Biology subjects

Zheng, M.

Publications and source records attributed to Zheng, M..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

MCIBox: A Toolkit for Single-molecule Multi-way Chromatin Interaction Visualization and Micro-Domains Identification

The emerging ligation-free three-dimensional (3D) genome mapping technologies can identify multiplex chromatin interactions with single-molecule precision. These technologies offer new insight into high-dimensional chromatin organization and gene regulation, but also introduce new challenges in data visualization and analysis. To overcome these challenges, we developed MCIBox, a toolkit for Multi-way Chromatin Interaction (MCI) analysis, including a visualization tool and a platform for identifying micro-domains with clustered single-molecule chromatin complexes. MCIBox is based on various clustering algorithms integrated with dimensionality reduction methods that can display multiplex chromatin interactions at single-molecule level, allowing users to explore chromatin extrusion patterns and super-enhancers regulation modes in transcription, and to identify single-molecule chromatin complexes that are clustered into micro-domains. Furthermore, MCIBox incorporates a two-dimensional kernel density estimation algorithm to identify micro-domains boundaries automatically. These micro-domains were stratified with distinctive signatures of transcription activity and contained different cell cycle associated genes. MCIBox could potentially distinguish the specificity of single-molecule chromatin interaction patterns in various phases of a cell cycle or cell types.

genomics↗

bioRxiv2022

PanGu Drug Model: Learn a Molecule Like a Human

Recent achievements in large-scale pre-trained models like GPT-3 and PanGu- showed amazing performances in many downstream tasks, which makes AI friendlier toward industrial users. Deep learning has been recognized as the most promising technology for pharmaceuticals, a powerful molecule pre-trained model could save researchers tons of time. In chemistry classes, the students learn two molecule representations, the molecular formula and the structure formula, and learn to translate them from one way to the other. Inspired by this, we developed a novel deep learning architecture using a graph-to-sequence asymmetric conditional variational autoencoders, called PanGu Drug Model, which can appropriately characterize the molecule from both representations and improve the performance of downstream drug discovery tasks. After pretrained with 1.7 billion small molecules, our proposed model achieved the state-of-the-art results in 20 drug discovery tasks, such as molecule property prediction (predict ADMET properties, compound-target interactions, drug-drug interactions and chemical reaction productivity), molecule generation and molecule optimization. A new drug screening library of 100 million drug-like small molecules with 99.68% novelty was generated by PanGu molecule generator, which could efficiently produce novel compounds with similar physiochemical properties to given distribution, this library could be used to supplement existing compound databases. In addition, PanGu molecule optimizer could optimize the chemical structures of starting molecule with improved molecular property of interest. An automatic multi-objective optimization web application implemented by PanGu Drug Model is available at http://www.pangu-drug.com/.

biochemistry↗

bioRxiv2022

Drug design and repurposing with a sequence-to-drug paradigm

Drug development based on target proteins has been a successful approach in recent decades. A conventional structure-based drug design pipeline is a complex, human-engineered pipeline with multiple independently optimized steps. Advances in end-to-end differentiable learning suggest the potential benefits of similarly reformulating drug design. Here, we proposed a new sequence-to-drug paradigm that discovers drug-like small-molecule modulators directly from protein sequences and validated this concept for the first time in three stages. First, we designed TransformerCPI2.0 as a core tool for the sequence-to-drug paradigm, which exhibited competitive performance with conventional structure-based drug design approaches. Second, we validated the binding knowledge that TransformerCPI2.0 has learned. Third, we applied a sequence-to-drug paradigm to discover new hits for E3 ubiquitin-protein ligases: speckle-type POZ protein (SPOP), ring finger protein 130 (RNF130) which does not have a 3D structure, and repurposed proton pump inhibitors (PPIs) for ADP-ribosylation factor 1 (ARF1). This first proof of concept shows that the sequence-to-drug paradigm is a promising direction for drug development.

