Limb development genes underlie variation in human fingerprint patterns.

Fingerprints are of long-standing practical and cultural interest, but little is known about the mechanisms that underlie their variation. Using genome-wide scans in Han Chinese cohorts, we identified 18 loci associated with fingerprint type across the digits, including a genetic basis for the long-recognized "pattern-block" correlations among the middle three digits. In particular, we identified a variant near EVI1 that alters regulatory activity and established a role for EVI1 in dermatoglyph patterning in mice. Dynamic EVI1 expression during human development supports its role in shaping the limbs and digits, rather than influencing skin patterning directly. Trans-ethnic meta-analysis identified 43 fingerprint-associated loci, with nearby genes being strongly enriched for general limb development pathways. We also found that fingerprint patterns were genetically correlated with hand proportions. Taken together, these findings support the key role of limb development genes in influencing the outcome of fingerprint patterning.

Multiple early factors anticipate post-acute COVID-19 sequelae.

Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific auto-antibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes, exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time, leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Multi-Omics Resolves a Sharp Disease-State Shift between Mild and Moderate COVID-19.

We present an integrated analysis of the clinical measurements, immune cells, and plasma multi-omics of 139 COVID-19 patients representing all levels of disease severity, from serial blood draws collected during the first week of infection following diagnosis. We identify a major shift between mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific classes of metabolites and metabolic processes. Within this stressed plasma environment at moderate disease, multiple unusual immune cell phenotypes emerge and amplify with increasing disease severity. We condensed over 120,000 immune features into a single axis to capture how different immune cell classes coordinate in response to SARS-CoV-2. This immune-response axis independently aligns with the major plasma composition changes, with clinical metrics of blood clotting, and with the sharp transition between mild and moderate disease. This study suggests that moderate disease may provide the most effective setting for therapeutic intervention.

Lipid-Sorting Specificity Encoded in K-Ras Membrane Anchor Regulates Signal Output.

K-Ras is targeted to the plasma membrane by a C-terminal membrane anchor that comprises a farnesyl-cysteine-methyl-ester and a polybasic domain. We used quantitative spatial imaging and atomistic molecular dynamics simulations to examine molecular details of K-Ras plasma membrane binding. We found that the K-Ras anchor binds selected plasma membrane anionic lipids with defined head groups and lipid side chains. The precise amino acid sequence and prenyl group define a combinatorial code for lipid binding that extends beyond simple electrostatics; within this code lysine and arginine residues are non-equivalent and prenyl chain length modifies nascent polybasic domain lipid preferences. The code is realized by distinct dynamic tertiary structures of the anchor on the plasma membrane that govern amino acid side-chain-lipid interactions. An important consequence of this specificity is the ability of such anchors when aggregated to sort subsets of phospholipids into nanoclusters with defined lipid compositions that determine K-Ras signaling output.

Limited increases in savanna carbon stocks over decades of fire suppression.

Savannas cover a fifth of the land surface and contribute a third of terrestrial net primary production, accounting for three-quarters of global area burned and more than half of global fire-driven carbon emissions1-3. Fire suppression and afforestation have been proposed as tools to increase carbon sequestration in these ecosystems2,4. A robust quantification of whole-ecosystem carbon storage in savannas is lacking however, especially under altered fire regimes. Here we provide one of the first direct estimates of whole-ecosystem carbon response to more than 60 years of fire exclusion in a mesic African savanna. We found that fire suppression increased whole-ecosystem carbon storage by only 35.4 ± 12% (mean ± standard error), even though tree cover increased by 78.9 ± 29.3%, corresponding to total gains of 23.0 ± 6.1 Mg C ha-1 at an average of about 0.35 ± 0.09 Mg C ha-1 year-1, more than an order of magnitude lower than previously assumed4. Frequently burned savannas had substantial belowground carbon, especially in biomass and deep soils. These belowground reservoirs are not fully considered in afforestation or fire-suppression schemes but may mean that the decadal sequestration potential of savannas is negligible, especially weighed against concomitant losses of biodiversity and function.

Genomic insights into the formation of human populations in East Asia.

