Gene-knockdown in the honey bee mite Varroa destructor by a non-invasive approach : studies on a glutathione S-transferase

Peer reviewedPublisher PD

RNA interference in marine and freshwater sponges

Background: The marine sponge Tethya wilhelma and the freshwater sponge Ephydatia muelleri are emerging model organisms to study evolution, gene regulation, development, and physiology in non-bilaterian animal systems. Thus far, functional methods (i.e., loss or gain of function) for these organisms have not been available. Results: We show that soaking developing freshwater sponges in double-stranded RNA and/or feeding marine and freshwater sponges bacteria expressing double-stranded RNA can lead to RNA interference and reduction of targeted transcript levels. These methods, first utilized in C. elegans, have been adapted for the development and feeding style of easily cultured marine and freshwater poriferans. We demonstrate phenotypic changes result from ‘knocking down’ expression of the actin gene. Conclusion: This technique provides an easy, efficient loss-of-function manipulation for developmental and gene regulatory studies in these important non-bilaterian animals

The Application of CRISPR Technology to High Content Screening in Primary Neurons

Axon growth is coordinated by multiple interacting proteins that remain incompletely characterized. High content screening (HCS), in which manipulation of candidate genes is combined with rapid image analysis of phenotypic effects, has emerged as a powerful technique to identify key regulators of axon outgrowth. Here we explore the utility of a genome editingapproach referred to as CRISPR (Clustered Regularly Interspersed Palindromic Repeats) for knockout screening in primary neurons. In the CRISPR approach a DNA-cleaving Cas enzyme is guided to genomic target sequences by user-created guide RNA (sgRNA), where it initiates a double-stranded break that ultimately results in frameshift mutation and loss of protein production. Using electroporation of plasmid DNA that co-expresses Cas9enzyme and sgRNA, we first verified the ability of CRISPR targeting to achieve protein-level knockdown in cultured postnatal cortical neurons. Targeted proteins included NeuN (RbFox3) and PTEN, a well-studied regulator of axon growth. Effective knockdown lagged at least four days behind transfection, but targeted proteins were eventually undetectable by immunohistochemistry in \u3e 80% of transfected cells. Consistent with this, anti-PTEN sgRNA produced no changes in neurite outgrowth when assessed three days post-transfection. When week-long cultures were replated, however, PTEN knockdown consistently increased neurite lengths. These CRISPR-mediated PTEN effects were achieved using multi-well transfection and automated phenotypic analysis, indicating the suitability of PTEN as a positive control for future CRISPR-based screening efforts. Combined, these data establish an example of CRISPR-mediated protein knockdown in primary cortical neurons and its compatibility with HCS workflows

Long non-coding RNAs in cutaneous melanoma : clinical perspectives

Metastatic melanoma of the skin has a high mortality despite the recent introduction of targeted therapy and immunotherapy. Long non-coding RNAs (lncRNAs) are defined as transcripts of more than 200 nucleotides in length that lack protein-coding potential. There is growing evidence that lncRNAs play an important role in gene regulation, including oncogenesis. We present 13 lncRNA genes involved in the pathogenesis of cutaneous melanoma through a variety of pathways and molecular interactions. Some of these lncRNAs are possible biomarkers or therapeutic targets for malignant melanoma

Viral Vector-based Improvement of Optic Nerve Regeneration: Characterization of Individual Axons\u27 Growth Patterns and Synaptogenesis in a Visual Target

Lack of axon growth ability in the central nervous system poses a major barrier to achieving functional connectivity after injury. Thus, a non-transgenic regenerative approach to reinnervating targets has important implications in clinical and research settings. Previous studies using knockout (KO) mice have demonstrated long distance axon regeneration. Using an optic nerve injury model, here we evaluate the efficacy of viral, RNAi and pharmacological approaches that target the PTEN and STAT3 pathways to improve long distance axon regeneration in wild type (WT) mice. Our data show that adeno-associated virus (AAV) expressing short hairpin RNA (shRNA) against PTEN (shPTEN) enhances retinal ganglion cell axon regeneration after crush injury. However, compared to the previous data in PTEN KO mice, AAV-shRNA results in a lesser degree of regeneration, likely due to incomplete gene silencing inherent to RNAi. In comparison, an extensive enhancement in regeneration is seen when AAV-shPTEN is coupled to AAV encoding ciliary neurotrophic factor (CNTF) and to a cyclic adenosine monophosphate (cAMP) analogue, allowing axons to travel long distances and reach their target. We apply whole tissue imaging that facilitates three-dimensional visualization of single regenerating axons and document heterogeneous terminal patterns in the targets. This shows that some axonal populations generate extensive arbors and make synapses with the target neurons. Collectively, we show a combinatorial viral RNAi and pharmacological strategy that improves long distance regeneration in WT animals and provide single fiber projection data that indicates a degree of preservation of target recognition

