Sctensor detects many-to-many cell-cell interactions from single cell RNA-sequencing data

BACKGROUND

Complex biological systems are described as a multitude of cell-cell interactions (CCIs). Recent single-cell RNA-sequencing studies focus on CCIs based on ligand-receptor (L-R) gene co-expression but the analytical methods are not appropriate to detect many-to-many CCIs.

RESULTS

In this work, we propose scTensor, a novel method for extracting representative triadic relationships (or hypergraphs), which include ligand-expression, receptor-expression, and related L-R pairs.

CONCLUSIONS

Through extensive studies with simulated and empirical datasets, we have shown that scTensor can detect some hypergraphs that cannot be detected using conventional CCI detection methods, especially when they include many-to-many relationships. scTensor is implemented as a freely available R/Bioconductor package.

Distinctiveness and continuity in transcriptome and connectivity in the anterior-posterior axis of the paraventricular nucleus of the thalamus

The paraventricular nucleus of the thalamus (PVT) projects axons to multiple areas, mediates a wide range of behaviors, and exhibits regional heterogeneity in both functions and axonal projections. Still, questions regarding the cell types present in the PVT and the extent of their differences remain inadequately addressed. We applied single-cell RNA sequencing to depict the transcriptomic characteristics of mouse PVT neurons. We found that one of the most significant variances in the PVT transcriptome corresponded to the anterior-posterior axis. While the single-cell transcriptome classified PVT neurons into five types, our transcriptomic and histological analyses showed continuity among the cell types. We discovered that anterior and posterior subpopulations had nearly non-overlapping projection patterns, while another population showed intermediate patterns. In addition, these subpopulations responded differently to appetite-related neuropeptides, with their activation showing opposing effects on food consumption. Our studies unveiled the contrasts and the continuity of PVT neurons that underpin their function.

WUSCHEL-RELATED HOMEOBOX 13 suppresses de novo shoot regeneration via cell fate control of pluripotent callus

Plants can regenerate their bodies via de novo establishment of shoot apical meristems (SAMs) from pluripotent callus. Only a small fraction of callus cells is eventually specified into SAMs but the molecular mechanisms underlying fate specification remain obscure. The expression of WUSCHEL (WUS) is an early hallmark of SAM fate acquisition. Here, we show that a WUS paralog, WUSCHEL-RELATED HOMEOBOX 13 (WOX13), negatively regulates SAM formation from callus in Arabidopsis thaliana. WOX13 promotes non-meristematic cell fate via transcriptional repression of WUS and other SAM regulators and activation of cell wall modifiers. Our Quartz-Seq2-based single cell transcriptome revealed that WOX13 plays key roles in determining cellular identity of callus cell population. We propose that reciprocal inhibition between WUS and WOX13 mediates critical cell fate determination in pluripotent cell population, which has a major impact on regeneration efficiency.

Single-cell transcriptomics uncovers EGFR signaling-mediated gastric progenitor cell differentiation in stomach homeostasis

Defects in gastric progenitor cell differentiation are associated with various gastric disorders, including atrophic gastritis, intestinal metaplasia, and gastric cancer. However, the mechanisms underlying the multilineage differentiation of gastric progenitor cells during healthy homeostasis remain poorly understood. Here, using a single-cell RNA sequencing method, Quartz-Seq2, we analyzed the gene expression dynamics of progenitor cell differentiation toward pit cell, neck cell, and parietal cell lineages in healthy adult mouse corpus tissues. Enrichment analysis of pseudotime-dependent genes and a gastric organoid assay revealed that EGFR-ERK signaling promotes pit cell differentiation, whereas NF-κB signaling maintains gastric progenitor cells in an undifferentiated state. In addition, pharmacological inhibition of EGFR in vivo resulted in a decreased number of pit cells. Although activation of EGFR signaling in gastric progenitor cells has been suggested as one of the major inducers of gastric cancers, our findings unexpectedly identified that EGFR signaling exerts a differentiation-promoting function, not a mitogenic function, in normal gastric homeostasis.

WormTensor: a clustering method for time-series whole-brain activity data from C. elegans

BACKGROUND

In the field of neuroscience, neural modules and circuits that control biological functions have been found throughout entire neural networks. Correlations in neural activity can be used to identify such neural modules. Recent technological advances enable us to measure whole-brain neural activity with single-cell resolution in several species including [Formula: see text]. Because current neural activity data in C. elegans contain many missing data points, it is necessary to merge results from as many animals as possible to obtain more reliable functional modules.

RESULTS

In this work, we developed a new time-series clustering method, WormTensor, to identify functional modules using whole-brain activity data from C. elegans. WormTensor uses a distance measure, modified shape-based distance to account for the lags and the mutual inhibition of cell-cell interactions and applies the tensor decomposition algorithm multi-view clustering based on matrix integration using the higher orthogonal iteration of tensors (HOOI) algorithm (MC-MI-HOOI), which can estimate both the weight to account for the reliability of data from each animal and the clusters that are common across animals.

CONCLUSION

We applied the method to 24 individual C. elegans and successfully found some known functional modules. Compared with a widely used consensus clustering method to aggregate multiple clustering results, WormTensor showed higher silhouette coefficients. Our simulation also showed that WormTensor is robust to contamination from noisy data. WormTensor is freely available as an R/CRAN package https://cran.r-project.org/web/packages/WormTensor .

