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Liu, Y.

Publications and source records attributed to Liu, Y..

At least 1,189 records · Page 66Linked to original sources

Electromigration of Charged Analytes Through Immiscible Fluids in Multiphasic Electrophoresis

Multiphasic buffer systems have been of greatest interest in electrophoresis and liquid-liquid electrotransfer; this study extends that foundation by exploring the interplay of the geometric and viscous properties of an interleaving oil layer on the electrotransfer of a charged analyte from an aqueous solution into a hydrogel. We utilized finite element analysis to examine two complementary configurations: one being electrotransfer of a charged analyte (protein) in an aqueous phase into a surrounding hydrogel layer and another being electrotransfer of the protein from that originating aqueous phase - through an interleaving oil layer of predetermined viscosity and thickness - and into a surrounding hydrogel layer. Results indicate that the presence of an oil layer leads to increased skew of the injected peak. To explain this difference in injection dispersion, we utilize Probsteins framework and compare the Peclet (Pe) number with the ratio between length scales characteristic to the axial and radial dispersion, respectively. The formulation assigns electrotransfer conditions into six different dispersion regimes. We show that the presence or absence of an interleaving oil layer moves the observed peak dispersion into distinct electrotransfer regimes; the presence of an oil layer augments the electrophoretic mobility mismatch between the different phases, resulting in a five-fold increase in Pe and a six-fold increase in the ratio between the axial to radial dispersion characteristic lengths. We further show that oil viscosity significantly influences resultant injection dispersion. A decrease in oil-layer viscosity from 0.08 Pa{middle dot}s to 0.02 Pa{middle dot}s results in a >100% decrease in injection dispersion. Our theoretical predictions were experimentally validated by comparing the electrotransfer regimes of three different mineral oil samples. We show that lowering the oil viscosity to 0.0039 Pa{middle dot}s results in an injection regime similar to that of the absence of an oil layer. Additionally, we measure the migration distance and show that average electromigration velocity over the transit duration is inversely proportional to the viscosity of an interleaving oil layer. Understanding of the impact of electrotransfer of charged species across multiple immiscible fluid layers on peak dispersion informs the design of multiphasic electrophoresis systems.

bioengineering↗

Nanoliter-scale selection of optimized bioengineered peptide antibiotics that rescue mice with bacterial lung infection

Increasing numbers of multi-drug resistant pathogens call for new chemical scaffolds, addressing novel targets, that can serve as lead structures for the development of life-saving drugs. For antibiotics, natural product-inspired molecules represent a most promising resource. Natural products evolved to high chemical complexity and occupy a chemical space different than synthetic libraries. However, clinical translation of promising natural products is often impeded by their relative inaccessibility to medicinal chemistry optimization, e.g. iterative synthesis of large series of derivatives. Here, this limitation is addressed with a randomized library of bicyclic heptapeptides based on the natural product darobactin that hits the clinically not addressed target BamA. Variants of the ribosomally synthesized and post-translationally modified peptides were generated using heterologous mutasynthesis. A parallelized screening assay is adapted in nanoliter-scale beads to test the darobactin derivatives against our sensor strain. Loss of fluorescence sorting prioritized 563 events out of the analyzed [~]500k beads. Re-testing confirmed 48 hit events, of which 40 proved to produce distinct darobactin-type molecules. Most promising structures were isolated and the growth inhibitory effects against Gram-negative pathogens validated. One of our current frontrunner compounds (i.e., darobactin B) was reinforced by the randomized screen. While microbiological investigations of the new derivatives is ongoing, darobactin B was profiled in later tier assays and compared to another promising, rationally-designed analog (i.e., darobactin B9, "D22"). Early ADMET profiling and efficacy tests in a mouse pneumonia model were performed. Darobactin B reduced bacterial load of Pseudomonas aeruginosa and Klebsiella pneumoniae by intraperitoneal, as well as intratracheal administration. Our study showcases the potential of mutasynthetic libraries for high-throughput screening and identification of functional peptides for drug lead discovery.

