High throughput isolation of RNA from single-cells within an intact tissue for spatial and temporal sequencing a reality.

Single-cell transcriptomics is essential for understanding biological variability among cells in a heterogenous population. Acquiring high-quality single-cell sequencing data from a tissue sample has multiple challenges including isolation of individual cells as well as amplification of the genetic material. Commercially available techniques require the isolation of individual cells from a tissue through extensive manual manipulation before single cell sequence data can be acquired. However, since cells within a tissue have different dissociation constants, enzymatic and mechanical manipulation do not guarantee the isolation of a homogenous population of cells. To overcome this drawback, in this research we have developed a revolutionary approach that utilizes a fully automated nanopipette technology in combination with magnetic nanoparticles to obtain high quality sequencing reads from individual cells within an intact tissue thereby eliminating the need for manual manipulation and single cell isolation. With the proposed technology, it is possible to sample an individual cell within the tissue multiple times to obtain longitudinal information. Single-cell RNAseq was achieved by aspirating only1-5% of sub-single-cell RNA content from individual cells within fresh frozen tissue samples. As a proof of concept, aspiration was carried out from 22 cells within a breast cancer tissue slice using quartz nanopipettes. The mRNA from the aspirate was then selectively captured using magnetic nanoparticles. The RNAseq data from aspiration of 22 individual cells provided high alignment rates (80%) with 2 control tissue samples. The technology is exceptionally simple, quick and efficient as the entire cell targeting and aspiration process is fully automated.

Predicting Splicing from Primary Sequence with Deep Learning.

The splicing of pre-mRNAs into mature transcripts is remarkable for its precision, but the mechanisms by which the cellular machinery achieves such specificity are incompletely understood. Here, we describe a deep neural network that accurately predicts splice junctions from an arbitrary pre-mRNA transcript sequence, enabling precise prediction of noncoding genetic variants that cause cryptic splicing. Synonymous and intronic mutations with predicted splice-altering consequence validate at a high rate on RNA-seq and are strongly deleterious in the human population. De novo mutations with predicted splice-altering consequence are significantly enriched in patients with autism and intellectual disability compared to healthy controls and validate against RNA-seq in 21 out of 28 of these patients. We estimate that 9%-11% of pathogenic mutations in patients with rare genetic disorders are caused by this previously underappreciated class of disease variation.

Ontology-based meta-analysis of global collections of high-throughput public data.

BACKGROUND: The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today. METHODOLOGY/RESULTS: We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets. CONCLUSIONS: Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.

Dynamic bookmarking of primary response genes by p300 and RNA polymerase II complexes.

Profiling the dynamic interaction of p300 with proximal promoters of human T cells identified a class of genes that rapidly coassemble p300 and RNA polymerase II (pol II) following mitogen stimulation. Several of these p300 targets are immediate early genes, including FOS, implicating a prominent role for p300 in the control of primary genetic responses. The recruitment of p300 and pol II rapidly transitions to the assembly of several elongation factors, including the positive transcriptional elongation factor (P-TEFb), the bromodomain-containing protein (BRD4), and the elongin-like eleven nineteen lysine-rich leukemia protein (ELL). However, transcription at many of these rapidly induced genes is transient, wherein swift departure of P-TEFb, BRD4, and ELL coincides with termination of transcriptional elongation. Unexpectedly, both p300 and pol II remain accumulated or "bookmarked" at the proximal promoter long after transcription has terminated, demarking a clear mechanistic separation between the recruitment and elongation phases of transcription in vivo. The bookmarked pol II is depleted of both serine-2 and serine-5 phosphorylation of its C-terminal domain and remains proximally positioned at the promoter for hours. Surprisingly, these p300/pol II bookmarked genes can be readily reactivated, and elongation factors can be reassembled by subsequent addition of nonmitogenic agents that, alone, have minimal effects on transcription in the absence of prior preconditioning by mitogen stimulation. These findings suggest that p300 is likely to play an important role in biological processes in which transcriptional bookmarking or preconditioning influences cellular growth and development through the dynamic priming of genes for response to rechallenge by secondary stimuli.

Transcriptional networks inferred from molecular signatures of breast cancer.

Global genomic approaches in cancer research have provided new and innovative strategies for the identification of signatures that differentiate various types of human cancers. Computational analysis of the promoter composition of the genes within these signatures may provide a powerful method for deducing the regulatory transcriptional networks that mediate their collective function. In this study we have systematically analyzed the promoter composition of gene classes derived from previously established genetic signatures that recently have been shown to reliably and reproducibly distinguish five molecular subtypes of breast cancer associated with distinct clinical outcomes. Inferences made from the trends of transcription factor binding site enrichment in the promoters of these gene groups led to the identification of regulatory pathways that implicate discrete transcriptional networks associated with specific molecular subtypes of breast cancer. One of these inferred pathways predicted a role for nuclear factor-kappaB in a novel feed-forward, self-amplifying, autoregulatory module regulated by the ERBB family of growth factor receptors. The existence of this pathway was verified in vivo by chromatin immunoprecipitation and shown to be deregulated in breast cancer cells overexpressing ERBB2. This analysis indicates that approaches of this type can provide unique insights into the differential regulatory molecular programs associated with breast cancer and will aid in identifying specific transcriptional networks and pathways as potential targets for tumor subtype-specific therapeutic intervention.

