Tetsutaro Hayashi

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.

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 Contact: hirotaka.matsumoto@riken.jp 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.

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.

Polysaccharide hydrolase of the hadal zone amphipods Hirondellea gigas

Abstract 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. The deepest sea amphipod, Hirondellea gigas digests plant debris with GH7 cellobiohydrolase, GH9 ß-1. 4 glucanase, and amylase to obtain nutrients in oligotrophic sea bottom.