Using normalization to resolve RNA-Seq biases caused by amplification from minimal input

An RNA-seq time series of the medaka pituitary gland during sexual maturation

Directing both organismal homeostasis and physiological adaptation, the pituitary is a key endocrine gland in all vertebrates. One of its major tasks is to coordinate sexual maturation through the production and release of hormones stimulating gonad development. In order to study its developmental dynamics in the model fish medaka (Oryzias latipes), we sampled both the pituitary and the ovaries of 68 female fish. Of these, 55 spanned the entire course of sexual maturation from prepubertal juveniles to spawning adults. An additional 13 showed either considerably faster or slower growth and development than the majority of fish. We used histological examination of the ovaries to determine a histological maturation stage, and analyzed the pituitary glands using RNA-seq optimized for low input. Taken together, these data reveal the timing of hormone production priorities, and form a comprehensive resource for the study of their regulation.

LAFITE Reveals the Complexity of Transcript Isoforms in Subcellular Fractions

Characterization of the subcellular distribution of RNA is essential for understanding the molecular basis of biological processes. Here, the subcellular nanopore direct RNA-sequencing (DRS) of four lung cancer cell lines (A549, H1975, H358, and HCC4006) is performed, coupled with a computational pipeline, Low-abundance Aware Full-length Isoform clusTEr (LAFITE), to comprehensively analyze the full-length cytoplasmic and nuclear transcriptome. Using additional DRS and orthogonal data sets, it is shown that LAFITE outperforms current methods for detecting full-length transcripts, particularly for low-abundance isoforms that are usually overlooked due to poor read coverage. Experimental validation of six novel isoforms exclusively identified by LAFITE further confirms the reliability of this pipeline. By applying LAFITE to subcellular DRS data, the complexity of the nuclear transcriptome is revealed in terms of isoform diversity, 3'-UTR usage, m6A modification patterns, and intron retention. Overall, LAFITE provides enhanced full-length isoform identification and enables a high-resolution view of the RNA landscape at the isoform level.

Characterization of hormone-producing cell types in the teleost pituitary gland using single-cell RNA-seq

The pituitary is the vertebrate endocrine gland responsible for the production and secretion of several essential peptide hormones. These, in turn, control many aspects of an animal’s physiology and development, including growth, reproduction, homeostasis, metabolism, and stress responses. In teleost fish, each hormone is presumably produced by a specific cell type. However, key details on the regulation of, and communication between these cell types remain to be resolved. We have therefore used single-cell sequencing to generate gene expression profiles for 2592 and 3804 individual cells from the pituitaries of female and male adult medaka (Oryzias latipes), respectively. Based on expression profile clustering, we define 15 and 16 distinct cell types in the female and male pituitary, respectively, of which ten are involved in the production of a single peptide hormone. Collectively, our data provide a high-quality reference for studies on pituitary biology and the regulation of hormone production, both in fish and in vertebrates in general.

Measurement(s)	RNA-seq gene expression profiling assay
Technology Type(s)	tag based single cell RNA sequencing
Factor Type(s)	sex
Sample Characteristic - Organism	Oryzias latipes
Sample Characteristic - Environment	fresh water aquarium

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16592621

Differential Expression Analysis of RNA-seq Reads: Overview, Taxonomy, and Tools

Analysis of RNA-sequence (RNA-seq) data is widely used in transcriptomic studies and it has many applications. We review RNA-seq data analysis from RNA-seq reads to the results of differential expression analysis. In addition, we perform a descriptive comparison of tools used in each step of RNA-seq data analysis along with a discussion of important characteristics of these tools. A taxonomy of tools is also provided. A discussion of issues in quality control and visualization of RNA-seq data is also included along with useful tools. Finally, we provide some guidelines for the RNA-seq data analyst, along with research issues and challenges which should be addressed.

Plasticity of Lh cells caused by cell proliferation and recruitment of existing cells

Luteinizing hormone (Lh) and follicle-stimulating hormone (Fsh) control reproduction in vertebrates. Using a transgenic line of medaka, in which green fluorescent protein expression is controlled by the endogenous lhb promotor, we studied development and plasticity of Lh cells, comparing juveniles and adults of both genders. Confocal imaging and 3D reconstruction revealed hypertrophy and hyperplasia of Lh cells in both genders from juvenile to adult stages. We show that Lh cell hyperplasia may be caused by recruitment of existing pituitary cells that start to produce lhb, as evidenced by time lapse recordings of primary pituitary cell cultures, and/or through Lh cell proliferation, demonstrated through a combination of 5-bromo-2'-deoxyuridine incubation experiments and proliferating cell nuclear antigen staining. Proliferating Lh cells do not belong to the classical type of multipotent stem cells, as they do not stain with anti-sox2. Estradiol exposure in vivo increased pituitary cell proliferation, particularly Lh cells, whereas pituitary lhb and gpa expression levels decreased. RNA-seq and in situ hybridization showed that Lh cells express two estrogen receptors, esr1 and esr2b, and the aromatase gene cyp19a1b, suggesting a direct effect of estradiol, and possibly androgens, on Lh cell proliferation. In conclusion, our study reveals a high degree of plasticity in the medaka Lh cell population, resulting from a combination of recruitment and cell proliferation.

A full-body transcriptome and proteome resource for the European common carp

Background

The common carp (Cyprinus carpio) is the oldest, most domesticated and one of the most cultured fish species for food consumption. Besides its economic importance, the common carp is also highly suitable for comparative physiological and disease studies in combination with the animal model zebrafish (Danio rerio). They are genetically closely related but offer complementary benefits for fundamental research, with the large body mass of common carp presenting possibilities for obtaining sufficient cell material for advanced transcriptome and proteome studies.

