Biology subjects

Li, M. J.

Publications and source records attributed to Li, M. J..

At least 19 recordsLinked to original sources

bioRxiv2026

A genomic foundation model for interpreting human genetic diversity

Interpreting human genomes requires models that recognize shared biological functions while accounting for variation underlying traits, disease susceptibility and adaptation. Here we present hEVO, a genomic foundation model trained on 4.784 billion distinct haplotype sequences reconstructed from whole genome sequencing (WGS) data for 63,809 individuals selected from 550,237 samples across eight cohorts. Pretraining integrates shared sequence features and naturally occurring allelic differences without clinical or functional labels. Against representatives of the Evo 2, NT, GPN and other genomic model families, hEVO ranked first in 18 of 19 primary comparisons spanning functional annotation, variant interpretation and human evolution. Its pretrained allele scores generalized across all six complementary variant benchmarks without task-specific training, achieving the highest performance across clinical pathogenicity, fine-mapped causal variants and experimentally measured regulatory effects. Retrospective ClinVar reclassification further demonstrated improved identification of pathogenic classifications later downgraded, supporting reassessment of earlier clinical interpretations. Predictive strengths extended to ancestry inference, human accelerated sequences and preference for reported selected alleles. This breadth was achieved with substantially fewer parameters than billion-parameter comparators and low inference overhead in the evaluated workloads. These findings establish human haplotype diversity as a source of transferable biological information for interpreting both the disruption of genome function and the variation retained during human evolution.

genomics↗

bioRxiv2026

An implantable sensor network for large-scale cellular force mapping in living embryos

Mechanical forces generated by cells are fundamental regulators of embryonic development, yet how locally generated forces are integrated across tissues to drive large-scale morphogenesis remains poorly understood. Addressing this question requires direct quantitative mapping of intercellular forces across tissue scale with cellular resolution while preserving native tissue architectures and dynamics, a capability not yet achieved. Here, we introduce FORCENET, an implantable force-sensing network that enables quantitative tissue-scale force mapping at cellular resolution within living embryos. FORCENET consists of a microfabricated network of ultrathin elastic sensors whose three-dimensional deformations are tracked over time and converted into intercellular force maps through physics-based reconstruction. FORCENET covers hundreds of cells while occupying a total volume 6- to 20-fold smaller than that of a single cell. Anatomical measurements, three-dimensional fluorescent imaging, and cell density and speed tracking confirmed that FORCENET seamlessly integrates within developing embryos without perturbing cell motion and proliferation, tissue architecture, and embryonic development. Applied to zebrafish gastrulation, FORCENET revealed that intercellular forces are dynamically coordinated across supracellular length scales of ~30-210 m. Inhibition of fibroblast growth factor signaling accelerated force accumulation and shortened the force-coordination length scales despite only modest changes in cell density and kinematics, demonstrating that FORCENET uncovers information not readily inferred from cell tracking alone. FORCENET establishes a scalable platform for in vivo force mapping and reveals that cell-generated forces are coordinated into supracellular mechanical patterns that are regulated by developmental signaling.

developmental biology↗

bioRxiv2026

Single-cell multiomic QTL mapping reveals state-dependent genetic regulation and associated gene during cellular senescence

How cellular senescence reshapes inherited regulatory effects across chromatin and transcription, and eventually contribute to non-coding risk loci of complex diseases, remains elusive. We generated single-cell multiome ATAC-RNA profiles from proliferating and replicatively senescent primary HUVECs derived from 100 genotyped donors. Alongside state-resolved eQTL and caQTL mapping, we implemented covariance-aware multivariate QTL mapping to identify chromatin accessibility-expression QTLs (caeQTLs), modeling accessibility and expression as a joint phenotype. Joint analysis recovered moderate, asymmetric and modality-distributed associations missed by single-modality scans, revealed senescence-associated regulatory programs, and prioritized candidate causal variants and effector genes at cardiovascular loci. Fine-mapping, chromatin-state annotation and heritability enrichment, together with independent SNP-to-gene algorithms, provided convergent orthogonal support. Mechanistic dissection revealed that rs2019090 modulates PDGFD expression and endothelial phenotypes through senescence-amplified, allele-specific, HMGA1-associated enhancer-promoter regulation. This study establishes senescence-resolved joint multiomic QTL mapping as a framework for narrowing the missing regulation gap in complex disease genetics.

