Biology subjects

Xiang, R.

Publications and source records attributed to Xiang, R..

At least 19 recordsLinked to original sources

bioRxiv2026

A multi-tissue epigenomic atlas links the sheep non-coding genome to domestication and complex traits

Non-coding regulatory variation drives complex traits, domestication, and evolutionary adaptation, yet the sheep genome lacks high-resolution functional annotation. Here we present SheepEpimap, a multi-tissue regulatory atlas harmonizing 516 CUT&Tag histone modifications, ATAC-seq, and RNA-seq datasets across 43 adult tissues in sheep. We annotated 2.93 million cis-regulatory elements, yielding 557,441 enhancer-gene pairs and 145,407 variants with allele-specific effects. By training a sequence-to-function deep-learning model, we decoded the base-pair syntax of chromatin accessibility, annotated transcription factor motif instances genome-wide, and constructed 12,210 tissue-specific gene regulatory networks (GRNs). Integrating this resource with multi-tissue expression quantitative trait loci, selection sweeps, and genome-wide association studies prioritized non-coding variants driving domestication and complex traits. Finally, cross-species analysis revealed that sequence-conserved, tissue-matched enhancers were significantly enriched in the heritability of complex traits and diseases in humans. In summary, SheepEpimap (https://genome.ucsc.edu/s/mengzhu/SheepEpimap) provides an open-access foundational ecosystem for sheep functional genomics, precision breeding, and comparative biology.

genetics↗

bioRxiv2026

Toward routine health phenotyping: High-throughput prediction of metabolic, immune, and inflammatory biomarkers from milk mid-infrared spectroscopy in early-lactation dairy cows

This study evaluated the potential of milk mid-infrared (MIR) spectroscopy, combined with routinely available on-farm variables, for predicting serum metabolic, immune, and inflammatory biomarkers in early-lactation cows. Data included 5,936 blood samples from 4,442 cows across 23 Australian dairy herds, with paired milk MIR spectra and serum measurements for up to 14 biomarkers. Prediction models were developed using partial least squares regression and evaluated using nested 10-fold random cross-validation and leave-one-herd-out validation. The results show that while basic herd-test data, including milk fat, protein, and lactose concentration, as well as on-farm variables, including DIM, calving age, breed, and herd could predict serum biomarkers, combining MIR spectra with these on-farm variables produced the best overall performance. In random cross-validation, blood urea nitrogen (BUN) was predicted most accurately (R2 = 0.78), while {beta}-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) showed moderate accuracy (R2 = 0.56 and 0.44, respectively). BUN also showed the strongest external validation performance, with leave-one-herd-out R2 = 0.58 and comparable accuracy for predicting records collected after 70 days in milk (R2 = 0.65). BHB and NEFA had moderate leave-one-herd-out accuracy but did not transfer beyond early lactation. Most other biomarkers showed low or inconsistent external validation performance. Overall, MIR spectroscopy combined with on-farm variables shows promise for routine prediction of BUN, BHB and NEFA, which can be used for monitoring and genetic evaluation of, for example, ketosis and energy deficit. Initial random cross-validation results for glucose, bilirubin and cholesterol were promising, but more data is needed to improve the prediction accuracy and robustness of the predictions. HighlightsO_LIMilk MIR can predict several serum biomarkers in early-lactation dairy cows. C_LIO_LIMIR-predicted blood urea nitrogen shows the greatest accuracy and robustness. C_LIO_LIMIR-predicted {beta}-hydroxybutyrate and nonesterified fatty acids show moderate accuracy. C_LIO_LIMost mineral, hepatic, and inflammatory biomarkers had limited accuracy. C_LIO_LIRoutine MIR phenotyping is most promising for BUN, BHB, and NEFA. C_LI SummaryMilk mid-infrared (MIR) spectroscopy and on-farm variables are evaluated as a high-throughput tool to predict health-related serum biomarkers in early-lactation dairy cows. The data include 5,936 paired blood and milk samples from 4,442 cows across 23 Australian dairy herds and up to 14 serum biomarkers. Prediction models are developed using partial least squares regression with nested random cross-validation and leave-one-herd-out validation. Blood urea nitrogen (BUN) shows the greatest and most transferable prediction accuracy across herds and lactation stages. {beta}-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) are predicted with moderate accuracy, but only during early lactation. Random cross-validation results for glucose and bilirubin are promising, but larger datasets are needed for robust external validation. Most other mineral, hepatic, and inflammatory biomarkers show limited external prediction accuracy. These results indicate that MIR-based routine health phenotyping is most promising for BUN, BHB, and NEFA.

