Find research datasets worth reusing

Data from: Mating system variation and gene expression in the male reproductive tract of Peromyscus mice

Genes involved in reproduction often evolve rapidly at the sequence level due to postcopulatory sexual selection (PCSS) driven by male-male competition and male-female sexual conflict, but the impact of PCSS on gene expression has been under-explored. Further, though multiple tissues contribute to male reproductive success, most studies have focused on the testes. To explore the influence of mating system variation on reproductive tract gene expression in natural populations, we captured adult males from monogamous Peromyscus californicus and polygynandrous P. boylii and P. maniculatus. We generated RNAseq libraries, quantified gene expression in the testis, seminal vesicle, epididymis, and liver, and identified 3,627 mating system-associated differentially expressed genes (MS-DEGs), where expression shifted in the same direction in P. maniculatus and P. boylii relative to P. californicus. Gene expression variation was most strongly associated with mating behavior in the seminal vesicles, where 89% of differentially expressed genes were MS-DEGs, including key seminal fluid proteins Svs2 and Pate4. We also used published rodent genomes to test for positive and relaxed selection on Peromyscus-expressed genes. Though we did not observe more overlap than expected by chance between MS-DEGs and positively selected genes, 203 MS-DEGs showed evidence of positive selection. Fourteen reproductive genes were under tree-wide positive selection but convergent relaxed selection in P. californicus and Microtus ochrogaster, a distantly related monogamous species. Changes in transcript abundance and gene sequence evolution in association with mating behavior suggest that male mice may respond to sexual selection intensity by altering aspects of sperm motility, sperm-egg binding, and copulatory plug formation.

opencc-by-4.0Apr 2024View details →

Fig. 2 in Angiostrongylus cantonensis induces energy imbalance and dyskinesia in mice by reducing the expression of melanin-concentrating hormone

Fig. 2 (See legend on previous page.)

Metabolomic analysis of cultured TRAMP-C2 cells in the presence or absence of PD-L1 expression

The interaction between the immune inhibitory receptor PD-1 and its ligand PD-L1 is a critical mechanism for altering immune responses, especially during chronic antigen exposures such as cancer. While much research has focused on the PD-1 receptor, recent evidence suggests that PD-L1 can have cell-intrinsic effects in cancer and immune cells. These functions are distinct from its ability to bind and trigger PD-1 activity and are notable given that PD-L1 is widely expressed in mammals. One such cell-intrinsic function is the modulation of cellular metabolism, including regulation of mTOR activity and glycolysis. As part of our investigation into PD-L1 function, we analyzed the metabolome of cultured mouse prostate cancer cells (TRAMP-C2) expressing PD-L1 or with PD-L1 deleted via CRISPR/Cas9. We quantified 186 water-soluble metabolites from TRAMP-C2 cells expressing PD-L1 or not to better understand what metabolic pathways and processes are regulated by PD-L1 expression/activity. We found a broad range of differentially abundant metabolites, most notably a decreased abundance of glycolytic metabolites when PD-L1 expression is knocked out. In our manuscript, we show that this has a functional outcome on viral infection and cytokine signaling.

opencc-by-4.0May 2023View details →

The IBEM Dataset: a large printed scientific image dataset for indexing and searching mathematical expressions

