus (PK2); bulb (PKW) vs in vitro regenerated plantlets (PK1) and callus (PK2) vs in vitro regenerated plantlets (PK1); (B) Venn diagram represents the differential gene expression in PKW vs PK1; PKW vs PK2; PK2 vs PK1, (C–E) Volcano plots represents the differential gene expression in PKW vs PK1; PKW vs PK2; PK2 vs PK1 as colour description image, where p-value & log2 fold-change in red colour represents genes with log2 fold-change cut off 2 and p-value <=0.05; p-value in blue colour represents genes with no cut off on log2 fold-change and p-value <=0.05. Whereas, log2 fold-change in green colour represents genes with fold-change cut off 2 but no p-value cut off and non-significant (NS) in grey colour represents genes with no filter on log2 fold-change and p-value, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Comparative transcriptome analysis infers bulb derived in vitro cultures as a promising source for sipeimine biosynthesis in Fritillaria cirrhosa D. Don (Liliaceae, syn. Fritillaria roylei Hook.) - High value Himalayan medicinal herb
Fig. 1. (A–F) Functional annotations and unigenes classification of comparative F. roylei transcriptome: (A) Unigenes annotation with top 15 different plant species; (B) Top 5 pathway representation as per Kyoto Encyclopedia of Genes and Genomes; (C) Gene Ontology classification under the cellular component, molecular function, and biological process categories; (D) COG (Cluster of Orthologous Groups of proteins) classification into nine different categories; (E) Unigenes classification into major transcription factor families; (F) Gene family and sub-family classification using TAIR database.
Fig. 4 in Comparative transcriptome analysis infers bulb derived in vitro cultures as a promising source for sipeimine biosynthesis in Fritillaria cirrhosa D. Don (Liliaceae, syn. Fritillaria roylei Hook.) - High value Himalayan medicinal herb
Fig. 4. Comparative expression pattern validation for the sipeimine biosynthetic pathway genes as obtained from RNA-Seq data and qRT-PCR.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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