Insulin Receptor Associates with Promoters Genome-wide and Regulates Gene Expression.

Insulin receptor (IR) signaling is central to normal metabolic control and dysregulated in prevalent chronic diseases. IR binds insulin at the cell surface and transduces rapid signaling via cytoplasmic kinases. However, mechanisms mediating long-term effects of insulin remain unclear. Here, we show that IR associates with RNA polymerase II in the nucleus, with striking enrichment at promoters genome-wide. The target genes were highly enriched for insulin-related functions including lipid metabolism and protein synthesis and diseases including diabetes, neurodegeneration, and cancer. IR chromatin binding was increased by insulin and impaired in an insulin-resistant disease model. Promoter binding by IR was mediated by coregulator host cell factor-1 (HCF-1) and transcription factors, revealing an HCF-1-dependent pathway for gene regulation by insulin. These results show that IR interacts with transcriptional machinery at promoters and identify a pathway regulating genes linked to insulin's effects in physiology and disease.

Evolutionary Changes in Transcriptional Regulation: Insights into Human Behavior and Neurological Conditions.

Understanding the biological basis for human-specific cognitive traits presents both immense challenges and unique opportunities. Although the question of what makes us human has been investigated with several different methods, the rise of comparative genomics, epigenomics, and medical genetics has provided tools to help narrow down and functionally assess the regions of the genome that seem evolutionarily relevant along the human lineage. In this review, we focus on how medical genetic cases have provided compelling functional evidence for genes and loci that appear to have interesting evolutionary signatures in humans. Furthermore, we examine a special class of noncoding regions, human accelerated regions (HARs), that have been suggested to show human-lineage-specific divergence, and how the use of clinical and population data has started to provide functional information to examine these regions. Finally, we outline methods that provide new insights into functional noncoding sequences in evolution.

TMEM161B regulates cerebral cortical gyration, Sonic Hedgehog signaling, and ciliary structure in the developing central nervous system.

Sonic hedgehog signaling regulates processes of embryonic development across multiple tissues, yet factors regulating context-specific Shh signaling remain poorly understood. Exome sequencing of families with polymicrogyria (disordered cortical folding) revealed multiple individuals with biallelic deleterious variants in TMEM161B, which encodes a multi-pass transmembrane protein of unknown function. Tmem161b null mice demonstrated holoprosencephaly, craniofacial midline defects, eye defects, and spinal cord patterning changes consistent with impaired Shh signaling, but were without limb defects, suggesting a CNS-specific role of Tmem161b. Tmem161b depletion impaired the response to Smoothened activation in vitro and disrupted cortical histogenesis in vivo in both mouse and ferret models, including leading to abnormal gyration in the ferret model. Tmem161b localizes non-exclusively to the primary cilium, and scanning electron microscopy revealed shortened, dysmorphic, and ballooned ventricular zone cilia in the Tmem161b null mouse, suggesting that the Shh-related phenotypes may reflect ciliary dysfunction. Our data identify TMEM161B as a regulator of cerebral cortical gyration, as involved in primary ciliary structure, as a regulator of Shh signaling, and further implicate Shh signaling in human gyral development.

The familial Alzheimer's disease APPV717I mutation alters APP processing and Tau expression in iPSC-derived neurons.

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by extracellular plaques containing amyloid ß (Aß)-protein and intracellular tangles containing hyperphosphorylated Tau protein. Here, we describe the generation of inducible pluripotent stem cell lines from patients harboring the London familial AD (fAD) amyloid precursor protein (APP) mutation (V717I). We examine AD-relevant phenotypes following directed differentiation to forebrain neuronal fates vulnerable in AD. We observe that over differentiation time to mature neuronal fates, APP expression and levels of Aß increase dramatically. In both immature and mature neuronal fates, the APPV717I mutation affects both ß- and γ-secretase cleavage of APP. Although the mutation lies near the γ-secretase cleavage site in the transmembrane domain of APP, we find that ß-secretase cleavage of APP is elevated leading to generation of increased levels of both APPsß and Aß. Furthermore, we find that this mutation alters the initial cleavage site of γ-secretase, resulting in an increased generation of both Aß42 and Aß38. In addition to altered APP processing, an increase in levels of total and phosphorylated Tau is observed in neurons with the APPV717I mutation. We show that treatment with Aß-specific antibodies early in culture reverses the phenotype of increased total Tau levels, implicating altered Aß production in fAD neurons in this phenotype. These studies use human neurons to reveal previously unrecognized effects of the most common fAD APP mutation and provide a model system for testing therapeutic strategies in the cell types most relevant to disease processes.