Maternal epigenetic factors in embryonic and postnatal development

Maternal factors present in oocytes and surrounding granulosa cells influence early development of embryos. In this study, we searched for epigenetic regulators that are expressed in oocytes and/or granulosa cells. Some of the 120 epigenetic regulators examined were expressed specifically in oocytes and/or granulosa cells. When their expression was examined in young versus aged oocytes or granulosa cells, many were significantly up- or downregulated in aged cells. The maternal role of six genes in development was investigated by generating oocyte-specific knock-out (MKO) mice. Two genes (Mllt10, Kdm2b) did not show maternal effects on later development, whereas maternal effects were evident for Kdm6a, Kdm4a, Prdm3, and Prdm16 for MKO female mice. Offspring from Kdm6a MKO mice underwent perinatal lethality at a higher rate. Pups derived from Prdm3;Prdm16 double MKO showed a higher incidence of postnatal death. Finally, embryos derived from Kdm4a MKO mice showed early developmental defects as early as the peri-implantation stage. These results suggest that many of maternal epigenetic regulators undergo differential expression upon aging. Some, such as Kdm4a, Kdm6a, Prdm3, and Prdm16, have maternal role in later embryonic or postnatal development. This article is protected by copyright. All rights reserved.

Single-oocyte transcriptome analysis reveals aging-associated effects influenced by life stage and calorie restriction

Chromosome segregation errors in oocytes lead to the production of aneuploid eggs, which are the leading cause of pregnancy loss and of several congenital diseases such as Down syndrome. The frequency of chromosome segregation errors in oocytes increases with maternal age, especially at a late stage of reproductive life. How aging at various life stages affects oocytes differently remains poorly understood. In this study, we describe aging‐associated changes in the transcriptome profile of mouse oocytes throughout reproductive life. Our single‐oocyte comprehensive RNA sequencing using RamDA‐seq revealed that oocytes undergo transcriptome changes at a late reproductive stage, whereas their surrounding cumulus cells exhibit transcriptome changes at an earlier stage. Calorie restriction, a paradigm that reportedly prevents aging‐associated egg aneuploidy, promotes a transcriptome shift in oocytes with the up‐regulation of genes involved in chromosome segregation. This shift is accompanied by the improved maintenance of chromosomal cohesin, the loss of which is a hallmark of oocyte aging and causes chromosome segregation errors. These findings have implications for understanding how oocytes undergo aging‐associated functional decline throughout their reproductive life in a context‐dependent manner.

Local states of chromatin compaction at transcription start sites control transcription levels

The ‘open’ and ‘compact’ regions of chromatin are considered to be regions of active and silent transcription, respectively. However, individual genes produce transcripts at different levels, suggesting that transcription output does not depend on the simple open-compact conversion of chromatin, but on structural variations in chromatin itself, which so far have remained elusive. In this study, weakly crosslinked chromatin was subjected to sedimentation velocity centrifugation, which fractionated the chromatin according to its degree of compaction. Open chromatin remained in upper fractions, while compact chromatin sedimented to lower fractions depending on the level of nucleosome assembly. Although nucleosomes were evenly detected in all fractions, histone H1 was more highly enriched in the lower fractions. H1 was found to self-associate and crosslinked to histone H3, suggesting that H1 bound to H3 interacts with another H1 in an adjacent nucleosome to form compact chromatin. Genome-wide analyses revealed that nearly the entire genome consists of compact chromatin without differences in compaction between repeat and non-repeat sequences; however, active transcription start sites (TSSs) were rarely found in compact chromatin. Considering the inverse correlation between chromatin compaction and RNA polymerase binding at TSSs, it appears that local states of chromatin compaction determine transcription levels.

Derepression of inflammation-related genes link to microglia activation and neural maturation defect in a mouse model of Kleefstra syndrome

Haploinsufficiency of EHMT1, which encodes histone H3 lysine 9 (H3K9) methyltransferase G9a-like protein (GLP), causes Kleefstra syndrome (KS), a complex disorder of developmental delay and intellectual disability. Here, we examined whether postnatal supply of GLP can reverse the neurological phenotypes seen in Ehmt1^Δ/+ mice as a KS model. Ubiquitous GLP supply from the juvenile stage ameliorated behavioral abnormalities in Ehmt1^Δ/+ mice. Postnatal neuron-specific GLP supply was not sufficient for the improvement of abnormal behaviors but still reversed the reduction of H3K9me2 and spine number in Ehmt1^Δ/+ mice. Interestingly, some inflammatory genes, including IL-1β (Il1b), were upregulated and activated microglial cells increased in the Ehmt1^Δ/+ brain, and such phenotypes were also reversed by neuron-specific postnatal GLP supply. Il1b inactivation canceled the microglial and spine number phenotypes in the Ehmt1^Δ/+ mice. Thus, H3K9me2 and some neurological phenotypes are reversible, but behavioral abnormalities are more difficult to improve depending on the timing of GLP supply.

