Kim, Kwanho · Lin, Zechuan · Simmons, Sean · et al.

1 files · 37 KB · pdf

This dataset contains CCS corrected HiFi long-read DNA sequencing (lrDNAseq) in FASTQ format for 100 PMDBS samples from Parkinson's patients and healthy controls. It's part of the PD5D atlas, where the same subjects were also profiled with other omics assays including genotyping, single-cell ATACseq, and spatial transcriptomics.

Kim, Kwanho · Lin, Zechuan · Simmons, Sean · et al.

1 files · 37 KB · pdf

This dataset contains raw FASTQ files from the midbrain single-nucleus RNA sequencing (snRNAseq) dataset with hybrid selection for the matching PMDBS samples from the PD5D chort. The same subjects were also profiled with other omics assays including genomic DNAseq, genotyping, single-cell ATACseq, and spatial transcriptomics.

Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.

1 files · 37 KB · pdf

This dataset consists of raw sequencing snRNA-seq data (10x Genomics Chromium Next GEM Single Cell 3ʹ). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.

Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.

1 files · 36 KB · pdf

This dataset consists of raw sequencing snRNA-seq data using ParseBio Evercode Whole Transcriptome. The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a specific ParseBio barcode. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.

Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.

1 files · 36 KB · pdf

This dataset consists of raw sequencing snATAC-seq data (10x Genomics Chromium Next GEM Single Cell ATAC v2). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors. (edited)

Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.

1 files · 36 KB · pdf

This dataset consists of raw sequencing snATAC-seq data (HyDrop v2). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.

Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.

1 files · 36 KB · pdf

This dataset consists of raw sequencing ATAC-seq data (Scale-ATAC pre-indexing followed by 10x Genomics snATAC v2). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.

Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.

1 files · 36 KB · pdf

This dataset consists of raw sequencing ATAC-seq data (Scale-ATAC + HyDrop v2). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocols followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108 ) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.

Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.

1 files · 37 KB · pdf

This dataset consists of raw sequencing snRNA-seq data and snATAC-seq data (10x Genomics Chromium Next GEM Multiome ATAC/GEX). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108 ) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors. (edited)

Yuan, Guangyuan

72 rows × 13 cols · 6.0 KB · csv, fasta

11 numeric · 2 categorical

This dataset supports the findings of the manuscript "Root anatomical traits modulate the assembly and nitrogen transformation potential of root-associated microbiomes in a temperate steppe" (NPH-MS-2026-55667). It contains root traits data, bacterial 16S rRNA gene absolute abundances, functional genes relative abundances, DNA extraction metadata, and phylogenetic marker sequences for 37 plant species from a temperate steppe ecosystem. The dataset includes the following files: 1. root traits.csv - Root traits including average diameter (AD), specific root length (SRL), specific root area (SRA), root tissue density (RTD), root nitrogen content (RNC), root carbon content (RCC), carbon‑nitrogen ratio (RCN), cortex layer number (CLN), cortex thickness (CT), and the ratio of cortex thickness to root diameter (CTRD). The first column lists plant species names. 2. Absolute abundance of 16S rRNA gene.csv - Quantitative PCR (qPCR) derived absolute abundances of bacterial 16S rRNA gene copies (copies/ng DNA) across different root compartments (rhizosphere, rhizoplane, endosphere), host species, root orders, and cotyledon classes (monocot/dicot). 3. DNA extraction sample weight.csv - Fresh weight (grams) of root material used for DNA extraction for each sample, linked by SampleID to the abundance data. 4. DNA extraction concentration.csv - Qubit‑measured DNA concentrations (ng/μL) and the sample volume (μL) used for quality control, together with sample metadata. 5. 37species.fasta - DNA sequences of two chloroplast markers (matK and rbcL) for the 37 plant species included in the study. The sequences are in FASTA format with headers formatted as ">Species". These were used for host phylogeny construction and Pagel's λ analyses. 6. Quantitative PCR results of functional gene.csv - Quantitative PCR (qPCR) derived relative abundances of bacterial 16S rRNA gene and functional genes across different root compartments (rhizosphere, rhizoplane, endosphere), host species, root orders, and cotyledon classes (monocot/dicot). 7. README.md - A detailed description of each file, column headers, abbreviations, units, and any missing value codings (NA). All data are provided to ensure transparency and reproducibility of the analyses. For methodological details, please refer to the Materials and Methods section of the associated publication. These data are under embargo until the associated research article is published. After that date, they will be freely available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. During the embargo period, the metadata (title, authors, abstract) and the DOI remain publicly visible, but the data files are not accessible. For access requests before the embargo expires, please contact the corresponding author.

