Transcriptome-wide identification of A > I RNA editing sites by inosine specific cleavage

Adenosine to inosine (A > I) RNA editing, which is catalyzed by the ADAR family of proteins, is one of the fundamental mechanisms by which transcriptomic diversity is generated. Indeed, a number of genome-wide analyses have shown that A > I editing is not limited to a few mRNAs, as originally thought, but occurs widely across the transcriptome, especially in the brain. Importantly, there is increasing evidence that A > I editing is essential for animal development and nervous system function. To more efficiently characterize the complete catalog of ADAR events in the mammalian transcriptome we developed a high-throughput protocol to identify A > I editing sites, which exploits the capacity of glyoxal to protect guanosine, but not inosine, from RNAse T1 treatment, thus facilitating extraction of RNA fragments with inosine bases at their termini for high-throughput sequencing. Using this method we identified 665 editing sites in mouse brain RNA, including most known sites and suite of novel sites that include nonsynonymous changes to protein-coding genes, hyperediting of genes known to regulate p53, and alterations to non-protein-coding RNAs. This method is applicable to any biological system for the de novo discovery of A > I editing sites, and avoids the complicated informatic and practical issues associated with editing site identification using traditional RNA sequencing data. This approach has the potential to substantially increase our understanding of the extent and function of RNA editing, and thereby to shed light on the role of transcriptional plasticity in evolution, development, and cognition

The relationship between transcription initiation RNAs and CCCTC-binding factor (CTCF) localization

Background: Transcription initiation RNAs (tiRNAs) are nuclear localized 18 nucleotide RNAs derived from sequences immediately downstream of RNA polymerase II (RNAPII) transcription start sites. Previous reports have shown that tiRNAs are intimately correlated with gene expression, RNA polymerase II binding and behaviors, and epigenetic marks associated with transcription initiation, but not elongation. Results: In the present work, we show that tiRNAs are commonly found at genomic CCCTC-binding factor (CTCF) binding sites in human and mouse, and that CTCF sites that colocalize with RNAPII are highly enriched for tiRNAs. To directly investigate the relationship between tiRNAs and CTCF we examined tiRNAs originating near the intronic CTCF binding site in the human tumor suppressor gene, p21 (cyclin-dependent kinase inhibitor 1A gene, also known as CDKN1A). Inhibition of CTCF-proximal tiRNAs resulted in increased CTCF localization and increased p21 expression, while overexpression of CTCF-proximal tiRNA mimics decreased CTCF localization and p21 expression. We also found that tiRNA-regulated CTCF binding influences the levels of trimethylated H3K27 at the alternate upstream p21 promoter, and affects the levels of alternate p21 (p21) transcripts. Extending these studies to another randomly selected locus with conserved CTCF binding we found that depletion of tiRNA alters nucleosome density proximal to sites of tiRNA biogenesis. Conclusions: Taken together, these data suggest that tiRNAs modulate local epigenetic structure, which in turn regulates CTCF localization

Human iPSC-Derived Cerebellar Neurons from a Patient with Ataxia-Telangiectasia Reveal Disrupted Gene Regulatory Networks

Ataxia-telangiectasia (A-T) is a rare genetic disorder caused by loss of function of the ataxia-telangiectasia-mutated kinase and is characterized by a predisposition to cancer, pulmonary disease, immune deficiency and progressive degeneration of the cerebellum. As animal models do not faithfully recapitulate the neurological aspects, it remains unclear whether cerebellar degeneration is a neurodevelopmental or neurodegenerative phenotype. To address the necessity for a human model, we first assessed a previously published protocol for the ability to generate cerebellar neuronal cells, finding it gave rise to a population of precursors highly enriched for markers of the early hindbrain such as EN1 and GBX2, and later more mature cerebellar markers including PTF1α, MATH1, HOXB4, ZIC3, PAX6, and TUJ1. RNA sequencing was used to classify differentiated cerebellar neurons generated from integration-free A-T and control induced pluripotent stem cells. Comparison of RNA sequencing data with datasets from the Allen Brain Atlas reveals in vitro-derived cerebellar neurons are transcriptionally similar to discrete regions of the human cerebellum, and most closely resemble the cerebellum at 22 weeks post-conception. We show that patient-derived cerebellar neurons exhibit disrupted gene regulatory networks associated with synaptic vesicle dynamics and oxidative stress, offering the first molecular insights into early cerebellar pathogenesis of ataxia-telangiectasia

Recessive mutations in POLR1C cause a leukodystrophy by impairing biogenesis of RNA polymerase III

A small proportion of 4H (Hypomyelination, Hypodontia and Hypogonadotropic Hypogonadism) or RNA polymerase III (POLR3)-related leukodystrophy cases are negative for mutations in the previously identified causative genes POLR3A and POLR3B. Here we report eight of these cases carrying recessive mutations in POLR1C, a gene encoding a shared POLR1 and POLR3 subunit, also mutated in some Treacher Collins syndrome (TCS) cases. Using shotgun proteomics and ChIP sequencing, we demonstrate that leukodystrophy-causative mutations, but not TCS mutations, in POLR1C impair assembly and nuclear import of POLR3, but not POLR1, leading to decreased binding to POLR3 target genes. This study is the first to show that distinct mutations in a gene coding for a shared subunit of two RNA polymerases lead to selective modification of the enzymes’ availability leading to two different clinical conditions and to shed some light on the pathophysiological mechanism of one of the most common hypomyelinating leukodystrophies, POLR3-related leukodystrophy