The IBEM dataset consists of 600 documents with a total number of 8272 pages, containing 29603 isolated and 137089 embedded Mathematical Expressions (MEs). The objective of the IBEM dataset is to facilitate the indexing and searching of MEs in massive collections of STEM documents. The dataset was built by parsing the LaTeX source files of documents from the <a href="https://www.cs.cornell.edu/projects/kddcup/datasets.html">KDD Cup Collection</a>. Several experiments can be carried out with the IBEM dataset ground-truth (GT): ME detection and extraction, ME recognition, etc.   The dataset consists of the following files: <ul> <li>“IBEM.json”: file containing the IBEM GT information. The data is firstly organized by pages, then by the type of expression (“embedded” or “displayed”), and lastly by the GT of each individual ME. For each ME we provide: <ul> <li>xy page-level coordinates, reported as relative (%) to the width/height of the page image.</li> <li>“split” attribute indicating the number of fragments in which the ME has been split. MEs can be split over various lines, columns or pages. The LaTeX transcript of split MEs have been exactly replicated (entire LaTeX definition) for each fragment.</li> <li>“latex” original transcript as extracted from the LaTeX source files of the documents. This definition can contain user-defined macros. In order to be able to compile these expressions, each page includes the preamble of the source files containing the defined macros and the packages used by the authors of the documents.</li> <li>“latex_expand” transcript reconstructed from the output stream of the LuaLaTeX engine in which user-defined macros have been expanded. The transcript has the same visual representation as the original transcript, with the addition that the LaTeX definitions are tokenized, the order of sub/super script elements have been fixed, and matrices have been transformed to arrays.</li> <li>“latex_norm” transcript resulting from applying an extra normalization process to the “latex_expand” expression. This normalization process includes removing font information such as slant, style, and weight.</li> </ul> </li> <li>“partitions/*.lst”: files containing list of pages forming the partition sets.</li> <li>“pages/*.jpg”: individual pages extracted from the documents.</li> </ul> The dataset is partitioned into various sets as provided for the ICDAR 2021 Competition on Mathematical Formula Detection. The ground-truth related to this competition, which is included in this dataset version, can also be found <a href="https://zenodo.org/record/4757865">here</a>. More information about the competition can be found in the following paper: D. Anitei, J.A. Sánchez, J.M. Fuentes, R. Paredes, and J.M. Benedí. ICDAR 2021 Competition on Mathematical Formula Detection. In ICDAR, pages 783–795, 2021.   For ME recognition tasks, we recommend rendering the “latex_expand” version of the formulae in order to create standalone expressions that have the same visual representation as MEs found in the original documents (see attached python script “extract_GT.py”). Extracting MEs from the documents based on coordinates is more complex, as special care is needed to concatenate the fragments of split expressions. Baseline results for ME recognition tasks will soon be made available.

Data from: The genomics of mimicry: Gene expression throughout development provides insights into convergent and divergent phenotypes in a Müllerian mimicry system

A common goal in evolutionary biology is to discern the mechanisms that produce the astounding diversity of morphologies seen across the tree of life. Aposematic species, those with a conspicuous phenotype coupled with some form of defense, are excellent models to understand the link between vivid color pattern variations, the natural selection shaping it, and the underlying genetic mechanisms underpinning this variation. Mimicry systems in which species share a conspicuous phenotype can provide an even better model for understanding the mechanisms of color production in aposematic species, especially if comimics have divergent evolutionary histories. Here we investigate the genetic mechanisms by which mimicry is produced in poison frogs. We assembled a 6.02 Gbp genome with a contig N50 of 310 Kbp, a scaffold N50 of 390 Kbp, and 85% of expected tetrapod genes. We leveraged this genome to conduct gene expression analyses throughout development of four color morphs of R. imitator and two color morphs from both R. fantastica and R. variabilis which R. imitator mimics. We identified a large number of pigmentation and patterning genes differentially expressed throughout development, many of them related to melanophores/melanin, iridophore development, and guanine synthesis. We also identify the pteridine synthesis pathway (including genes such as qdpr and xdh) as a key driver of the variation in color between morphs of these species, and identify several plausible candidates for coloration in vertebrates (e.g., cd36, ep-cadherin, perlwapin). Finally, we hypothesize that keratin genes (e.g., krt8) are important for producing different structural colors within these frogs.

The mRNA expression changes in neonatal primary mouse ventricular cardiomyocytes treated with epirubicin (2uM)

Epirubicin (EPI) is effective in the treatment of malignant cancers, but its application is limited by life-threatening cardiotoxicity. Iron homeostasis disturbance has been implicated in anthracycline-induced cardiotoxicity (AIC), and ferroptosis is involved in AIC which is dependent upon intracellular iron. However, the role and exact mechanisms of ferroptosis in the pathogenesis of epirubicin-induced cardiotoxicity (EIC) remain elusive. In this study, we aimed to investigate mechanisms underlying ferroptosis-driven EIC. Epirubicin triggered ferroptosis both in vivo and in cultured cardiomyocytes, and pretreatment with ferroptosis inhibitor, Ferrostatin-1(Fer-1) alleviates EIC. Microarray analysis was performed to screen for potential molecules involved in EIC in neonatal primary mouse ventricular cardiomyocytes (NMVMs). We found that the transcript level of ATP6V0A2, a subunit of vacuolar ATPase (V-ATPase), was significantly downregulated when NMVMs were subjected to EPI, which was verified in vivo and in vitro as measured by real-time quantitative reverse transcription PCR (qRT-PCR) and immunoblotting. Intriguingly, overexpression of ATP6V0A2 effectively decreased excessive oxidative stress and lipid-peroxidation accumulation, thereby inhibiting ferroptosis and protecting cardiomyocytes against EIC, as evidenced by functional, enzymatic, and morphological changes. Mechanistically, forced expression of ATP6V0A2 restored lysosomal acidification in EPI-treated cardiomyocytes and protected cardiomyocytes and mice hearts from ferroptosis-driven EIC. In this study, our data elucidate that ferroptosis is involved in EIC, which is ignited by ATP6V0A2-dependent lysosomal acidification dysfunction. Our study provides a new potential therapeutic target for ameliorating EIC.

