Biology subjects

Cheung, N.

Publications and source records attributed to Cheung, N..

3 recordsLinked to original sources

bioRxiv2026

A boundary-referenced framework for quantifying shoreline-associated movement in white sharks

Persistent habitat edges can structure animal movement, yet many analyses treat boundary geometry only implicitly. Advances in aerial platforms, sensor miniaturization, and battery durations now enable high spatial and temporal resolution tracking, creating new opportunities to quantify fine-scale movements. We develop and apply a boundary-referenced framework to quantify movements of white sharks (Carcharodon carcharias) off of Cape Cod, Massachusetts, using [~]50 hours of tracking data. Trajectories were analyzed in a local Cartesian coordinate system and a shoreline-referenced system in which displacement was decomposed into along-shore and cross-shore components. Four complementary metrics quantified path straightness, net and continuous alignment with the shoreline, and unique shoreline traversal. These metrics enabled movement modes to be defined directly from movement relative to the boundary. A parsimonious rules-based classifier recovered visually assigned modes with 88% leave-one-out cross-validated accuracy. Among 90 mode-separated tracks derived from tracks exceeding 15 min, nearly three quarters consisted primarily of sustained along-shore travel, whereas spatially confined movement and nearshore-offshore transitions were less frequent. Boundary-referenced metrics revealed site-level differences in shoreline alignment and space usage across beaches. Findings demonstrate that boundary-referenced metrics recover recurrent, interpretable movement modes in a large predator and provide a general framework for quantifying movements along environmental boundaries.

ecology↗

bioRxiv2026

Minimally invasive measurement of maternal transcripts enables predicting the developmental potential of mammalian zygotes

Maternal transcripts are stored in the oocyte cytoplasm during oogenesis and play a pivotal role in early embryonic development after fertilization. However, specific maternal transcripts that reflect the developmental potential of embryos have not been systematically identified, and the use of maternal transcript levels as an indicator of successful development has not been explored. Here, we link the maternal transcriptome to the zygotes developmental potential by examining transcripts in a single polar body. The transcriptome of a zygote or an oocyte was highly similar to that of its accompanying polar body in mouse, cow, and human. We have identified a set of maternal transcripts whose expression levels fluctuate between poor- and good-quality zygotes. Specifically, Sipa1and Zmym6 were identified as marker transcripts that accurately reflect the developmental potential of zygotes. Using these marker genes, combined with machine learning, the development of zygotes to the blastocyst stage was successfully predicted with more than 80% specificity as early as 12 hours after fertilization. Furthermore, our prediction platform significantly improved implantation rates and live births to term. Thus, we have demonstrated a minimally invasive method for identifying maternal transcripts associated with zygote developmental potential. Our developed prediction system provides a generalizable conceptual framework for human infertility treatment to reduce the risk of implantation failure by excluding embryos with low developmental potential, especially when early embryos are transferred, and for livestock propagation to assess selected expressed maternal trait-associated variants before embryo transfer.

developmental biology↗

bioRxiv2021

LeafGo: Leaf to Genome, a quick workflow to produce high-quality De novo genomes with Third Generation Sequencing technology

Recent years have witnessed a rapid development of sequencing technologies. Fundamental differences and limitations among various platforms impact the time, the cost and the accuracy for sequencing whole genomes. Here we designed a complete de novo plant genome generation workflow that starts from plant tissue samples and produces high-quality draft genomes with relatively modest laboratory and bioinformatic resources within seven days. To optimize our workflow we selected different species of plants which were used to extract high molecular weight DNA, to make PacBio and ONT libraries for sequencing with the Sequel I, Sequel II and GridION platforms. We assembled high-quality draft genomes of two different Eucalyptus species E. rudis, and E. camaldulensis to chromosome level without using additional scaffolding technologies. For the rapid production of de novo genome assembly of plant species we showed that our DNA extraction protocol followed by PacBio high fidelity sequencing, and assembly with new generation assemblers such as hifiasm produce excellent results. Our findings will be a valuable benchmark for groups planning wet- and dry-lab plant genomics research and for high throughput plant genomics initiatives.

genomics↗