Systematic interrogation of the Conus marmoreus venom duct transcriptome with ConoSorter reveals 158 novel conotoxins and 13 new gene superfamilies

International audienceConopeptides, often generically referred to as conotoxins, are small neurotoxins found in the venom of predatory marine cone snails. These molecules are highly stable and are able to efficiently and selectively interact with a wide variety of heterologous receptors and channels, making them valuable pharmacological probes and potential drug leads. Recent advances in next-generation RNA sequencing and high-throughput proteomics have led to the generation of large data sets that require purpose-built and dedicated bioinformatics tools for efficient data mining

Umberto Eco, Narratives of Conspiracy and the Anti-Semite Among Us

http://www.quest-cdecjournal.it/discussion.php?id=3

Expanding the genotypic spectrum of CCBE1 mutations in Hennekam syndrome

Hennekam lymphangiectasia-lymphedema syndrome is an autosomal recessive disorder, with 25% of patients having mutations in CCBE1. We identified a family with two brothers presenting with primary lymphedema, and performed exome sequencing to determine the cause of their disease. Analysis of four family members showed that both affected brothers had the same rare compound heterozygous mutations in CCBE1. The presumed paternally inherited NM_133459.3:c.310G>A; p.(Asp104Asn), lies adjacent to other known pathogenic CCBE1 mutations, while the maternally inherited NM_133459.3:c.80T>C; p.(Leu27Pro) lies in the CCBE1 signal peptide, which has not previously been associated with disease. Functional analysis in a zebrafish model of lymphatic disease showed that both mutations lead to CCBE1 loss of function, confirming the pathogenicity of these variants and expanding the genotypic spectrum of lymphatic disorders. (c) 2016 Wiley Periodicals, Inc

A transcriptional sketch of a primary human breast cancer by 454 deep sequencing

Background: The cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of "unconventional" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions and deletions have been associated with the tumoral state. Massively parallel sequencing techniques provide a framework for exploring the transcriptional complexity inherent to cancer with a limited laboratory and financial effort. We developed a deep sequencing and bioinformatics analysis protocol to investigate the molecular composition of a breast cancer poly(A)+ transcriptome. This method utilizes a cDNA library normalization step to diminish the representation of highly expressed transcripts and biology-oriented bioinformatic analyses to facilitate detection of rare and novel transcripts. Results: We analyzed over 132,000 Roche 454 high-confidence deep sequencing reads from a primary human lobular breast cancer tissue specimen, and detected a range of unusual transcriptional events that were subsequently validated by RT-PCR in additional eight primary human breast cancer samples. We identified and validated one deletion, two novel ncRNAs (one intergenic and one intragenic), ten previously unknown or rare transcript isoforms and a novel gene fusion specific to a single primary tissue sample. We also explored the non-protein-coding portion of the breast cancer transcriptome, identifying thousands of novel non-coding transcripts and more than three hundred reads corresponding to the non-coding RNA MALAT1, which is highly expressed in many human carcinomas. Conclusion: Our results demonstrate that combining 454 deep sequencing with a normalization step and careful bioinformatic analysis facilitates the discovery and quantification of rare transcripts or ncRNAs, and can be used as a qualitative tool to characterize transcriptome complexity, revealing many hitherto unknown transcripts, splice isoforms, gene fusion events and ncRNAs, even at a relatively low sequence sampling

A clinical approach to the diagnosis of patients with leukodystrophies and genetic leukoencephelopathies

Leukodystrophies (LD) and genetic leukoencephalopathies (gLE) are disorders that result in white matter abnormalities in the central nervous system (CNS). Magnetic resonance (MR) imaging (MRI) has dramatically improved and systematized the diagnosis of LDs and gLEs, and in combination with specific clinical features, such as Addison’s disease in Adrenoleukodystrophy or hypodontia in Pol-III related or 4H leukodystrophy, can often resolve a case with a minimum of testing. The diagnostic odyssey for the majority LD and gLE patients, however, remains extensive – many patients will wait nearly a decade for a definitive diagnosis and at least half will remain unresolved. The combination of MRI, careful clinical evaluation and next generation genetic sequencing holds promise for both expediting the diagnostic process and dramatically reducing the number of unresolved cases. Here we present a workflow detailing the Global Leukodystrophy Initiative (GLIA) consensus recommendations for an approach to clinical diagnosis, including salient clinical features suggesting a specific diagnosis, neuroimaging features and molecular genetic testing. We also discuss recommendations on the use of broad-spectrum next-generation sequencing in instances of ambiguous MRI or clinical findings. We conclude with a proposal for systematic trials of genome-wide agnostic testing as a first line diagnostic in LDs and gLEs given the increasing number of genes associated with these disorders

SEQADAPT: an adaptable system for the tracking, storage and analysis of high throughput sequencing experiments

<p>Abstract</p> <p>Background</p> <p>High throughput sequencing has become an increasingly important tool for biological research. However, the existing software systems for managing and processing these data have not provided the flexible infrastructure that research requires.</p> <p>Results</p> <p>Existing software solutions provide static and well-established algorithms in a restrictive package. However as high throughput sequencing is a rapidly evolving field, such static approaches lack the ability to readily adopt the latest advances and techniques which are often required by researchers. We have used a loosely coupled, service-oriented infrastructure to develop SeqAdapt. This system streamlines data management and allows for rapid integration of novel algorithms. Our approach also allows computational biologists to focus on developing and applying new methods instead of writing boilerplate infrastructure code.</p> <p>Conclusion</p> <p>The system is based around the Addama service architecture and is available at our website as a demonstration web application, an installable single download and as a collection of individual customizable services.</p