The deep population history of East Asia remains poorly understood owing to a lack of ancient DNA data and sparse sampling of present-day people1,2. Here we report genome-wide data from 166 East Asian individuals dating to between 6000 BC and AD 1000 and 46 present-day groups. Hunter-gatherers from Japan, the Amur River Basin, and people of Neolithic and Iron Age Taiwan and the Tibetan Plateau are linked by a deeply splitting lineage that probably reflects a coastal migration during the Late Pleistocene epoch. We also follow expansions during the subsequent Holocene epoch from four regions. First, hunter-gatherers from Mongolia and the Amur River Basin have ancestry shared by individuals who speak Mongolic and Tungusic languages, but do not carry ancestry characteristic of farmers from the West Liao River region (around 3000 BC), which contradicts theories that the expansion of these farmers spread the Mongolic and Tungusic proto-languages. Second, farmers from the Yellow River Basin (around 3000 BC) probably spread Sino-Tibetan languages, as their ancestry dispersed both to Tibet-where it forms approximately 84% of the gene pool in some groups-and to the Central Plain, where it has contributed around 59-84% to modern Han Chinese groups. Third, people from Taiwan from around 1300 BC to AD 800 derived approximately 75% of their ancestry from a lineage that is widespread in modern individuals who speak Austronesian, Tai-Kadai and Austroasiatic languages, and that we hypothesize derives from farmers of the Yangtze River Valley. Ancient people from Taiwan also derived about 25% of their ancestry from a northern lineage that is related to, but different from, farmers of the Yellow River Basin, which suggests an additional north-to-south expansion. Fourth, ancestry from Yamnaya Steppe pastoralists arrived in western Mongolia after around 3000 BC but was displaced by previously established lineages even while it persisted in western China, as would be expected if this ancestry was associated with the spread of proto-Tocharian Indo-European languages. Two later gene flows affected western Mongolia: migrants after around 2000 BC with Yamnaya and European farmer ancestry, and episodic influences of later groups with ancestry from Turan.

Distinct Binding Preferences between Ras and Raf Family Members and the Impact on Oncogenic Ras Signaling.

The Ras GTPases are frequently mutated in human cancer, and, although the Raf kinases are essential effectors of Ras signaling, the tumorigenic properties of specific Ras-Raf complexes are not well characterized. Here, we examine the ability of individual Ras and Raf proteins to interact in live cells using bioluminescence resonance energy transfer (BRET) technology. We find that C-Raf binds all mutant Ras proteins with high affinity, whereas B-Raf exhibits a striking preference for mutant K-Ras. This selectivity is mediated by the acidic, N-terminal segment of B-Raf and requires the K-Ras polybasic region for high-affinity binding. In addition, we find that C-Raf is critical for mutant H-Ras-driven signaling and that events stabilizing B-Raf/C-Raf dimerization, such as Raf inhibitor treatment or certain B-Raf mutations, can allow mutant H-Ras to engage B-Raf with increased affinity to promote tumorigenesis, thus revealing a previously unappreciated role for C-Raf in potentiating B-Raf function.

Accurate estimation of biological age and its application in disease prediction using a multimodal image Transformer system.

Aging in an individual refers to the temporal change, mostly decline, in the body's ability to meet physiological demands. Biological age (BA) is a biomarker of chronological aging and can be used to stratify populations to predict certain age-related chronic diseases. BA can be predicted from biomedical features such as brain MRI, retinal, or facial images, but the inherent heterogeneity in the aging process limits the usefulness of BA predicted from individual body systems. In this paper, we developed a multimodal Transformer-based architecture with cross-attention which was able to combine facial, tongue, and retinal images to estimate BA. We trained our model using facial, tongue, and retinal images from 11,223 healthy subjects and demonstrated that using a fusion of the three image modalities achieved the most accurate BA predictions. We validated our approach on a test population of 2,840 individuals with six chronic diseases and obtained significant difference between chronological age and BA (AgeDiff) than that of healthy subjects. We showed that AgeDiff has the potential to be utilized as a standalone biomarker or conjunctively alongside other known factors for risk stratification and progression prediction of chronic diseases. Our results therefore highlight the feasibility of using multimodal images to estimate and interrogate the aging process.

BAG6 inhibits influenza A virus replication by inducing viral polymerase subunit PB2 degradation and perturbing RdRp complex assembly.