genetics↗

bioRxiv2026

New genes play a prominent role in evolution of new sperm classes of Drosophila

The widespread and regulated production of infertile parasperm assisting fertilization of eusperm provides a compelling model for elucidating the mechanisms of cellular innovation and altruism. Here we identify two specific parasperm lineages in Drosophila pseudoobscura that are segregated in development from the eusperm lineage by their single-cell transcriptomes. Most X-linked genes, except for species-specific new genes, show testis-specific repressive epigenetic modifications and become downregulated upon meiotic entry, supporting meiotic X chromosome inactivation. Between sperm classes, nearly half of the known meiotic arrest genes and their downstream targets are differentially transcribed, with over 200 genes displaying a gradient of transcription levels correlated with that of tail lengths. New genes are overrepresented throughout the hierarchical regulatory network of sperm divergence and over 60% of them exhibit a new cell-level expression compared to their parental copies. These results together indicate that new genes play a prominent role in the emergence of low-cost parasperm that shield the eusperm until fertilization.

evolutionary biology↗

bioRxiv2026

Multi-objective Engineering of Trimethylamine Monooxygenase for Improved Thermostability and Cofactor Use

Trimethylamine (TMA) is a major contributor to undesirable odours in protein hydrolysates derived from marine by-products, limiting their industrial use. Flavin-containing monooxygenases (FMOs) catalyse the conversion of TMA to the odourless trimethylamine N-oxide (TMAO); however, industrial applications demand enzymes that are both thermally stable and compatible with cost-effective cofactors. A thermostable variant of the Methylophaga aminisulfidivorans FMO (mFMO_20) can function at elevated temperatures but depends exclusively on the expensive and unstable cofactor NADPH. In this study, we investigated whether it is possible to simultaneously enhance thermostability and NADH compatibility using a multi-objective engineering strategy. We first targeted residues in the cofactor binding site of mFMO_20 to restore NADH activity, which had been completely lost despite the wild type enzyme being naturally active with both cofactors. Variants derived from the thermostable scaffold partially recovered NADH activity but showed reduced NADPH activity. Given the wild types inherent NADH compatibility, we next pursued a stability-improvement approach, introducing highly conserved stabilizing mutations. This preserved cofactor competence but produced only modest improvements in thermostability. Finally, by combining physical, evolutionary, and statistical metrics, we obtained variants that retained higher NADPH activity after heat treatment than any previously reported thermostable mutants, while a subset also retained measurable NADH activity before heat treatment. These findings show that combining complementary scoring strategies helps navigate the trade-off between stability and activity; while, robust NADH function under thermal stress remains elusive, with only one variant retaining detectable NADH activity after heat treatment, the results provide valuable insight into the underlying constraints linking stability and cofactor usage and highlights possible directions for engineering FMOs with both enhanced thermostability and cofactor compatibility. Author summaryIn this work, we aimed to improve an enzyme that could be useful in industrial applications but is limited by two common constraints: poor stability at high temperatures and dependence on an expensive cofactor. To make the enzyme more suitable for large-scale applications, we sought to engineer variants that are both more thermostable and compatible with a cheaper cofactor, NADH. For enzyme engineering, we used a strategy that balances several properties rather than prioritizing a single trait. We combined tools that capture evolutionary patterns, protein physics, and AI-based predictions to explore which mutations might provide the right combination of stability and function. Through this approach, we obtained variants with improved heat resistance and higher cofactor activity retention.