Combining machine learning and remote sensing-integrated crop modeling for rice and soybean crop simulation.

Machine learning (ML) techniques offer a promising avenue for improving the integration of remote sensing data into mathematical crop models, thereby enhancing crop growth prediction accuracy. A critical variable for this integration is the leaf area index (LAI), which can be accurately assessed using proximal or remote sensing data based on plant canopies. This study aimed to (1) develop a machine learning-based method for estimating the LAI in rice and soybean crops using proximal sensing data and (2) evaluate the performance of a Remote Sensing-Integrated Crop Model (RSCM) when integrated with the ML algorithms. To achieve these objectives, we analyzed rice and soybean datasets to identify the most effective ML algorithms for modeling the relationship between LAI and vegetation indices derived from canopy reflectance measurements. Our analyses employed a variety of ML regression models, including ridge, lasso, support vector machine, random forest, and extra trees. Among these, the extra trees regression model demonstrated the best performance, achieving test scores of 0.86 and 0.89 for rice and soybean crops, respectively. This model closely replicated observed LAI values under different nitrogen treatments, achieving Nash-Sutcliffe efficiencies of 0.93 for rice and 0.97 for soybean. Our findings show that incorporating ML techniques into RSCM effectively captures seasonal LAI variations across diverse field management practices, offering significant potential for improving crop growth and productivity monitoring.

Rare variation in noncoding regions with evolutionary signatures contributes to autism spectrum disorder risk.

Little is known about the role of noncoding regions in the etiology of autism spectrum disorder (ASD). We examined three classes of noncoding regions: Human Accelerated Regions (HARs), which show signatures of positive selection in humans; experimentally validated neural Vista Enhancers (VEs); and conserved regions predicted to act as neural enhancers (CNEs). Targeted and whole genome analysis of >16,600 samples and >4900 ASD probands revealed that likely recessive, rare, inherited variants in HARs, VEs, and CNEs substantially contribute to ASD risk in probands whose parents share ancestry, which enriches for recessive contributions, but modestly, if at all, in simplex family structures. We identified multiple patient variants in HARs near IL1RAPL1 and in a VE near SIM1 and showed that they change enhancer activity. Our results implicate both human-evolved and evolutionarily conserved noncoding regions in ASD risk and suggest potential mechanisms of how changes in regulatory regions can modulate social behavior.

Somatic Mosaicism in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia Reveals Widespread Degeneration from Focal Mutations.

Although mutations in dozens of genes have been implicated in familial forms of amyotrophic lateral sclerosis (fALS) and frontotemporal degeneration (fFTD), most cases of these conditions are sporadic (sALS and sFTD), with no family history, and their etiology remains obscure. We tested the hypothesis that somatic mosaic mutations, present in some but not all cells, might contribute in these cases, by performing ultra-deep, targeted sequencing of 88 genes associated with neurodegenerative diseases in postmortem brain and spinal cord samples from 404 individuals with sALS or sFTD and 144 controls. Known pathogenic germline mutations were found in 20.6% of ALS, and 26.5% of FTD cases. Predicted pathogenic somatic mutations in ALS/FTD genes were observed in 2.7% of sALS and sFTD cases that did not carry known pathogenic or novel germline mutations. Somatic mutations showed low variant allele fraction (typically <2%) and were often restricted to the region of initial discovery, preventing detection through genetic screening in peripheral tissues. Damaging somatic mutations were preferentially enriched in primary motor cortex of sALS and prefrontal cortex of sFTD, mirroring regions most severely affected in each disease. Somatic mutation analysis of bulk RNA-seq data from brain and spinal cord from an additional 143 sALS cases and 23 controls confirmed an overall enrichment of somatic mutations in sALS. Two adult sALS cases were identified bearing pathogenic somatic mutations in DYNC1H1 and LMNA, two genes associated with pediatric motor neuron degeneration. Our study suggests that somatic mutations in fALS/fFTD genes, and in genes associated with more severe diseases in the germline state, contribute to sALS and sFTD, and that mosaic mutations in a small fraction of cells in focal regions of the nervous system can ultimately result in widespread degeneration.