molecular biology↗

bioRxiv2022

Global Spatial Transcriptome of Macaque Brain at Single-Cell Resolution

Global profile of gene expression at single-cell resolution remains to be determined for primates. Using a recently developed technology ("Stereo-seq"), we have obtained a comprehensive single-cell spatial transcriptome map at the whole-brain level for cynomolgus monkeys, with [~]600 genes per cell for 10 m-thick coronal sections (up to 15 cm2 in size). Large-scale single-nucleus RNA-seq analysis for [~]1 million cells helped to identify cell types corresponding to Stereo-seq gene expression profiles, providing a 3-D cell type atlas of the monkey brain. Quantitative analysis of Stereo-seq data revealed molecular fingerprints that mark distinct neocortical layers and subregions, as well as domains within subcortical structures including hippocampus, thalamus, striatum, cerebellum, hypothalamus and claustrum. Striking whole-brain topography and coordinated patterns were found in the expression of genes encoding receptors and transporters for neurotransmitters and neuromodulators. These results pave the way for cellular and molecular understanding of organizing principles of the primate brain.

cell biology↗

bioRxiv2022

Melanin Nanoparticles as an Alternative to Natural Melanin in Retinal Pigment Epithelium Cells and Their Therapeutic Effects against Age-Related Macular Degeneration

Melanin is a natural pigment that is widely distributed in many parts of the human body, such as the skin and retinal pigment epithelium (RPE) in eyes. In contrast to skin melanin, which is being constantly synthesized by the epidermal melanocytes, melanin in the RPE does not regenerate. Melanin is known to function as a potential radical scavenger and photoprotective agent. However, the protective effects of melanin against oxidative stress decline with increasing age. This phenomenon has been significantly correlated with the pathogenesis of age-related macular degeneration (AMD). To increase the potential antioxidant and photoprotective characteristics of the melanin, we designed a new strategy by replenishment of melanin using PEGylated-synthetic melanin nanoparticles (MNPs) in the RPE for the treatment of AMD. We performed experiments using AMD-like cellular and mouse models and demonstrated that MNPs are safe, biocompatible, and selectively target reactive oxygen species (ROS) with powerful antioxidant properties. MNPs can traffic and accumulate in the RPE and are exclusively located in cytosol, but not the nucleus and mitochondria of the cells, for up to three months after a single-dose intravitreal (IVT) injection. Our findings demonstrate, for the first time, that MNPs are able to substitute for natural melanin in the RPE of eyes and suggest the potential efficacy of MNPs as a natural radical scavenger against oxidative stress in ROS-related diseases, such as AMD. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/481315v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@18929e6org.highwire.dtl.DTLVardef@1dc929org.highwire.dtl.DTLVardef@181c8c2org.highwire.dtl.DTLVardef@1a36eab_HPS_FORMAT_FIGEXP M_FIG C_FIG Intracellular trafficking showing that PEGylated-synthetic melanin nanoparticles (MNPs) reach their target and are stable in the retinal pigment epithelial cells for up to 3 months via a single-dose intravitreal (IVT) injection.

molecular biology↗

bioRxiv2022

Pore-C Simultaneously Captures Genome-wide Multi-way Chromatin Interaction and Associated DNA Methylation Status in Arabidopsis

In the past decade, genome-wide characterization of the three-dimensional chromatin structure in plants using high-throughput methods has greatly advanced our knowledge in plant genome architecture (Liu and Weigel, 2015; Ouyang et al., 2020). However, due to the limitation of Illumina short-read sequencing, the genome-wide contact map obtained by Hi-C/ChIA-PET is pairwise, and the multi-way interaction can only be inferred from the two-way data. To directly capture multi-way interaction in Arabidopsis, we applied a long-read-based method called Pore-C that directly sequences the DNA fragments joined by proximity-based ligation (Ulahannan et al., 2019).

molecular biology↗

bioRxiv2021

Temporal response characterization across individual multiomics profiles of prediabetic and diabetic subjects

Longitudinal deep multi-omics profiling, which combines biomolecular, physiological, environmental and clinical measures data, shows great promise for precision health. However, integrating and understanding the complexity of such data remains a big challenge. Here we propose a bottom-up framework starting from assessing single individuals multi-omics time series, and using individual responses to assess multi-individual grouping based directly on similarity of their longitudinal deep multi-omics profiles. We applied our method to individual profiles from a study profiling longitudinal responses in type 2 diabetes mellitus. After generating periodograms for individual subject omics signals, we constructed within-person omics networks and analyzed personal-level immune changes. The results showed that our method identified both individual-level responses to immune perturbation, and the clusters of individuals that have similar behaviors in immune response and which was associated to measures of their diabetic status.

genomics↗

bioRxiv2021

Differential Network Analysis of Longitudinal Gene Expression in Response to Perturbations.