MacDonald, Adam · Stratton, Jo Anne

1 files · 35 KB · pdf

We performed 10X Genomics single-cell RNAsequencing of human prepheral blood mononuclear cells from healthy control, PD and RBD patients. This dataset contains raw FASTQ files. Sequencing was performed using NovaSeq 6000 S4 PE 100bp. Reads were processed using the 10X Genomics Cell Ranger Single Cell 2.0.0 pipeline. FASTQs generated from sequencing output were aligned to the human GRCh38 reference genome using STAR algorithm 2.7.3a.

Stratton, Jo Anne · Mukherjee, Sriparna · Trudeau, Louis-Eric

1 files · 5.0 KB · pdf

We performed bulk RNAsequencing of substantia nigra from wild type and PINK1 KO mice 26-days post C.rodentium infection. This dataset contains raw fastq files from striatal cells, sorted into 4 groups namely wild type and PINK1 KO uninfected and infected mice. Sequencing was performed using NextSeq500. FASTQs generated from sequencing output were aligned to the mm10 reference genome using STAR aligner.

Stratton, Jo Anne · Mukherjee, Sriparna · Trudeau, Louis-Eric

1 files · 6.1 KB · pdf

We performed bulk RNAsequencing of striatum from wild type and PINK1 KO mice 26-days post C.rodentium infection. This dataset contains raw fastq files from striatal cells, sorted into 4 groups namely wild type and PINK1 KO uninfected and infected mice. Sequencing was performed using NextSeq500. FASTQs generated from sequencing output were aligned to the mm10 reference genome using STAR aligner.

Recinto, Sherilyn · Stratton, Jo Anne

1 files · 6.1 KB · pdf

We performed 10X Genomics single-cell RNAsequencing of human iSPC-derived monocytes and macrophages in vitro. Cells were treated with 500 ng/mL lipopolysaccharide (LPS) and 50 ng/mL interleukin-1 beta (IL1b) for 24 hours. This dataset contains raw FASTQ files from myeloid cells, sorted into 4 groups namely monocytes (Mono) and Macrophages (Mac) non-stimulated (NS) and LPS+IL1b-stimulated cells. Sequencing was performed using NovaSeq 6000 S4 PE 100bp. Reads were processed using the 10X Genomics Cell Ranger Single Cell 2.0.0 pipeline. FASTQs generated from sequencing output were aligned to the human GRCh38 reference genome using STAR algorithm 2.7.3a.

Recinto, Sherilyn · Stratton, Jo Anne · Pei, Jessica · et al.

2 files · 6.0 KB · pdf

We performed 10X Genomics single-cell RNAsequencing of colonic lamina propria cells from wild type and LRRK2 G2019S mice following 1-week post C. rodentium infection. The cells were pooled from 3 mice per group of both sexes at 8-12 weeks of age. This dataset contains raw FASTQ files from mouse colonic lamina propria, sorted into 4 groups namely wild type and LRRK2 G2019S uninfected and infected mice. Sequencing was performed using NovaSeq 6000 S4 PE 100bp. Reads were processed using the 10X Genomics Cell Ranger Single Cell 2.0.0 pipeline. FASTQs generated from sequencing output were aligned to the mouse GRCm38 reference genome using STAR algorithm 2.7.3a.

Recinto, Sherilyn · Stratton, Jo Anne

1 files · 5.7 KB · pdf

We performed 10X Genomics single-cell RNA sequencing of colonic lamina propria cells from wild type and PINK1 KO mice following either 1-week or 2-weeks post C. rodentium infection. The cells were pooled from 3 mice per group of both sexes at 8-12 weeks of age. This dataset contains raw FASTQ files from mouse colonic lamina propria, sorted into 8 groups namely wild type and PINK1 KO uninfected and infected mice at 1- or 2-weeks post-infection. Sequencing was performed using NovaSeq 6000 S4 PE 100bp. Reads were processed using the 10X Genomics Cell Ranger Single Cell 2.0.0 pipeline. FASTQs generated from sequencing output were aligned to the mouse GRCm38 reference genome using STAR algorithm 2.7.3a.

Budzinski, Lisa · Beenken, Anne Elisabeth · Sempert, Toni · et al.

