Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations.

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

The Polygenic and Monogenic Basis of Blood Traits and Diseases.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

Mutational Landscape of Secondary Glioblastoma Guides MET-Targeted Trial in Brain Tumor.

Low-grade gliomas almost invariably progress into secondary glioblastoma (sGBM) with limited therapeutic option and poorly understood mechanism. By studying the mutational landscape of 188 sGBMs, we find significant enrichment of TP53 mutations, somatic hypermutation, MET-exon-14-skipping (METex14), PTPRZ1-MET (ZM) fusions, and MET amplification. Strikingly, METex14 frequently co-occurs with ZM fusion and is present in ∼14% of cases with significantly worse prognosis. Subsequent studies show that METex14 promotes glioma progression by prolonging MET activity. Furthermore, we describe a MET kinase inhibitor, PLB-1001, that demonstrates remarkable potency in selectively inhibiting MET-altered tumor cells in preclinical models. Importantly, this compound also shows blood-brain barrier permeability and is subsequently applied in a phase I clinical trial that enrolls MET-altered chemo-resistant glioma patients. Encouragingly, PLB-1001 achieves partial response in at least two advanced sGBM patients with rarely significant side effects, underscoring the clinical potential for precisely treating gliomas using this therapy.

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.

Population-based heteropolymer design to mimic protein mixtures.

Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined1. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed2-4. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters5,6; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.

PI3Kß controls immune evasion in PTEN-deficient breast tumours.

Loss of the PTEN tumour suppressor is one of the most common oncogenic drivers across all cancer types1. PTEN is the major negative regulator of PI3K signalling. The PI3Kß isoform has been shown to play an important role in PTEN-deficient tumours, but the mechanisms underlying the importance of PI3Kß activity remain elusive. Here, using a syngeneic genetically engineered mouse model of invasive breast cancer driven by ablation of both Pten and Trp53 (which encodes p53), we show that genetic inactivation of PI3Kß led to a robust anti-tumour immune response that abrogated tumour growth in syngeneic immunocompetent mice, but not in immunodeficient mice. Mechanistically, PI3Kß inactivation in the PTEN-null setting led to reduced STAT3 signalling and increased the expression of immune stimulatory molecules, thereby promoting anti-tumour immune responses. Pharmacological PI3Kß inhibition also elicited anti-tumour immunity and synergized with immunotherapy to inhibit tumour growth. Mice with complete responses to the combined treatment displayed immune memory and rejected tumours upon re-challenge. Our findings demonstrate a molecular mechanism linking PTEN loss and STAT3 activation in cancer and suggest that PI3Kß controls immune escape in PTEN-null tumours, providing a rationale for combining PI3Kß inhibitors with immunotherapy for the treatment of PTEN-deficient breast cancer.

CHIT1-positive microglia drive motor neuron ageing in the primate spinal cord.

Ageing is a critical factor in spinal-cord-associated disorders1, yet the ageing-specific mechanisms underlying this relationship remain poorly understood. Here, to address this knowledge gap, we combined single-nucleus RNA-sequencing analysis with behavioural and neurophysiological analysis in non-human primates (NHPs). We identified motor neuron senescence and neuroinflammation with microglial hyperactivation as intertwined hallmarks of spinal cord ageing. As an underlying mechanism, we identified a neurotoxic microglial state demarcated by elevated expression of CHIT1 (a secreted mammalian chitinase) specific to the aged spinal cords in NHP and human biopsies. In the aged spinal cord, CHIT1-positive microglia preferentially localize around motor neurons, and they have the ability to trigger senescence, partly by activating SMAD signalling. We further validated the driving role of secreted CHIT1 on MN senescence using multimodal experiments both in vivo, using the NHP spinal cord as a model, and in vitro, using a sophisticated system modelling the human motor-neuron-microenvironment interplay. Moreover, we demonstrated that ascorbic acid, a geroprotective compound, counteracted the pro-senescent effect of CHIT1 and mitigated motor neuron senescence in aged monkeys. Our findings provide the single-cell resolution cellular and molecular landscape of the aged primate spinal cord and identify a new biomarker and intervention target for spinal cord degeneration.