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Activated microglias increase in a Ehmt1^Δ/+ mouse model of Kleefstra syndrome

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Diminished H3K9me2 in Ehmt1^Δ/+ mouse neurons is reversed by post-natal GLP supply

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GLP supply from the juvenile stage can improve abnormal behaviors of Ehmt1^Δ/+ mice

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Il1b KO cancelles the microglial and spine number phenotypes in the Ehmt1^Δ/+ mice

Genome-wide kinetic properties of transcriptional bursting in mouse embryonic stem cells

Transcriptional bursting is the stochastic activation and inactivation of promoters, contributing to cell-to-cell heterogeneity in gene expression. However, the mechanism underlying the regulation of transcriptional bursting kinetics (burst size and frequency) in mammalian cells remains elusive. In this study, we performed single-cell RNA sequencing to analyze the intrinsic noise and mRNA levels for elucidating the transcriptional bursting kinetics in mouse embryonic stem cells. Informatics analyses and functional assays revealed that transcriptional bursting kinetics was regulated by a combination of promoter- and gene body-binding proteins, including the polycomb repressive complex 2 and transcription elongation factors. Furthermore, large-scale CRISPR-Cas9-based screening identified that the Akt/MAPK signaling pathway regulated bursting kinetics by modulating transcription elongation efficiency. These results uncovered the key molecular mechanisms underlying transcriptional bursting and cell-to-cell gene expression noise in mammalian cells.

Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets

BACKGROUND

Read coverage of RNA sequencing data reflects gene expression and RNA processing events. Single-cell RNA sequencing (scRNA-seq) methods, particularly "full-length" ones, provide read coverage of many individual cells and have the potential to reveal cellular heterogeneity in RNA transcription and processing. However, visualization tools suited to highlighting cell-to-cell heterogeneity in read coverage are still lacking.

RESULTS

Here, we have developed Millefy, a tool for visualizing read coverage of scRNA-seq data in genomic contexts. Millefy is designed to show read coverage of all individual cells at once in genomic contexts and to highlight cell-to-cell heterogeneity in read coverage. By visualizing read coverage of all cells as a heat map and dynamically reordering cells based on diffusion maps, Millefy facilitates discovery of "local" region-specific, cell-to-cell heterogeneity in read coverage. We applied Millefy to scRNA-seq data sets of mouse embryonic stem cells and triple-negative breast cancers and showed variability of transcribed regions including antisense RNAs, 3 ' UTR lengths, and enhancer RNA transcription.

CONCLUSIONS

Millefy simplifies the examination of cellular heterogeneity in RNA transcription and processing events using scRNA-seq data. Millefy is available as an R package (https://github.com/yuifu/millefy) and as a Docker image for use with Jupyter Notebook (https://hub.docker.com/r/yuifu/datascience-notebook-millefy).

Benchmarking principal component analysis for large-scale single-cell RNA-sequencing

BACKGROUND

Principal component analysis (PCA) is an essential method for analyzing single-cell RNA-seq (scRNA-seq) datasets, but for large-scale scRNA-seq datasets, computation time is long and consumes large amounts of memory.

RESULTS

In this work, we review the existing fast and memory-efficient PCA algorithms and implementations and evaluate their practical application to large-scale scRNA-seq datasets. Our benchmark shows that some PCA algorithms based on Krylov subspace and randomized singular value decomposition are fast, memory-efficient, and more accurate than the other algorithms.

CONCLUSION

We develop a guideline to select an appropriate PCA implementation based on the differences in the computational environment of users and developers.

Developmental excitation-inhibition imbalance underlying psychoses revealed by single-cell analyses of discordant twins-derived cerebral organoids

Despite extensive genetic and neuroimaging studies, detailed cellular mechanisms underlying schizophrenia and bipolar disorder remain poorly understood. Recent progress in single-cell RNA sequencing (scRNA-seq) technologies enables identification of cell-type-specific pathophysiology. However, its application to psychiatric disorders is challenging because of methodological difficulties in analyzing human brains and the confounds due to a lifetime of illness. Brain organoids derived from induced pluripotent stem cells (iPSCs) of the patients are a powerful avenue to investigate the pathophysiological processes. Here, we generated iPSC-derived cerebral organoids from monozygotic twins discordant for psychosis. scRNA-seq analysis of the organoids revealed enhanced GABAergic specification and reduced cell proliferation following diminished Wnt signaling in the patient, which was confirmed in iPSC-derived forebrain neuronal cells. Two additional monozygotic twin pairs discordant for schizophrenia also confirmed the excess GABAergic specification of the patients' neural progenitor cells. With a well-controlled genetic background, our data suggest that unbalanced specification of excitatory and inhibitory neurons during cortical development underlies psychoses.

An NMF-based approach to discover overlooked differentially expressed gene regions from single-cell RNA-seq data

Single-cell RNA sequencing has enabled researchers to quantify the transcriptomes of individual cells, infer cell types and investigate differential expression among cell types, which will lead to a better understanding of the regulatory mechanisms of cell states. Transcript diversity caused by phenomena such as aberrant splicing events have been revealed, and differential expression of previously unannotated transcripts might be overlooked by annotation-based analyses. Accordingly, we have developed an approach to discover overlooked differentially expressed (DE) gene regions that complements annotation-based methods. Our algorithm decomposes mapped count data matrix for a gene region using non-negative matrix factorization, quantifies the differential expression level based on the decomposed matrix, and compares the differential expression level based on annotation-based approach to discover previously unannotated DE transcripts. We performed single-cell RNA sequencing for human neural stem cells and applied our algorithm to the dataset. We also applied our algorithm to two public single-cell RNA sequencing datasets correspond to mouse ES and primitive endoderm cells, and human preimplantation embryos. As a result, we discovered several intriguing DE transcripts, including a transcript related to the modulation of neural stem/progenitor cell differentiation.