9 rows × 1 cols · 743 B · csv, docx, zip

1 categorical

We have investigated an IgG4-RD (IgG4-RD) cohort by our multi-parameter microbiota flow cytometry approach to characterise the microbiota on single-cell level for attributes of the disease. The microbiota is isolated from stool samples and stained according to the published protocol for (a) host immunoglobulins IgA1, IgA2, IgM, IgG and (b) agglutinin binding to mannose, galactose or N-Acetyl-glucosamine surface sugar moieties. For all samples we also determined the microbiome composition by 16S rRNA (V3-V4) sequencing on the illumina MiSeq platform. We provide the raw .fcs and FASTQ files of 40 IgG4-RD patients. For comparison we additionally analysed 36 healthy donors. All .fcs files were generated on BD Influx®. The metadata is collected in the provided meta.csv. The staining parameters are summarized in provided panel.csv.

Manghi, Paolo

2 files · 8.0 MB · gzip, tsv

Using gene-level and species-level shotgun metagenomics, we provide the first characterization of the rural, Bolivian microbiome; we identified microbial genes which strongly correlate (rho>0.45) with arsenic in urine, and that overall contribute to substantiate that the gut microbiome helps tolerate arsenic via a evict-out-of-house mechanism. Mediation analysis, followed by phylogenetic investigation of metagenomic-assembled genomes, further strengthens this observation. This study elucidates the role of the microbiome in helping to tolerate arsenic-rich environments, and paves the way for probiotic interventions that may mitigate the effects of this toxic metal. This repository contains 2,478 HQ MAGs from the MicroToxBol cohort in fasta format and a descriptive table comprising taxonomic annotation, quality-checks, and coverage estimation.

Goncalves dos Santos, Karen Cristine · Desgagné-Penix, Isabel · Merindol, Natacha