A male germ-cell-specific ribosome controls male fertility.

Ribosomes are highly sophisticated translation machines that have been demonstrated to be heterogeneous in the regulation of protein synthesis1,2. Male germ cell development involves complex translational regulation during sperm formation3. However, it remains unclear whether translation during sperm formation is performed by a specific ribosome. Here we report a ribosome with a specialized nascent polypeptide exit tunnel, RibosomeST, that is assembled with the male germ-cell-specific protein RPL39L, the paralogue of core ribosome (RibosomeCore) protein RPL39. Deletion of RibosomeST in mice causes defective sperm formation, resulting in substantially reduced fertility. Our comparison of single-particle cryo-electron microscopy structures of ribosomes from mouse kidneys and testes indicates that RibosomeST features a ribosomal polypeptide exit tunnel of distinct size and charge states compared with RibosomeCore. RibosomeST predominantly cotranslationally regulates the folding of a subset of male germ-cell-specific proteins that are essential for the formation of sperm. Moreover, we found that specialized functions of RibosomeST were not replaceable by RibosomeCore. Taken together, identification of this sperm-specific ribosome should greatly expand our understanding of ribosome function and tissue-specific regulation of protein expression pattern in mammals.

Reference-informed prediction of alternative splicing and splicing-altering mutations from sequences.

Alternative splicing plays a crucial role in protein diversity and gene expression regulation in higher eukaryotes, and mutations causing dysregulated splicing underlie a range of genetic diseases. Computational prediction of alternative splicing from genomic sequences not only provides insight into gene-regulatory mechanisms but also helps identify disease-causing mutations and drug targets. However, the current methods for the quantitative prediction of splice site usage still have limited accuracy. Here, we present DeltaSplice, a deep neural network model optimized to learn the impact of mutations on quantitative changes in alternative splicing from the comparative analysis of homologous genes. The model architecture enables DeltaSplice to perform "reference-informed prediction" by incorporating the known splice site usage of a reference gene sequence to improve its prediction on splicing-altering mutations. We benchmarked DeltaSplice and several other state-of-the-art methods on various prediction tasks, including evolutionary sequence divergence on lineage-specific splicing and splicing-altering mutations in human populations and neurodevelopmental disorders, and demonstrated that DeltaSplice outperformed consistently. DeltaSplice predicted ∼15% of splicing quantitative trait loci (sQTLs) in the human brain as causal splicing-altering variants. It also predicted splicing-altering de novo mutations outside the splice sites in a subset of patients affected by autism and other neurodevelopmental disorders (NDDs), including 19 genes with recurrent splicing-altering mutations. Integration of splicing-altering mutations with other types of de novo mutation burdens allowed the prediction of eight novel NDD-risk genes. Our work expanded the capacity of in silico splicing models with potential applications in genetic diagnosis and the development of splicing-based precision medicine.

The mouse cortico-basal ganglia-thalamic network.

The cortico-basal ganglia-thalamo-cortical loop is one of the fundamental network motifs in the brain. Revealing its structural and functional organization is critical to understanding cognition, sensorimotor behaviour, and the natural history of many neurological and neuropsychiatric disorders. Classically, this network is conceptualized to contain three information channels: motor, limbic and associative1-4. Yet this three-channel view cannot explain the myriad functions of the basal ganglia. We previously subdivided the dorsal striatum into 29 functional domains on the basis of the topography of inputs from the entire cortex5. Here we map the multi-synaptic output pathways of these striatal domains through the globus pallidus external part (GPe), substantia nigra reticular part (SNr), thalamic nuclei and cortex. Accordingly, we identify 14 SNr and 36 GPe domains and a direct cortico-SNr projection. The striatonigral direct pathway displays a greater convergence of striatal inputs than the more parallel striatopallidal indirect pathway, although direct and indirect pathways originating from the same striatal domain ultimately converge onto the same postsynaptic SNr neurons. Following the SNr outputs, we delineate six domains in the parafascicular and ventromedial thalamic nuclei. Subsequently, we identify six parallel cortico-basal ganglia-thalamic subnetworks that sequentially transduce specific subsets of cortical information through every elemental node of the cortico-basal ganglia-thalamic loop. Thalamic domains relay this output back to the originating corticostriatal neurons of each subnetwork in a bona fide closed loop.