The interaction between influenza A virus (IAV) and host proteins is an important process that greatly influences viral replication and pathogenicity. PB2 protein is a subunit of viral ribonucleoprotein (vRNP) complex playing distinct roles in viral transcription and replication. BAG6 (BCL2-associated athanogene 6) as a multifunctional host protein participates in physiological and pathological processes. Here, we identify BAG6 as a new restriction factor for IAV replication through targeting PB2. For both avian and human influenza viruses, overexpression of BAG6 reduced viral protein expression and virus titers, whereas deletion of BAG6 significantly enhanced virus replication. Moreover, BAG6-knockdown mice developed more severe clinical symptoms and higher viral loads upon IAV infection. Mechanistically, BAG6 restricted IAV transcription and replication by inhibiting the activity of viral RNA-dependent RNA polymerase (RdRp). The co-immunoprecipitation assays showed BAG6 specifically interacted with the N-terminus of PB2 and competed with PB1 for RdRp complex assembly. The ubiquitination assay indicated that BAG6 promoted PB2 ubiquitination at K189 residue and targeted PB2 for K48-linked ubiquitination degradation. The antiviral effect of BAG6 necessitated its N-terminal region containing a ubiquitin-like (UBL) domain (17-92aa) and a PB2-binding domain (124-186aa), which are synergistically responsible for viral polymerase subunit PB2 degradation and perturbing RdRp complex assembly. These findings unravel a novel antiviral mechanism via the interaction of viral PB2 and host protein BAG6 during avian or human influenza virus infection and highlight a potential application of BAG6 for antiviral drug development.

Mixed Selectivity Coding of Content-Temporal Detail by Dorsomedial Posterior Parietal Neurons.

The dorsomedial posterior parietal cortex (dmPPC) is part of a higher-cognition network implicated in elaborate processes underpinning memory formation, recollection, episode reconstruction, and temporal information processing. Neural coding for complex episodic processing is however under-documented. Here, we recorded extracellular neural activities from three male rhesus macaques (Macaca mulatta) and revealed a set of neural codes of "neuroethogram" in the primate parietal cortex. Analyzing neural responses in macaque dmPPC to naturalistic videos, we discovered several groups of neurons that are sensitive to different categories of ethogram items, low-level sensory features, and saccadic eye movement. We also discovered that the processing of category and feature information by these neurons is sustained by the accumulation of temporal information over a long timescale of up to 30 s, corroborating its reported long temporal receptive windows. We performed an additional behavioral experiment with additional two male rhesus macaques and found that saccade-related activities could not account for the mixed neuronal responses elicited by the video stimuli. We further observed monkeys' scan paths and gaze consistency are modulated by video content. Taken altogether, these neural findings explain how dmPPC weaves fabrics of ongoing experiences together in real time. The high dimensionality of neural representations should motivate us to shift the focus of attention from pure selectivity neurons to mixed selectivity neurons, especially in increasingly complex naturalistic task designs.

IMperm: a fast and comprehensive IMmune Paired-End Reads Merger for sequencing data.

The adaptive immune receptor repertoire (AIRR), consisting of T- and B-cell receptors, is the core component of the immune system. The AIRR sequencing is commonly used in cancer immunotherapy and minimal residual disease (MRD) detection of leukemia and lymphoma. The AIRR is captured by primers and sequenced to yield paired-end (PE) reads. The PE reads could be merged into one sequence by the overlapped region between them. However, the wide range of AIRR data raises the difficulty, so a special tool is required. We developed a software package for IMmune PE reads merger of sequencing data, named IMperm. We used the k-mer-and-vote strategy to pin down the overlapped region rapidly. IMperm could handle all types of PE reads, eliminate adapter contamination and successfully merge low-quality and minor/non-overlapping reads. Compared with existing tools, IMperm performed better in both simulated and sequencing data. Notably, IMperm was well suited to processing the data of MRD detection in leukemia and lymphoma and detected 19 novel MRD clones in 14 patients with leukemia from previously published data. Additionally, IMperm can handle PE reads from other sources, and we demonstrated its effectiveness on two genomic and one cell-free deoxyribonucleic acid datasets. IMperm is implemented in the C programming language and consumes little runtime and memory. It is freely available at https://github.com/zhangwei2015/IMperm.