microbiology↗

INSTINCT: Multi-sample integration of spatial chromatin accessibility sequencing data via stochastic domain translation

Recent advances in spatial epigenomic techniques have given rise to spatial assay for transposase-accessible chromatin using sequencing (spATAC-seq) data, enabling the characterization of epigenomic heterogeneity and spatial information simultaneously. Integrative analysis of multiple spATAC-seq samples, for which no method has been developed, allows for effective identification and elimination of unwanted non-biological factors within the data, enabling comprehensive exploration of tissue structures and providing a holistic epigenomic landscape, thereby facilitating the discovery of biological implications and the study of regulatory processes. In this article, we present INSTINCT, a method for multi-sample INtegration of Spatial chromaTIN accessibility sequencing data via stochastiC domain Translation. INSTINCT can efficiently handle the high dimensionality of spATAC-seq data and eliminate the complex noise and batch effects of samples from different conditions through a stochastic domain translation procedure. We demonstrate the superiority and robustness of INSTINCT in integrating spATAC-seq data across multiple simulated scenarios and real datasets. Additionally, we highlight the advantages of INSTINCT in spatial domain identification, visualization, spot-type annotation, and various downstream analyses, including motif enrichment analysis, expression enrichment analysis, and partitioned heritability analysis.

bioinformatics↗

PEX14 acts as the interface linking optineurin to cell type-selective pexophagy

Pexophagy, the selective degradation of peroxisomes, is essential for removing excess or dysfunctional peroxisomes, and its dysregulation is linked to various diseases. Previous research has shown that optineurin (OPTN), an autophagy receptor involved in mitophagy, aggrephagy, and xenophagy, can induce pexophagy in HEK-293 cells. However, the underlying mechanism remains unclear. In this study, we used proximity labeling to identify PEX14, a peroxisomal membrane protein, as a neighboring partner of OPTN. Biochemical analyses revealed that PEX14 and OPTN interact through their respective coiled-coil and ubiquitin-binding domains. Further analyses demonstrated that the C-terminal half of overexpressed OPTN triggers pexophagy, likely by forming oligomers with endogenous OPTN. The co-localization of PEX14-OPTN complexes with LC3, combined with the suppression of OPTN-mediated peroxisome degradation by bafilomycin A1, supports a model in which PEX14 acts as a docking site for OPTN on the peroxisomal membrane, enabling the recruitment of the autophagic machinery for OPTN-mediated pexophagy. SummaryThis study uncovers and defines the peroxisomal membrane protein PEX14 as a key player in optineurin-driven pexophagy, advancing our mechanistic understanding of this cellular process. These findings open new avenues for developing therapeutic strategies targeting diseases associated with defective pexophagy.

cell biology↗

Spatiotemporally resolved transcriptome atlas of developing mouse placenta reveals mechanisms of embryonic lethality.

Proper placentation is fundamental to the growth and viability of the maturing embryo. However, a thorough grasp of the spatial organization of cell types, their interactions, and gene expression patterns along the maternal-fetal function during placental development remains incomplete. Here, we utilized Stereo-seq to construct the spatiotemporal transcriptomic atlas of the mouse placenta (STAMP) spanning embryonic (E) days 9.5 to 18.5 at single cell resolution (https://db.cngb.org/stomics/stamp/). This resource delineates spatially resolved cellular dynamics and gene expression patterns across placental and maternal compartments. We identified distinct glycogen trophoblast cell (GC) subclusters, mapped their developmental trajectories, and uncovered transcriptional transitions accompanying their migration from the junctional zone to the maternal decidua from E12.5 onward. In a defective placentation model with perinatal lethality, GCs abnormally persisted at E18.5 with excessive glycogen and reduced degradation metabolites in placenta and fetal liver, indicating impaired glycogen breakdown. Maternal glucose supplementation restored glucose levels and rescued fetal survival, underscoring GC-mediated metabolic support as critical for viability. Together, this study provides a comprehensive spatiotemporal placental atlas and demonstrates that GC-mediated glycogen metabolism is essential for sustaining fetal viability.