PTEN Suppresses Glycolysis by Dephosphorylating and Inhibiting Autophosphorylated PGK1.

The PTEN tumor suppressor is frequently mutated or deleted in cancer and regulates glucose metabolism through the PI3K-AKT pathway. However, whether PTEN directly regulates glycolysis in tumor cells is unclear. We demonstrate here that PTEN directly interacts with phosphoglycerate kinase 1 (PGK1). PGK1 functions not only as a glycolytic enzyme but also as a protein kinase intermolecularly autophosphorylating itself at Y324 for activation. The protein phosphatase activity of PTEN dephosphorylates and inhibits autophosphorylated PGK1, thereby inhibiting glycolysis, ATP production, and brain tumor cell proliferation. In addition, knockin expression of a PGK1 Y324F mutant inhibits brain tumor formation. Analyses of human glioblastoma specimens reveals that PGK1 Y324 phosphorylation levels inversely correlate with PTEN expression status and are positively associated with poor prognosis in glioblastoma patients. This work highlights the instrumental role of PGK1 autophosphorylation in its activation and PTEN protein phosphatase activity in governing glycolysis and tumorigenesis.

miniSNV: accurate and fast single nucleotide variant calling from nanopore sequencing data.

Nanopore sequence technology has demonstrated a longer read length and enabled to potentially address the limitations of short-read sequencing including long-range haplotype phasing and accurate variant calling. However, there is still room for improvement in terms of the performance of single nucleotide variant (SNV) identification and computing resource usage for the state-of-the-art approaches. In this work, we introduce miniSNV, a lightweight SNV calling algorithm that simultaneously achieves high performance and yield. miniSNV utilizes known common variants in populations as variation backgrounds and leverages read pileup, read-based phasing, and consensus generation to identify and genotype SNVs for Oxford Nanopore Technologies (ONT) long reads. Benchmarks on real and simulated ONT data under various error profiles demonstrate that miniSNV has superior sensitivity and comparable accuracy on SNV detection and runs faster with outstanding scalability and lower memory than most state-of-the-art variant callers. miniSNV is available from https://github.com/CuiMiao-HIT/miniSNV.

Kled: an ultra-fast and sensitive structural variant detection tool for long-read sequencing data.

Structural Variants (SVs) are a crucial type of genetic variant that can significantly impact phenotypes. Therefore, the identification of SVs is an essential part of modern genomic analysis. In this article, we present kled, an ultra-fast and sensitive SV caller for long-read sequencing data given the specially designed approach with a novel signature-merging algorithm, custom refinement strategies and a high-performance program structure. The evaluation results demonstrate that kled can achieve optimal SV calling compared to several state-of-the-art methods on simulated and real long-read data for different platforms and sequencing depths. Furthermore, kled excels at rapid SV calling and can efficiently utilize multiple Central Processing Unit (CPU) cores while maintaining low memory usage. The source code for kled can be obtained from https://github.com/CoREse/kled.

SVDF: enhancing structural variation detect from long-read sequencing via automatic filtering strategies.

Structural variation (SV) is an important form of genomic variation that influences gene function and expression by altering the structure of the genome. Although long-read data have been proven to better characterize SVs, SVs detected from noisy long-read data still include a considerable portion of false-positive calls. To accurately detect SVs in long-read data, we present SVDF, a method that employs a learning-based noise filtering strategy and an SV signature-adaptive clustering algorithm, for effectively reducing the likelihood of false-positive events. Benchmarking results from multiple orthogonal experiments demonstrate that, across different sequencing platforms and depths, SVDF achieves higher calling accuracy for each sample compared to several existing general SV calling tools. We believe that, with its meticulous and sensitive SV detection capability, SVDF can bring new opportunities and advancements to cutting-edge genomic research.