Spatial Transcriptomics Reveals the Transcriptomic Signatures in a Mouse Model of Pediatric Metabolic Dysfunction-Associated Steatohepatitis.

Metabolic dysfunction-associated steatohepatitis (MASH) is considered the progressive form of metabolic dysfunction-associated steatotic liver disease, which is the leading cause of chronic liver disease in children. However, the pathogenesis of pediatric MASH remains poorly understood because of the lack of animal models. In this study, we developed a mouse model of pediatric MASH and characterized the hepatic transcriptomic profile using spatial transcriptomics technology. C57BL/6J mice were fed a Western diet (WD) along with weekly injections of carbon tetrachloride (CCl4) from the age of 3 to 8 weeks. After 5 weeks of feeding, WD + CCl4-treated mice showed significant liver injury without the development of insulin resistance. Histologically, WD + CCl4 induced key features of type 2 MASH, the most common type observed in children, characterized by liver steatosis, portal inflammation, and portal fibrosis. Through spatial transcriptomics analysis of liver tissues, we identified that cluster 0 in the mouse from the WD + CCl4 group was enriched in pathways associated with lipid metabolism. Further investigation revealed that cytochrome p450 2E1 was the top marker gene of cluster 0, and its expression was increased in the periportal area of mice from the WD + CCl4 group. These findings suggest that our mouse model of pediatric MASH mirrors the histologic features of human MASH, and the up-regulation of cytochrome p450 2E1 may be linked to the disease pathogenesis.

Multi-regional sequencing reveals the genetic and immune heterogeneity of non-cancerous tissues in gastric cancer.

Gastric cancer (GC) is one of the most heterogeneous tumors. However, research on normal tissue adjacent to the tumor (NAT) is very limited. We performed multi-regional omics sequencing on 150 samples to assess the genetic basis and immune microenvironment in NAT and matched primary tumor or lymph node metastases. NATs demonstrated different mutated genes compared with GC, and NAT genomes underwent independent evolution with low variant allele frequency. Mutation profiles were predominated by aging and smoking-associated signatures in NAT instead of signatures associated with genetic instability. Although the immune microenvironment within NATs shows substantial intra-patient heterogeneity, the proportion of shared TCR clones among NATs is five times higher than that of tumor regions. These findings support the notion that subclonal expansion is not pronounced in NATs. We also demonstrated remarkable intra-patient heterogeneity of GCs and revealed heterogeneity of focal amplification of CD274 (encoding PD-L1) that leads to differential expression. Finally, we identified that monoclonal seeding is predominant in GC, which is followed by metastasis-to-metastasis dissemination in individual lymph nodes. These results provide novel insights into GC carcinogenesis. © 2024 The Pathological Society of Great Britain and Ireland.

Probabilistic cell/domain-type assignment of spatial transcriptomics data with SpatialAnno.

In the analysis of both single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) data, classifying cells/spots into cell/domain types is an essential analytic step for many secondary analyses. Most of the existing annotation methods have been developed for scRNA-seq datasets without any consideration of spatial information. Here, we present SpatialAnno, an efficient and accurate annotation method for spatial transcriptomics datasets, with the capability to effectively leverage a large number of non-marker genes as well as 'qualitative' information about marker genes without using a reference dataset. Uniquely, SpatialAnno estimates low-dimensional embeddings for a large number of non-marker genes via a factor model while promoting spatial smoothness among neighboring spots via a Potts model. Using both simulated and four real spatial transcriptomics datasets from the 10x Visium, ST, Slide-seqV1/2, and seqFISH platforms, we showcase the method's improved spatial annotation accuracy, including its robustness to the inclusion of marker genes for irrelevant cell/domain types and to various degrees of marker gene misspecification. SpatialAnno is computationally scalable and applicable to SRT datasets from different platforms. Furthermore, the estimated embeddings for cellular biological effects facilitate many downstream analyses.

Heavy metal ions exchange driven protein phosphorylation cascade functions in genomic instability in spermatocytes and male infertility.