Incorporation of machine learning and deep neural network approaches into a remote sensing-integrated crop model for the simulation of rice growth.

Machine learning (ML) and deep neural network (DNN) techniques are promising tools. These can advance mathematical crop modelling methodologies that can integrate these schemes into a process-based crop model capable of reproducing or simulating crop growth. In this study, an innovative hybrid approach for estimating the leaf area index (LAI) of paddy rice using climate data was developed using ML and DNN regression methodologies. First, we investigated suitable ML regressors to explore the LAI estimation of rice based on the relationship between the LAI and three climate factors in two administrative rice-growing regions of South Korea. We found that of the 10 ML regressors explored, the random forest regressor was the most effective LAI estimator, and it even outperformed the DNN regressor, with model efficiencies of 0.88 in Cheorwon and 0.82 in Paju. In addition, we demonstrated that it would be feasible to simulate the LAI using climate factors based on the integration of the ML and DNN regressors in a process-based crop model. Therefore, we assume that the advancements presented in this study can enhance crop growth and productivity monitoring practices by incorporating a crop model with ML and DNN plans.

Rates and Patterns of Clonal Oncogenic Mutations in the Normal Human Brain.

Although oncogenic mutations have been found in nondiseased, proliferative nonneural tissues, their prevalence in the human brain is unknown. Targeted sequencing of genes implicated in brain tumors in 418 samples derived from 110 individuals of varying ages, without tumor diagnoses, detected oncogenic somatic single-nucleotide variants (sSNV) in 5.4% of the brains, including IDH1 R132H. These mutations were largely present in subcortical white matter and enriched in glial cells and, surprisingly, were less common in older individuals. A depletion of high-allele frequency sSNVs representing macroscopic clones with age was replicated by analysis of bulk RNA sequencing data from 1,816 nondiseased brain samples ranging from fetal to old age. We also describe large clonal copy number variants and that sSNVs show mutational signatures resembling those found in gliomas, suggesting that mutational processes of the normal brain drive early glial oncogenesis. This study helps understand the origin and early evolution of brain tumors. SIGNIFICANCE: In the nondiseased brain, clonal oncogenic mutations are enriched in white matter and are less common in older individuals. We revealed early steps in acquiring oncogenic variants, which are essential to understanding brain tumor origins and building new mutational baselines for diagnostics.This article is highlighted in the In This Issue feature, p. 1.

Simulation of Wheat Productivity Using a Model Integrated With Proximal and Remotely Controlled Aerial Sensing Information.

A crop model incorporating proximal sensing images from a remote-controlled aerial system (RAS) can serve as an enhanced alternative for monitoring field-based geospatial crop productivity. This study aimed to investigate wheat productivity for different cultivars and various nitrogen application regimes and determine the best management practice scenario. We simulated spatiotemporal wheat growth and yield by integrating RAS-based sensing images with a crop-modeling system to achieve the study objective. We conducted field experiments and proximal sensing campaigns to acquire the ground truth data and RAS images of wheat growth conditions and yields. These experiments were performed at Gyeongsang National University (GNU), Jinju, South Gyeongsang province, Republic of Korea (ROK), in 2018 and 2019 and at Chonnam National University (CNU), Gwangju, ROK, in 2018. During the calibration at GNU in 2018, the wheat yields simulated by the modeling system were in agreement with the corresponding measured yields without significant differences (p = 0.27-0.91), according to two-sample t-tests. Furthermore, the yields simulated via this approach were in agreement with the measured yields at CNU in 2018 and at GNU in 2019 without significant differences (p = 0.28-0.86), as evidenced by two-sample t-tests; this proved the validity of the proposed modeling system. This system, when integrated with remotely sensed images, could also accurately reproduce the geospatial variations in wheat yield and growth variables. Given the results of this study, we believe that the proposed crop-modeling approach is applicable for the practical monitoring of wheat growth and productivity at the field level.