Quit bugging me: Phorid fly parasitoids affect expression of an immune gene in foraging fire ant workers

This data contains RT-qPCR and diet measurements for quantifying gene expression of red imported fire ant, Solenopsis invicta workers in the presence and absence of the parasitoid fire ant decapitating fly, Pseudacteon curvatus, and assessing the amount of food after exposure to P. curvatus, respectively. The genes investigated were the Solenopsis invicta foraging gene (Sifor), odorant binding protein 11 (OBP-11), abaecin, defensin-2 (Def-2), cytochrome P450 4C1-like (CYP4C1-like), and hymenoptaecin (hym). Ribosomal Protein 18 (RPL18) was used as the reference gene. These genes of S. invicta workers of unknown infection status in fire ant colonies exposed to decapitating flies and control colonies were observed over a 48-h period. Two diets were measured before and after in control and treatment colonies (i.e., colonies exposed to P. curvatus).

Neural FoxP2 expression in an aging open-ended vocal learner

Most vocal learning species exhibit an early critical period during which their vocal control neural circuity can facilitate the acquisition of new vocalizations. Some taxa, most notably humans and parrots, retain this neurobehavioral plasticity throughout adulthood. Downregulation of the transcription factor FoxP2 in both songbird and parrot vocal control nuclei has been identified as a key expression pattern facilitating vocal learning. We hypothesize that open-ended vocal learning is vulnerable to cognitive decline, and that this deterioration will be reflected in age-related changes in neural FoxP2 expression. We tested this hypothesis in the budgerigar (Melopsittacus undulatus), a small gregarious parrot in which adults converge on shared call types in response to shifts in group membership. We formed novel flocks of 4 previously unfamiliar males belonging to the same age class, either "young adult" (6 mo-1 yr) or "older adult" (≥ 3 yr), and then collected audio-recordings over a 20-day learning period to assess vocal learning ability. Following behavioral recording, whole brains were extracted and immunohistochemistry was performed to measure FoxP2 protein expression in a parrot vocal learning center, the magnocellular nucleus of the medial striatum (MMSt), and its adjacent striatum. We find similarly downregulated FoxP2 expression and equivalent vocal plasticity and vocal convergence in young and older adults suggesting the maintenance of two components of open-ended learning into old age in the budgerigar. No relationship between individual variation in vocal learning measures and FoxP2 expression was detected.

opencc-by-4.0Jul 2024View details →

Resolving single-cell expression profiles by pseudo-temporal integration of transcriptomic and proteomic datasets.

Raw and processed single cell proteomics (scp-MS) and scRNA-Seq data of HEK293-PIP-FUCCI cells which were challanged with hypoxia. The repository contains data for recreating the pseudo-temporal alignment analysis of transcription-translation profiles.

opencc-zeroJul 2024View details →

Single cell multiomic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients

Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing. To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omic approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls. We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC. Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.

opencc-by-4.0Oct 2023View details →

Geomorphic expressions of active rifting reflect the role of structural inheritance: A new model for the evolution of the Shanxi Rift, North China

A geopackage and associated raster files for the geomorphic indices that were used in this study. Can be opened with the freely available QGIS software. Excel table of fault values used for generation of violin plots in R

opencc-by-4.0Dec 2022View details →

Figure 1 in TiO nanoparticles and salinity stress in relation to artemisinin production and ADS and DBR2 expression in Artemisia absinthium L.

