GigaDB

Protected: Holobiomic division of labor in fungus-farming termites project data

admin — Wed, 15 May 2013 03:49:49 +0000

A test-retest functional MRI dataset for motor, language and spatial attention functions

admin — Mon, 08 Apr 2013 03:48:29 +0000

The following data comes from the study “A test-retest fMRI dataset for motor, language and spatial attention functions”, which is a test-retest dataset acquired to validate functional magnetic resonance imaging (fMRI) tasks used in pre-surgical planning. Five task-related fMRI time series (finger, foot and lip movement, overt verb generation, covert verb generation, overt word repetition, and landmark tasks) were used to investigate which protocols gave reliable single-subject results. Ten healthy participants in their fifties were scanned twice using an identical protocol 2-3 days apart. In addition to the fMRI sessions, high-angular resolution diffusion tensor MRI (DTI), and high-resolution 3D T1-weighted volume scans were acquired.

Each subject was assigned a random, unique identifier using the DICOM confidential de-identification toolkit to replace their name and any other medical identification information. DICOM files for each scanning sequence were anonymized according to the Health Insurance Portability and Accountability Act guidelines, and DICOM to NIfTI conversion was performed using the dcm2nii tool. To prevent visual identification, the 3D T1-weighted volumes have been defaced using mri_deface. Seven NIfTI files are provided for each subject/session: five 4D fMRI, one 4D DTI, and one 3D T1-weighted volume scan.

Due to the fact that the overt language tasks were scanned using sparse sampling, we were able to record and analyze each subject’s responses (not included due to privacy concerns). This analysis lead to exclusion of one session of one subject of the overt word repetition task, due to the fact that the subject failed to perform the task correctly. Data and its description are arranged according to the OpenfMRI layout. Together, this dataset provides a unique opportunity to investigate the reliability of different fMRI tasks, as well as methods and algorithms used to analyze, de-noise and combine fMRI, DTI and structural T1-weighted volume data.

Related code in GitHub: https://github.com/chrisfilo/2010-Reliability-Study

Aspera server

Readme

README

Code

Code

MRI_data

MRI data

History

April 08, 2013: Data released.

In accordance with our terms of use, please cite this dataset as:
Gorgolewski, KJ; Storkey, A; Bastin,ME; Whittle, IR; Wardlaw, JM; Pernet, CR (2013) A test-retest functional MRI dataset for motor, language and spatial attention functions. GigaScience Database http://dx.doi.org/10.5524/100051

Related manuscript available at:
doi:10.1186/2047-217X-2-6

Genomic data from Aegilops tauschii – The Progenitor of Wheat D Genome

admin — Thu, 07 Mar 2013 02:29:27 +0000

A spontaneous hybridization of the wild diploid grass Aegilops tauschii (2n=14, DD) with cultivated tetraploid wheat Triticum turgidum (2n=4x=28, AABB) 8,000~10,000 years ago in the Fertile Crescent resulted in the bread wheat (Triticum aestivum; 2n=6x=42, AABBDD), one of the earliest cultivated crops in modern agriculture. We sequenced the 4.36-gigabase (Gb) genome of Ae. tauschii by generating ~90x genome coverage of short reads from a series of libraries with various insert sizes. The assembled scaffolds of high quality sequences represent 83.4% of the genome, in which 65.9% comprised of repetitive elements. Assisted with comprehensive RNA-Seq data, we identified 43,150 protein-coding genes, with 30,697 (71.1%) of them uniquely anchored to chromosomes based on an integrated density genetic map. A number of agriculturally relevant gene families, such as disease resistance, abiotic stress tolerance, and grain quality genes, were found to expand in Ae. tauschii. The draft genome of Ae. tauschii hence provides novel insights into its role in enabling environmental adaptation of common wheat and in defining the large and complicated genomes of wheat species.

Aspera server

Readme

README.txt

Annotation

wheatD_final_43150.gff.cds.Corrected
wheatD_final_43150.gff.Corrected
wheatD_final_43150.gff.pep.Corrected

wheatD_final_43150.gff.cds
wheatD_final_43150.gff
wheatD_final_43150.gff.pep

md5

Assembly

wheatD_kgf.scafSeq.FG.fill
md5

Genomic Raw Reads
Genomic Raw Reads

Reseq Raw Data
Reseq Raw Data

RNAseq
RNAseq

History

March 08, 2013: Data released.
May 02, 2013: Annotation update.