DNA double-strand breaks (DSBs) are functionally linked to genomic instability in spermatocytes and to male infertility. The heavy metal cadmium (Cd) is known to induce DNA damage in spermatocytes by unknown mechanisms. Here, we showed that Cd ions impaired the canonical non-homologous end-joining (NHEJ) repair pathway, but not the homologous recombination (HR) repair pathway, through stimulation of Ser2056 and Thr2609 phosphorylation of DNA-PKcs at DSB sites. Hyper-phosphorylation of DNA-PKcs led to its premature dissociation from DNA ends and the Ku complex, preventing recruitment of processing enzymes and further ligation of DNA ends. Specifically, this cascade was initiated by the loss of PP5 phosphatase activity, which results from the dissociation of PP5 from its activating ions (Mn), that is antagonized by Cd ions through a competitive mechanism. In accordance, in a mouse model Cd-induced genomic instability and consequential male reproductive dysfunction were effectively reversed by a high dosage of Mn ions. Together, our findings corroborate a protein phosphorylation-mediated genomic instability pathway in spermatocytes that is triggered by exchange of heavy metal ions.

UBR2 targets myosin heavy chain IIb and IIx for degradation: Molecular mechanism essential for cancer-induced muscle wasting.

Cancer cachexia is a lethal metabolic syndrome featuring muscle wasting with preferential loss of fast-twitching muscle mass through an undefined mechanism. Here, we show that cancer induces muscle wasting by selectively degrading myosin heavy chain (MHC) subtypes IIb and IIx through E3 ligase UBR2-mediated ubiquitylation. Induction of MHC loss and atrophy in C2C12 myotubes and mouse tibialis anterior (TA) by murine cancer cells required UBR2 up-regulation by cancer. Genetic gain or loss of UBR2 function inversely altered MHC level and muscle mass in TA of tumor-free mice. UBR2 selectively interacted with and ubiquitylated MHC-IIb and MHC-IIx through its substrate recognition and catalytic domain, respectively, in C2C12 myotubes. Elevation of UBR2 in muscle of tumor-bearing or free mice caused loss of MHC-IIb and MHC-IIx but not MHC-I and MHC-IIa or other myofibrillar proteins, including α-actin, troponin, tropomyosin, and tropomodulin. Muscle-specific knockout of UBR2 spared KPC tumor-bearing mice from losing MHC-IIb and MHC-IIx, fast-twitching muscle mass, cross-sectional area, and contractile force. The rectus abdominis (RA) muscle of patients with cachexia-prone cancers displayed a selective reduction of MHC-IIx in correlation with higher UBR2 levels. These data suggest that UBR2 is a regulator of MHC-IIb/IIx essential for cancer-induced muscle wasting, and that therapeutic interventions can be designed by blocking UBR2 up-regulation by cancer.

A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset.

BACKGROUND: Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable. RESULTS: Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a "subpopulation aware" 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq). CONCLUSIONS: This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment.

NOX4-TIM23 interaction regulates NOX4 mitochondrial import and metabolic reprogramming.

Pulmonary fibrosis is a progressive lung disease characterized by macrophage activation. Asbestos-induced expression of nicotinamide adenine dinucleotide phosphate hydrogen oxidase 4 (NOX4) in lung macrophages mediates fibrotic progression by the generation of mitochondrial reactive oxygen species (ROS), modulating mitochondrial biogenesis, and promoting apoptosis resistance; however, the mechanism(s) by which NOX4 localizes to mitochondria during fibrosis is not known. Here, we show that NOX4 localized to the mitochondrial matrix following asbestos exposure in lung macrophages via direct interaction with TIM23. TIM23 and NOX4 interaction was found in lung macrophages from human subjects with asbestosis, while it was absent in mice harboring a conditional deletion of NOX4 in lung macrophages. This interaction was localized to the proximal transmembrane region of NOX4. Mechanistically, TIM23 augmented NOX4-induced mitochondrial ROS and metabolic reprogramming to oxidative phosphorylation. Silencing TIM23 decreased mitochondrial ROS and oxidative phosphorylation. These observations highlight the important role of the mitochondrial translocase TIM23 interaction with NOX4. Moreover, this interaction is required for mitochondrial redox signaling and metabolic reprogramming in lung macrophages.