Biology subjects

Sun, J. J.

Publications and source records attributed to Sun, J. J..

7 recordsLinked to original sources

bioRxiv2026

A community benchmark enables high-resolution, cross-lab quantification of mouse social behavior

Social behavior is a sensitive readout of brain state, but quantifying rodent social behavior at scale has relied on siloed, lab-specific tools. We assembled Days of our Mice (DooM), a benchmark of manually annotated video and pose tracking spanning 15 laboratories and 33 social and solitary behaviors, and hosted a community behavior classification challenge. We built on challenge solutions to develop the High-Dimensional Rodent Annotator (HiDRA), a behavior classification tool that generalizes to labs unseen during training and learns cross-lab movement features. Applied without retraining to experimental data, HiDRA resolves line-specific and state-dependent behavioral fingerprints with strong generalizability and reproducibility, establishing high-resolution, shareable social phenotyping as a scalable readout of brain and internal state. We release the DooM dataset and HiDRA classifiers as open resources.

neuroscience↗

bioRxiv2025

Extensive and differential platinum chemotherapy mutagenesis in children

Childhood cancer survivors often develop long-term adverse effects, which may be caused by direct mutagenesis of cytotoxic agents. Some of these agents generate distinctive DNA imprints (mutational signatures), as exemplified by platinum chemotherapeutics. Here, we examined chemotherapy mutagenesis in paediatric tissues by deploying a duplex sequencing method (NanoSeq), which enables mutation calling from single DNA molecules. We surveyed whole genomes of paediatric liver, blood and other tissues, obtained from surgical resections and at post-mortem. Platinum signatures pervaded all tissues extensively, elevating mutation burdens of paediatric tissues to levels seen in adults. Remarkably, we found a tissue-specific mutational signature in the liver. We examined the functional potential of mutations by gene focused NanoSeq, which revealed that platinum agents cause a vast repertoire of cancer causing variants across normal tissues, such as leukaemogenic mutations in blood. This finding may conceivably link cancer treatment in childhood to mutation-driven long term sequelae.

cancer biology↗

bioRxiv2024

Video Foundation Models for Animal Behavior Analysis

Computational approaches leveraging computer vision and machine learning have transformed the quantification of animal behavior from video. However, existing methods often rely on task-specific features or models, which struggle to generalize across diverse datasets and tasks. Recent advances in machine learning, particularly the emergence of vision foundation models, i.e., large-scale models pre-trained on massive, diverse visual repositories, offers a way to tackle these challenges. Here, we investigate the potential of frozen video foundation models across a range of behavior analysis tasks, including classification, retrieval, and localization. We use a single, frozen model to extract general-purpose representations from video data, and perform extensive evaluations on diverse open-sourced animal behavior datasets. Our results demonstrate that features with minimal adaptation from foundation models achieve competitive performance compared to existing methods specifically designed for each dataset, across species, behaviors, and experimental contexts. This highlights the potential of frozen video foundation models as a powerful and accessible backbone for automated behavior analysis, with the ability to accelerate research across diverse fields from neuroscience, to ethology, and to ecology.

animal behavior and cognition↗

bioRxiv2022

Cellular reprogramming with ATOH1, GFI1, and POU4F3 implicate epigenetic changes and cell-cell signaling as obstacles to hair cell regeneration in mature mammals

Reprogramming of the cochlea with hair cell-specific transcription factors such as ATOH1 has been proposed as a potential therapeutic strategy for hearing loss. ATOH1 expression in the developing cochlea can efficiently induce hair cell regeneration but the efficiency of hair cell reprogramming declines rapidly as the cochlea matures. We developed Cre-inducible mice to compare hair cell reprogramming with ATOH1 alone or in combination with two other hair cell transcription factors, GFI1 and POU4F3. In newborn mice, all transcription factor combinations tested produced large numbers of cells with the morphology of hair cells and rudimentary mechanotransduction properties. However, one week later, only a combination of ATOH1, GFI1 and POU4F3 could reprogram non-sensory cells of the cochlea to a hair cell fate, and these new cells were less mature than cells generated by reprogramming one week earlier. We used scRNA-seq and combined scRNA-seq and ATAC-seq to suggest at least two impediments to hair cell reprogramming in older animals. First, hair cell gene loci become less epigenetically accessible in non-sensory cells of the cochlea with increasing age. Second, signaling from hair cells to supporting cells, including Notch signaling, can prevent reprogramming of many supporting cells to hair cells, even with three hair cell transcription factors. Our results shed light on the molecular barriers that must be overcome to promote hair cell regeneration in the adult cochlea.