genetics↗

bioRxiv2026

Polarization-engineered aberration-resilient light sheet microscopy

Light sheet fluorescence microscopy enables volumetric imaging with high imaging speed, optical sectioning capability, and reduced photobleaching and phototoxicity, and has become a workhorse in bioimaging. However, widely adopted Gaussian light sheets face an inherent trade-off between axial resolution and field-of-view due to diffraction. State-of-the-art nondiffracting light sheets--including Bessel beam, Airy beam, and lattice light sheet--alleviate this trade-off but suffer from optical aberrations that compromise performance with increasing imaging depth. While the integration of adaptive optics offers a promising solution, such integrated systems are typically complex, expensive, and slow due to the need for serial mapping and correction of spatially varying aberrations across the specimen. Here, we present polarization-engineered aberration-resilient light sheet (PEARLS), a new class of monochromatic nondiffracting light sheet with temporally invariant profile and robustness to optical aberrations. In comparison with existing light sheets, PEARLS showed significantly reduced photobleaching and enhanced aberration-resilience, permitting imaging of three-dimensional subcellular dynamics in optically complex environments. We applied PEARLS for noninvasive observations of biological dynamics in various living systems, revealing phenotypic diversity across spatial and temporal scales--from rapid membrane dynamics and organelle interactions in cultured cells to coordinated mitosis and cell migrations in developing embryos.

cell biology↗

bioRxiv2026

Tunable Bessel beam two-photon fluorescence microscopy for high-speed volumetric imaging of brain dynamics

High-speed volumetric imaging of the brain is essential for linking diverse cellular events to tissue-level functions. However, the brains structural and dynamic heterogeneity--spanning microns to millimeters and milliseconds to hours--requires imaging techniques with tunable spatiotemporal resolution, flexible 3D sampling, and compatibility with targeted perturbations. Here, we present tunable Bessel beam two-photon fluorescence microscopy (tBessel-TPFM), a compact, low-cost, and versatile platform for intravital brain imaging across millimeter scale with subcellular resolution. tBessel-TPFM transforms slow 3D volume scans into fast 2D frame scans via an axially elongated Bessel focus, achieving acquisition rates [~]100-fold faster and reduced motion artifacts compared with conventional TPFM. Exploiting its full tunability of the Bessel focus, we applied tBessel-TPFM for quantitative mapping of cerebral blood flow and neurovascular coupling in normal and ischemic stroke mice. Unlike existing Bessel focus generation methods, the axial center of tBessel-TPFM remains fixed at the objective focal plane during profile tuning. Leveraging this advantage, we integrated tBessel-TPFM with simultaneous 3D targeted optogenetic stimulation for volumetric neuronal connectivity mapping. We also tracked microglial process dynamics following single-cell laser ablation, revealing diverse neuroimmune responses across spatial and temporal scales. By combining high speed, deep penetration, tunable sampling, and multimodal perturbation, tBessel-TPFM empowers a broad spectrum of neurobiological investigations--from vascular physiology and functional connectivity to neuroimmune interactions.

bioengineering↗

bioRxiv2025

In Situ, Antibody-Independent, and Multiplexed Characterization of Amyloid Plaques by MALDI MS/MS Imaging Using iprm-PASEF

