Biology subjects

Chan, D. Y. L.

Publications and source records attributed to Chan, D. Y. L..

3 recordsLinked to original sources

bioRxiv2023

A Dataset for Deep Learning based Cleavage-stage Blastocyst Prediction with Time-lapse Images

Recent advances in deep learning and artificial intelligence techniques have obtained notable progress in automated embryo image analysis. However, most current research focuses on blastocyst-stage embryo evaluation (more than 5 days after in vitro fertilization), which may reduce the number of transferable embryos and increase the risk of canceled circles. Therefore, this paper aims to investigate the possibility of evaluating blastocyst development at the cleavage stage with deep neural networks (DNNs). To this end, we collect a dataset that consists of time-lapse images of more than 500 embryos (about 194k frames in total). We evaluate several widely used DNNs on the dataset, including those of single-frame architectures and multi-frame architectures. Experimental results show that the accuracy of different DNNs varies from 66.42% to 77.74% and we also provide the possible reasons behind the performance gap. Our dataset and code will be published soon to facilitate related research.

bioinformatics↗

bioRxiv2020

scATAC-Seq reveals epigenetic heterogeneity associated with an EMT-like process in male germline stem cells and its regulation by G9a

BackgroundEpithelial-mesenchymal transition (EMT) is a phenomenon in which epithelial cells acquire mesenchymal traits. It contributes to organogenesis and tissue homeostasis, as well as stem cell differentiation. Emerging evidence indicates that heterogeneous expression of EMT gene markers presents in sub-populations of germline stem cells (GSCs). However, the functional implications of such heterogeneity are largely elusive. ResultsWe unravelled an EMT-like process in GSCs by in vitro extracellular matrix (ECM) model and single-cell genomics approaches. We found that histone methyltransferase G9a regulated an EMT-like program in GSC in vitro and contributed to neonatal germ cell migration in vivo. Through modulating ECM, we demonstrated that GSCs exist in interconvertible epithelial-like and mesenchymal-like cell states. GSCs gained higher migratory ability after transition to a mesenchymal-like cell state, which was largely mediated by the TGF-{beta} signaling pathway. Dynamics of epigenetic regulation at the single-cell level was also found to align with the EMT-like process. Chromatin accessibility profiles generated by single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) clustered GSCs into epithelial-like and mesenchymal-like states, which were associated with differentiation status. The high-resolution data revealed regulators in the EMT-like process, including transcription factors Zeb1. We further identified putative enhancer-promoter interactions and cis-co-accessibility networks at loci such as Tgfb1, Notch1 and Lin28a. Lastly, we identified HES1 as the putative target underlying G9as regulation. ConclusionOur work provides the foundation for understanding the EMT-like process and a comprehensive resource for future investigation of epigenetic regulatory networks in GSCs.

cell biology↗

bioRxiv2020

Simultaneous transcriptome and methylome profiles of single mouse oocytes provide novel insights on maturation and aging

BackgroundAdvanced maternal aging has become a worldwide public health issue that contributes to female fertility decline and significant risk to embryo development. Despite transcriptional and epigenetic alterations reported in oocyte maturation and development, the dynamics of gene expression and DNA dynamics associated with aging remain elusive. Here we generated simultaneous transcriptome and methylome profiles of mouse oocytes during aging and maturation at single-cell and single-base resolution to examine key biological processes and identify the key targets for novel treatment options. ResultsWe report the dynamics in transcriptome and DNA methylome in mouse oocytes during maternal aging and oocyte maturation. Age-associated gene expression changes showed mitochondrial dysfunction in GV oocytes and defects of chromosome segregation and spindle assembly in MII oocytes. EIF2 signaling protein synthesis pathway was also impaired during aged oocyte maturation. Moreover, distinctive DNA methylation patterns were demonstrated during maternal aging in GV and MII oocytes. A positive correlation between gene expression and methylation in gene body was characterized. Furthermore, we identified several promising biomarkers, including IL-7, to assess oocyte quality, which are potential therapeutic targets for improve oocyte maturation. More importantly, we built the first mouse oocyte maturation and age prediction model using transcriptome data and validated its feasibility in published data. ConclusionsThis work provides a better understanding of molecular and cellular mechanisms during mouse oocyte aging, points a new direction of oocyte quality assessment, and paves the way for developing novel treatments to improve oocyte maturation and quality in the future.

genomics↗