Understanding changes in gene expression under the effects of a perturbation is a key goal of systems biology. A powerful approach to address this goal uses gene networks and describes the perturbations effects as a rewiring of each genes connections. This approach is known as differential network (DN) analysis. Here, we used DNs to analyze RNA-sequencing time series datasets, focusing on expression changes: (i) In the saliva of a human subject after vaccination with a pneumococcal vaccine (PPSV23), and (ii) in B cells treated ex vivo with a monoclonal antibody drug (Rituximab). Using network community detection, we revealed the collective behavior of clusters of genes, and detected communities of genes based on their longitudinal behavior, and corresponding pathway activations. We identified biological pathways consistent with the mechanism of action of the vaccine and with Rituximabs targets. The approach may be useful in drug development by providing an effective analysis of expressing changes in response to a drug.

bioinformatics↗

bioRxiv2021

Regional Cell Atlas of Human Intestine Shapes Distinct Immune Surveillance

Regional intestinal immune surveillance remains obscure. In this study, we integrated single-cell RNA sequencing and spatial transcriptomics to create a regional atlas of fetal and adult intestines, consisting of 59 cell subsets, of which eight new subsets and ILCs transition states were identified. Results revealed that microenvironment determines in-situ cell differentiation and shapes the regional molecular characteristics, allowing different intestinal segments with diverse functions. We characterized the regional expression of mucins, immunoglobulins, and antimicrobial peptides (AMPs) and their shift during development and in inflammatory bowel disease. Notably, -defensins expressed most abundantly in small intestinal LGR5+ stem cells, rather than in Paneth cells, and down-regulated as cell maturing. Common upstream transcription factors controlled the AMPs expression, illuminating the concurrent change of AMPs during epithelial differentiation, and the spatial co-expression patterns. We demonstrated the correspondence of cell focus of risk genes to diseases location susceptibility and identified distinct cell-cell crosstalk and spatial heterogeneity of immune cell homing in different gut segments. Overall, a cross-spatiotemporal approach to transcriptomes at single-cell resolution revealed that the regional milieu of the human intestine determined cellular and molecular cues of immune surveillance, dictating gut homeostasis and disease.

cell biology↗

bioRxiv2021

Comparative genomic and pan-genomic characteristion of Staphylococcus epidermidis from different sources unveils the molecular basis and potential biomarkers of pathogenic strains

Coagulase-negative Staphylococcus (CoNS) is the most common pathogen causing traumatic endophthalmitis, Staphylococcus epidermidis is the most common species which colonizes human skin, eye surfaces and nasal cavity and is the main cause of nosocomial infection, specially foreign body-related bloodstream infections (FBR-BSIs). Although some studies have reported the genome characteristics of S. epidermidis, a comprehensive understanding of its pathogenicity and the genome of ocular trauma-sourced strains is still lacking. In this study, we sequenced, analyzed and reported the whole genomes of 11 ocular trauma-sourced samples of S. epidermidis that caused traumatic endophthalmitis. By integrating publicly available genomes, we obtained a total of 187 S. epidermidis samples from healthy and diseased eyes, skin, respiratory tract and blood. Combined with pangenome, phylogenetic and comparative genomic analyses, our study supported that S. epidermidis, regardless of niche source, exhibits two founder lineages with different pathogenicities. Moreover, we identified potential biomarkers associated with the virulence of S. epidermidis, namely, essD, uhpt, sdrF, sdrG, fbe and icaABCDR. The essD and uhpt genes have high homology with esaD and hpt in Staphylococcus aureus, showing that the genomes of S. epidermidis and S. aureus may have communicated during evolution, while the sdrF, sdrG, fbe, and icaABCDR genes are related to biofilm formation. Compared to S. epidermidis from blood sources, ocular-sourced strains causing intraocular infection had no direct relationship with biofilm formation. In conclusion, this study not only provided additional data resources for studies on S. epidermidisis, but also improved understanding of the evolution and pathogenicity of different source strains. ImportantsIn this study, we comprehensively analysied and reported the whole genome sequence (WGS) of the strains that caused traumatic endophthalmitis. Through comparative genomic analyses among 187 S. epidermidis samples from healthy and diseased eyes, skin, respiratory tract and blood, we identified 10 potential biomarkers of pathogenic strains. Finally, we revealed S. epidermidis-induced traumatic endophthalmitis may be independent of biofilm formation. Overall, our data may facilitate comparative research of S. epidermidis and provide clinical value for identifying pathogenic or contaminating strains.