developmental biology↗

Soybean PHR1-regulated low phosphorus-responsive GmRALF22 increases uptake of phosphate via stimulating GmPTs expression

Phosphorus (P) is one of essential macronutrients for plant growth and development. Rapid Alkalization Factors (RALFs) play crucial roles in plant responses to nutrient stresses, however, the functions of Glycine max RALFs (GmRALFs) under low P (LP) stress remain elusive. In this study, we first identified 27 GmRALFs in soybean, then we revealed that GmRALF10, GmRALF11, and GmRALF22 are induced in both roots and leaves, while only GmRALF5, GmRALF6, and GmRALF25 are up-regulated in leaves in LP conditions. Furthermore, GmRALF22 was found to be the target gene of transcription factor GmPHR1, which binds the P1BS cis-element in the promoter of GmRALF22 via electrophoretic mobility shift assay (EMSA) and DUAL-LUC experiment. Colonization of Bacillus subtilis that deliver GmRALF22 increases the expression of high affinity phosphate (Pi) transporter gene GmPT2, GmPT11, GmPT13 and GmPT14, thus increases the total amount of dry matter and soluble Pi in soybean. RNA-sequencing uncovered that GmRALF22 alleviates LP stress by regulating the expression of JA-, SA- and immune-related genes. Finally, we verified that GmRALF22 is dependent on FERONIA to promote Arabidopsis primary root growth under LP conditions. In summary, GmPHR1-GmRALF22 module positively regulates soybeans tolerance to LP. HighlightsO_LISoybean genome has 27 GmRALFs. GmRALF5, GmRALF6, GmRALF10, GmRALF11, GmRALF22 and GmRALF25 are induced in low phosphorus (LP). C_LIO_LIGmPHR1 directly regulate the transcription of GmRALF22 via binding the promoter P1BS cis-element. C_LIO_LISecretion of GmRALF22 protein by Bacillus subtilis promoted soybean growth under LP conditions by improving soybean P nutrition through increased expression of high affinity phosphate (Pi) transporter gene. C_LIO_LIGmRALF22 regulates soybean P nutrition by JA-, SA- and immune-related genes expression at transcriptome level. That application of GmRALF22 promoted primary root growth in Arabidopsis in LP is dependent on FER receptor. C_LI

molecular biology↗

Dynamic Single Cell Transcriptomics Defines Kidney FGF23/KL Bioactivity and Novel Segment-Specific Inflammatory Targets

FGF23 via its coreceptor Klotho (KL) provides critical control of phosphate metabolism, which is altered in rare and very common syndromes, however the spatial-temporal mechanisms dictating renal FGF23 functions remain poorly understood. Thus, developing approaches to modify specific FGF23-dictated pathways has proven problematic. Herein, wild type mice were injected with rFGF23 for 1, 4 and 12h and renal FGF23 bioactivity was determined at single cell resolution. Computational analysis identified distinct epithelial, endothelial, stromal, and immune cell clusters, with differential expressional analysis uniquely tracking FGF23 bioactivity at each time point. FGF23 actions were sex independent but critically relied upon constitutive KL expression mapped within proximal tubule (S1-S3) and distal tubule (DCT/CNT) cell sub-populations. Temporal KL-dependent FGF23 responses drove unique and transient cellular identities, including genes in key MAPK- and vitamin D-metabolic pathways via early- (AP-1-related) and late-phase (EIF2 signaling) transcriptional regulons. Combining ATACseq/RNAseq data from a cell line stably expressing KL with the in vivo scRNAseq pinpointed genomic accessibility changes in MAPK-dependent genes, including the identification of FGF23-dependent EGR1 distal enhancers. Finally, we isolated unexpected crosstalk between FGF23-mediated MAPK signaling and pro-inflammatory TNF receptor activation via NF-{kappa}B, which blocked FGF23 bioactivity in vitro and in vivo. Collectively, our findings have uncovered novel pathways at the single cell level that likely influence FGF23-dependent disease mechanisms. Translational statementInflammation and elevated FGF23 in chronic kidney disease (CKD) are both associated with poor patient outcomes and mortality. However, the links between these manifestations and the effects of inflammation on FGF23-mediated mineral metabolism within specific nephron segments remain unclear. Herein, we isolated an inflammatory pathway driven by TNF/NF-{kappa}B associated with regulating FGF23 bioactivity. The findings from this study could be important in designing future therapeutic approaches for chronic mineral diseases, including potential combination therapies or early intervention strategies. We also suggest that further studies could explore these pathways at the single cell level in CKD models, as well as test translation of our findings to interactions of chronic inflammation and elevated FGF23 in human CKD kidney datasets.