Figure 1. TEM micrograph of the used Titanium dioxide nanoparticles.

opencc-by-4.0Dec 2022View details →

Figure 1 in Detection of respiratory viruses and expression of inflammatory cytokines in patients with acute exacerbation chronic obstructive pulmonary disease in Mongolia China

Figure 1. Distribution of Viruses.

opencc-by-4.0Mar 2016View details →

Fig. 2. A in Changes in midgut gene expression following Bacillus thuringiensis (Bacillales: Bacillaceae) infection in Monochamus alternatus (Coleoptera: Cerambycidae)

Fig. 2. A plotted regression for RT-qPCR validation analysis.

opencc-by-4.0Jul 2024View details →

Moore_Schultz_Sox14_expressing_neurons

Sox14-expressing cell count data from ~50 brain regions in two groups of mice: Sox14/GFP heterozygotes and Sox14 null.

opencc-by-4.0Jul 2024View details →

Post-transcriptional regulation supports the homeostatic expression of mature RNA

<h3>Overview</h3> This dataset consists of RNA sequencing data stored in HDF5 files. The data has been processed to quantify gene expression changes at the precursor RNA (preRNA) and mature RNA (matureRNA) levels across various biological conditions, including normal tissues and diseases. The dataset supports the study "Post-transcriptional regulation supports the homeostatic expression of mature RNA," providing insight into the general influence of post-transcriptional regulation (PTR) on gene expression homeostasis. <h3>File Contents</h3> Each HDF5 file contains the following datasets: <ul> <li>logFC_MatureRNA: Represents the log fold change of mature RNA expression levels between different conditions or tissues.</li> <li>logCPM_MatureRNA: Represents the log counts per million for mature RNA.</li> <li>PValue_MatureRNA: Represents the p-value for the statistical test performed on mature RNA expression levels.</li> <li>FDR_MatureRNA: Represents the false discovery rate for the mature RNA expression levels.</li> <li>logFC_preRNA: Represents the log fold change of precursor RNA expression levels between different conditions or tissues.</li> <li>logCPM_preRNA: Represents the log counts per million for precursor RNA.</li> <li>PValue_preRNA: Represents the p-value for the statistical test performed on precursor RNA expression levels.</li> <li>FDR_preRNA: Represents the false discovery rate for the precursor RNA expression levels.</li> <li>genes: A list of gene identifiers used in the study.</li> <li>studies: A list of study or condition names included in the dataset.</li> </ul> <h3>File Naming Convention</h3> The HDF5 files are named to reflect the filtering applied to exclude lowly expressed genes (logCPM > 5), and DESeq2 and edgeR refer to the tools used for differential expression analysis: <ul> <li><code>DESeq2_filtered_exon_intron_abnormal_conditions_all_reads.h5</code></li> <li><code>edgeR_filtered_exon_intron_abnormal_conditions_all_reads.h5</code></li> <li><code>DESeq2_filtered_exon_intron_gtex_tissue_all_reads.h5</code></li> <li><code>edgeR_filtered_exon_intron_gtex_tissue_all_reads.h5</code></li> </ul> <h3>Example Usage</h3> To query the HDF5 files, you can use the provided `<a href="https://github.com/suzheng/PTR_RNA_seq/blob/main/notebooks/parse_h5_file.ipynb">parse_h5_file.ipynb</a>` example notebook to parse the HDF5 files.

opencc-by-4.0Oct 2017View details →

Supplementary Material v1: Multivariate entropy characterizes the gene expression and protein -protein networks in four types of cancer

Supplementary Material PDF Multivariate entropy characterizes the gene expression and protein -protein networks in four types of cancer

opencc-by-4.0Apr 2018View details →

Huntingtin Exon 1 Q16 and Q46 pET32a thioredoxin tagged expression and purification 2018/04/09

Huntingtin structure-function open lab notebook project. Huntingtin Exon 1 Q16 and Q46 pET32a thioredoxin tagged expression and purification 2018/04/09.

opencc-by-4.0Apr 2018View details →

Huntingtin Exon 1 Q16 and Q46 pET32a thioredoxin tagged expression and purification 2018/04/02

Huntingtin structure-function open lab notebook project. Huntingtin Exon 1 Q16 and Q46 pET32a thioredoxin tagged, attempted expression and purification 2018/04/02