Find research datasets worth reusing

opencc-by-4.0Mar 2023View details →

Titrating Avidity of Yeast-Displayed Proteins Using a Transcriptional Regulator

Data underlying the figures in the publication: Lopez-Morales, J. et al. “Titrating Avidity of Yeast-Displayed Proteins Using a Transcriptional Regulator” ACS Synth. Biol. 2023, 12, 419-31, <a href="https://doi.org/10.1021/acssynbio.2c00351">https://doi.org/10.1021/acssynbio.2c00351</a> Table of Contents Fig1_subplots_EMpty pJL100 full atc range analysis.xlsx: Flow cytometry data of displaying fraction and median fluorescence for Fig. 1c and d. Fig2_subplots_20.08.05 tit disp GOx ABTS.xlsx: Flow cytometry data of displaying fraction and median fluorescence of Gox variants; GOX enzymatic activity assay data for Fig. 2 Fig3_subplots_ SDA data for sharing.xlsx and disks + sup data plot.pptx: Spinning disk assay data and micrographs for Fig. 3. Fig4_ subplots_20220421 YTD affibody aTc vs Gal titration curves.xlsx and 20220423 Gal good volume.xlsx: Flow cytometry data and PDL1 titration on yeast data for Fig. 4. Supplementary_Gal comparison_ Gal time point-2.xlsx: Flow cytometry data for comparing the YTD system to the standard yeast surface display for sup. Fig. S1. Supplementary_Fig S3_Titrated Affibody Kd analysis.xlsx and Simulations.pzf: ICE tables and simulation spreadsheet for sup. Fig. S3.

dryad32/100

Transcriptional profiling of the response to starvation and fattening reveals differential regulation of autophagy genes in mammals

Nutrient deprivation (starvation) induced by fasting and hypercaloric regimens are stress factors that can influence cell and tissue homeostasis in mammals. One of the key cellular responses to changes in nutrient availability is the cell survival pathway, autophagy. While there has been much research into the protein networks regulating autophagy, less is known about the gene expression networks involved in this fundamental process. Here, we applied a network algorithm designed to analyze omics datasets, to identify sub-networks that are enriched for induced genes in response to starvation. This enabled us to identify two prominent active modules composed of key stress-induced transcription factors, including members of the Jun, Fos, and ATF families, and the other comprising autophagosome sub-network genes, including ULK1. The results were validated in the brain, liver, and muscle of fasting mice. Moreover, differential expression analysis of autophagy genes in the brain, liver, and muscle of high-fat diet-exposed mice, showed significant suppression of GABARAPL1 in the liver. Finally, our data provide a resource that may facilitate the future identification of regulators of autophagy.

opencc-zeroMar 2023View details →

openApr 2023View details →

DNA-guided transcription factor cooperativity shapes face and limb mesenchyme

Code and processed data for "DNA-guided transcription factor cooperativity shapes face and limb mesenchyme," Kim et al, Cell 2024.

openother-pdJun 2023View details →

Selection of Han dynasty transcriptions of foreign names and words

This dataset contains the Chinese transcriptions of foreign words and names in Han dynasty sources that appear in the appendix of the following article: Schuessler, Axel (2014). "Phonological Notes on Hàn Period Transcriptions of Foreign Names and Words." Richard VanNess Simmons and Newell Ann Van Auken, eds. Studies in Chinese and Sino-Tibetan Linguistics: Dialect, Phonology, Transcription and Text, pp. 249- 293. Taipei: Institute of Linguistics, Academia Sinica.

opencc-by-4.0Jul 2023View details →

Stepwise modifications of transcriptional hubs link pioneer factor activity to a burst of transcription

This dataset includes the raw imaging data and custom codes related to the publication: Stepwise modifications of transcriptional hubs link pioneer factor activity to a burst of transcription, Nat. Commun., 2023.

Fig. 1 in Rapid screening of glycosyltransferases in plants using a linear DNA expression template based cell-free transcription-translation system

Fig. 1. Rapid screening of plant glycosyltransferases using the LET-based-TX-TL system. We can either use long primers which contain a promoter, a ribosome binding site, and a terminator to generate expressible linear DNAs or use short primers to amplify the targeted gene fragments and then ligate them with a promoter, a ribosome binding site, a terminator, and a backbone; then another pair of primers is used to generate expressible linear DNAs. Afterward, combine TX-TL extracts, buffers, and expressible linear DNAs to start protein expression. Then this TX-TL mixture is directly added with substrates (such as quercetin) to start glycosylation reactions. Finally, UPLC-MS is used to analyze the reaction mixture to examine whether targeted products (such as isoquercitrin) are generated.