In accordance with our terms of use, please cite this dataset as:
Jia, J; Zhao, S; He, W; Tao, Y; Zhang, C; Gao, C; Li, D; Mao, L; Wang, J (2013): Genomic data from Aegilops tauschii – The Progenitor of Wheat D Genome. GigaScience Database http://dx.doi.org/10.5524/100054

Accession codes associated with this data:
NCBI SRA SRP005974

Related manuscript available at:doi:10.1038/nature12028

Genomic data from Triticum urartu – the progenitor of wheat A genome

admin — Thu, 07 Mar 2013 01:57:20 +0000

The wheat A genome, as a basic genome of bread wheat and other polyploid wheats, is centrally important to the evolution, domestication, and genetic improvement of wheat. The progenitor of the A genome is the diploid wild einkorn wheat Triticum urartu. Here, we sequenced T. urartu (accession G1812) using a whole-genome shotgun strategy on the Illumina HiSeq 2000 platform, and assembled the genome using SOAPdenovo2 with 448.49 Gb of filtered high-quality sequence data. The genome assembly reached 3.92 Gb (without Ns) with a contig N50 length of 3.42 kb and 4.66 Gb (with Ns) with a scaffold N50 length of 63.69 kb . To facilitate gene prediction, we generated a 116.65 Mb transcriptome of T. urartu with 67.14 Gb RNA-Seq data from eight different tissues and treatments, and 49,935 assembled transcripts from six tissues using the Roche 454 sequencing platform. In total, we predicted 34,879 protein-coding gene models. The average gene size was 3,207 bp, with a mean of 4.7 exons per gene.

Aspera server

Readme
README.txt

Annotation

TRIUR3.120813.filter150.cds
TRIUR3.120813.filter150.gff
TRIUR3.120813.filter150.pep
md5

Assembly

wheatA_1020_63m.scafSeq.fill.FG
md5

Genomic Raw Reads
Genomic Raw Reads
Reseq Raw Data
Reseq Raw Data
RNAseq
RNAseq
History

March 07, 2013: Data released.

In accordance with our terms of use, please cite this dataset as:
Ling, H-Q; Zhao, S; Zhang, C; Tao, Y; Gao, C; Liang, Q; Wang, D; Zhang, A; Wang, J (2013): Genomic data from Triticum urartu – the progenitor of wheat A genome. GigaScience Database http://dx.doi.org/10.5524/100050

Accession codes associated with this data:
NCBI SRA SRP005973

Related manuscript available at: doi:10.1038/nature11997

Quantitative proteomics data using mTRAQ/MRM looking at human AKR family members in cancer cell lines

admin — Wed, 20 Feb 2013 06:17:36 +0000

Members of the human aldo-keto reductase（AKR）superfamily have been reported to be involved in cancer progression, and to investigate their role further a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM) has been developed. AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. This approach was employed to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3 and AKR1C4 in 7 different cancer cell lines, and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among cells demonstrating diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, and may enable further insight on the role of AKR proteins are involved in tumorigenesis.

readme

PASS00087_DESCRIPTION.txt

MRM_readme.txt

MRM Raw Data

Standard curves in huh7 background.rar

data of 7 samples.rar

stander curves in mixed background.rar

Transition List

transition list.docx

History

May 13, 2013: Data released.

In accordance with our terms of use, please cite this dataset as:
Zhang, S; Wen, B; Zhou, B; Yang, L; Cha, C; Xu, S; Qiu, X; Wang, Q; Sun, H; Lou, X; Zi, J; Zhang, Y; Lin, L; Liu S (2013): Quantitative proteomics data using mTRAQ/MRM looking at human AKR family members in cancer cell lines. GigaScience Database. http://dx.doi.org/10.5524/100047

Related paper available at:
http://pubs.acs.org/doi/abs/10.1021/pr301153z

Quantitative proteomics and transcriptomics data from the anaerobic thermophilic eubacterium Thermoanaerobacter tengcongensis

admin — Wed, 20 Feb 2013 02:48:31 +0000

Thermoanaerobacter tengcongensis (T. tengcongensis) is a thermophilic eubacterium isolated from Tengchong, China. It is an anaerobic, Gram-negative, rod-shaped bacterium, able to survive in temperatures ranging from 50 to 80 °C. The genome sequence of T. tengcongensis was decoded in 2001, comprising 2.69 Mb in length and containing 2,588 predicted proteins. Previous studies of the proteomic response to growth temperature changes and thermo-survival of T. tengcongensis have been carried out with 2DE and MALDI-TOF/TOF MS. However, due to limitations of the technique, only few proteins with semi-quantitative estimation for the differential 2DE spots responsive to temperature changes are obtained.