physiology↗

The genomic and epigenomic dynamics of hemizygous genes across crops with contrasting mating systems

Hemizygous genes, which present on only one of the two homologous chromosomes of diploid organisms, have been mainly studied in the context of sex chromosomes and sex-linked genes. However, structural variants (SVs), such as a deletion/insertion of one allele, can lead to hemizygous genes, a phenomenon largely unexplored in plants. Here, we investigated the genomic and epigenomic landscapes of hemizygous genes across 22 genomes with varying propagation histories: eleven clonal lineages, seven outcrossed samples and four inbred and putatively homozygous genomes. We identified SVs leading to genic hemizygosity. As expected, very few genes (0.01%-1.2%) were hemizygous in the homozygous genomes, representing negative controls. Hemizygosity was appreciable among outcrossed lineages, averaging 8.7% of genes, but consistently elevated for the clonal samples at 13.8% genes, likely reflecting heterozygous SVs accumulation during clonal propagation. Compared to diploid genes, hemizygous genes were more often situated in centromeric than telomeric regions and underlying weaker purifying selection. They also had reduced levels of expression, averaging [~]20% of the expression levels of diploid genes, violating the evolutionary model of dosage compensation. We also detected higher DNA methylation levels, in hemizygous genes and transposable elements, which may contribute to the reduced expression of hemizygous genes. Finally, expression profiles showed that hemizygous genes were more specifically expressed in contexts related to fruit development, organ differentiation and stress responses. Overall, hemizygous genes accumulate in clonally propagated lineages and display distinct genetic, and epigenetic features compared to diploid genes, shedding new insights on genetic studies and breeding programs of clonal crops.

plant biology↗

Machine learning assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues

SignificanceLabel-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tumor-microenvironment where fibrillar collagens architectural changes are associated with cancer progression. To address this need, we present a multimodal computational imaging method where mid-infrared spectral imaging (MIRSI) is employed with second harmonic generation (SHG) microscopy to identify fibrillar collagen in biological tissues. AimTo demonstrate a multimodal approach where a morphology-specific contrast mechanism guides a mid-infrared spectral imaging method to detect fibrillar collagen based on its chemical signatures. ApproachWe trained a supervised machine learning (ML) model using SHG images as ground truth collagen labels to classify fibrillar collagen in biological tissues based on their mid-infrared hyperspectral images. Five human pancreatic tissue samples (sizes are in the order of millimeters) were imaged by both MIRSI and SHG microscopes. In total, 2.8 million MIRSI spectra were used to train a random forest (RF) model. The remaining 68 million spectra were used to validate the collagen images generated by the RF-MIRSI model in terms of collagen segmentation, orientation, and alignment. ResultsCompared to the SHG ground truth, the generated MIRSI collagen images achieved a high average boundary F-score (0.8 at 4 pixels threshold) in the collagen distribution, high correlation (Pearsons R 0.82) in the collagen orientation, and similarly high correlation (Pearsons R 0.66) in the collagen alignment. ConclusionsWe showed the potential of ML-aided label-free mid-infrared hyperspectral imaging for collagen fiber and tumor microenvironment analysis in tumor pathology samples.

