Dwarfism in Fleckvieh cattle
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB12832 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance. The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frame shifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
2013-08-07 | E-ERAD-74 | biostudies-arrayexpress
Project description:This project aims to find causal variants in 50 patients diagnosed with Microcephalic Osteodysplastic Primordial Dwarfism (MOPD), of presumed recessive inheritance performing whole exome sequencing to ~50x mean depth. This is a collaboration with Prof A. Jackson, MRC Human Genetics Unit, Edinburgh
| EGAS00001000064 | EGA
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2017-08-01 | PRJEB21794 | EVA
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Project description:To ensure efficient genome duplication, cells have evolved a multitude of factors that promote unperturbed DNA replication, and protect, repair and restart damaged forks. Here we identify DONSON as a novel fork protection factor, and report biallelic DONSON mutations in individuals with microcephalic dwarfism. We demonstrate that DONSON is a component of the replisome that stabilises forks during normal genome replication. Loss of DONSON leads to severe replication-associated DNA damage arising from nucleolytic cleavage of stalled replication forks. Furthermore, ATR-dependent ,signalling in response to replication stress is impaired in DONSON-deficient cells, resulting in decreased checkpoint activity, and potentiating chromosomal instability. Hypomorphic mutations substantially reduce DONSON protein levels and impair fork stability in patient cells, consistent with defective DNA replication underlying the disease phenotype In summary, we identify mutations in DONSON as a common cause of microcephalic dwarfism, and establish DONSON as a critical replication fork protein required for mammalian DNA replication and genome stability
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2016-11-04 | GSE89519 | GEO
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Project description:Disproportionate short stature refers to a heterogeneous group of hereditary disorders, which are classified according to their mode of inheritance, their clinical skeletal and non-skeletal manifestations, and their radiological characteristics. In the present study, we report on a novel autosomal recessive osteocutaneous disorder that we termed short stature-onychodysplasia-facial dysmorphism-hypotrichosis (SOFT) syndrome. we identified a homozygous point mutation (p.L171P) in POC1A (Centriolar Protein Homolog A). The mutation affects a highly conserved amino acid residue and is predicted to interfere with protein function. To gain insight into the pathomechanisms underlying the deleterious effect of the causative mutation, we compared transcription profiles of patient and control fibroblasts.
2012-08-22 | E-MEXP-3650 | biostudies-arrayexpress
Project description:The transcriptome signature of peripheral blood mononuclear cells (PBMCs) of Ladakhi cattle adapted to high altitude vis a vis Sahiwal cattle adapted to the arid/semi-arid region at mean sea level was established using bovine expression microarray chips. The transcriptome analysis of PBMCs from these cattle types living at two distinct altitudes, resulted in identification of several hundred differentially expressed genes, biological processes, molecular functions and pathways.
2021-07-09 | GSE116800 | GEO
Project description:Transcriptome studies in patients with rare genetic diseases can potentially aid in the
interpretation of likely causal genetic variation through identification of altered transcript
abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating
transcript structure and abundance
The primary aim of this pilot project is to investigate to what degree integrating exome-Seq
and RNA-Seq data on the same individual can accelerate the identification of causal alleles
for rare genetic diseases. There are two main strands to this: (i) identifying which variants
discovered in exome-seq appear to be having a functional impact on transcripts, and (ii)
identifying transcript outliers, especially among known causal genes, that may not necessarily
have a causal variant identified from exome sequencing. The latter may identify the presence
of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites
deep within introns, or loss of long range regulatory elements), which can be confirmed with
further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the
Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.
nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).
This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with
primordial dwarfism syndromes, for 10 of these samples we have previously generate exome
data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining
samples are positive controls where the causal mutation is known, and is known to affect
transcript structure and/or abundance.
Primordial dwarfism is a prime candidate for these RNA-seq studies because all known
causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the
products of the causal genes are typically ubiquitously expressed.
Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per
sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads.
Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.
This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
| EGAS00001000283 | EGA