molecular biology↗

bioRxiv2026

Sex-specific Genetic Regulatory Effects in Chickens

Sexual dimorphism is a defining vertebrate feature, yet its sex-specific molecular architecture remains poorly understood. Here we established a sex-balanced, uniformly reared chicken cohort to map this landscape, integrating individual whole-genome sequencing with 7,969 bulk and 779,380 single nucleus transcriptomes across 32 tissues from 280 birds. We identified 495,098 independent expression quantitative trait loci for 20,194 genes, including 10,937 loci modulated by cell-type composition. Notably, 340 genes were regulated by 449 loci in a sex-dependent manner, significantly enrichment in endocrine tissues like adipose and the adrenal gland. Furthermore, we fine-mapped 1,219 structural variants, demonstrating their unique roles to tissue- and sex-specific expression beyond SNPs. Ultimately, we showed the utility of these regulatory effects in elucidating the molecular basis of metabolism and complex traits in both chickens and humans. This comprehensive atlas of regulatory effects provides profound insights into the genomic and molecular basis of sexual dimorphism in vertebrates.

genomics↗

bioRxiv2026

BayesR3AD: Joint analysis of additive and dominance in Bayesian mixture models

BackgroundGenomic prediction in livestock is predominantly based on additive models, even though dominance and other non-additive effects can contribute appreciably to phenotypic variance for fitness and fertility traits. Bayesian mixture models, such as Bayes R, have proven effective for modelling sparse, heterogeneous additive SNP effects, but most implementations do not explicitly accommodate dominance. In this study, we extended BayesR3 to jointly model additive and dominance marker effects within a unified Bayesian mixture framework, denoted BayesR3AD, and used this method to estimate additive and dominance effects for fertility and cow survival (longevity) in Holstein cattle. ResultsUsing real Holstein genotypes (227,942 animals, 74,626 SNPs), we simulated phenotypes with additive and dominance effects. When dominance was present in the simulated data, BayesR3AD improved prediction accuracy of genetic values by +0.1011 (0.6144 vs 0.5133; {approx}19.7% relative) compared with the additive-only BayesR3 model and recovered additive and dominance variance components without bias. Under purely additive simulations, dominance mixture components were effectively empty, confirming that the extended model shrinks unnecessary dominance effects toward zero. In real fertility data, including calving interval (63,378 records) and survival (68,514 records), BayesR3AD estimated small dominance variance ({approx}1-3% of total genetic variance). The model highlighted a very large additive loci at 57.82 Mb on BTA18 for both calving interval and survival. concordant with previous GWAS studies of Holstein fertility. Additionally, a large dominance effect was found at 44.37 Mb on BTA18 for calving interval implicating a heterozygote advantage that increases fertility. ConclusionsBayesR3AD provides a practical extension of BayesR3 that captures both additive and dominance contributions to genomic prediction. The method is robust, reverting effectively to the additive model when dominance is absent, while delivering accurate variance decomposition, and potential gains in prediction accuracy when dominance is present. Application to Holstein fertility traits demonstrates that dominance can be detected and quantified without compromising additive inference, supporting improved prediction of total genetic merit. While validated in cattle, BayesR3AD can be directly applied to other species to better model and predict traits related to fitness.

genetics↗

bioRxiv2025

Acute cold exposure in humans shifts the circulating proteome to a cardioprotective and anti-aging profile