Cell type-specific transcriptome analysis unveils secreted signaling molecule genes expressed in apical epithelial cap during appendage regeneration

Wound epidermis (WE) and the apical epithelial cap (AEC) are believed to trigger regeneration of amputated appendages such as limb and tail in amphibians by producing certain secreted signaling molecules. To date, however, only limited information about the molecular signatures of these epidermal structures is available. Here we used a transgenic Xenopus laevis line harboring the enhanced green fluorescent protein (egfp) gene under control of an es1 gene regulatory sequence to isolate WE/AEC cells by performing fluorescence-activated cell sorting during the time course of tail regeneration (day 1, day 2, day 3 and day 4 after amputation). Time-course transcriptome analysis of these isolated WE/AEC cells revealed that more than 8,000 genes, including genes involved in signaling pathways such as those of reactive oxygen species, fibroblast growth factor (FGF), canonical and non-canonical Wnt, transforming growth factor β (TGF β) and Notch, displayed dynamic changes of their expression during tail regeneration. Notably, this approach enabled us to newly identify seven secreted signaling molecule genes (mdk, fstl, slit1, tgfβ1, bmp7.1, angptl2 and egfl6) that are highly expressed in tail AEC cells. Among these genes, five (mdk, fstl, slit1, tgfβ1 and bmp7.1) were also highly expressed in limb AEC cells but the other two (angptl2 and egfl6) are specifically expressed in tail AEC cells. Interestingly, there was no expression of fgf8 in tail WE/AEC cells, whose expression and pivotal role in limb AEC cells have been reported previously. Thus, we identified common and different properties between tail and limb AEC cells.

CellFishing.jl: an ultrafast and scalable cell search method for single-cell RNA sequencing

Recent technical improvements in single-cell RNA sequencing (scRNA-seq) have enabled massively parallel profiling of transcriptomes, thereby promoting large-scale studies encompassing a wide range of cell types of multicellular organisms. With this background, we propose CellFishing.jl, a new method for searching atlas-scale datasets for similar cells and detecting noteworthy genes of query cells with high accuracy and throughput. Using multiple scRNA-seq datasets, we validate that our method demonstrates comparable accuracy to and is markedly faster than the state-of-the-art software. Moreover, CellFishing.jl is scalable to more than one million cells, and the throughput of the search is approximately 1600 cells per second.

Strategies for Converting RNA to Amplifiable cDNA for Single-Cell RNA Sequencing Methods

This review describes the features of molecular biology techniques for single-cell RNA sequencing (scRNA-seq), including methods developed in our laboratory. Existing scRNA-seq methods require the conversion of first-strand cDNA to amplifiable cDNA followed by whole-transcript amplification. There are three primary strategies for this conversion: poly-A tagging, template switching, and RNase H-DNA polymerase I-mediated second-strand cDNA synthesis for in vitro transcription. We discuss the merits and limitations of these strategies and describe our Reverse Transcription with Random Displacement Amplification technology that allows for direct first-strand cDNA amplification from RNA without the need for conversion to an amplifiable cDNA. We believe that this review provides all users of single-cell transcriptome technologies with an understanding of the relationship between the quantitative performance of various methods and their molecular features.

Polysaccharide hydrolase of the hadal zone amphipods Hirondellea gigas

Hirondellea species are common inhabitants in the hadal region deeper than 7,000 m. We found that Hirondellea gigas thrived in the Challenger Deep possessed polysaccharide hydrolases as digestive enzymes. To obtain various enzymes of other H. gigas, we captured amphipods from the Japan Trench, and Izu-Ogasawara (Bonin) Trench. A phylogenetic analysis based on the cytochrome oxidase I gene showed close relationships among amphipods, despite the geographic distance between the localities. However, several differences in enzymatic properties were observed in these H. gigas specimens. We also carried out RNA sequencing of H. gigas from the Izu-Ogasawara Trench. The cellulase gene of H. gigas was highly homologous to cellobiohydrolase of Glucosyl Hydrolase family 7 (GH7). On the other hand, enzymatic properties of H. gigas's cellulase were different from those of typical GH7 cellobiohydrolase. Thus, these results indicate that hadal-zone amphipod can be good candidates as the new enzyme resource.

SCODE: an efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation

Motivation

The analysis of RNA-Seq data from individual differentiating cells enables us to reconstruct the differentiation process and the degree of differentiation (in pseudo-time) of each cell. Such analyses can reveal detailed expression dynamics and functional relationships for differentiation. To further elucidate differentiation processes, more insight into gene regulatory networks is required. The pseudo-time can be regarded as time information and, therefore, single-cell RNA-Seq data are time-course data with high time resolution. Although time-course data are useful for inferring networks, conventional inference algorithms for such data suffer from high time complexity when the number of samples and genes is large. Therefore, a novel algorithm is necessary to infer networks from single-cell RNA-Seq during differentiation.

Results

In this study, we developed the novel and efficient algorithm SCODE to infer regulatory networks, based on ordinary differential equations. We applied SCODE to three single-cell RNA-Seq datasets and confirmed that SCODE can reconstruct observed expression dynamics. We evaluated SCODE by comparing its inferred networks with use of a DNaseI-footprint based network. The performance of SCODE was best for two of the datasets and nearly best for the remaining dataset. We also compared the runtimes and showed that the runtimes for SCODE are significantly shorter than for alternatives. Thus, our algorithm provides a promising approach for further single-cell differentiation analyses.