microbiology↗

bioRxiv2021

Regeneration of the larval sea star nervous system by wounding induced respecification to the sox2 lineage

The ability to restore lost body parts following traumatic injury is a fascinating area of biology that challenges current understanding of the ontogeny of differentiation. The origin of new cells needed to regenerate lost tissue, and whether they are pluripotent stem cells, tissue-specific stem cells or have de- or trans- differentiated, remains one of the most important open questions in regeneration. Additionally, it is not clearly known whether developmental gene regulatory networks (GRNs) are reused to direct specification in these cells or whether regeneration specific networks are deployed. Echinoderms, including sea stars, have extensive ability for regeneration and have therefore been the subject of many thorough studies on the ultrastructural and molecular properties of cells needed for regeneration. However, the technologies for obtaining transgenic echinoderms are limited and tracking cells involved in regeneration, and thus identifying the cellular sources and potencies has proven challenging. In this study we develop new transgenic tools for cell tracking in the regenerating bipinnaria larva of the sea star Patira minaita. We show that the larval serotonergic nervous system can regenerate following decapitation. Using a BAC-transgenesis approach with photoconvertible fluorescent proteins, we show that expression of the pan ectodermal marker, sox2, is induced in previously sox2 minus cells at the wound site, even when cell division is inhibited. sox2+ cells give rise to new sox4+ neural precursors that then proceed along an embryonic neurogenesis pathway to reform the anterior nervous systems. sox2+ cells contribute to only neural and ectoderm lineages, indicating that these progenitors maintain their normal, embryonic lineage restriction. This indicates that sea star larval regeneration uses a combination of existing lineage restricted stem cells, as well as respecification of cells into neural lineages, and at least partial reuse of developmental GRNs to regenerate their nervous system.

developmental biology↗

bioRxiv2021

Machine-Perception Nanosensor Platform to Detect Cancer Biomarkers

Conventional molecular recognition elements, such as antibodies, present issues for the development of biomolecular assays for use in point-of-care devices, implantable/wearables, and under-resourced settings. Additionally, antibody development and use, especially for highly multiplexed applications, can be slow and costly. We developed a perception-based platform based on an optical nanosensor array that leverages machine learning algorithms to detect multiple protein biomarkers in biofluids. We demonstrated this platform in gynecologic cancers, which are often diagnosed at advanced stages, leading to low survival rates. We investigated the platform for detection in uterine lavage samples, which are enriched with cancer biomarkers compared to blood. We found that the method enables the simultaneous detection of multiple biomarkers in patient samples, with F1-scores of ~0.95 in uterine lavage samples from cancer patients. This work demonstrates the potential of perception-based systems for the development of multiplexed sensors of disease biomarkers without the need for specific molecular recognition elements.

bioengineering↗

bioRxiv2021

Quantitative multidimensional phenotypes improve genetic analysis of laterality traits