bioengineering↗

Deep mutational scanning of H5 hemagglutinin to inform influenza virus surveillance

H5 influenza is a potential pandemic threat. Previous studies have identified molecular phenotypes of the viral hemagglutinin (HA) protein that contribute to pandemic risk, including cell entry, receptor preference, HA stability, and reduced neutralization by polyclonal sera. Here we use pseudovirus deep mutational scanning to measure how all mutations to a clade 2.3.4.4b H5 HA affect each phenotype. We identify mutations that allow HA to better bind 2-6-linked sialic acids, and show that some viruses already carry mutations that stabilize HA. We also identify recent viral strains with reduced neutralization to sera elicited by candidate vaccine virus. Overall, the systematic nature of deep mutational scanning combined with the safety of pseudoviruses enables comprehensive characterization of mutations to inform surveillance of H5 influenza.

microbiology↗

Gene drive-based population suppression in the malaria vector Anopheles stephensi

Gene drives are alleles that can bias the inheritance of specific traits in target populations for the purpose of modification or suppression. Here, we constructed a homing suppression drive in the major urban malaria vector Anopheles stephensi targeting the female-specific exon of doublesex, incorporating two gRNAs and a nanos-Cas9 promoter to reduce functional resistance and improve female heterozygote fitness. Our result showed that the drive was recessive sterile in both females and males, with various intersex phenotypes in drive homozygotes. Both male and female drive heterozygotes showed only moderate drive conversion, indicating that the nos promoter has lower activity in A. stephensi than in Anopheles gambiae. By amplicon sequencing, we detected a very low level of resistance allele formation. Combination of the homing suppression and a vasa-Cas9 line demonstrated a boost in the drive conversion rate of the homing drive to 100%, suggesting the use of similar systems for population suppression in a continuous release strategy with a lower release rate than SIT or fRIDL techniques. This study contributes valuable insights to the development of more efficient and environmentally friendly pest control tools aimed at disrupting disease transmission.

genetics↗

Discovery and binding site identification of a single-stranded DNA-binding protein that interacts with double-stranded DNA

Scientists have conducted in-depth studies on single-stranded DNA (ssDNA) binding and protein interaction network of single-stranded DNA binding proteins (SSBs). SSBs are widely present in cells from lower prokaryotes to higher mammals and are important proteins for ssDNA protection. In-depth studies in recent years have revealed a wide range of interactions between SSBs and other proteins. Studies have shown that in addition to playing the role of ssDNA protector, SSBs are also important members of biochemical pathways such as DNA replication and recombination. In this study, a single-stranded DNA binding protein SSF encoded by E. coli F plasmid with highly conserved N-terminal region was demonstrated to have ssDNA binding ability similar to E. coli SSB through gel migration experiments. At the same time, the dsDNA binding ability of SSF was also demonstrated, and the dissociation constant of this interaction (in the range of microliters) was determined by Micro-scale Thermophoresis (MST). Through the above experiments, a previously unreported SSB with dsDNA binding ability was revealed, and the region interacting with dsDNA was determined to be the C-terminal unstructured region. This study lays a foundation for further understanding of the mechanism of bacterial conjugation conducted by F plasmid, as well as the potential dsDNA binding ability and biological significance of other SSBs.

biochemistry↗

Large scale loss-of-function mutations during chicken evolution and domestication