Availability and Implementation

The R source code of SCODE is available at https://github.com/hmatsu1226/SCODE

Supplementary information

Supplementary data are available at Bioinformatics online.

Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads

High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30-50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

Single-cell full-length total RNA sequencing uncovers dynamics of recursive splicing and enhancer RNAs

Total RNA sequencing has been used to reveal poly(A) and non-poly(A) RNA expression, RNA processing and enhancer activity. To date, no method for full-length total RNA sequencing of single cells has been developed despite the potential of this technology for single-cell biology. Here we describe random displacement amplification sequencing (RamDA-seq), the first full-length total RNA-sequencing method for single cells. Compared with other methods, RamDA-seq shows high sensitivity to non-poly(A) RNA and near-complete full-length transcript coverage. Using RamDA-seq with differentiation time course samples of mouse embryonic stem cells, we reveal hundreds of dynamically regulated non-poly(A) transcripts, including histone transcripts and long noncoding RNA Neat1. Moreover, RamDA-seq profiles recursive splicing in >300-kb introns. RamDA-seq also detects enhancer RNAs and their cell type-specific activity in single cells. Taken together, we demonstrate that RamDA-seq could help investigate the dynamics of gene expression, RNA-processing events and transcriptional regulation in single cells.

Chromatin remodeler CHD7 regulates the stem cell identity of human neural progenitors

Multiple congenital disorders often present complex phenotypes, but how the mutation of individual genetic factors can lead to multiple defects remains poorly understood. In the present study, we used human neuroepithelial (NE) cells and CHARGE patient-derived cells as an in vitro model system to identify the function of chromodomain helicase DNA-binding 7 (CHD7) in NE-neural crest bifurcation, thus revealing an etiological link between the central nervous system (CNS) and craniofacial anomalies observed in CHARGE syndrome. We found that CHD7 is required for epigenetic activation of superenhancers and CNS-specific enhancers, which support the maintenance of the NE and CNS lineage identities. Furthermore, we found that BRN2 and SOX21 are downstream effectors of CHD7, which shapes cellular identities by enhancing a CNS-specific cellular program and indirectly repressing non-CNS-specific cellular programs. Based on our results, CHD7, through its interactions with superenhancer elements, acts as a regulatory hub in the orchestration of the spatiotemporal dynamics of transcription factors to regulate NE and CNS lineage identities.

An application of MeSH enrichment analysis in livestock

An integral part of functional genomics studies is to assess the enrichment of specific biological terms in lists of genes found to be playing an important role in biological phenomena. Contrasting the observed frequency of annotated terms with those of the background is at the core of overrepresentation analysis (ORA). Gene Ontology (GO) is a means to consistently classify and annotate gene products and has become a mainstay in ORA. Alternatively, Medical Subject Headings (MeSH) offers a comprehensive life science vocabulary including additional categories that are not covered by GO. Although MeSH is applied predominantly in human and model organism research, its full potential in livestock genetics is yet to be explored. In this study, MeSH ORA was evaluated to discern biological properties of identified genes and contrast them with the results obtained from GO enrichment analysis. Three published datasets were employed for this purpose, representing a gene expression study in dairy cattle, the use of SNPs for genome‐wide prediction in swine and the identification of genomic regions targeted by selection in horses. We found that several overrepresented MeSH annotations linked to these gene sets share similar concepts with those of GO terms. Moreover, MeSH yielded unique annotations, which are not directly provided by GO terms, suggesting that MeSH has the potential to refine and enrich the representation of biological knowledge. We demonstrated that MeSH can be regarded as another choice of annotation to draw biological inferences from genes identified via experimental analyses. When used in combination with GO terms, our results indicate that MeSH can enhance our functional interpretations for specific biological conditions or the genetic basis of complex traits in livestock species.

MeSH ORA framework: R/Bioconductor packages to support MeSH over-representation analysis

Background

In genome-wide studies, over-representation analysis (ORA) against a set of genes is an essential step for biological interpretation. Many gene annotation resources and software platforms for ORA have been proposed. Recently, Medical Subject Headings (MeSH) terms, which are annotations of PubMed documents, have been used for ORA. MeSH enables the extraction of broader meaning from the gene lists and is expected to become an exhaustive annotation resource for ORA. However, the existing MeSH ORA software platforms are still not sufficient for several reasons.

Results

In this work, we developed an original MeSH ORA framework composed of six types of R packages, including MeSH.db, MeSH.AOR.db, MeSH.PCR.db, the org.MeSH.XXX.db-type packages, MeSHDbi, and meshr.

Conclusions

Using our framework, users can easily conduct MeSH ORA. By utilizing the enriched MeSH terms, related PubMed documents can be retrieved and saved on local machines within this framework.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0453-z) contains supplementary material, which is available to authorized users.

Context-dependent wiring of Sox2 regulatory networks for self-renewal of embryonic and trophoblast stem cells

Sox2 is a transcription factor required for the maintenance of pluripotency. It also plays an essential role in different types of multipotent stem cells, raising the possibility that Sox2 governs the common stemness phenotype. Here we show that Sox2 is a critical downstream target of fibroblast growth factor (FGF) signaling, which mediates self-renewal of trophoblast stem cells (TSCs). Sustained expression of Sox2 together with Esrrb or Tfap2c can replace FGF dependency. By comparing genome-wide binding sites of Sox2 in embryonic stem cells (ESCs) and TSCs combined with inducible knockout systems, we found that, despite the common role in safeguarding the stem cell state, Sox2 regulates distinct sets of genes with unique functions in these two different yet developmentally related types of stem cells. Our findings provide insights into the functional versatility of transcription factors during embryogenesis, during which they can be recursively utilized in a variable manner within discrete network structures.

Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity

Development of a highly reproducible and sensitive single-cell RNA sequencing (RNA-seq) method would facilitate the understanding of the biological roles and underlying mechanisms of non-genetic cellular heterogeneity. In this study, we report a novel single-cell RNA-seq method called Quartz-Seq that has a simpler protocol and higher reproducibility and sensitivity than existing methods. We show that single-cell Quartz-Seq can quantitatively detect various kinds of non-genetic cellular heterogeneity, and can detect different cell types and different cell-cycle phases of a single cell type. Moreover, this method can comprehensively reveal gene-expression heterogeneity between single cells of the same cell type in the same cell-cycle phase.

Transcriptome tomography for brain analysis in the web-accessible anatomical space

Increased information on the encoded mammalian genome is expected to facilitate an integrated understanding of complex anatomical structure and function based on the knowledge of gene products. Determination of gene expression-anatomy associations is crucial for this understanding. To elicit the association in the three-dimensional (3D) space, we introduce a novel technique for comprehensive mapping of endogenous gene expression into a web-accessible standard space: Transcriptome Tomography. The technique is based on conjugation of sequential tissue-block sectioning, all fractions of which are used for molecular measurements of gene expression densities, and the block- face imaging, which are used for 3D reconstruction of the fractions. To generate a 3D map, tissues are serially sectioned in each of three orthogonal planes and the expression density data are mapped using a tomographic technique. This rapid and unbiased mapping technique using a relatively small number of original data points allows researchers to create their own expression maps in the broad anatomical context of the space. In the first instance we generated a dataset of 36,000 maps, reconstructed from data of 61 fractions measured with microarray, covering the whole mouse brain (ViBrism: http://vibrism.riken.jp/3dviewer/ex/index.html) in one month. After computational estimation of the mapping accuracy we validated the dataset against existing data with respect to the expression location and density. To demonstrate the relevance of the framework, we showed disease related expression of Huntington's disease gene and Bdnf. Our tomographic approach is applicable to analysis of any biological molecules derived from frozen tissues, organs and whole embryos, and the maps are spatially isotropic and well suited to the analysis in the standard space (e.g. Waxholm Space for brain-atlas databases). This will facilitate research creating and using open-standards for a molecular-based understanding of complex structures; and will contribute to new insights into a broad range of biological and medical questions.

Quantitative expression profile of distinct functional regions in the adult mouse brain

The adult mammalian brain is composed of distinct regions with specialized roles including regulation of circadian clocks, feeding, sleep/awake, and seasonal rhythms. To find quantitative differences of expression among such various brain regions, we conducted the BrainStars (B*) project, in which we profiled the genome-wide expression of ∼50 small brain regions, including sensory centers, and centers for motion, time, memory, fear, and feeding. To avoid confounds from temporal differences in gene expression, we sampled each region every 4 hours for 24 hours, and pooled the samples for DNA-microarray assays. Therefore, we focused on spatial differences in gene expression. We used informatics to identify candidate genes with expression changes showing high or low expression in specific regions. We also identified candidate genes with stable expression across brain regions that can be used as new internal control genes, and ligand-receptor interactions of neurohormones and neurotransmitters. Through these analyses, we found 8,159 multi-state genes, 2,212 regional marker gene candidates for 44 small brain regions, 915 internal control gene candidates, and 23,864 inferred ligand-receptor interactions. We also found that these sets include well-known genes as well as novel candidate genes that might be related to specific functions in brain regions. We used our findings to develop an integrated database (http://brainstars.org/) for exploring genome-wide expression in the adult mouse brain, and have made this database openly accessible. These new resources will help accelerate the functional analysis of the mammalian brain and the elucidation of its regulatory network systems.

Id4, a new candidate gene for senile osteoporosis, acts as a molecular switch promoting osteoblast differentiation

Excessive accumulation of bone marrow adipocytes observed in senile osteoporosis or age-related osteopenia is caused by the unbalanced differentiation of MSCs into bone marrow adipocytes or osteoblasts. Several transcription factors are known to regulate the balance between adipocyte and osteoblast differentiation. However, the molecular mechanisms that regulate the balance between adipocyte and osteoblast differentiation in the bone marrow have yet to be elucidated. To identify candidate genes associated with senile osteoporosis, we performed genome-wide expression analyses of differentiating osteoblasts and adipocytes. Among transcription factors that were enriched in the early phase of differentiation, Id4 was identified as a key molecule affecting the differentiation of both cell types. Experiments using bone marrow-derived stromal cell line ST2 and Id4-deficient mice showed that lack of Id4 drastically reduces osteoblast differentiation and drives differentiation toward adipocytes. On the other hand knockdown of Id4 in adipogenic-induced ST2 cells increased the expression of Pparγ2, a master regulator of adipocyte differentiation. Similar results were observed in bone marrow cells of femur and tibia of Id4-deficient mice. However the effect of Id4 on Pparγ2 and adipocyte differentiation is unlikely to be of direct nature. The mechanism of Id4 promoting osteoblast differentiation is associated with the Id4-mediated release of Hes1 from Hes1-Hey2 complexes. Hes1 increases the stability and transcriptional activity of Runx2, a key molecule of osteoblast differentiation, which results in an enhanced osteoblast-specific gene expression. The new role of Id4 in promoting osteoblast differentiation renders it a target for preventing the onset of senile osteoporosis.