BackgroundAmyloidosis collectively describes a heterogeneous group of protein aggregation-based diseases involving the misfolding and extracellular accumulation of fibril-forming amyloid proteins. The tissue deposition of these fibrils occurs either localized (limited to one organ) or systemically, impairing organ function and, in severe cases, leading to organ failure. Identification of the amyloidogenic protein leading to the correct subtyping is challenging but crucial for treatment decisions. Imaging parallel reaction monitoring (iprm)-parallel accumulation-serial fragmentation (PASEF) is a novel method for matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) that enables the fast, spatially resolved, multiplexed, and antibody-independent identification of peptides and proteins in situ. In this proof-of-concept study, we demonstrate the applicability of iprm-PASEF for the in situ characterization of amyloidosis. MethodsA multiplexed iprm-PASEF panel (comprising trapped ion mobility spectrometry (TIMS) and m/z values) for characterizing amyloid plaques by MALDI-MSI was compiled. The panel included nine peptide entries of amyloidosis-associated proteins (vitronectin, apolipoprotein E, serum amyloid P component) and the prevalent amyloidosis-subtype proteins serum amyloid A, transthyretin, and immunoglobulin light chain 2. The multiplexed iprm-PASEF panel was applied to a tissue microarray (TMA) assembled from formalin-fixed, paraffin-embedded (FFPE) specimens, comprising biopsies of amyloidosis-positive tissues from 18 patients, including six different tissue types, and representing the following amyloidosis subtypes: ATTR (transthyretin amyloidosis), AL (immunoglobulin light chain amyloidosis), and AA (secondary amyloidosis). For comparison and co-localization, congo red staining was performed on adjacent slides. ResultsMALDI TIMS MS1 imaging was acquired from the amyloidosis TMA, providing an m/z feature list containing 1390 entries that was subsequently refined to only include m/z features likely stemming from amyloidosis-related peptides. Further, we focused on optimal usage of the m/z and ion mobility range to increase the number of targeted peptides. The final iprm-PASEF panel comprised 10 entries ranging from m/z 887.51 - 1,986.85 and 1/K0 1.4 - 2.1 V{middle dot}s/cm2; targeting nine peptides from six different amyloidosis-related proteins. Apolipoprotein E, serum amyloid P component, and immunoglobulin light chain 1/2 were included with two entries. Transthyretin, vitronectin, and serum amyloid A were covered by one peptide. One entry was included as a positive control targeting actin A. We applied the iprm-PASEF (MS2 mode) panel to the amyloidosis TMA and fragment (MS2) spectra were analyzed by the search engine MASCOT. Eight out of ten peptides derived from vitronectin, apolipoprotein E, serum amyloid A, serum amyloid P component, and transthyretin were successfully identified with MASCOT scores above 18. Comparison to Congo red staining indicated a more localized and heterogeneous pattern of amyloid-associated proteins (vitronectin, apolipoprotein E, serum amyloid P component) by iprm-PASEF. Compared to the clinical annotation, transthyretin and serum amyloid A were only found in their respective subtypes. In total, it was possible to describe the spatial distribution of five different amyloid-associated proteins, thereby further characterizing Congo red-positive amyloid plaques in one single iprm-PASEF measurement. Conclusion and perspectiveThis proof-of-concept study demonstrates feasibility for in situ, antibody-independent, and multiplexed proteomic typing of amyloidosis plaques. Future enlargement of the multiplex panel is likely to increase the number of targetable amyloid proteins and to probe for the presence of post-translational modifications. The present study highlights the value of iprm-PASEF for MALDI imaging strategies.

molecular biology↗

bioRxiv2025

The China Brain Multi-omics Atlas Project (CBMAP)

The China Brain Multi-omics Atlas Project (CBMAP) aims to generate a comprehensive molecular reference map of over 1,000 human brains (Phase I), spanning a broad age range and multiple regions in China, to address the underrepresentation of East Asian populations in brain research. By integrating genome, epigenome, transcriptome, proteome (including multiple post-translational modifications), and metabolome data, CBMAP is set to provide a rich and invaluable resource for investigating the molecular underpinnings of aging-related brain phenotypes and neuropsychiatric disorders. Leveraging high-throughput omics data and advanced technologies, such as spatial transcriptomics, proteomics, and single-nucleus 3D chromatin structure analysis, this atlas will serve as a crucial resource for the brain science community, illuminating disease mechanisms and enhancing the utility of data from genome-wide association studies (GWAS). CBMAP is also poised to accelerate drug discovery and precision medicine for brain disorders.