Fig. 2 in Rapid screening of glycosyltransferases in plants using a linear DNA expression template based cell-free transcription-translation system

Fig. 2. UPLC-MS analysis of isoquercitrin converted from quercetin by AtUGTs expressed in TX-TL. (A) A glycosylation reaction catalyzed by a UDP-glucose glycosyltransferase. (B) The chromatogram of the blank sample, which only has 50% methanol solvent. (C) The chromatogram of the negative group, which has TX-TL, quercetin, UDPglucose but no additional DNA. (D) The chromatogram of the quercetin standard. (E) The chromatogram of the isoquercitrin standard. (F–O) Chromatograms of products from the catalysis of quercetin by different AtUGTs (the final concentrations of the linear DNAs used for each AtUGTs are listed below in brackets): (F) AT1G07250 (32.25 nM), (G) AT1G07260 (29.24 nM), (H) AT2G36790 (20.64 nM), (I) AT2G15480 (29.98 nM), (J) AT2G15490 (29.50 nM), (K) AT3G16520 (25.03 nM), (L) AT3G21750 (23.7 nM), (M) AT3G46660 (24.14 nM), (N) AT4G15280 (24.47 nM), and (O) AT4G34138 (22.52 nM), see Supplementary Fig. S4 for the duplicate group. The y axis indicates ion signal abundance relative to the highest signal in each chromatogram (%). The numbers in the top right of each chromatogram (for instance 3.38e7 in [E]) indicate the ion counts represented by "100" relative abundance. The retention time of the isoquercitrin standard is 4.0 min, and the red arrow in each figure indicates the retention time of the product isoquercitrin. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4 in Rapid screening of glycosyltransferases in plants using a linear DNA expression template based cell-free transcription-translation system

Fig. 4. UPLC-MS analysis of isoquercitrin converted from quercetin by ArUGTs using heterologous expression. (A) The SDS-PAGE gel of heterologous expression of ArUGTs AR14572, AR11662, and AR43718 protein. The theoretical molecular weights of AR14572 protein, AR11662 protein, and AR43718 protein are 80.1 kDa, 79.8 kDa, and 80.4 kDa, respectively. (B) The chromatogram of isoquercitrin standard. (C–E) Chromatograms of products from the catalysis of quercetin by different ArUGTs using heterologous expression: (C) AR14572, (D) AR11662, and (E) AR43718, see Supplementary Fig. S6 for the duplicate group. The y axis indicates ion signal abundance relative to the highest signal in each chromatogram (%). The numbers in the top right of each chromatogram (for instance 4.56e6 in [B]) indicate the ion counts represented by "100" relative abundance. The retention time of the isoquercitrin standard is 3.93 min, and the red arrow in each figure indicates the retention time of the product isoquercitrin. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5. A in Rapid screening of glycosyltransferases in plants using a linear DNA expression template based cell-free transcription-translation system

Fig. 5. A phylogenetic tree based on protein sequences of six ArUGTs: AR06047, AR06981, AR07558, AR11662, AR14572, and AR43718. The phylogenetic tree is constructed using MEGA. Numbers at the forks are bootstrap values from 100 replicates.

Fig. 3 in Rapid screening of glycosyltransferases in plants using a linear DNA expression template based cell-free transcription-translation system

Fig. 3. UPLC-MS analysis of isoquercitrin converted from quercetin by ArUGTs expressed in TX-TL. (A) A glycosylation reaction catalyzed by a UDP-glucose glycosyltransferase. (B) The chromatogram of the blank sample is 50% methanol solvent. (C) The chromatogram of the negative group, which has TXTL, quercetin, UDP-glucose but no additional DNA. (D) The chromatogram of quercetin standard. (E) The chromatogram of isoquercitrin standard. (F–K) Chromatograms of products from the catalysis of quercetin by different ArUGTs (the final concentrations of the linear DNAs used for each ArUGTs are 30 nM): (F) AR14572, (G) AR11662, (H) AR43718, (I) AR06047, (J) AR06981, and (K) AR07558, see Supplementary Fig. S5 for the duplicate group. The y axis indicates ion signal abundance relative to the highest signal in each chromatogram (%). The numbers in the top right of each chromatogram (for instance 2.21e7 in [E]) indicate the ion counts represented by "100" relative abundance. The retention time of the isoquercitrin standard is 4.08 min, and the red arrow in each figure indicates the retention time of the product isoquercitrin. The numbers under the protein names are the peak intensities of the product. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 6 in Genome-wide transcriptional analysis unveils the molecular basis of organ-specific expression of isosteroidal alkaloids biosynthesis in critically endangered Fritillaria roylei Hook