Whole-genome analysis reveals the contribution of non-coding de novo transposon insertions to autism spectrum disorder.

BACKGROUND: Retrotransposons have been implicated as causes of Mendelian disease, but their role in autism spectrum disorder (ASD) has not been systematically defined, because they are only called with adequate sensitivity from whole genome sequencing (WGS) data and a large enough cohort for this analysis has only recently become available. RESULTS: We analyzed WGS data from a cohort of 2288 ASD families from the Simons Simplex Collection by establishing a scalable computational pipeline for retrotransposon insertion detection. We report 86,154 polymorphic retrotransposon insertions-including > 60% not previously reported-and 158 de novo retrotransposition events. The overall burden of de novo events was similar between ASD individuals and unaffected siblings, with 1 de novo insertion per 29, 117, and 206 births for Alu, L1, and SVA respectively, and 1 de novo insertion per 21 births total. However, ASD cases showed more de novo L1 insertions than expected in ASD genes. Additionally, we observed exonic insertions in loss-of-function intolerant genes, including a likely pathogenic exonic insertion in CSDE1, only in ASD individuals. CONCLUSIONS: These findings suggest a modest, but important, impact of intronic and exonic retrotransposon insertions in ASD, show the importance of WGS for their analysis, and highlight the utility of specific bioinformatic tools for high-throughput detection of retrotransposon insertions.

Rewiring of human neurodevelopmental gene regulatory programs by human accelerated regions.

Human accelerated regions (HARs) are the fastest-evolving regions of the human genome, and many are hypothesized to function as regulatory elements that drive human-specific gene regulatory programs. We interrogate the in vitro enhancer activity and in vivo epigenetic landscape of more than 3,100 HARs during human neurodevelopment, demonstrating that many HARs appear to act as neurodevelopmental enhancers and that sequence divergence at HARs has largely augmented their neuronal enhancer activity. Furthermore, we demonstrate PPP1R17 to be a putative HAR-regulated gene that has undergone remarkable rewiring of its cell type and developmental expression patterns between non-primates and primates and between non-human primates and humans. Finally, we show that PPP1R17 slows neural progenitor cell cycle progression, paralleling the cell cycle length increase seen predominantly in primate and especially human neurodevelopment. Our findings establish HARs as key components in rewiring human-specific neurodevelopmental gene regulatory programs and provide an integrated resource to study enhancer activity of specific HARs.

Empirical Comparison and Analysis of Web-Based DNA N 4-Methylcytosine Site Prediction Tools.

DNA N 4-methylcytosine (4mC) is a crucial epigenetic modification involved in various biological processes. Accurate genome-wide identification of these sites is critical for improving our understanding of their biological functions and mechanisms. As experimental methods for 4mC identification are tedious, expensive, and labor-intensive, several machine learning-based approaches have been developed for genome-wide detection of such sites in multiple species. However, the predictions projected by these tools are difficult to quantify and compare. To date, no systematic performance comparison of 4mC tools has been reported. The aim of this study was to compare and critically evaluate 12 publicly available 4mC site prediction tools according to species specificity, based on a huge independent validation dataset. The tools 4mCCNN (Escherichia coli), DNA4mC-LIP (Arabidopsis thaliana), iDNA-MS (Fragaria vesca), DNA4mC-LIP and 4mCCNN (Drosophila melanogaster), and four tools for Caenorhabditis elegans achieved excellent overall performance compared with their counterparts. However, none of the existing methods was suitable for Geoalkalibacter subterraneus, Geobacter pickeringii, and Mus musculus, thereby limiting their practical applicability. Model transferability to five species and non-transferability to three species are also discussed. The presented evaluation will assist researchers in selecting appropriate prediction tools that best suit their purpose and provide useful guidelines for the development of improved 4mC predictors in the future.