neuroscience↗

bioRxiv2025

Autocrine CXCL1-CXCR2 Signaling Mediates Leptomeningeal Resistance to Radiation Therapy

Leptomeningeal metastasis (LM) is a fatal neurological complication of cancer. Proton craniospinal irradiation (pCSI) has emerged as a promising life-prolonging intervention for LM patients, but the response to this treatment varies. Here, we aimed to characterize the molecular basis of pCSI resistance and response. Proteomic analysis of CSF collected from LM patients at baseline (before pCSI), and at multiple time points post-treatment, identified the CXC-motif chemokine, CXCL1, as associated with LM growth. Higher CXCL1 levels in the CSF prior to pCSI correlated with worse response to this treatment. To define the role of CXCL1 in LM, we established syngeneic mouse models of LM-CSI. We found that both metastatic cancer and host cells generate CXCL1. Genetic interruption of Cxcl1 expression in metastatic cancer, but not host cells, impaired cancer cell growth within the leptomeninges. Moreover, a subset of LM cancer cells expressed Cxcr2, the primary receptor for Cxcl1, and this population was enriched over time in the leptomeninges. Transcriptomic profiling of this rare population revealed an enrichment in pathways implicated in cell cycle progression. Finally, interruption of Cxcl1-Cxcr2 signaling with intrathecally-delivered Cxcr2 antagonist hampered LM growth and sensitized the cells to CSI. Our results demonstrate that the Cxcl1-Cxcr2 signaling axis mediates LM growth, and identifies a potential actionable intervention to improve response to pCSI and halt LM progression. One Sentence SummaryCXCL1-CXCR2 axis is a potential actionable therapeutic target to halt leptomeningeal metastasis progression and enhance response to craniospinal irradiation.

cancer biology↗

bioRxiv2024

Exploring Genetic Interactions with Rare Variants Reveals Gene Networks Susceptible to Complex Diseases

Genetic interactions play a crucial role in understanding the susceptibility and etiology of complex human diseases. However, existing methods for analyzing gene-gene interactions are often limited to common variants and may not capture the effects of rare variants. In this study, we propose a novel method called GGI-RUNNER that is specifically designed for analyzing gene-gene interactions of rare variants. GGI-RUNNER evaluates the enrichment of rare variant interaction burden in patients relative to baselines in the general population. The baselines are estimated for pairwise genes by a recursive truncated negative-binomial regression model on multiple genomic features available from public data. Intensive simulations demonstrate that GGI-RUNNER exhibits substantially higher statistical power than alternative epistasis tests and maintains reasonable type I error rates even in stratified populations. Applied to real data, GGI-RUNNER identified significant rare variant interactions associated with Alzheimers disease, Hirschsprungs disease, Ulcerative colitis and Crohns disease. Furthermore, we found that these identified genes for each trait can form interconnected networks, which may provide valuable insights into the underlying molecular mechanisms.

bioinformatics↗

bioRxiv2024

Spatial Proteomics by Trapped Ion Mobility supported MALDI MS/MS Imaging: A First Glance into Multiplexed and Spatial Peptide Identification

RATIONALEIn spatial proteomics, matrix-assisted laser desorption/ionization (MALDI) imaging enables rapid and cost-effective peptide measurements. Yet, in situ peptide identification remains challenging. Therefore, this study aims to integrate the trapped ion mobility spectrometry (TIMS)-based parallel accumulation-serial fragmentation (PASEF) into MALDI imaging of tryptic peptides to enable multiplexed MS/MS imaging. METHODSAn initial MALDI TIMS MS1 survey measurement was performed, followed by a manual generation of a precursor list containing mass over charge values and ion mobility windows. Inside the dual TIMS system, submitted precursors were trapped, separately eluted by their ion mobility and analyzed in a quadrupole time-of-flight device, thereby enabling multiplexed MALDI MS/MS imaging. Finally, precursors were identified by peptide to spectrum matching. RESULTSThis study presents the first multiplexed MALDI TIMS MS/MS imaging (iprm-PASEF) of tryptic peptides. Its applicability was showcased on two histomorphologically distinct tissue specimens in a 4-plex and 5-plex setup. Precursors were successfully identified by the search engine MASCOT in one single MALDI imaging experiment for each respective tissue. Peptide identifications were corroborated by liquid-chromatography tandem mass spectrometry experiments and fragment co-localization analyses. CONCLUSIONSIn this study, we present a novel pipeline, based on iprm-PASEF that allows the multiplexed and spatial identification of tryptic peptides in MALDI imaging. Hence, it marks a first step towards the integration of MALDI imaging into the emerging field of spatial proteomics.

