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Modified sequence capture for standard and methylation analyses of the same sample

ABSTRACT: A modified sequence capture approach allowing standard and methylation analyses of the same enriched genomic DNA sample

PROVIDER: PRJEB21533 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	ERR2017841_1.fastq.gz	Fastqsanger.gz
	ERR2017841_2.fastq.gz	Fastqsanger.gz
	ERR2017842_1.fastq.gz	Fastqsanger.gz
	ERR2017842_2.fastq.gz	Fastqsanger.gz
	ERR2017843_1.fastq.gz	Fastqsanger.gz

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A modified sequence capture approach allowing standard and methylation analyses of the same enriched genomic DNA sample.

Project description:BackgroundBread wheat has a large complex genome that makes whole genome resequencing costly. Therefore, genome complexity reduction techniques such as sequence capture make re-sequencing cost effective. With a high-quality draft wheat genome now available it is possible to design capture probe sets and to use them to accurately genotype and anchor SNPs to the genome. Furthermore, in addition to genetic variation, epigenetic variation provides a source of natural variation contributing to changes in gene expression and phenotype that can be profiled at the base pair level using sequence capture coupled with bisulphite treatment. Here, we present a new 12 Mbp wheat capture probe set, that allows both the profiling of genotype and methylation from the same DNA sample. Furthermore, we present a method, based on Agilent SureSelect Methyl-Seq, that will use a single capture assay as a starting point to allow both DNA sequencing and methyl-seq.ResultsOur method uses a single capture assay that is sequentially split and used for both DNA sequencing and methyl-seq. The resultant genotype and epi-type data is highly comparable in terms of coverage and SNP/methylation site identification to that generated from separate captures for DNA sequencing and methyl-seq. Furthermore, by defining SNP frequencies in a diverse landrace from the Watkins collection we highlight the importance of having genotype data to prevent false positive methylation calls. Finally, we present the design of a new 12 Mbp wheat capture and demonstrate its successful application to re-sequence wheat.ConclusionsWe present a cost-effective method for performing both DNA sequencing and methyl-seq from a single capture reaction thus reducing reagent costs, sample preparation time and DNA requirements for these complementary analyses.

| S-EPMC5899405 | biostudies-literature

SSSMuG: Same Sample Sequential Multi-Glycomics

Project description:The mammalian glycome is structurally complex and diverse, composed of many glycan classes such as N- and O-linked glycans, glycosaminoglycans (GAGs), glycosphingolipids (GSLs) and other distinct glycan features such as polysialic acids (PolySia), sulfation and proteoglycan attachment stubs. Various methods are used to analyse these different components of the glycome, but they require pre-fractionated/partitioned samples to target each glycan class individually. To address this need for a knowledge of the relationship between the different glycan components of a biological system, we have developed a sequential release workflow for analysis of multiple conjugated glycan classes (PolySia, GAGs, GSL glycans, N-glycans O-glycans) from the same tissue lysate, termed SSSMuG: Same Sample Sequential Multi-Glycomics. With this sequential glycan release approach, five glycan classes were characterized (or four glycan classes plus proteomics) from a single sample using enzymatic or chemical release from the same spot immobilized on a polyvinylidene difluoride membrane. The various released glycan classes were then analysed by HPLC and/or MS techniques. Compared to single glycan class release approaches, SSSMuG is able to identify more glycans and more proteins with higher intensity analytical peaks and provides a better comparative normalisation of the different glycan classes of the complex glycome.

2024-02-13 | PXD046012 | Pride

miRNA profiling of mature C2C12 myotubes using modified (COS) vs standard (STD) tissue culture conditions

Project description:miRNA profiling comparing modified (COS = Cytokine (low dose), Oxygen (physiological), Stimulation (low frequency electrical)) or standard (STD) culture condtions for 72hrs prior to harvest at day 8 post differentiation. Secondary experiment to assess additional impact of dexamethasone when given in COS conditions. 5 arrays were labeled with same RNA in each channel (self-self hybridisations) to establish parameters for detecting real change for each probe on the arrays.

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Volatile Organic Compound and Proteomics Data from the Same Exhaled Breath Condensate Sample

Project description:Obtaining multiple sample types from the same exhaled breath condensate (EBC) sample can reduce the number of samples needed for diagnostics purposes, allowing for sampling to be completed quicker and making it even easier to collect breath from patients. In this study, we performed analysis for volatile organic compounds (VOCs) and proteins from the same EBC sample. Pooled EBC samples were split into two groups: three samples that utilized immersion thin film-solid phase microextraction (TF-SPME) sampling for VOCs analysis and three samples that did not undergo TF-SPME sampling (non-TF-SPME). All six EBC samples were analyzed using liquid chromatography with tandem mass spectrometry (LC-MS/MS) for proteomics analysis. VOCs were analyzed via two-dimensional gas chromatography-mass spectrometry (GC x GC-MS). One hundred and eighty-four VOCs were found to be more abundant in EBC samples compared to blank or controls. There was no significant difference in the number of proteins detected in the TF-SPME samples compared to the non-TF-SPME samples and 144 of the 206 total unique proteins detected were found in both sample groups. These results indicate that TF-SPME sampling does not negatively affect the number of proteins that can be detected in EBC. This work is a step towards linking VOC and protein data together to obtain multi-omics breath data from a single breath sample.

2025-07-20 | PXD062224 | Pride

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Gene expression analysis between primary keratinocytes and primary dermal fibroblasts obtained from the same skin sample

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2016-09-01 | GSE85803 | GEO

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