developmental biology↗

bioRxiv2021

A CRISPR toolbox for generating intersectional genetic mice for functional, molecular, and anatomical circuit mapping

BackgroundA full understanding of circuits and cellular mechanisms governing health and disease requires the dissection and multi-faceted study of discrete cell subtypes in developing and adult animal models. Recombinase-driven expression of transgenic response alleles represents a significant and powerful approach to delineate cell populations for functional, molecular, and anatomical study. In addition to single recombinase systems, the expression of two recombinases in distinct, but partially overlapping, populations allow for more defined target expression. Although the application of this method is becoming increasingly popular, the expense and difficulty associated with production of customized intersectional mouse lines have limited widespread application to more common allele manipulations that are often commercially produced at great expense. ResultsWe present a simplified CRISPR toolkit for rapid, inexpensive, and facile intersectional allele production. Briefly, we produced 7 intersectional mouse lines using a dual recombinase system, one mouse line with a single recombinase system, and three embryonic stem (ES) cell lines that are designed to study how functional, molecular, and anatomical features relate to each other in building circuits that underlie physiology and behavior. As a proof-of-principle, we applied three of these lines to different neuronal populations for anatomical mapping and functional in vivo investigation of respiratory control. We also generated a mouse line with a single recombinase-responsive allele that controls the expression of the calcium sensor Twitch-2B. This mouse line was applied globally to study the effects of follicle stimulating hormone (FSH) and luteinizing hormone (LH) on calcium release in the ovarian follicle. ConclusionsLines presented here are representative examples of outcomes possible with the successful application of our genetic toolkit for the facile development of diverse, modifiable animal models. This toolkit will allow labs to create single or dual recombinase effector lines easily for any cell population or subpopulation of interest when paired with the appropriate Cre and FLP recombinase mouse lines or viral vectors. We have made our tools and derivative intersectional mouse and ES cell lines openly available for non-commercial use through publicly curated repositories for plasmid DNA, ES cells, and transgenic mouse lines.

genetics↗

bioRxiv2020

The Mouse Action Recognition System (MARS): a software pipeline for automated analysis of social behaviors in mice

The study of naturalistic social behavior requires quantification of animals interactions. This is generally done through manual annotation--a highly time consuming and tedious process. Recent advances in computer vision enable tracking the pose (posture) of freely-behaving animals. However, automatically and accurately classifying complex social behaviors remains technically challenging. We introduce the Mouse Action Recognition System (MARS), an automated pipeline for pose estimation and behavior quantification in pairs of freely interacting mice. We compare MARSs annotations to human annotations and find that MARSs pose estimation and behavior classification achieve human-level performance. We also release the pose and annotation datasets used to train MARS, to serve as community benchmarks and resources. Finally, we introduce the Behavior Ensemble and Neural Trajectory Observatory (BENTO), a graphical user interface for analysis of multimodal neuroscience datasets. Together, MARS and BENTO provide an end-to-end pipeline for behavior data extraction and analysis, in a package that is user-friendly and easily modifiable.

neuroscience↗

bioRxiv2017

Serial dependence is absent at the time of perception but increases in visual working memory

Recent experiments have shown that visual cognition blends current visual input with that from the recent past to guide ongoing decision making. This serial dependence is tuned to the similarity between consecutive stimuli and appears to exploit the temporal autocorrelation normally present in visual scenes to promote perceptual stability. While these benefits have been assumed, evidence that serial dependence directly alters stimulus perception has been limited. In the present study, we parametrically vary the delay between stimulus and response in a spatial delayed response task to explore the trajectory of serial dependence from the moment of perception into post-perceptual visual working memory. We find that behavioral responses made immediately after viewing a stimulus show evidence of adaptation, but not attractive serial dependence. Only as the memory period lengthens is a blending of past and present information apparent in behavior, reaching its maximum with a memory delay of six seconds. These results dovetail with other recent findings to bolster the interpretation that serial dependence is a phenomenon of mnemonic rather than perceptual processes. We also demonstrate that when leading mathematical models of visual working memory are adjusted to account for this trial-history effect, their fit to behavioral data is substantially improved.

animal behavior and cognition↗