Results

Here we have used 19 different tissues from an F1 hybrid strain of the common carp to perform transcriptome analyses using RNA-Seq. For a subset of the tissues we also have performed deep proteomic studies. As a reference, we updated the European common carp genome assembly using low coverage Pacific Biosciences sequencing to permit high-quality gene annotation. These annotated gene lists were linked to zebrafish homologs, enabling direct comparisons with published datasets. Using clustering, we have identified sets of genes that are potential selective markers for various types of tissues. In addition, we provide a script for a schematic anatomical viewer for visualizing organ-specific expression data.

Conclusions

The identified transcriptome and proteome data for carp tissues represent a useful resource for further translational studies of tissue-specific markers for this economically important fish species that can lead to new markers for organ development. The similarity to zebrafish expression patterns confirms the value of common carp as a resource for studying tissue-specific expression in cyprinid fish. The availability of the annotated gene set of common carp will enable further research with both applied and fundamental purposes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3038-y) contains supplementary material, which is available to authorized users.

Identified lhb-expressing cells from medaka (Oryzias latipes) show similar Ca(2+)-response to all endogenous Gnrh forms, and reveal expression of a novel fourth Gnrh receptor

We have previously characterized the response to gonadotropin-releasing hormone (Gnrh) 2 in luteinizing hormone (lhb)-expressing cells from green fluorescent protein (Gfp)-transgenic medaka (Oryzias latipes), with regard to changes in the cytosolic Ca(2+) concentration. In the current study we present the corresponding responses to Gnrh1 and Gnrh3. Ca(2+) imaging revealed three response patterns to Gnrh1 and Gnrh3, one monophasic and two types of biphasic patterns. There were few significant differences in the shape of the response patterns between the three Gnrh forms, although the amplitude of the Ca(2+) signal was considerably lower for Gnrh1 and Gnrh3 than for Gnrh2, and the distribution between the two different biphasic patterns differed. The different putative Ca(2+) sources were examined by depleting intracellular Ca(2+) stores with thapsigargin, or preventing influx of extracellular Ca(2+) by either extracellular Ca(2+) depletion or the L-type Ca(2+)-channel blocker verapamil. Both Gnrh1 and 3 relied on Ca(2+) from both intracellular and extracellular sources, with some unexpected differences in the relative contribution. Furthermore, gene expression of Gnrh-receptors (gnrhr) in whole pituitaries was studied during development from juvenile to adult. Only two of the four identified medaka receptors were expressed in the pituitary, gnrhr1b and gnrhr2a, with the newly discovered gnrhr2a showing the highest expression level at all stages as analyzed by quantitative PCR. While both receptors differed in expression level according to developmental stage, only the expression of gnrhr2a showed a clear-cut increase with gonadal maturation. RNA sequencing analysis of FACS-sorted Gfp-positive lhb-cells revealed that both gnrhr1b and gnrhr2a were expressed in lhb-expressing cells, and confirmed the higher expression of gnrhr2a compared to gnrhr1b. These results show that although lhb-expressing gonadotropes in medaka show similar Ca(2+) response patterns to all three endogenous Gnrh forms through the activation of two different receptors, gnrhr1b and gnrhr2a, the differences observed between the Gnrh forms indicate activation of different Ca(2+) signaling pathways.

Advanced Applications of RNA Sequencing and Challenges

Next-generation sequencing technologies have revolutionarily advanced sequence-based research with the advantages of high-throughput, high-sensitivity, and high-speed. RNA-seq is now being used widely for uncovering multiple facets of transcriptome to facilitate the biological applications. However, the large-scale data analyses associated with RNA-seq harbors challenges. In this study, we present a detailed overview of the applications of this technology and the challenges that need to be addressed, including data preprocessing, differential gene expression analysis, alternative splicing analysis, variants detection and allele-specific expression, pathway analysis, co-expression network analysis, and applications combining various experimental procedures beyond the achievements that have been made. Specifically, we discuss essential principles of computational methods that are required to meet the key challenges of the RNA-seq data analyses, development of various bioinformatics tools, challenges associated with the RNA-seq applications, and examples that represent the advances made so far in the characterization of the transcriptome.

QoRTs: a comprehensive toolset for quality control and data processing of RNA-Seq experiments

BACKGROUND

High-throughput next-generation RNA sequencing has matured into a viable and powerful method for detecting variations in transcript expression and regulation. Proactive quality control is of critical importance as unanticipated biases, artifacts, or errors can potentially drive false associations and lead to flawed results.

RESULTS

We have developed the Quality of RNA-Seq Toolset, or QoRTs, a comprehensive, multifunction toolset that assists in quality control and data processing of high-throughput RNA sequencing data.

CONCLUSIONS

QoRTs generates an unmatched variety of quality control metrics, and can provide cross-comparisons of replicates contrasted by batch, biological sample, or experimental condition, revealing any outliers and/or systematic issues that could drive false associations or otherwise compromise downstream analyses. In addition, QoRTs simultaneously replaces the functionality of numerous other data-processing tools, and can quickly and efficiently generate quality control metrics, coverage counts (for genes, exons, and known/novel splice-junctions), and browser tracks. These functions can all be carried out as part of a single unified data-processing/quality control run, greatly reducing both the complexity and the total runtime of the analysis pipeline. The software, source code, and documentation are available online at http://hartleys.github.io/QoRTs.