Evolution and domestication are often driven by genetic innovations, yet the role of gene loss remains debated. Here, we present comparative genomic analyses of four indigenous chicken breeds from Yunnan Province, China and a reference red jungle fowl genome (GRCg6a). We identify extensive gene presence-absence variation and large numbers of pseudogenes, revealing highly dynamic gene repertoires among closely related chickens. By reconstructing ancestral gene content, we estimate that the common ancestor harbored at least 21,972 genes, of which 7,993 are dispensable. Each lineage has independently lost thousands of genes through both complete gene loss and pseudogenization. These loss-of-function events are non-random: pseudogenization mutations are biased toward gene termini, frequently fixed in populations, and enriched in specific biological pathways. Notably, patterns of gene loss recapitulate phylogenetic relationships, suggesting that loss-of-function mutations are shaped by selection rather than neutral drift. Analysis of four other chicken genomes assembled using PacBio HiFi reads draws the same conclusion. Thus, our results support a model in which large-scale loss-of-function mutations are a major driver of chicken evolution and domestication, consistent with the "less-is-more" hypothesis of adaptive evolution.

bioinformatics↗

BioInformatics Agent (BIA): Unleashing the Power of Large Language Models to Reshape Bioinformatics Workflow

Bioinformatics plays a crucial role in understanding biological phenomena, yet the exponential growth of biological data and rapid technological advancements have heightened the barriers to in-depth exploration of this domain. Thereby, we propose Bio-Informatics Agent (BIA), an intelligent agent leveraging Large Language Models (LLMs) technology, to facilitate autonomous bioinformatic analysis through natural language. The primary functionalities of BIA encompass extraction and processing of raw data and metadata, querying both locally deployed and public databases for information. It further undertakes the formulation of workflow designs, generates executable code, and delivers comprehensive reports. Focused on the single-cell RNA sequencing (scRNA-seq) data, this paper demonstrates BIAs remarkable proficiency in information processing and analysis, as well as executing sophisticated tasks and interactions. Additionally, we analyzed failed executions from the agent and demonstrate prospective enhancement strategies including selfrefinement and domain adaptation. The future outlook includes expanding BIAs practical implementations across multi-omics data, to alleviating the workload burden for the bioinformatics community and empowering more profound investigations into the mysteries of life sciences. BIA is available at: https://github.com/biagent-dev/biagent.

bioinformatics↗

LncCE: Landscape of Cellular-Elevated LncRNAs in Single Cells Across Normal and Cancer Tissues

Long non-coding RNAs (lncRNAs) have emerged as significant players for maintaining the morphology and function of tissues or cells. The precise regulatory effectiveness of lncRNA is closely associated with the spatial expression patterns across tissues and cells. Here, we proposed the Cellular-Elevated LncRNA (LncCE) database to systematically explore cellular-elevated (CE) lncRNAs across normal and cancer tissues in single cells. LncCE encompasses 87,946 CE lncRNAs of 149 cell types by analyzing 181 single-cell RNA sequencing (scRNA-seq) datasets, involved in 20 fetal normal tissues, 59 adult normal tissues, as well as 32 adult and 5 pediatric cancer tissues.Two main search options were provided via a given lncRNA name or a cell type. The output results emphasize both qualitative and quantitative expression features of lncRNAs across different cell types, co-expression with protein-coding genes as well as their involved in biological functions. For cancers, LncCE particularly provided quantitative figures for exhibiting their expression changes compared to control samples and clinical associations with patient overall survivals. Together, LncCE offers an extensive, quantitative and user-friendly interface to investigate cellular-elevated expression atlas for lncRNAs across normal and cancers tissues at single-cell level. The LncCE database is available at http://bio-bigdata.hrbmu.edu.cn/LncCE.

cancer biology↗

Harnessing Data-Intelligence-Intensive Multi-Agent System for Life Science Research