Cold exposure has been proposed to provide a constellation of salutary effects, yet its molecular correlates remain largely unknown. Brown adipose tissue (BAT) is the main site of adaptive thermogenesis, and its prevalence is linked with cardiometabolic health. Since the benefits of BAT activation and cold exposure more generally may be mediated through blood-borne factors, we conducted an extensive analysis of the circulating proteome linked with an acute cold challenge in healthy adults. Our goal was to uncover early molecular changes triggered by cooling and establish their specific relationships with the human brown adipocyte secretome as well as various phenotypic traits. Based on comprehensive inter-cohort validations, we provide the first reproducible proteomic signature of cold exposure in humans. Our data demonstrate that cooling favorably modulates circulating mediators linked with chronological aging, as well as metabolic and cardiovascular diseases, providing new potential biochemical transducers of the benefits associated with cold therapy. HighlightsO_LICooling alters the plasma proteome with striking concordance in independent human cohorts. C_LIO_LICooling represses circulating proteins linked with type 2 diabetes, hypercholesterolemia, hypertension, coronary heart disease and heart failure. C_LIO_LIThe circulating signature of cooling resembles a cardioprotective and anti-aging profile. C_LI

physiology↗

bioRxiv2025

Dynamic neural representations of scene beauty are relatively unaffected by stimulus timing and task

Understanding the neural correlates of aesthetic experiences in natural environments is a central question in neuroaesthetics. A previous EEG study (Kaiser, 2022) identified early and temporally sustained neural representations of visual scene beauty. These results were obtained with long presentation durations (1,450 ms) and with explicit beauty judgments, rendering it unclear how presentation time and task demands shape the neural correlates of scene beauty. In two EEG experiments, we replicated this study while varying presentation time and task. Experiment 1 tested whether reducing stimulus presentation time from 1,450 ms to 100 ms altered neural representations of beauty. Experiment 2 examined whether beauty-related representations prevailed when participants performed an orthogonal task instead of explicitly judging beauty. Representational similarity analysis revealed that beauty-related neural representations emerged early (within 150 - 200 ms post-stimulus) and were sustained over time, in line with previous findings. Critically, we found that neither reduced presentation time nor the absence of an explicit beauty judgment significantly altered beauty-related neural dynamics. These results suggest that the neural correlates of scene beauty are relatively robust to stimulus presentation and task regimes, providing a potential correlate of the spontaneous perception of beauty in natural environments.

neuroscience↗

bioRxiv2024

A multi-tissue developmental gene expression atlas towards understanding the biological basis of phenotypes in sheep

Sheep (Ovis aries) represents one of the most important livestock species for animal protein and wool production worldwide. However, little is known about the genetic and biological basis of ovine phenotypes, particularly for those of high economic value and environmental impact. Here, by generating and integrating 1,413 RNA-seq samples from 51 distinct tissues across 14 developmental time points, representing early prenatal, late prenatal, neonate, lamb, juvenile, adult, and elderly stages, we built a high-resolution developmental Gene Expression Atlas (dGEA) in sheep. We observed dynamic patterns of gene expression and regulatory networks across tissues and developmental stages. When harnessing this resource for interpreting genomic associations of 48 monogenetic and 12 complex traits in sheep, we found that genes upregulated at prenatal developmental stages played more important roles in shaping these phenotypes than those upregulated at postnatal stages. For instance, genetic associations of crimp number, mean staple length (MSL), and individual birth weight were significantly enriched in the prenatal rather than postnatal skin and immune tissues. By comprehensively integrating fine-mapping results and the sheep dGEA, we identified several key genes associated with complex traits in sheep, such as SOX9 (associated with MSL), GNRHR (associated with litter size at birth), and PRKDC (associated with live weight). These results provide novel insights into the gene regulatory and developmental architecture underlying ovine phenotypes. The dGEA (https://sheepdgea.njau.edu.cn/) will serve as an invaluable resource for sheep developmental biology, genetics, genomics, and selective breeding.

genetics↗

bioRxiv2024

An integrative approach to prioritize candidate causal genes for complex traits in cattle