Type II and IV toxin-antitoxin systems coordinately stabilize the integrative and conjugative element of the ICESa2603 family conferring multiple drug resistance in Streptococcus suis.

Integrative and conjugative elements (ICEs) play a vital role in bacterial evolution by carrying essential genes that confer adaptive functions to the host. Despite their importance, the mechanism underlying the stable inheritance of ICEs, which is necessary for the acquisition of new traits in bacteria, remains poorly understood. Here, we identified SezAT, a type II toxin-antitoxin (TA) system, and AbiE, a type IV TA system encoded within the ICESsuHN105, coordinately promote ICE stabilization and mediate multidrug resistance in Streptococcus suis. Deletion of SezAT or AbiE did not affect the strain's antibiotic susceptibility, but their duple deletion increased susceptibility, mainly mediated by the antitoxins SezA and AbiEi. Further studies have revealed that SezA and AbiEi affect the genetic stability of ICESsuHN105 by moderating the excision and extrachromosomal copy number, consequently affecting the antibiotic resistance conferred by ICE. The DNA-binding proteins AbiEi and SezA, which bind palindromic sequences in the promoter, coordinately modulate ICE excision and extracellular copy number by binding to sequences in the origin-of-transfer (oriT) and the attL sites, respectively. Furthermore, AbiEi negatively regulates the transcription of SezAT by binding directly to its promoter, optimizing the coordinate network of SezAT and AbiE in maintaining ICESsuHN105 stability. Importantly, SezAT and AbiE are widespread and conserved in ICEs harbouring diverse drug-resistance genes, and their coordinated effects in promoting ICE stability and mediating drug resistance may be broadly applicable to other ICEs. Altogether, our study uncovers the TA system's role in maintaining the genetic stability of ICE and offers potential targets for overcoming the dissemination and evolution of drug resistance.

PI3Kγ maintains the self-renewal of acute myeloid leukemia stem cells by regulating the pentose phosphate pathway.

ABSTRACT: Acute myeloid leukemia (AML) is an aggressive hematological malignancy originating from transformed hematopoietic stem or progenitor cells. AML prognosis remains poor owing to resistance and relapse driven by leukemia stem cells (LSCs). Targeting molecules essential for LSC function is a promising therapeutic approach. The phosphatidylinositol 3-kinase (PI3K)/AKT pathway is often dysregulated in AML. We found that although PI3Kγ is highly enriched in LSCs and critical for self-renewal, it was dispensable for normal hematopoietic stem cells. Mechanistically, PI3Kγ-AKT signaling promotes nuclear factor erythroid 2-related factor 2 (NRF2) nuclear accumulation, which induces 6-phosphogluconate dehydrogenase (PGD) and the pentose phosphate pathway, thereby maintaining LSC stemness. Importantly, genetic or pharmacological inhibition of PI3Kγ impaired expansion and stemness of murine and human AML cells in vitro and in vivo. Together, our findings reveal a key role for PI3Kγ in selectively maintaining LSC function by regulating AKT-NRF2-PGD metabolic pathway. Targeting the PI3Kγ pathway may, therefore, eliminate LSCs without damaging normal hematopoiesis, providing a promising therapeutic strategy for AML.

Single-chain heteropolymers transport protons selectively and rapidly.

Precise protein sequencing and folding are believed to generate the structure and chemical diversity of natural channels1,2, both of which are essential to synthetically achieve proton transport performance comparable to that seen in natural systems. Geometrically defined channels have been fabricated using peptides, DNAs, carbon nanotubes, sequence-defined polymers and organic frameworks3-13. However, none of these channels rivals the performance observed in their natural counterparts. Here we show that without forming an atomically structured channel, four-monomer-based random heteropolymers (RHPs)14 can mimic membrane proteins and exhibit selective proton transport across lipid bilayers at a rate similar to those of natural proton channels. Statistical control over the monomer distribution in an RHP leads to segmental heterogeneity in hydrophobicity, which facilitates the insertion of single RHPs into the lipid bilayers. It also results in bilayer-spanning segments containing polar monomers that promote the formation of hydrogen-bonded chains15,16 for proton transport. Our study demonstrates the importance of the adaptability that is enabled by statistical similarity among RHP chains and of the modularity provided by the chemical diversity of monomers, to achieve uniform behaviour in heterogeneous systems. Our results also validate statistical randomness as an unexplored approach to realize protein-like behaviour at the single-polymer-chain level in a predictable manner.