[Gene expression profile of human normal gastrointestinal tract tissues: bioinformatic study].

AIM: To identify up-regulated genes specific to human normal gastrointestinal tissues. METHODS: Study was made on human normal tissue gene expression database open to the public. Tissue-specific genes were identified using one-tailed student T test. Online software including Ingenuity and KEGG were applied for physiological function analyses. Unsupervised two-way hierarchical clustering method was used to analyze the expression profile of stomach-specific genes in gastric cancer gene expression datasets. RESULTS: The analyses identified 196 stomach-specific genes, 203 ileum-specific genes and 224 colon-specific genes, respectively. The gene expression profiles reflect major organ-specific physiological functions on the molecular level. Some putative oncogenes and tumor suppressor genes were found in the tissue-specific gene list. Hierarchical clustering analysis revealed that the stomach-specific genes were up-regulated in normal stomach tissues but down-regulated in stomach cancer tissues. The normal tissues clustered together, so did the cancer tissues. At the meantime, clustering could also distinguish the moderate and severe differentiated stomach cancer. CONCLUSION: Human normal stomach, ileum and colon possess tissue-specific up-regulated genes, which are closely associated with physiological functions.

qPrimerDepot: a primer database for quantitative real time PCR.

Gene expression studies employing high throughput real time PCR methods require finding uniform conditions for optimal amplification of multiple targets, often a daunting task. We developed a primer database, qPrimerDepot, which provides optimized primers for all human and mouse RefSeq genes. These primers are designed to amplify desired templates under unified annealing temperature. For most intron-bearing genes, primers flank one of the largest introns thus minimizing background noise due to genomic DNA contamination. The qPrimerDepot database can be accessed at http://primerdepot.nci.nih.gov/ and http://mouseprimerdepot.nci.nih.gov/.

Selective leukemic-cell killing by a novel functional class of thalidomide analogs.

Using a novel cell-based assay to profile transcriptional pathway targeting, we have identified a new functional class of thalidomide analogs with distinct and selective antileukemic activity. These agents activate nuclear factor of activated T cells (NFAT) transcriptional pathways while simultaneously repressing nuclear factor-kappaB (NF-kappaB) via a rapid intracellular amplification of reactive oxygen species (ROS). The elevated ROS is associated with increased intracellular free calcium, rapid dissipation of the mitochondrial membrane potential, disrupted mitochondrial structure, and caspase-independent cell death. This cytotoxicity is highly selective for transformed lymphoid cells, is reversed by free radical scavengers, synergizes with the antileukemic activity of other redox-directed compounds, and preferentially targets cells in the S phase of the cell cycle. Live-cell imaging reveals a rapid drug-induced burst of ROS originating in the endoplasmic reticulum and associated mitochondria just prior to spreading throughout the cell. As members of a novel functional class of "redoxreactive" thalidomides, these compounds provide a new tool through which selective cellular properties of redox status and intracellular bioactivation can be leveraged by rational combinatorial therapeutic strategies and appropriate drug design to exploit cell-specific vulnerabilities for maximum drug efficacy.

Human promoter genomic composition demonstrates non-random groupings that reflect general cellular function.

BACKGROUND: The purpose of this study is to determine whether or not there exists nonrandom grouping of cis-regulatory elements within gene promoters that can be perceived independent of gene expression data and whether or not there is any correlation between this grouping and the biological function of the gene. RESULTS: Using ProSpector, a web-based promoter search and annotation tool, we have applied an unbiased approach to analyze the transcription factor binding site frequencies of 1400 base pair genomic segments positioned at 1200 base pairs upstream and 200 base pairs downstream of the transcriptional start site of 7298 commonly studied human genes. Partitional clustering of the transcription factor binding site composition within these promoter segments reveals a small number of gene groups that are selectively enriched for gene ontology terms consistent with distinct aspects of cellular function. Significance ranking of the class-determining transcription factor binding sites within these clusters show substantial overlap between the gene ontology terms of the transcriptions factors associated with the binding sites and the gene ontology terms of the regulated genes within each group. CONCLUSION: Thus, gene sorting by promoter composition alone produces partitions in which the "regulated" and the "regulators" cosegregate into similar functional classes. These findings demonstrate that the transcription factor binding site composition is non-randomly distributed between gene promoters in a manner that reflects and partially defines general gene class function.