An improved iTRAQ-based quantification proteomics protocol has been developed, and using this method data produced to analyze the T. tengcongensis cultured at four temperatures: 55, 65, 75, and 80 oC. In order to obtain reproducible data, two biological replicates and multiple technical replicates (four times for the first sample preparation and three times for the second one) were carried out. Using the iTRAQ labeled sample analyzing procedure of high-pH RP HPLC coupled with LTQ Orbitrap Velos MS, 732,234 MS/MS spectra in total were obtained. The raw data were searched by Mascot 2.3, approximately 23% of the spectra were matched to peptides (FDR<0.01), while 0.5% less of the identified peptides were absent with the reporter tags. In total, 1,589 proteins elicited from 13,223 unique peptides, were identified with quantitative information, which covered 61.4% of the 2,588 predicted proteins of the T. tengcongensis genome. To study the abundance correlation between protein and mRNA, RNA-seq was carried out to study the transcription of the different cultured samples. Using Illumina HiSeqTM 2000 sequencing and the analyzing the raw data using SOAP2, the RNA-seq data covered approximately 97% (2501/2588) of the predicted genes, with more than two reads for each gene. These two datasets help show that the temperature-dependent responses of transcription and translation can happen in synchrony.

readme

TTE_iTRAQ_readme.txt

Mass Spectrometry Data

Mass Spectrometry Data

RNA-Seq Data

RNA-Seq Data

History

May 18, 2013: Data released.

In accordance with our terms of use, please cite this dataset as:

Chen, Z; Wen, B; Wang, Q; Tong, W; Guo, J; Bai, X; Zhao, J; Sun, Y; Tang, Q; Lin, Z; Lin, L; Liu (2013): Quantitative proteomics and transcriptomics data from the anaerobic thermophilic eubacterium Thermoanaerobacter tengcongensis. GigaScience Database http://dx.doi.org/10.5524/100048

Related paper available at:
http://dx.doi.org/10.1074/mcp.M112.025817

Accession code associated with this data:
ProteomeXchange DOI: 10.6019/PXD000264
NCBI SRA: SRP022748

NGS Biodiversity Software

admin — Mon, 04 Feb 2013 18:20:04 +0000

The software is a pipeline for mitochondrial protein annotation in mixed bulk samples. The pipeline annotates mitochondrial genes using homolog prediction with TBLASTN based on known complete mitochondrial genomes from GenBank RefSeq. The BLAST results were then used to determine gene ontology (e.g., mRNA and coding sequence regions) using Genewise. Annotation results include gff format annotation file, DNA and protein sequences of annotated genes. Compared to other mitochondrial annotation pipelines, the MT_annotation_BGI pipeline is easier to run a batch of annotation tasks with high speed and precision. For additional methodological details see the published paper using an example of bulk insect data suitable for running on this pipeline (see dataset here: doi:10.5524/100045).

Code is also available from github: https://github.com/gigascience/papers/tree/master/zhou2013

These pipelines will also soon be made available from our data platform as Galaxy workflows: http://galaxy.cbiit.cuhk.edu.hk/

Aspera server

readme

README.txt

Pipelines

MT_annotation_BGI

History

February 21, 2013: Data released.

In accordance with our terms of use, please cite this dataset as:

Zhou, X; Li, Y; Liu, S; Yang, Q; Su, X; Zhou, L; Tang, M; Fu, R; Li, J; Huang, Q (2013): Software and supporting material for: “Ultra-deep sequencing enables high-fidelity recovery of biodiversity for bulk arthropod samples without PCR amplification”. GigaScience Database http://dx.doi.org/10.5524/100046
Related manuscript available at:
doi:10.1186/2047-217X-2-4

NGS Biodiversity Data

admin — Mon, 04 Feb 2013 18:12:59 +0000

The following data comes from the study “Ultra-deep sequencing enables high-fidelity recovery of biodiversity for bulk arthropod samples without PCR amplification”, which is the first systematic meta-barcoding study sequencing the total DNA from insect communities independent of PCR amplification. Following mitochondrial enrichment using differential centrifugation, a preliminary sample and a formal sample are achieved respectively with 2.2G and 13.2G from the Illumina HiSeq 2000 platform using 100 bp paired-end (PE) sequencing, following manufacturer’s instructions. The data was assembled using SOAPdenovo2 and annotated using the MT_annotation_BGI pipeline (tools and pipelines available here: doi:10.5524/100046). Further details are available in the published paper and the metadata provided in the MIMS formatted table.

Aspera server

readme

readme.txt

Data

PreliminarySample
FormalSample
MIMS_table.xls
Sanger reference barcodes

History

February 21, 2013: Data released.
April 2, 2013: Added sanger reference barcodes

In accordance with our terms of use, please cite this dataset as:

Zhou, X; Li, Y; Liu, S; Yang, Q; Su, X; Zhou, L; Tang, M; Fu, R; Li, J (2013): Raw data, assembly and annotation results for: “Ultra-deep sequencing enables high-fidelity recovery of biodiversity for bulk arthropod samples without PCR amplification”. GigaScience Database http://dx.doi.org/10.5524/100045