Advancements in high-throughput sequencing technologies and artificial intelligence offer unprecedented opportunities for groundbreaking discoveries in bioinformatics research. However, the challenges of exponential growth of omics data and the rapid development of artificial intelligence technologies require automated big biological data analysis capability and interdisciplinary knowledge-driven scientific insight. Here we propose a data-intelligence-intensive bioinformatics copilot (Bio-Copilot) system that synergizes AI capabilities with human expertise to facilitate hypothesis-free exploratory research and inspire novel scientific insights in large-scale omics studies. Bio-Copilot forms high-quality intensive intelligence through close collaboration between multiple agents, driven by large language models (LLMs), and human experts. To augment the capabilities of Bio-Copilot, this study devises an agent group management strategy, an effective human-agent interaction mechanism, a shared interdisciplinary knowledge database, and continuous learning strategies for the agents. We comprehensively compare Bio-Copilot against GPT-4o and several leading AI agents across diverse bioinformatics tasks, using a broad range of evaluation metrics. Bio-Copilot achieves the overall state-of-the-art performance across all tasks, while showcases exceptional task completeness. Furthermore, in the application of constructing a large-scale human lung cell atlas, Bio-Copilot not only reproduces the intricate data integration process detailed in a seminal study but also introduces a hierarchical annotation strategy to capture the continuous nature of cellular states and uncovers the characteristics of rare cell types, highlighting its potential to unravel hidden complexities in biological systems. Beyond the technical achievements, this study also underscores the profound implications of integrating AI capabilities with expert knowledge in accelerating impactful biological discoveries and exploring uncharted territories in life sciences.

bioinformatics↗

Genome sequencing of 'Fuji' apple clonal varieties reveals evolutionary history and genetic mechanism of the spur-type morphology

Somatic variations arising during asexual reproduction can lead to the emergence of bud sports exhibiting advantageous traits, forming the basis for bud sport breeding in perennial plants. Here, we report a near-complete, fully phased genome assembly of Fuji apple, enabling comprehensive identification of somatic variants across 74 clonally propagated Fuji varieties. Phylogenetic analysis of Fuji sport varieties indicates that the emergence of spur-type and early maturation traits results from multiple independent formation events. A number of putative functional somatic variants are identified, including one spur-type specific deletion located in the promoter of the TCP transcription factor gene MdTCP11. DNA methylation level of the deletion-associated miniature inverted-repeat transposable element is lower in the spur-type varieties compared to the standard-type varieties, while the expression of MdTCP11 is significantly higher. Overexpression of MdTCP11 in apple decreases the plant height, highlighting its important role in the development of spur-type apple varieties. This study sheds light on the 80-year cloning history of Fuji and provides valuable candidate causative mutations for apple breeding.

plant biology↗

Physiological role and mechanisms of action for a long noncoding haplotype region

Most common sequence variants associated with human traits are in noncoding regions of the genome, form haplotypes with other noncoding variants, and exhibit small effect sizes in the general population. Determining the physiological roles and mechanisms of action for these noncoding variants, particularly large haplotypes containing multiple variants, is both critical and challenging. To address this challenge, we developed an approach that integrates physiological studies in genetically engineered and phenotypically permissive animal models, precise editing of large haplotypes in human induced pluripotent stem cells (hiPSCs), and targeted chromatin conformation analysis. We applied this approach to examine the blood pressure associated rs1173771 locus, which includes a haplotype containing 11 single nucleotide polymorphisms (SNPs) spanning 17.4 kbp. Deleting the orthologous noncoding region in the genome of the Dahl salt-sensitive rat attenuated the salt-induced increase in systolic blood pressure by nearly 10 mmHg. This attenuation of hypertension appeared to be mediated by upregulation of the adjacent gene Npr3 (natriuretic peptide receptor 3) in arteries, enhancing vasodilation. The blood pressure-elevating and -lowering haplotypes were precisely reconstituted in hiPSCs using an efficient, two-step genome editing technique. The blood pressure-elevating haplotype decreased NPR3 expression in endothelial cells and vascular smooth muscle cells derived from the edited, isogenic hiPSCs. The influence of the haplotype was partially recapitulated by the sentinel SNP rs1173771. Additionally, the blood pressure-elevating haplotype showed significantly greater chromatin interactions with the NPR3 promoter region. This study illustrates the feasibility of ascertaining the physiological roles and mechanisms of action for large noncoding haplotypes. Our efficient, integrated, and targeted approach can be applied to investigate other noncoding variants.

genetics↗