biochemistry↗

bioRxiv2024

Retinoid X Receptor Signaling Mediates Cancer Cell Lipid Metabolism in the Leptomeninges

Cancer cells metastatic to the leptomeninges encounter a metabolically-challenging extreme microenvironment. To understand adaptations to this space, we subjected leptomeningeal-metastatic (LeptoM) mouse breast and lung cancers isolated from either the leptomeninges or orthotopic primary sites to ATAC-and RNA-sequencing. When inhabiting the leptomeninges, the LeptoM cells demonstrated transcription downstream of retinoid-X-receptors (RXRs). We found evidence of local retinoic acid (RA) generation in both human leptomeningeal metastasis and mouse models in the form of elevated spinal fluid retinol and expression of RA-generating dehydrogenases within the leptomeningeal microenvironment. Stimulating LeptoM cells with RA induced expression of transcripts encoding de novo fatty acid synthesis pathway enzymes in vitro. In vivo, while deletion of Stra6 did not alter cancer cell leptomeningeal growth, knockout of Rxra/b/g interrupted cancer cell lipid biosynthesis and arrested cancer growth. These observations illustrate a mechanism whereby metastatic cancer cells awake locally-generated developmental cues for metabolically reprograming, suggesting novel therapeutic approaches.

cancer biology↗

bioRxiv2024

Stratifying variant deleteriousness and trait-modulating effect under human recent adaptation

Despite advances in annotating and interpreting human genetic variants, existing methods to distinguish deleterious/pathogenic from neutral variants still inadequately capture the nuanced impact of genetic variants on fitness and disease susceptibility. In this study, we introduced a new deep learning framework, the FIND model, by stratifying genetic variants into refined categories based on selection pressures and derived allele frequency. FIND demonstrated superior performance over existing genome-wide methods, delivering enhanced resolution in differentiating trait-modulating alleles from those that are pathogenic or neutral. Access to base-wise informative annotations has unveiled novel features that significantly enhance the model interpretability, and FIND has adeptly delineated evolutionary trends in human accelerated regions. Furthermore, applying FIND to the interpretation of clinical variants demonstrates its substantial potential in reclassifying variants of unknown significance. This work advances our understanding of the genetic underpinnings of human adaptation and disease, providing a new tool to explore the complexities of genetic contributions to health.

genetics↗

bioRxiv2024

Fluorescence hybridization chain reaction enables localization of multiple molecular classes combined with plant cell ultrastructure

BackgroundRecent developments in hybridization chain reaction (HCR) have enabled robust simultaneous localization of multiple mRNA transcripts using fluorescence in situ hybridization (FISH). Once multiple split initiator oligonucleotide probes bind their target mRNA, HCR uses DNA base-pairing of fluorophore-labeled hairpin sets to self-assemble into large polymers, amplifying the fluorescence signal and reducing non-specific background. Few studies have applied HCR in plants, despite its demonstrated utility in whole mount animal tissues and cell culture. Our aim was to optimize this technique for sectioned plant tissues embedded with paraffin and methacrylate resins, and to test its utility in combination with immunolocalization and subsequent correlation with cell ultrastructure using scanning electron microscopy. ResultsApplication of HCR to 10 {micro}m paraffin sections of 17-day-old Setaria viridis (green millet) inflorescences using confocal microscopy revealed that the transcripts of the transcription factor KNOTTED 1 (KN1) were localized to developing floret meristem and vascular tissue while SHATTERING 1 (SH1) and MYB26 transcripts were co-localized to the breakpoint below the floral structures (the abscission zone). We also used methacrylate de-embedment with 1.5 {micro}m and 0.5 {micro}m sections of 3-day-old Arabidopsis thaliana seedlings to show tissue specific CHLOROPHYLL BINDING FACTOR a/b (CAB1) mRNA highly expressed in photosynthetic tissues and ELONGATION FACTOR 1 ALPHA (EF1) highly expressed in meristematic tissues of the shoot apex. The housekeeping gene ACTIN7 (ACT7) mRNA was more uniformly distributed with reduced signals using lattice structured-illumination microscopy. HCR using 1.5 {micro}m methacrylate sections was followed by backscattered imaging and scanning electron microscopy thus demonstrating the feasibility of correlating fluorescent localization with ultrastructure. ConclusionHCR was successfully adapted for use with both paraffin and methacrylate de-embedment on diverse plant tissues in two model organisms, allowing for concurrent cellular and subcellular localization of multiple mRNAs, antibodies and other affinity probe classes. The mild hybridization conditions used in HCR made it highly amenable to observe immunofluorescence in the same section. De-embedded semi-thin methacrylate sections with HCR were compatible with correlative electron microscopy approaches. Our protocol provides numerous practical tips for successful HCR and affinity probe labeling in electron microscopy-compatible, sectioned plant material.

plant biology↗

bioRxiv2023

Endogenous fine-mapping of functional regulatory elements in complex genetic loci

The vast majority of genetic loci associated with polygenic complex traits are located in non-coding regions of the human genome. However, many of these regions exhibit high- order gene regulatory relationships and complicated linkage disequilibrium (LD) configurations, which bring challenges to accurately identify causal variants and their target genes controlling specific molecular processes or traits. We employed multiplexed single-cell CRISPR interference and activation perturbations to explore the links between cis-regulatory element (CRE) and target gene expression within tight LD in the endogenous chromatin context. We validated the prevalence of multiple causality in perfect LD (pLD) for independent expression quantitative trait locus (eQTL), and revealed fine-grained genetic effects on gene expression within pLD. These effects are difficult to decipher using conventional eQTL fine-mapping or to predict via existing computational methods. We found that nearly half of the casual CREs lack classical epigenetic markers, potentially affecting gene expression through hidden regulatory mechanisms. Integrative analysis on different types of perturbation effects suggested a high regulatory plasticity of the human genome. These findings will propel further in-depth exploration of functional genomic elements, facilitating a more comprehensive understanding of gene expression regulatory patterns and the development of complex traits.

genomics↗

bioRxiv2023

Gender-specific impact of trans 10, cis 12-conjugated linoleic acid on pai transgenic female mice

Dietary trans 10, cis 12-conjugated linoleic acid (t10c12-CLA) is a potential candidate in anti-obesity trials. A transgenic mouse was previously successfully established to determine the anti-obesity properties of t10c12-CLA in male mice that could produce endogenous t10c12-CLA. To test whether there is a different impact of t10c12-CLA on lipid metabolism in both sexes, this study investigated the adiposity and metabolic profiles of female Pai mice that exhibited a dose-dependent expression of foreign Pai gene and a shift of t10c12-CLA content in tested tissues. Compared to their gender-match wild-type littermates, Pai mice had no fat reduction but exhibited enhanced lipolysis and thermogenesis by phosphorylated hormone-sensitive lipase and up-regulating uncoupling proteins in brown adipose tissue. Simultaneously, Pai mice showed hepatic steatosis and hypertriglyceridemia by decreasing gene expression involved in lipid and glucose metabolism. Further investigations revealed that t10c10-CLA induced excessive prostaglandin E2, adrenaline, corticosterone, glucagon and inflammatory factors in a dose-dependent manner, resulting in less heat release and oxygen consumption in Pai mice. Moreover, fibroblast growth factor 21 overproduction only in monoallelic Pai/wt mice indicates that it was sensitive to low doses of t10c12-CLA. These results suggest that chronic t10c12-CLA has system-wide effects on female health via synergistic actions of various hormones.