Fig. 6. Heatmap representing organ specific significantly enriched genes corresponding to (A) Isosteroidal alkaloid biosynthesis, (B) Sucrose and starch metabolism, (C) UGTs and CYPs, (D) aquaporins, (E) ABC transporters, (F) Transcription factor and Transposable elements. The red-blue scale represents positive enrichment (red) and negative enrichment (Blue) of transcripts. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5 in Genome-wide transcriptional analysis unveils the molecular basis of organ-specific expression of isosteroidal alkaloids biosynthesis in critically endangered Fritillaria roylei Hook

Fig. 5. Significantly enriched transcripts (nodes) in predicted interactome network. (A) Steroidal alkaloid biosynthesis pathways (B) Isopentenyl diphosphate biosynthesis pathway, (C) Sucrose and starch metabolic pathways and (D) Aquaporins. The nodes encircled in red color represents higher enrichment in the bulb while the nodes encircled in grey and blue represents higher enrichment in arial organs (leaf and stem). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 7 in Genome-wide transcriptional analysis unveils the molecular basis of organ-specific expression of isosteroidal alkaloids biosynthesis in critically endangered Fritillaria roylei Hook

Fig. 7. qRT-PCR expression-based validation of RNA-seq data using potential 20 genes involved in isosteroidal alkaloid biosynthetic pathway. (A) Bulb vs. Leaf, (B) Leaf vs. Stem and (C) Bulb vs. Stem.

Fig. 3 in Genome-wide transcriptional analysis unveils the molecular basis of organ-specific expression of isosteroidal alkaloids biosynthesis in critically endangered Fritillaria roylei Hook

Fig. 3. Significant KEGG pathway enrichment analysis in tissues from aerial organs (leaf & Stem) and bulb. The green colour enrichment indicates higher expression in aerial tissue while pink represents higher enrichment in bulb. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4 in Genome-wide transcriptional analysis unveils the molecular basis of organ-specific expression of isosteroidal alkaloids biosynthesis in critically endangered Fritillaria roylei Hook

Fig. 4. Transcriptional protein-protein interactome (PPIN) prediction in F. roylei along the network statistics. (A) Overall prediction of PPI network based on significantly differential expressed transcripts. Spatial PPI network prediction of significantly enriched transcripts in (B) Bulb, (C) Leaf and (D) Stem.

Fig. 1 in Genome-wide transcriptional analysis unveils the molecular basis of organ-specific expression of isosteroidal alkaloids biosynthesis in critically endangered Fritillaria roylei Hook

Fig. 1. Summary of organ specific spatial transcriptome sequencing in F. roylei. (A): Overall quality filtering of sequenced reads; (B): Tissue specific high quality filtered reads obtained after removing low quality/adaptor contaminated sequences; (C): Assembly statistics details; (D): Venn diagram representing functional annotation with six different public protein databases.

Fig. 8 in Genome-wide transcriptional analysis unveils the molecular basis of organ-specific expression of isosteroidal alkaloids biosynthesis in critically endangered Fritillaria roylei Hook

Fig. 8. Representation of isosteroidal alkaloid biosynthesis pathway in F. roylei and heat map representing expression of genes in Stem, Leaf and Bulb tissue using red-blue scale (red: positive enrichment and Blue: negative enrichment of transcripts). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2 in Genome-wide transcriptional analysis unveils the molecular basis of organ-specific expression of isosteroidal alkaloids biosynthesis in critically endangered Fritillaria roylei Hook

Fig. 2. Clustering of 2488 significant differentially expressed transcripts in leaf, stem and bulb in F. roylei (A) sub-cluster 1 represent transcripts with significant higher expression in bulb; (B): Sub-cluster 2 in Stem and (C): Sub-cluster 3 in leaf; (D): Pearson's correlation of organ specific significant differentially expressed clustered transcripts in leaf, stem and bulb tissues.

opennotspecifiedFeb 2020View details →

Fig. 1. Transcript levels for OsRIP1 in Involvement of OsRIP1, a ribosome-inactivating protein from rice, in plant defense against Nilaparvata lugens

Fig. 1. Transcript levels for OsRIP1 in rice shoots after high (A) or low (B) infestation with N. lugens. Expression of OsRIP1 in BPH infested seedlings was determined at different timepoints (3, 5, 6, 9 or 13 days post infestation (dpi)), relative to the transcript levels in mock treated plants. Bars represent mean expression values from three independent biological replicates (normalized to three reference genes), error bars indicate standard errors. Asterisks indicate statistically significant differences compared to expression levels in mock treated plants (*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001).