Increased bone marrow adiposity is observed in the bone marrow of senile osteoporosis patients. This is caused by unbalanced differentiation of mesenchymal stem cells (MSCs) into osteoblast or adipocyte. Previous reports have indicated that several transcription factors play important roles in determining the direction of MSCs differentiation into osteoblast or adipocyte. So far, little is known about the overall dynamics and regulation of transcription factor expression changes leading to the imbalance of osteoblast and adipocyte differentiation inside the bone marrow. We have performed genome-wide gene expression analyses during the differentiation of MSCs into osteoblast or adipocyte. We identified basic helix-loop-helix transcription factor family member Id4 as a leading candidate controlling the differentiation toward adipocyte or osteoblast. Suppression of Id4 expression in MSCs repressed osteoblast differentiation and increased adipocyte differentiation. In contrast, overexpression of Id4 in MSCs promoted osteoblast differentiation and attenuated adipocyte differentiation. Moreover, Id4-mutant mice showed abnormal accumulation of lipid droplets in bone marrow and impaired bone formation activity. In summary, we have demonstrated a molecular function of Id4 in osteoblast differentiation. The findings revealed that Id4 is a molecular switch enhancing osteoblast differentiation at the expense of adipocyte differentiation.

Integration of exogenous DNA into mouse embryonic stem cell chromosomes shows preference into genes and frequent modification at junctions

Chromosomal integration of exogenous DNA in mammalian cells allows stable gene expression for a variety of biological applications. Although it is presumably mediated by DNA repair machinery, little is known regarding site preferences and other characteristics. We isolated and analyzed 256 chromosomal-plasmid DNA integration junctions from 158 plasmid integrants after electroporation in mouse embryonic stem (ES) cells. The frequency of integrations in transcription units (40%) showed a slight but significant increase over the frequency estimated by computer simulation of random events (30%), suggesting preferential integration into genes. Microarray analysis revealed preference into genes, which are expressed in mouse ES cells. In contrast, bias toward integrations around transcriptional start sites, CpG islands and repeat elements was not observed. Furthermore, all host chromosome sequences as well as the majority of plasmids (96%) at the integration junctions were modified by deletions and/or insertions of additional nucleotides. Detailed analyses revealed frequent stem loop/hairpin formation mediated by weak homologies near plasmid ends before integration. Our study sheds light on a natural fate of exogenous DNA, which preferentially integrates into transcriptionally active chromosomal sites and by an imprecise end-joining pathway, associated with highly frequent modification of the end sequences.

EICO (Expression-based Imprint Candidate Organizer): finding disease-related imprinted genes

We have developed an integrated database that is specialized for the study of imprinted disease genes. The database contains novel candidate imprinted genes identified by the RIKEN full-length mouse cDNA microarray study, information on validated single nucleotide polymorphisms (SNPs) to confirm imprinting using reciprocal mouse crosses and the predicted physical position of imprinting-related disease loci in the mouse and human genomes. It has two user-friendly search interfaces: the SNP-central view (MuSCAT: MoUse SNP CATalog) and the candidate gene-central view (CITE: Candidate Imprinted Transcripts by Expression). The database, EICO (Expression-based Imprint Candidate Organizer), can be accessed via the World Wide Web (http://fantom2.gsc.riken.jp/EICODB/) and the DAS client software. These data and interfaces facilitate understanding of the mechanism of imprinting in mammalian inherited traits.

Development and evaluation of an automated annotation pipeline and cDNA annotation system

Manual curation has long been held to be the "gold standard" for functional annotation of DNA sequence. Our experience with the annotation of more than 20,000 full-length cDNA sequences revealed problems with this approach, including inaccurate and inconsistent assignment of gene names, as well as many good assignments that were difficult to reproduce using only computational methods. For the FANTOM2 annotation of more than 60,000 cDNA clones, we developed a number of methods and tools to circumvent some of these problems, including an automated annotation pipeline that provides high-quality preliminary annotation for each sequence by introducing an "uninformative filter" that eliminates uninformative annotations, controlled vocabularies to accurately reflect both the functional assignments and the evidence supporting them, and a highly refined, Web-based manual annotation tool that allows users to view a wide array of sequence analyses and to assign gene names and putative functions using a consistent nomenclature. The ultimate utility of our approach is reflected in the low rate of reassignment of automated assignments by manual curation. Based on these results, we propose a new standard for large-scale annotation, in which the initial automated annotations are manually investigated and then computational methods are iteratively modified and improved based on the results of manual curation.