Handedness is the most commonly investigated lateralised phenotype and is usually measured as a binary left/right category. Its links with psychiatric and neurodevelopmental disorders prompted studies aimed at understanding the underlying genetics, while other measures and side preferences have been less studied. We investigated the heritability of hand, as well as foot, and eye preference by assessing parental effects (n [≤] 5 028 family trios) and SNP-based heritability (SNP-h2, n [≤] 5 931 children) in the Avon Longitudinal Study of Parents and Children (ALSPAC). An independent twin cohort from Hong Kong (n = 358) was used to replicate results from structural equation modelling (SEM). Parental left-side preference increased the chance of an individual to be left-sided for the same trait, with stronger maternal than paternal effects for footedness. By regressing out the effects of sex, age, and ancestry, we transformed laterality categories into quantitative measures. The SNP-h2 for quantitative handedness and footedness was .21 and .23, respectively, which is higher than the SNP-h2 reported in larger genetic studies using binary handedness measures. The heritability of the quantitative measure of handedness increased (.45) compared to a binary measure for writing hand (.27) in the Hong Kong twins. Genomic and behavioural SEM identified a shared genetic factor contributing to handedness, footedness, and eyedness, but no independent effects on individual phenotypes. Our analysis demonstrates how quantitative multidimensional laterality phenotypes are better suited to capture the underlying genetics than binary traits.

genetics↗

bioRxiv2021

Crowdsourced Identification of Multi-Target Kinase Inhibitors for RET- and TAU- Based Disease: the Multi-Targeting Drug DREAM Challenge

A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ( polypharmacology). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology. Author SummaryMany modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact, dirty; they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop cleaner therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease.

pharmacology and toxicology↗

bioRxiv2020

Microparticle-based Biochemical Sensing Using Optical Coherence Tomography and Deep Learning

Advancing continuous health monitoring beyond vital signs to biochemistry will revolutionize personalized medicine. Herein, we report a novel platform to achieve remote biochemical monitoring using microparticle-based biosensors and optical coherence tomography (OCT). Stimuli-responsive, polymeric microparticles were designed to serve as freely-dispersible biorecognition units, wherein binding with a target biochemical induces volumetric changes of the microparticle. Analytical approaches to detect these sub-micron changes in 3D using OCT were devised by modeling the microparticle as an optical cavity, enabling estimations far below the resolution of the OCT system. As a proof of concept, we demonstrated the 3D spatiotemporal monitoring of glucose-responsive microparticles distributed throughout a tissue-mimic in response to dynamically-fluctuating levels of glucose. Deep learning was further implemented using 3D convolutional neural networks to automate the vast processing of the continuous stream of three-dimensional time series data, resulting in a robust end-to-end pipeline with immense potential for continuous in vivo biochemical monitoring.

bioengineering↗

bioRxiv2020

COVID-19 cytokines and the hyperactive immune response: Synergism of TNF-α and IFN-γ in triggering inflammation, tissue damage, and death

The COVID-19 pandemic has caused significant morbidity and mortality. Currently, there is a critical shortage of proven treatment options and an urgent need to understand the pathogenesis of multi-organ failure and lung damage. Cytokine storm is associated with severe inflammation and organ damage during COVID-19. However, a detailed molecular pathway defining this cytokine storm is lacking, and gaining mechanistic understanding of how SARS-CoV-2 elicits a hyperactive inflammatory response is critical to develop effective therapeutics. Of the multiple inflammatory cytokines produced by innate immune cells during SARS-CoV-2 infection, we found that the combined production of TNF- and IFN-{gamma} specifically induced inflammatory cell death, PANoptosis, characterized by gasdermin-mediated pyroptosis, caspase-8-mediated apoptosis, and MLKL-mediated necroptosis. Deletion of pyroptosis, apoptosis, or necroptosis mediators individually was not sufficient to protect against cell death. However, cells deficient in both RIPK3 and caspase-8 or RIPK3 and FADD were resistant to this cell death. Mechanistically, the JAK/STAT1/IRF1 axis activated by TNF- and IFN-{gamma} co-treatment induced iNOS for the production of nitric oxide. Pharmacological and genetic deletion of this pathway inhibited pyroptosis, apoptosis, and necroptosis in macrophages. Moreover, inhibition of PANoptosis protected mice from TNF- and IFN-{gamma}-induced lethal cytokine shock that mirrors the pathological symptoms of COVID-19. In vivo neutralization of both TNF- and IFN-{gamma} in multiple disease models associated with cytokine storm showed that this treatment provided substantial protection against not only SARS-CoV-2 infection, but also sepsis, hemophagocytic lymphohistiocytosis, and cytokine shock models, demonstrating the broad physiological relevance of this mechanism. Collectively, our findings suggest that blocking the cytokine-mediated inflammatory cell death signaling pathway identified here may benefit patients with COVID-19 or other cytokine storm-driven syndromes by limiting inflammation and tissue damage. The findings also provide a molecular and mechanistic description for the term cytokine storm. Additionally, these results open new avenues for the treatment of other infectious and autoinflammatory diseases and cancers where TNF- and IFN-{gamma} synergism play key pathological roles.