Accession codes associated with this data:
NCBI SRA SRA067357

Related manuscript available at:
doi:10.1186/2047-217X-2-4

SOAPdenovo2

admin — Fri, 07 Dec 2012 04:29:41 +0000

SOAPdenovo2 is the latest de novo genome assembly package from BGI’s SOAP (short oligonucleotide analysis package) suite of tools (homepage here: http://soap.genomics.org.cn/). Compared to SOAPdenovo1, this new version has the advantage of a new algorithm design that reduces memory consumption in graph construction, resolves more repeat regions in contig assembly, increases coverage and length in scaffold construction, improves gap closure, and is optimized for large genomes. Using new sequencing data from the YH (Homo sapiens) diploid genome – the first sequenced Han Chinese individual, an updated assembly was produced (see dataset here: doi:10.5524/100038), with the N50 scores for the contig and scaffold being 3-fold and 50-fold longer, respectively, than the first published version. The genome coverage increased from 81.16% to 93.91%, and memory consumption was ~2/3 times lower during the point of largest memory consumption. Benchmarking with Assemblathon1 and GAGE datasets shows that SOAPdenovo2 greatly surpasses its predecessor SOAPdenovo1 and is competitive to other assemblers on both assembly length and accuracy.

In order to facilitate readers to repeat and recreate these findings, configured packages with the compressed pipelines containing all of the necessary shell scripts and tools are available from the BGI FTP server (ftp://public.genomics.org.cn/BGI/SOAPdenovo2).

The latest version of SOAPdenovo2 is available from Sourceforge: http://soapdenovo2.sourceforge.net/

These pipelines will also soon be made available from our data platform as Galaxy workflows: http://galaxy.cbiit.cuhk.edu.hk/

Aspera server

Pipelines
README.pdf
Assemblathon1_pipeline.tgz
Bombus_impatiens_pipeline.tgz
Rhodobacter_sphaeroides_pipeline.tgz
Staphylococcus_aureus_pipeline.tgz
YH_pipeline.tgz

History

December 13, 2012: Data released.

In accordance with our terms of use, please cite this dataset as:

Luo, R; Liu, B; Xie, Y; Li, Z; Huang, W; Yuan, J; He, G; Chen, Y; Pan, Q; Liu, Y; Tang, J; Wu, G; Zhang, H; Shi, Y; Liu, Y; Yu, C; Wang, B; Lu, Y; Han, C; Cheung, D; Yiu, SM; Liu, G; Zhu, X; Peng, S; Li, Y; Yang, H; Wang, J; Lam, TW; Wang, J (2012): Software and supporting material for “SOAPdenovo2: An empirically improved memory-efficient short read de novo assembly”. GigaScience Database. http://dx.doi.org/10.5524/100044

Related manuscript available at:
doi:10.1186/2047-217X-1-1

Parasitic nematode

admin — Fri, 14 Sep 2012 11:58:07 +0000

Trichinella spiralis is the smallest nematode parasite of humans and is also infectious in the rat, pig and bear species. Responsible for the disease trichinosis, it is often referred to as the “pork worm” due to infection usually being caused by the consumption of undercooked pork products. Adults mature in the intestines of an intermediate host, and each female produces batches of larvae that bore through the intestinal wall and the lymphatic system. They are then carried to striated muscle where they encyst.

To date 5′-cytosine methylation (5mC) has not been reported in Caenorhabditis elegans, and using ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) the existence of DNA methylation in T. spiralis was detected, making it the first 5mC reported in any species of nematode. Technological advances now enable the high-resolution detection of 5′-cytosine methylation, providing a stronger basis for examining the role of DNA methylation in eukaryotic genomes such as these.

Using MethylC-seq, here we present the first comprehensive study that confirms the existence of DNA methylation in the parasitic nematode, T. spiralis and we characterised the methylomes during the three life-cycle stages of this food-borne infectious parasite of humans. We generated 61.65, 23.52 and 55.77 million raw reads, almost all of which (96.36%, 91.30% and 99.27%, respectively) were able to be aligned to the T. spiralis reference sequence, yielding 2.91, 1.05 and 2.71 Gb of DNA sequence data for the three life-cycle stages. To further validate the DNA methylation level we randomly selected genomic regions and performed Bisulfite-PCR combined with cloning Sanger sequencing. This additional data further supports the existence of DNA methylation in the parasitic nematode, T. spiralis.

readme
readme.txt

Methylome data
fa
methy_info
UPLC-MS

ISA-Tab formatted metadata
ISA-Tab

History
October 8, 2012: Data released.
October 17, 2012: ISA-Tab files added.

In accordance with our terms of use, please cite this dataset as:

Gao, F; Wang, J; Ji, G (2012): Bisulfite-PCR combined with cloning Sanger sequencing data for validating DNA methylation level in Trichinella spiralis. GigaScience. http://dx.doi.org/10.5524/100043

Related manuscript available at:
doi:10.1186/gb-2012-13-10-r100

Accession codes associated with this data:
NCBI BioProject PRJNA170655
NCBI GEO GSE39328
NCBI SRA SRP014316