Systematic expression profiling of the mouse transcriptome using RIKEN cDNA microarrays

The number of known mRNA transcripts in the mouse has been greatly expanded by the RIKEN Mouse Gene Encyclopedia project. Validation of their reproducible expression in a tissue is an important contribution to the study of functional genomics. In this report, we determine the expression profile of 57,931 clones on 20 mouse tissues using cDNA microarrays. Of these 57,931 clones, 22,928 clones correspond to the FANTOM2 clone set. The set represents 20,234 transcriptional units (TUs) out of 33,409 TUs in the FANTOM2 set. We identified 7206 separate clones that satisfied stringent criteria for tissue-specific expression. Gene Ontology terms were assigned for these 7206 clones, and the proportion of 'molecular function' ontology for each tissue-specific clone was examined. These data will provide insights into the function of each tissue. Tissue-specific gene expression profiles obtained using our cDNA microarrays were also compared with the data extracted from the GNF Expression Atlas based on Affymetrix microarrays. One major outcome of the RIKEN transcriptome analysis is the identification of numerous nonprotein-coding mRNAs. The expression profile was also used to obtain evidence of expression for putative noncoding RNAs. In addition, 1926 clones (70%) of 2768 clones that were categorized as "unknown EST," and 1969 (58%) clones of 3388 clones that were categorized as "unclassifiable" were also shown to be reproducibly expressed.

Comprehensive analysis of the mouse metabolome based on the transcriptome

The complete set of cDNAs encoding the enzymes of known metabolic pathways has not previously been available for any mammal. Here, transcripts encoding the metabolic pathways of the mouse (mouse metabolome) were reconstructed by making use of the KEGG metabolic pathway database and gene ontology (GO) assignment to the mouse representative transcript and protein set (RTPS), which contains all available mouse transcript sequences including the FANTOM set of RIKEN mouse cDNA clones. By assigning EC numbers extracted from the molecular function ontology in GO, the known mouse transcriptome was predicted to encode enzymes with 726 unique EC numbers. Of these, 648 EC numbers were newly assigned based on the FANTOM set. The mouse metabolome confirmed by cDNA analysis includes almost all of the enzymes of well known pathways such as the tricarboxylic acid cycle and urea cycle. On the other hand, analysis of enzymes required for the tryptophan metabolism pathway revealed a lack of connectivity, indicating that cDNAs/genes encoding several key enzymes remain to be identified. The information derived from coexpression from the cDNA microarray analysis of enzymes of known function may lead to identification of the missing components of the metabolome, and will add new insights into the connectivity of the mammalian metabolic pathways.

Discovery of imprinted transcripts in the mouse transcriptome using large-scale expression profiling

Candidate imprinted transcriptional units in the mouse genome were identified systematically from 27,663 FANTOM2 full-length mouse cDNA clones by expression profiling. Large-scale cDNA microarrays were used to detect differential expression dependent upon chromosomal parent of origin by comparing the mRNA levels in the total tissue of 9.5 dpc parthenogenote and androgenote mouse embryos. Of the FANTOM2 transcripts, 2114 were identified as candidates on the basis of the array data. Of these, 39 mapped to known imprinted regions of the mouse genome, 56 were considered as nonprotein-coding RNAs, and 159 were natural antisense transcripts. The imprinted expression of two transcripts located in the mouse chromosomal region syntenic to the human Prader-Willi syndrome region was confirmed experimentally. We further mapped all candidate imprinted transcripts to the mouse and human genome and were shown in correlation with the imprinting disease loci. These data provide a major resource for understanding the role of imprinting in mammalian inherited traits.

Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs

Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.

Asb4, Ata3, and Dcn are novel imprinted genes identified by high-throughput screening using RIKEN cDNA microarray

Genes differentially expressed between parthenogenetic and androgenetic embryos are candidates for the identification of imprinted genes, which are expressed specifically from the maternal or paternal allele. To search for genes differentially expressed between parthenogenetic and androgenetic embryos, we used the RIKEN full-length enriched mouse cDNA microarray. The 25 candidates obtained included 8 known imprinted genes (such as IgfII, Snrpn, and Neuronatin) and 3 new ones--Asb4 (ankyrin repeat and SOCS box-containing protein 4), Ata3 (amino acid transport system A3), and Decorin--which were confirmed by using normal diploid embryos from the reciprocal F1 crosses of B6 and JF1 mice. The 25 candidates also included genes that showed no imprinting-associated expression in normal diploid embryos. We describe a feasible high-throughput method of screening for novel imprinted genes by using the RIKEN cDNA microarray.

Functional annotation of a full-length mouse cDNA collection

The RIKEN Mouse Gene Encyclopaedia Project, a systematic approach to determining the full coding potential of the mouse genome, involves collection and sequencing of full-length complementary DNAs and physical mapping of the corresponding genes to the mouse genome. We organized an international functional annotation meeting (FANTOM) to annotate the first 21,076 cDNAs to be analysed in this project. Here we describe the first RIKEN clone collection, which is one of the largest described for any organism. Analysis of these cDNAs extends known gene families and identifies new ones.

Generation of 10,154 expressed sequence tags from a leafy gametophyte of a marine red alga, Porphyra yezoensis

A total of 10,154 5'-end expressed sequence tags (EST) were established from the normalized and size-selected cDNA libraries of a marine red alga, Porphyra yezoensis. Among the ESTs, 2140 were unique species, and the remaining 8014 were grouped into 1127 species. Database search of the 3267 non-redundant ESTs by BLAST algorithm showed that the sequences of 1080 species (33.1%) have similarity to those of registered genes from various organisms including higher plants, mammals, yeasts, and cyanobacteria, while 2187 (66.9%) are novel. Codon usage analysis in the coding regions of 101 non-redundant EST groups showing significant similarity to known genes indicated the higher GC contents at the third position of codons (79.4%) than the first (62.2%) and the second position (45.0%), suggesting that the genome has been exposed to high GC pressure during evolution. The sequence data of individual ESTs are available at the web site http://www.kazusa.or.jp/en/plant/porphyra/EST/.