Ectopic Pax6 expression disturbs lens fiber cell differentiation.

PURPOSE: Pax6 is a transcription factor necessary for the specification and subsequent formation of the ocular lens. It is expressed in all lens cells at early stages of development. After lens formation, Pax6 expression is maintained in the lens epithelium, whereas its level abruptly decreases in differentiated fiber cells. This study is to test the hypothesis that normal fiber cell differentiation would be perturbed by sustained Pax6 expression. METHODS: Transgenic mice expressing the canonical form of mouse Pax6 were created under the control of a modified mouse alphaA-crystallin promoter. The phenotypic changes in the transgenic lens were analyzed by light and electron microscopy. The effect of ectopic Pax6 expression on the lens fiber cells was investigated by in situ hybridization, immunohistochemical staining, real-time reverse transcriptase-polymerase chain reaction (RT-PCR), and two-dimensional (2-D) gel electrophoresis. RESULTS: Transgenic mice from seven different lines all had cataracts with severity that correlated with the transgene expression level in lens fiber cells. In severely affected lines, a lumen was present between the apical surfaces of the epithelial and fiber cells, suggesting that secondary fiber cell elongation is incomplete. Electron microscopy analysis showed that the ball-and-socket interdigitations between neighboring fiber cells were underdeveloped or attenuated in the transgenic lens. Most interesting, elevated levels of Pax6 in fiber cells reduced the protein levels of transcription factor cMaf, which is known to be essential in fiber cell differentiation. Furthermore, the total amount of lens proteins was 60% less than normal in the Pax6 transgenic lens. Among the crystallins examined, the relative ratio of intact betaB1-crystallin protein to total lens protein was significantly reduced. Real-time reverse transcriptase PCR showed that the ratio of betaB1-crystallin transcript levels to total mRNA levels were reduced by 87%. CONCLUSIONS: The data demonstrate that high levels of Pax6 expression disrupt normal fiber cell differentiation and maturation.

OptiRNAi, an RNAi design tool.

RNA interference (RNAi), a recently developed reverse genetics tool, has many advantages compared to traditional gene knockout methods. Appropriate selection of double stranded RNAs identical to a specific region(s) of the target gene is critical for the successful implementation of this technology. Recently, Elbashir et al. [Methods 26 (2002) 199] has established empirical criteria for siRNA sequence selection that significantly improved the success rate for RNAi attempts. We have developed OptiRNAi, a computational tool, which uses the Elbashir et al. criteria to predict appropriate target sequences for siRNA production. Specificity of these siRNAs for the target of interest can then be assessed by the investigator using the embedded Blast search engine optimized for RNAi design. Thus, OptiRNAi is an efficient and user friendly tool for RNAi design based on criteria that are more stringent than other available tools.

Mafs, Prox1, and Pax6 can regulate chicken betaB1-crystallin gene expression.

During lens fiber cell differentiation, the regulation of crystallin gene expression is coupled with dramatic morphological changes. Here we report that Mafs, Prox1, and Pax6, which are essential transcription factors for normal lens development, bind to three functionally important cis elements, PL1, PL2, and OL2, in the chicken betaB1-crystallin promoter and may cooperatively direct the transcription of this lens fiber cell preferred gene. Gel shift assays demonstrated that Mafs bind to the MARE-like sequences in the PL1 and PL2 elements, whereas Prox1, a sequence-specific DNA-binding protein like its Drosophila homolog Prospero, interacts with the OL2 element. Furthermore, Pax6, a known repressor of the chicken betaB1-crystallin promoter, binds to all three of these cis elements. In transfection assays, Mafs and Prox1 activated the chicken betaB1-crystallin promoter; however, their transactivation ability was repressed when co-transfected with Pax6. Taken together with the known spatiotemporal expression patterns of Mafs, Prox1, and Pax6 in the developing lens, we propose that Pax6 occupies and represses the chicken betaB1-crystallin promoter in lens epithelial cells, and is displaced by Prox1 and Mafs, which activate the promoter, in differentiating cortical fiber cells.

Prox1 is differentially localized during lens development.

Prox1, the vertebrate cognate of Drosophila Prospero, is a homeodomain protein essential for the development of the lens, liver and lymphatic system. While it is well established that the subcellular distribution of Prospero changes during development, this had not been demonstrated for Prox1. Here, high-resolution confocal microscopy demonstrated that Prox1 protein is predominately cytoplasmic in the lens placode as well as the lens epithelium and germinative zone throughout development. However during fiber cell differentiation, Prox1 protein redistributes to cell nuclei. Finally, as lens fiber cells condense their chromatin in response to lens denucleation, Prox1 remains in the nucleus but does not appear to interact with DNA. Thus, it appears that the function of Prox1, like that of its Drosophila cognate Prospero, is at least partially controlled by changes in its subcellular distribution during development.