16 files · 8.0 MB · gzip

General description Compiled dataset of transcriptome assemblies, transcriptome annotation and expression quantification for 27 Amaryllidoideae species and 4 hybrid cultivars: Amaryllis belladonna , Clivia miniata , Crinum asiaticum , Crinum x powellii , Galanthus elwesii , Galanthus sp., Hippeastrum cv. Blossom Peacock, Hippeastrum cv. Jewel, Hippeastrum cv. Royal Velvet, Hippeastrum striatum , Hippeastrum vittatum , Leucojum aestivum , Lycoris aurea , Lycoris chinensis , Lycoris incarnata , Lycoris longituba , Lycoris radiata , Lycoris sprengeri , Narcissus aff pseudonarcissus , Narcissus papyraceus , Narcissus pseudonarcissus , Narcissus cv. Tête-à-Tête, Narcissus tazetta , Narcissus viridiflorus , Phycella aff cyrtanthoides , Rhodophiala pratensis , Scadoxus multiflorus , Traubia modesta , Zephyranthes candida , Zephyranthes carinata , Zephyranthes treatiae. Data includes transcriptome assemblies, Transdecoder predictions of peptide sequences (along with predicted coding seqeunces, GFF3 and BED files), expression quantification (count and TPM matrices for genes and trinity isoforms obtained with Kallisto and from Salmon), and annotation results (from EggNOG, Pfam, Uniprot Swissprot and Rfam), as well as signal peptide and transmemberane domain predictions (from SignalP and TmHMM). Annotations were compiled into a report for each species using Trinotate. For Lycoris aurea and Narcissus cv. Tête-à-Tête, there are two assemblies and corresponding files: Lycoris_aurea_PB and Lycoris_aurea_TH, and Narcissus_TaT_PB Narcissus_TaT_TH. PB assemblies were constructed solely with long-read sequencing data (PacBio, PB); while TH assemblies were constructed with short reads using Trinity, with long-read assembly being used for scaffolding step of Trinity (Trinity Hybrid, TH). Expression quantification was published on NCBI GEO (accessions GSE329951 , GSE329957 , GSE330014 and GSE331457 ). File descriptions All unitigs and predicted protein sequences are prefixed with an acronym to identify the species: Species Acronym NCBI TSA accession Amaryllis belladonna Ambel deposited on GSE331457 Clivia miniata Clmin DBNKRK000000000 Crinum asiaticum Crasi DBNIJL000000000 Crinum x powellii Crpow DBNKRS000000000 Galanthus elwesii Gaelw DBNKRO000000000 Galanthus sp. Gasp DBNKRR000000000 Hippeastrum cv. Blossom Peacock HispBP DBNMYE000000000 Hippeastrum cv. Jewel HispJW DBNMYC000000000 Hippeastrum cv. Royal Velvet HispRV DBNMYD000000000 Hippeastrum striatum Histr DBNIJG000000000 Hippeastrum vittatum Hivit DBNKRF000000000 Leucojum aestivum Leaes DBNIJJ000000000 Lycoris aurea (PB) Lyaur DBNFTY000000000 Lycoris aurea (TH) Lyaur DBNKRI000000000 Lycoris chinensis Lychi DBNKRE000000000 Lycoris incarnata Lyinc DBNKRD000000000 Lycoris longituba Lylon DBNKRG000000000 Lycoris radiata Lyrad deposited on GSE331457 Lycoris sprengeri Lyspr DBNKRL000000000 Narcissus aff pseudonarcissus Naafps DBNKRP000000000 Narcissus papyraceus Napap DBNKRN000000000 Narcissus pseudonarcissus Napse DBNIJK000000000 Narcissus Tête-à-Tête (PB) NaspPB DBNNFO000000000 Narcissus Tête-à-Tête (TH) NaspTH DBNUFN000000000 Narcissus tazetta Nataz DBNPME000000000 Narcissus viridiflorus Navir deposited on GSE331457 Phycella sp. Phsp deposited on GSE331457 Rhodophiala pratensis Rhpra deposited on GSE331457 Scadoxus multiflorus Scmul DBNIJH000000000 Traubia modesta Trmod deposited on GSE331457 Zephyranthes candida Zecan DBNKRH000000000 Zephyranthes carinata Zecar DBNIJI000000000 Zephyranthes treatiae Zetre deposited on GSE331457 Files Files are organized by type of analysis/data, meaning all expression quantification data obtained with Kallisto are compressed into a single file, all results from BlastP are in the same file, etc. Compressed file name Individual file type Content Blastp_Uniprot.tar.gz Tabular 33 files (1 per assembly) generated with BLASTP against Uniprot SwissProt release 2024_04. Files in blast output format 6 (standard columns). EggNOG_Emapper.tar.gz Tabular 33 tabular files (1 per assembly). Generated with eggnog.emapper (annotations file format described in eggnog.emapper's wiki ) Expression_Kallisto.tar.gz Tabular 128 files (4 per assembly, 2 for long-read assemblies): read counts and TPM values for both trinity "genes" and trinity "isoforms"). Row names are "gene"/ "isoform" IDs, column names are SRA run IDs. Expression_Salmon.tar.gz Tabular 128 files (4 per assembly, 2 for long-read assemblies): read counts and TPM values for both trinity "genes" and trinity "isoforms"). Row names are "gene"/ "isoform" IDs, column names are SRA run IDs. Final_assemblies.tar.gz Fasta 33 files (1 per assembly). Assemblies generated in this study, after contamination and expression filtering. HMMScan_PfamA.tar.gz Domain hits table 33 files (1 per assembly). Generated with hmmscan (option ‑‑domtblout, domain hits table, explained in hmmer's user guide [119] ) against the Pfam-A database. Infernal_Rfam.tar.gz Target hits table format 2 33 files (1 per assembly) generated with Infernal's cmscan (using the Trinotate wrapper) against the Rfam database. Table format 2 described in Infernal's user guide section 6 ). Metadata_studies.tar.gz Tabular (semi-colon separated columns) 31 tabular files (one per species/cultivar) indicating: Bioproject ID, SRA run ID, Sample name, Biosample ID, tissue, genotype (cultivar, when specified), treatment, batch, original publication citation, and DOI of original publication. Signalp6.tar.gz Tabular or GFF3 99 files (3 per assembly: prediction_results.txt, output.gff3 and region_output.gff3) generated with SignalP6. TmHMM2.tar.gz Tabular 33 files (1 per assembly) generated with TmHMM2 (short format, described in the guide tab of https://services.healthtech.dtu.dk/services/TMHMM-2.0/ Transcriptomes_unfiltered.tar.gz Fasta 33 files (1 per assembly). Unfiltered (prior to contamination and expression screening) assemblies generated in this study. Transdecoder_bed.tar.gz BED 33 BED files (1 per assembly) generated with TransDecoder.Predict (using BLASTp against Uniprot and hmmscan against Pfam) Transdecoder_cds.tar.gz Fasta 33 fasta files (1 per assembly) of predicted coding sequences generated with TransDecoder.Predict (using BLASTp against Uniprot and hmmscan against Pfam) Transdecoder_gff3.tar.gz GFF3 33 GFF3 files (1 per assembly) generated with TransDecoder.Predict (using BLASTp against Uniprot and hmmscan against Pfam). Transdecoder_proteomes.tar.gz Fasta 33 predicted proteome files (.pep, 1 per assembly) generated with TransDecoder.Predict (using BLASTp against Uniprot and hmmscan against Pfam).