Genome-wide association studies (GWAS) have identified many quantitative trait loci (QTL) associated with complex traits, predominantly in non-coding regions, posing challenges in pinpointing the causal variants and their target genes. Three types of evidence can help identify the gene through which QTL act: (1) proximity to the most significant GWAS variant, (2) correlation of gene expression with the trait, and (3) the genes physiological role in the trait. However, there is still uncertainty in the success of these methods in identifying the correct genes. Here we test the ability of these methods in a comparatively simple series of traits associated with the concentration of polar lipids in milk. We conducted single-trait GWAS for [~]14 million imputed variants and 56 individual milk polar lipid (PL) phenotypes in 336 cows. A meta-analysis of multi-trait GWAS identified 10,063 significant SNPs at FDR [≤] 10% (P [≤] 7.15E-5). Transcriptome data from blood ([~]12.5K genes, 143 cows) and mammary tissue ([~]12.2K genes, 169 cows) were analysed using the genetic score omics regression (GSOR) method. This method links observed gene expression to genetically predicted phenotypes and was used to find associations between gene expression and 56 PL phenotypes. GSOR identified 2,186 genes in blood and 1,404 in mammary tissue associated with at least one PL phenotype (FDR [≤] 1%). We partitioned the genome into non-overlapping windows of 100 Kb to test for overlap between GSOR-identified genes and GWAS signals. We found a significant overlap between these two datasets, indicating GSOR significant genes were more likely to be located within 100 Kb windows that have GWAS signals compared to those without (P = 0.01; odds ratio = 1.47). These windows included 70 significant genes expressed in mammary tissue and 95 in blood. Compared to all expressed genes in each tissue, these genes were enriched for lipid metabolism gene ontology (GO). That is, 7 of the 70 significant mammary transcriptome genes (P < 0.01; odds ratio = 3.98) and 5 of the 95 significant blood genes (P < 0.10; odds ratio = 2.24) were involved in lipid metabolism GO. The candidate causal genes include DGAT1, ACSM5, SERINC5, ABHD3, CYP2U1, PIGL, ARV1, SMPD5, and NPC2, with some overlap between the two tissues. The overlap between GWAS, GSOR, and GO analyses suggests that together these methods can identify genes mediating QTL, though their power remains limited, as reflected by modest odds ratios. Larger sample sizes would enhance the power of these analyses, but issues like linkage disequilibrium would remain.

genomics↗

bioRxiv2024

Deciphering the Cell Specific Transcript Heterogeneity and Alternative Splicing during the Early Embryonic Development of Zebrafish

Cell fate determination during early embryonic development is a complex process modulated by gene expression. The intricate interplay of transcriptional and post-transcriptional regulation is integral to the developmental trajectory of embryogenesis, yet how RNA processing may contribute to early development programming is largely elusive. Leveraging recent technological advances in single-molecule nanopore sequencing, we developed a single-cell long-read transcriptome sequencing technology, allowing a clear view of transcript diversity during zebrafish embryogenesis during pre- and post-zygotic genome activation (ZGA). A closer examination of the dynamic transcript usage and potential alternative splicing revealed that abundant stage-specific transcripts with differential coding potentials are involved in distinct biological functions. Specifically, we identified two cell populations at the onset of ZGA based on isoform diversity instead of gene profiling, which followed divergent developmental trajectories toward the ectoderm and the presumptive ectoderm. These two populations of cells were characterized by divergent splicing regulations linked to differential RNA-binding proteins, including SNRPA and SFPQ. Altogether, using the single-cell long-read transcriptome sequencing strategy, we work has revealed the cell-specific transcriptome dynamics contributing to the cell fate determination during embryogenesis.

developmental biology↗

bioRxiv2024

Spatiotemporal transcriptomic maps of mouse intracerebral hemorrhage at single-cell resolution

Intracerebral hemorrhage (ICH) is a severe and widespread disease that results in high mortality and morbidity. Despite significant advances made in clinical and preclinical research, the prognosis of ICH remains poor due to an incomplete understanding of the complex pathological responses. To address this challenge, we generated single-cell resolution spatiotemporal transcriptomic maps of mouse brain 1, 3, 7, 14, and 28 days after ICH. Our analysis revealed the cellular constituents and their dynamic responses following ICH. We found changes in gene expression that are indicative of active phagocytosis and lipid processing in the lesion core and identified genes associated with brain repair at the lesion border. Persistent lipid accumulation culminated in the phenotypic transition of macrophages into foam cells. Furthermore, our results demonstrate that ICH could stimulate neural stem cells in the subventricular zone, thereby enhancing neurogenesis in this niche. This study provides a spatiotemporal molecular atlas of mouse ICH that advances the understanding of both local and global responses of brain cells to ICH and offers a valuable resource that can aid the development of novel therapies for this devastating condition.