immunology↗

bioRxiv2020

Tropomyosin in mugwort cross-reacts to house dust mite, eliciting non-Th2 response in allergic rhinitis patients sensitized to house dust mite

BackgroundMugwort and house dust mite (HDM) are two of the most common inhalant allergens in Asia; however, whether or not mugwort affects polysensitized HDM+ allergic rhinitis (AR) patients has not been elucidated. MethodsOverall, 15884 AR outpatients were assessed for clinical status. Amino acid sequences of mugwort were determined by mass spectrometry. Afterward, cross-reactivity between mugwort tropomyosin and Dermatophagoides pteronyssinus 10 (Der p10) was analysed by ELISA inhibition and basophils activation experiments. To compare immunologic responses eliciting by two different tropomyosins, peripheral blood mononuclear cells (PBMCs) of HDM-monosensitized patients were stimulated by mugwort, HDM, Der p10 and synthetic peptides representing mugwort tropomyosin respectively. ResultsPolysensitized HDM+AR patients were mainly sensitized to cat and mugwort, and the positive rate of monosensitized HDM+AR out-clinic patients was increased during the mugwort pollen season. Mugwort tropomyosin protein had similar structural domains to HDM tropomyosin, Der p10. ELISA inhibition experiment showed synthetic mugwort tropomyosin peptide inhibited IgE binding to Der p10; mugwort tropomyosin peptide activated basophils which were primed by HDM-specific IgE. Unlike HDM and Derp 10, mugwort and mugwort tropomyosin mainly induced IFN-{gamma} and IL-17, release in PBMCs of monosensitized HDM+AR patients, but not IL-5. ConclusionsPan-allergen tropomyosin is a major protein accounting for the cross-reactivity between mugwort and HDM, which reminds HDM+ patients to reduce mugwort exposure in mugwort pollen season in virtue of the tropomyosin induced mild inflammation.

immunology↗

bioRxiv2020

High Throughput Computational Mouse Genetic Analysis

BackgroundGenetic factors affecting multiple biomedical traits in mice have been identified when GWAS data that measured responses in panels of inbred mouse strains was analyzed using haplotype-based computational genetic mapping (HBCGM). Although this method was previously used to analyze one dataset at a time; but now, a vast amount of mouse phenotypic data is now publicly available, which could lead to many more genetic discoveries. ResultsHBCGM and a whole genome SNP map covering 53 inbred strains was used to analyze 8462 publicly available datasets of biomedical responses (1.52M individual datapoints) measured in panels of inbred mouse strains. As proof of concept, causative genetic factors affecting susceptibility for eye, metabolic and infectious diseases were identified when structured automated methods were used to analyze the output. One analysis identified a novel genetic effector mechanism; allelic differences within the mitochondrial targeting sequence affected the subcellular localization of a protein. We also found allelic differences within the mitochondrial targeting sequences of many murine and human proteins, and these could affect a wide range of biomedical phenotypes. ImplicationsThese initial results indicate that genetic factors affecting biomedical responses could be identified through analysis of very large datasets, and they provide an early indication of how this type of augmented intelligence can facilitate genetic discovery.

bioinformatics↗