A Posterior Probability Approach for Gene Regulatory Network Inference in Genetic Perturbation Data

Inferring gene regulatory networks is an important problem in systems biology. However, these networks can be hard to infer from experimental data because of the inherent variability in biological data as well as the large number of genes involved. We propose a fast, simple method for inferring regulatory relationships between genes from knockdown experiments in the NIH LINCS dataset by calculating posterior probabilities, incorporating prior information. We show that the method is able to find previously identified edges from TRANSFAC and JASPAR and discuss the merits and limitations of this approach

GeneFishing to reconstruct context specific portraits of biological processes.

Rapid advances in genomic technologies have led to a wealth of diverse data, from which novel discoveries can be gleaned through the application of robust statistical and computational methods. Here, we describe GeneFishing, a semisupervised computational approach to reconstruct context-specific portraits of biological processes by leveraging gene-gene coexpression information. GeneFishing incorporates multiple high-dimensional statistical ideas, including dimensionality reduction, clustering, subsampling, and results aggregation, to produce robust results. To illustrate the power of our method, we applied it using 21 genes involved in cholesterol metabolism as "bait" to "fish out" (or identify) genes not previously identified as being connected to cholesterol metabolism. Using simulation and real datasets, we found that the results obtained through GeneFishing were more interesting for our study than those provided by related gene prioritization methods. In particular, application of GeneFishing to the GTEx liver RNA sequencing (RNAseq) data not only reidentified many known cholesterol-related genes, but also pointed to glyoxalase I (GLO1) as a gene implicated in cholesterol metabolism. In a follow-up experiment, we found that GLO1 knockdown in human hepatoma cell lines increased levels of cellular cholesterol ester, validating a role for GLO1 in cholesterol metabolism. In addition, we performed pantissue analysis by applying GeneFishing on various tissues and identified many potential tissue-specific cholesterol metabolism-related genes. GeneFishing appears to be a powerful tool for identifying related components of complex biological systems and may be used across a wide range of applications

Challenges in identifying cancer genes by analysis of exome sequencing data.

Massively parallel sequencing has permitted an unprecedented examination of the cancer exome, leading to predictions that all genes important to cancer will soon be identified by genetic analysis of tumours. To examine this potential, here we evaluate the ability of state-of-the-art sequence analysis methods to specifically recover known cancer genes. While some cancer genes are identified by analysis of recurrence, spatial clustering or predicted impact of somatic mutations, many remain undetected due to lack of power to discriminate driver mutations from the background mutational load (13-60% recall of cancer genes impacted by somatic single-nucleotide variants, depending on the method). Cancer genes not detected by mutation recurrence also tend to be missed by all types of exome analysis. Nonetheless, these genes are implicated by other experiments such as functional genetic screens and expression profiling. These challenges are only partially addressed by increasing sample size and will likely hold even as greater numbers of tumours are analysed

The Functional Consequences of Variation in Transcription Factor Binding

One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This combination of data allowed us to infer functional TF binding. On average, 14.7% of genes bound by a factor were differentially expressed following the knockdown of that factor, suggesting that most interactions between TF and chromatin do not result in measurable changes in gene expression levels of putative target genes. We found that functional TF binding is enriched in regulatory elements that harbor a large number of TF binding sites, at sites with predicted higher binding affinity, and at sites that are enriched in genomic regions annotated as active enhancers.Comment: 30 pages, 6 figures (7 supplemental figures and 6 supplemental tables available upon request to [email protected]). Submitted to PLoS Genetic