neuroscience↗

bioRxiv2024

A single-cell 3D spatiotemporal multi-omics atlas from Drosophila embryogenesis to metamorphosis

The development of a multicellular organism is a highly intricate process tightly regulated by numerous genes and pathways in both spatial and temporal manners. Here, we present Flysta3D, a comprehensive multi-omics atlas of the model organism Drosophila, spanning its developmental lifespan from embryo to pupa. Our datasets encompass 3D single-cell spatial transcriptomic, single-cell transcriptomic, and single-cell chromatin accessibility information. By integrating these multi-dimensional data, we constructed cell state trajectories that uncover the detailed profiles of tissue development. With a focus on the central nervous system (CNS) and midgut, we dissected the spatiotemporal dynamics of gene regulatory networks, cell type diversity, and morphological changes from a multi-omics perspective. This extensive atlas provides an unprecedentedly rich resource and serves as a systematic platform for studying Drosophila development with integrated single-cell data at an ultra-high spatiotemporal resolution.

developmental biology↗

bioRxiv2023

Integrating large-scale meta-GWAS and PigGTEx resources to decipher the genetic basis of complex traits in pig.

Understanding the molecular and cellular mechanisms that underlie complex traits in pigs is crucial for enhancing their genetic improvement program and unleashing their substantial potentials in human biomedicine research. Here, we conducted a meta-GWAS analysis for 232 complex traits with 28.3 million imputed whole-genome sequence variants in 70,328 individuals from 14 pig breeds. We identified a total of 6,878 genomic regions associated with 139 complex traits. By integrating with the Pig Genotype-Tissue Expression (PigGTEx) resource, we systemically explored the biological context and regulatory circuits through which these trait-associated variants act and finally prioritized 16,664 variant-gene-tissue-trait circuits. For instance, rs344053754 regulates the expression of UGT2B31 in the liver by affecting the activity of regulatory elements and ultimately influences litter weight at weaning. Furthermore, we investigated the conservation of genetic and regulatory mechanisms underlying 136 human traits and 232 pig traits. Overall, our multi-breed meta-GWAS in pigs provides invaluable resources and novel insights for understanding the regulatory and evolutionary mechanisms of complex traits in both pigs and humans.

genetics↗

bioRxiv2022

Spateo: multidimensional spatiotemporal modeling of single-cell spatial transcriptomics

Cells do not live in a vacuum, but in a milieu defined by cell-cell communication that can be measured via emerging high-resolution spatial transcriptomics approaches. However, analytical tools that fully leverage such data for kinetic modeling remain lacking. Here we present Spateo (aristoteleo/spateo-release), a general framework for quantitative spatiotemporal modeling of single-cell resolution spatial transcriptomics. Spateo delivers novel methods for digitizing spatial layers/columns to identify spatially-polar genes, and develops a comprehensive framework of cell-cell interaction to reveal spatial effects of niche factors and cell type-specific ligand-receptor interactions. Furthermore, Spateo reconstructs 3D models of whole embryos, and performs 3D morphometric analyses. Lastly, Spateo introduces the concept of "morphometric vector field" of cell migrations, and integrates spatial differential geometry to unveil regulatory programs underlying various organogenesis patterns of Drosophila. Thus, Spateo enables the study of the ecology of organs at a molecular level in 3D space, beyond isolated single cells.

systems biology↗

bioRxiv2022

The first homosporous lycophyte genome revealed the association between the dynamic accumulation of LTR-RTs and genome size variation

