Transcriptional profiling of single fiber cells in a transgenic paradigm of an inherited childhood cataract reveals absence of molecular heterogeneity.

Our recent single-cell transcriptomic analysis has demonstrated that heterogeneous transcriptional activity attends molecular transition from the nascent to terminally differentiated fiber cells in the developing mouse lens. To understand the role of transcriptional heterogeneity in terminal differentiation and the functional phenotype (transparency) of this tissue, here we present a single-cell analysis of the developing lens, in a transgenic paradigm of an inherited pathology, known as the lamellar cataract. Cataracts hinder transmission of light into the eye. Lamellar cataract is the most prevalent bilateral childhood cataract. In this disease of early infancy, initially, the opacities remain confined to a few fiber cells, thus presenting an opportunity to investigate early molecular events that lead to cataractogenesis. We used a previously established paradigm that faithfully recapitulates this disease in transgenic mice. About 500 single fiber cells, manually isolated from a 2-day-old transgenic lens were interrogated individually for the expression of all known 17 crystallins and 78 other relevant genes using a Biomark HD (Fluidigm). We find that fiber cells from spatially and developmentally discrete regions of the transgenic (cataract) lens show remarkable absence of the heterogeneity of gene expression. Importantly, the molecular variability of cortical fiber cells, the hallmark of the WT lens, is absent in the transgenic cataract, suggesting absence of specific cell-type(s). Interestingly, we find a repetitive pattern of gene activity in progressive states of differentiation in the transgenic lens. This molecular dysfunction portends pathology much before the physical manifestations of the disease

CRISPR-Mediated VHL Knockout Generates an Improved Model for Metastatic Renal Cell Carcinoma.

Metastatic renal cell carcinoma (mRCC) is nearly incurable and accounts for most of the mortality associated with RCC. Von Hippel Lindau (VHL) is a tumour suppressor that is lost in the majority of clear cell RCC (ccRCC) cases. Its role in regulating hypoxia-inducible factors-1α (HIF-1α) and -2α (HIF-2α) is well-studied. Recent work has demonstrated that VHL knock down induces an epithelial-mesenchymal transition (EMT) phenotype. In this study we showed that a CRISPR/Cas9-mediated knock out of VHL in the RENCA model leads to morphologic and molecular changes indicative of EMT, which in turn drives increased metastasis to the lungs. RENCA cells deficient in HIF-1α failed to undergo EMT changes upon VHL knockout. RNA-seq revealed several HIF-1α-regulated genes that are upregulated in our VHL knockout cells and whose overexpression signifies an aggressive form of ccRCC in the cancer genome atlas (TCGA) database. Independent validation in a new clinical dataset confirms the upregulation of these genes in ccRCC samples compared to adjacent normal tissue. Our findings indicate that loss of VHL could be driving tumour cell dissemination through stabilization of HIF-1α in RCC. A better understanding of the mechanisms involved in this phenomenon can guide the search for more effective treatments to combat mRCC

Algorithms for Transcriptome Quantification and Reconstruction from RNA-Seq Data

Massively parallel whole transcriptome sequencing and its ability to generate full transcriptome data at the single transcript level provides a powerful tool with multiple interrelated applications, including transcriptome reconstruction, gene/isoform expression estimation, also known as transcriptome quantification. As a result, whole transcriptome sequencing has become the technology of choice for performing transcriptome analysis, rapidly replacing array-based technologies. The most commonly used transcriptome sequencing protocol, referred to as RNA-Seq, generates short (single or paired) sequencing tags from the ends of randomly generated cDNA fragments. RNA-Seq protocol reduces the sequencing cost and significantly increases data throughput, but is computationally challenging to reconstruct full-length transcripts and accurately estimate their abundances across all cell types. We focus on two main problems in transcriptome data analysis, namely, transcriptome reconstruction and quantification. Transcriptome reconstruction, also referred to as novel isoform discovery, is the problem of reconstructing the transcript sequences from the sequencing data. Reconstruction can be done de novo or it can be assisted by existing genome and transcriptome annotations. Transcriptome quantification refers to the problem of estimating the expression level of each transcript. We present a genome-guided and annotation-guided transcriptome reconstruction methods as well as methods for transcript and gene expression level estimation. Empirical results on both synthetic and real RNA-seq datasets show that the proposed methods improve transcriptome quantification and reconstruction accuracy compared to previous methods

A STUDY OF STRUCTURAL ELEMENTS OF GOSSIP AMONG FEMALE UNIVERSITY STUDENTS

Abstract. Artikel ini melaporkan penelitian tentang unsur-unsur struktural percakapan dalam gosip. Gosip adalah salah satu jenis percakapan santai dalam satu kelompok yang terjadi dalam kontens informal. Fokus  penelitian adalah menemukan topik dan fungsi gosip di kalangan mahasiswi. Penelitian ini didasarkan atas teori tentang gosip oleh Eggins dan Slade (1997) yang menyatakan bahwa gosip berfungsi untuk membangun dan mempertahankan keanggotaan dalam kelompok dan sebagai salah satu bentuk kontrol sosial. Gosip dapat dianalisis berdasarkan unsur wajib dan pilihannya. Pertanyaan yang diajukan dalam penelitian adalah: (1) apakah topik-topik dalam gosip di kalangan mahasiswi? dan (2) apakah unsur-unsur struktural dalam gosip di kalangan mahasiswi? Penelitian menggunakan ancangan deskriptif kualitatif. Data diperoleh dari percakapan santai antara mahasiswi di dalam tempat kos mereka. Hasil penelitian menunjukkan bahwa ada tiga topik utama dalam gosip di kalangan mahasiswi dan terdapat unsur wajib, pilihan dan tambahan dalam struktur gosip. Keywords: casual conversation, gossip, structural element

ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues.

High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki

Computational strategies for dissecting the high-dimensional complexity of adaptive immune repertoires

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity in order to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic and (iv) machine learning methods applied to dissect, quantify and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology towards coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.Comment: 27 pages, 2 figure

TRIP: A method for novel transcript reconstruction from paired-end RNA-seq reads

Preliminary experimental results on synthetic datasets generated with various sequencing parameters and distribution assumptions show that TRIP has increased transcriptome reconstruction accuracy compared to previous methods that ignore fragment length distribution information

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde