12 research outputs found

    Benchmarking single cell RNA-sequencing analysis pipelines using mixture control experiments

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    Single cell RNA-sequencing (scRNA-seq) technology has undergone rapid development in recent years, leading to an explosion in the number of tailored data analysis methods. However, the current lack of gold-standard benchmark datasets makes it difficult for researchers to systematically compare the performance of the many methods available. Here, we generated a realistic benchmark experiment that included single cells and admixtures of cells or RNA to create 'pseudo cells' from up to five distinct cancer cell lines. In total, 14 datasets were generated using both droplet and plate-based scRNA-seq protocols. We compared 3,913 combinations of data analysis methods for tasks ranging from normalization and imputation to clustering, trajectory analysis and data integration. Evaluation revealed pipelines suited to different types of data for different tasks. Our data and analysis provide a comprehensive framework for benchmarking most common scRNA-seq analysis steps

    Single cell RNA sequencing of stem cell-derived retinal ganglion cells

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    We used single cell sequencing technology to characterize the transcriptomes of 1,174 human embryonic stem cell-derived retinal ganglion cells (RGCs) at the single cell level. The human embryonic stem cell line BRN3B-mCherry (A81-H7), was differentiated to RGCs using a guided differentiation approach. Cells were harvested at day 36 and prepared for single cell RNA sequencing. Our data indicates the presence of three distinct subpopulations of cells, with various degrees of maturity. One cluster of 288 cells showed increased expression of genes involved in axon guidance together with semaphorin interactions, cell-extracellular matrix interactions and ECM proteoglycans, suggestive of a more mature RGC phenotype

    Genome assembly of the Australian black tiger shrimp (<i>Penaeus monodon</i>) reveals a novel fragmented IHHNV EVE sequence

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    AbstractShrimp are a valuable aquaculture species globally; however, disease remains a major hindrance to shrimp aquaculture sustainability and growth. Mechanisms mediated by endogenous viral elements have been proposed as a means by which shrimp that encounter a new virus start to accommodate rather than succumb to infection over time. However, evidence on the nature of such endogenous viral elements and how they mediate viral accommodation is limited. More extensive genomic data on Penaeid shrimp from different geographical locations should assist in exposing the diversity of endogenous viral elements. In this context, reported here is a PacBio Sequel-based draft genome assembly of an Australian black tiger shrimp (Penaeus monodonP. monodo

    A single-cell transcriptome atlas of the adult human retina

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    The retina is a specialized neural tissue that senses light and initiates image processing. Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single-cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, MĂŒller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post-mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult MĂŒller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease

    Fatal Perinatal Mitochondrial Cardiac Failure Caused by Recurrent De Novo Duplications in the ATAD3 Locus

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    Background: In about half of all patients with a suspected monogenic disease, genomic investigations fail to identify the diagnosis. A contributing factor is the difficulty with repetitive regions of the genome, such as those generated by segmental duplications. The ATAD3 locus is one such region in which recessive deletions and dominant duplications have recently been reported to cause lethal perinatal mitochondrial diseases characterized by pontocerebellar hypoplasia or cardiomyopathy, respectively. Methods: Whole-exome, whole-genome, and long-read DNA sequencing techniques combined with studies of RNA and quantitative proteomics were used to investigate 17 subjects from 16 unrelated families with suspected mitochondrial disease. Findings: We report 6 different de novo duplications in the ATAD3 gene locus causing a distinctive presentation, including lethal perinatal cardiomyopathy, persistent hyperlactacidemia, and frequently, corneal clouding or cataracts and encephalopathy. The recurrent 68-kb ATAD3 duplications are identifiable from genome and exome sequencing but usually missed by microarrays. The ATAD3 duplications result in the formation of identical chimeric ATAD3A/ATAD3C proteins, altered ATAD3 complexes, and a striking reduction in mitochondrial oxidative phosphorylation complex I and its activity in heart tissue. Conclusions: ATAD3 duplications appear to act in a dominant-negative manner and the de novo inheritance infers a low recurrence risk for families, unlike most pediatric mitochondrial diseases. More than 350 genes underlie mitochondrial diseases. In our experience, the ATAD3 locus is now one of the five most common causes of nuclear-encoded pediatric mitochondrial disease, but the repetitive nature of the locus means ATAD3 diagnoses may be frequently missed by current genomic strategies. Funding: Australian NHMRC, US Department of Defense, US National Institutes of Health, Japanese AMED and JSPS agencies, Australian Genomics Health Alliance, and Australian Mito Foundation
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