Lycophytes and euphyllophytes (ferns and seed plants) are the two surviving lineages of vascular plants. The modern lycophytes (clubmosses) are herbaceous found either heterosporous (Isoetales and Selaginellales) or homosporous (Lycopodiales). The contrasting genome size between homosporous and heterosporous plants has long been an attractive topic. Most clubmosses are the resource plants of Huperzine A (HupA) which is invaluable for treating Alzheimers disease, but the evolutionary trajectory of which in land plants is unexplored. To better understand these fundamental questions, the genome data of a homosporous lycophyte is urgently required. We generated the Lycopodium clavatum L. genome by applying a reformed pipeline for filtering out non-plant sequences. The obtained genome size is 2.30 Gb, distinguished in more than 85% repetitive elements of which 62% is LTR. Two whole genome duplications (WGDs) are rigorously detected. The content of LTR-RTs was more than ten times higher in homosporous lycophytes than heterosporous ones, although most appeared within one Mya. Then, we find that the LTR-RTs birth-death mode (a much greater birth and extremely slower death) contributes the accumulation of LTR-RTs resulting homosporous lycophyte genome expansion, while in heterosporous lycophytes, the mode is exactly the opposite. Furthermore, the five necessary enzymes of the HupA biosynthetic pathway were identified in the L. clavatum genome, but absent in the other land plants. This decoded genome data will be a key cornerstone to elucidating the fundamental aspects of lycophyte biology and land plant evolution.

genomics↗

bioRxiv2022

Development of an affinity-enhanced clinical candidate TCR targeting NY-ESO-1 with optimal potency and high specificity

The clinical success of T-cell receptor (TCR)-based immunotherapy depends on the efficacy and specificity of TCRs. Naturally occurring TCRs have limited anti-tumor potency due to their low affinity for tumor antigens. Affinity enhancement is a promising strategy to generate highly potent TCRs. However, it is concerned that affinity-enhanced TCRs are prone to lose specificity. We isolated low affinity TCRs specific for NY-ESO-1157-165/HLA-A*02:01 from peripheral blood mononuclear cells of healthy donors. An affinity-enhanced TCR candidate with optimal affinity and specificity was generated using phage display and an extensive set of in vitro and in vivo assays. Alanine scanning mutagenesis showed that the TCR candidate retained specificity by making extensive contacts to the side chains of NY-ESO-1157-165 peptide. Adoptive transfer of T cells engineered with this candidate (termed TAEST16001) significantly inhibited tumor growth in subcutaneous, metastatic, and patient-derived xenograft (PDX) mouse tumor models. This study demonstrates that sophisticated engineering and screening techniques can be utilized to generate a clinical candidate TCR with potent anti-tumor activity without losing specificity. TAEST16001 was approved by the Center for Drug Evaluation (CDE) as the first TCR-based immunotherapy clinical trial in China (ClinicalTrials.gov Identifier: NCT03159585).

immunology↗

bioRxiv2022

Genetic score omics regression and multi-trait meta-analysis detect widespread cis-regulatory effects shaping bovine complex traits

To complete the genome-to-phenome map, transcriptome-wide association studies (TWAS) are performed to correlate genetically predicted gene expression with observed phenotypic measurements. However, the relatively small training population assayed with gene expression could limit the accuracy of TWAS. We propose Genetic Score Omics Regression (GSOR) correlating observed gene expression with genetically predicted phenotype, i.e., genetic score. The score, calculated using variants near genes with assayed expression, provides a powerful association test between cis-effects on gene expression and the trait. In simulated and real data, GSOR outperforms TWAS in detecting causal/informative genes. Applying GSOR to transcriptomes of 16 tissue (N[~]5000) and 37 traits in [~]120,000 cattle, multi-trait meta-analyses of omics-associations (MTAO) found that, on average, each significant gene expression and splicing mediates cis-genetic effects on 8[~]10 traits. Supported by Mendelian Randomisation, MTAO prioritised genes/splicing show increased evolutionary constraints. Many newly discovered genes/splicing regions underlie previously thought single-gene loci to influence multiple traits.

genomics↗