physiology↗

bioRxiv2023

Leptomeningeal anti-tumor immunity follows unique signaling principles

Metastasis to the cerebrospinal fluid (CSF)-filled leptomeninges, or leptomeningeal metastasis (LM), represents a fatal complication of cancer. Proteomic and transcriptomic analyses of human CSF reveal a substantial inflammatory infiltrate in LM. We find the solute and immune composition of CSF in the setting of LM changes dramatically, with notable enrichment in IFN-{gamma} signaling. To investigate the mechanistic relationships between immune cell signaling and cancer cells within the leptomeninges, we developed syngeneic lung, breast, and melanoma LM mouse models. Here we show that transgenic host mice, lacking IFN-{gamma} or its receptor, fail to control LM growth. Overexpression of Ifng through a targeted AAV system controls cancer cell growth independent of adaptive immunity. Instead, leptomeningeal IFN-{gamma} actively recruits and activates peripheral myeloid cells, generating a diverse spectrum of dendritic cell subsets. These migratory, CCR7+ dendritic cells orchestrate the influx, proliferation, and cytotoxic action of natural killer cells to control cancer cell growth in the leptomeninges. This work uncovers leptomeningeal-specific IFN-{gamma} signaling and suggests a novel immune-therapeutic approach against tumors within this space.

cancer biology↗

bioRxiv2023

Metabolic impact of trans 10, cis 12-conjugated linoleic acid in pai transgenic mice

Trans 10, cis 12-conjugated linoleic acid (t10c12-CLA) from ruminant-derived foodstuffs can induce body fat loss in mammals after oral administration, while its mechanism on fat reduction has yet to be clarified fully until now. In the current study, a transgenic mouse that produced t10c12-CLA had been generated by inserting the Propionibacterium acnes isomerase (Pai) expression cassette into the Rosa26 locus, and its male offspring were used to decipher an irreversible long-term impact of t10c12-CLA on health and its mechanism of action. Compared to their wild-type C57BL/6J littermates, comprehensive phenotype profiling of biallelic pai/pai mice indicated that white fat was decreased while brown fat was increased reversely; meanwhile, more heat was released and the central activities were reduced. Besides decreased plasma triglycerides in both pai genotypes and increased serum FGF21 in pai/wt mice, RNA and protein analysis revealed that the fatty acid oxidation and thermogenesis capacity of brown adipose tissues were elevated via CPT1B and UCP1/2 over-expression. The results indicate that the t10c12-CLA-induced fat loss might be caused by the excess FGF21 and the increased mass and extra thermogenesis of brown adipose tissue in transgenic mice.

physiology↗

bioRxiv2023

Unraveling the causal genes and transcriptomic determinants of human telomere length

Telomere length (TL) shortening is a pivotal indicator of biological aging and is associated with many human diseases. The genetic determinates of human TL have been widely investigated, however, most existing studies were conducted based on adult tissues which are heavily influenced by lifetime exposure. Based on the analyses of terminal restriction fragment (TRF) length of telomere, individual genotypes, and gene expressions on 166 healthy placental tissues, we systematically interrogated TL-modulated genes and their potential functions. We found that placental TL is relatively longer across human tissues and which maintenance is mostly connected to genes responsible for alternative lengthening of telomeres. Trans-ancestral TL genome-wide association studies (GWASs) on 644,553 individuals identified 20 novel genetic associations and provided increased polygenic determination of human TL. Next, we integrated the powerful TL GWAS with placental expression quantitative trait locus (eQTL) mapping to prioritize 31 likely causal genes, among which 4 were functionally validated, including MMUT, RRM1, KIAA1429, and YWHAZ. Finally, modeling transcriptomic signatures and TRF-based TL improved the prediction performance of human TL. This study deepened our understanding of causal genes and transcriptomic determinants of human TL, promoting the mechanistic research on fine-grained TL regulation.

genetics↗