Nuclear PGK1 Alleviates ADP-Dependent Inhibition of CDC7 to Promote DNA Replication.

DNA replication is initiated by assembly of the kinase cell division cycle 7 (CDC7) with its regulatory activation subunit, activator of S-phase kinase (ASK), to activate DNA helicase. However, the mechanism underlying regulation of CDC7-ASK complex is unclear. Here, we show that ADP generated from CDC7-mediated MCM phosphorylation binds to an allosteric region of CDC7, disrupts CDC7-ASK interaction, and inhibits CDC7-ASK activity in a feedback way. EGFR- and ERK-activated casein kinase 2α (CK2α) phosphorylates nuclear phosphoglycerate kinase (PGK) 1 at S256, resulting in interaction of PGK1 with CDC7. CDC7-bound PGK1 converts ADP to ATP, thereby abrogating the inhibitory effect of ADP on CDC7-ASK activity, promoting the recruitment of DNA helicase to replication origins, DNA replication, cell proliferation, and brain tumorigenesis. These findings reveal an instrumental self-regulatory mechanism of CDC7-ASK activity by its kinase reaction product ADP and a nonglycolytic role for PGK1 in abrogating this negative feedback in promoting tumor development.

EGFR-Phosphorylated Platelet Isoform of Phosphofructokinase 1 Promotes PI3K Activation.

EGFR activates phosphatidylinositide 3-kinase (PI3K), but the mechanism underlying this activation is not completely understood. We demonstrated here that EGFR activation resulted in lysine acetyltransferase 5 (KAT5)-mediated K395 acetylation of the platelet isoform of phosphofructokinase 1 (PFKP) and subsequent translocation of PFKP to the plasma membrane, where the PFKP was phosphorylated at Y64 by EGFR. Phosphorylated PFKP binds to the N-terminal SH2 domain of p85α, which is distinct from binding of Gab1 to the C-terminal SH2 domain of p85α, and recruited p85α to the plasma membrane resulting in PI3K activation. PI3K-dependent AKT activation results in enhanced phosphofructokinase 2 (PFK2) phosphorylation and production of fructose-2,6-bisphosphate, which in turn promotes PFK1 activation. PFKP Y64 phosphorylation-enhanced PI3K/AKT-dependent PFK1 activation and GLUT1 expression promoted the Warburg effect, tumor cell proliferation, and brain tumorigenesis. These findings underscore the instrumental role of PFKP in PI3K activation and enhanced glycolysis through PI3K/AKT-dependent positive-feedback regulation.

circRNADisease v2.0: an updated resource for high-quality experimentally supported circRNA-disease associations.

circRNADisease v2.0 is an enhanced and reliable database that offers experimentally verified relationships between circular RNAs (circRNAs) and various diseases. It is accessible at http://cgga.org.cn/circRNADisease/ or http://cgga.org.cn:9091/circRNADisease/. The database currently includes 6998 circRNA-disease entries across multiple species, representing a remarkable 19.77-fold increase compared to the previous version. This expansion consists of a substantial rise in the number of circRNAs (from 330 to 4246), types of diseases (from 48 to 330) and covered species (from human only to 12 species). Furthermore, a new section has been introduced in the database, which collects information on circRNA-associated factors (genes, proteins and microRNAs), molecular mechanisms (molecular pathways), biological functions (proliferation, migration, invasion, etc.), tumor and/or cell line and/or patient-derived xenograft (PDX) details, and prognostic evidence in diseases. In addition, we identified 7 159 865 relationships between mutations and circRNAs among 30 TCGA cancer types. Due to notable enhancements and extensive data expansions, the circRNADisease 2.0 database has become an invaluable asset for both clinical practice and fundamental research. It enables researchers to develop a more comprehensive understanding of how circRNAs impact complex diseases.