Sodium Channel SCN3A (NaV1.3) Regulation of Human Cerebral Cortical Folding and Oral Motor Development.

Channelopathies are disorders caused by abnormal ion channel function in differentiated excitable tissues. We discovered a unique neurodevelopmental channelopathy resulting from pathogenic variants in SCN3A, a gene encoding the voltage-gated sodium channel NaV1.3. Pathogenic NaV1.3 channels showed altered biophysical properties including increased persistent current. Remarkably, affected individuals showed disrupted folding (polymicrogyria) of the perisylvian cortex of the brain but did not typically exhibit epilepsy; they presented with prominent speech and oral motor dysfunction, implicating SCN3A in prenatal development of human cortical language areas. The development of this disorder parallels SCN3A expression, which we observed to be highest early in fetal cortical development in progenitor cells of the outer subventricular zone and cortical plate neurons and decreased postnatally, when SCN1A (NaV1.1) expression increased. Disrupted cerebral cortical folding and neuronal migration were recapitulated in ferrets expressing the mutant channel, underscoring the unexpected role of SCN3A in progenitor cells and migrating neurons.

Cell-type Dependent Alzheimer's Disease Phenotypes: Probing the Biology of Selective Neuronal Vulnerability.

Alzheimer's disease (AD) induces memory and cognitive impairment in the absence of motor and sensory deficits during its early and middle course. A major unresolved question is the basis for this selective neuronal vulnerability. Aß, which plays a central role in AD pathogenesis, is generated throughout the brain, yet some regions outside of the limbic and cerebral cortices are relatively spared from Aß plaque deposition and synapse loss. Here, we examine neurons derived from iPSCs of patients harboring an amyloid precursor protein mutation to quantify AD-relevant phenotypes following directed differentiation to rostral fates of the brain (vulnerable) and caudal fates (relatively spared) in AD. We find that both the generation of Aß and the responsiveness of TAU to Aß are affected by neuronal cell type, with rostral neurons being more sensitive than caudal neurons. Thus, cell-autonomous factors may in part dictate the pattern of selective regional vulnerability in human neurons in AD.

Immunoglobulin Fc-fused, neuropilin-1-specific peptide shows efficient tumor tissue penetration and inhibits tumor growth via anti-angiogenesis.

Neuropilin-1 (NRP1) receptor, involved in vascular endothelial growth factor (VEGF)-mediated vascular permeability and tumor angiogenesis, is targeted by peptides that bind to its VEGF-binding site. However, these peptides also cross-react with the structurally related receptor, NRP2. Here, we describe an immunoglobulin Fc-fused peptide, Fc-TPP11, which specifically binds to the VEGF-binding site of NRP1 with approximately 2nM affinity, but negligibly to that of NRP2. Fc-TPP11 triggered NRP1-dependent signaling, enhanced vascular permeability via vascular endothelial (VE)-cadherin downregulation, and increased paracellular permeability via E-cadherin downregulation in tumor tissues. Fc-TPP11 also significantly enhanced the tumor penetration of co-injected anti-cancer drug, doxorubicin, leading to the improved in vivo anti-tumor efficacy. Fc-TPP11 was easily adapted to the full-length anti-epidermal growth factor receptor (EGFR) monoclonal antibody (mAb) cetuximab (Erbitux), cetuximab-TPP11, exhibiting more than 2-fold improved tumor penetration than the parent cetuximab. Fc-TPP11 exhibited a similar whole-body half-life to that of intact Fc in tumor bearing mice. In addition to the tumor-penetrating activity, Fc-TPP11 suppressed VEGF-dependent angiogenesis by blocking VEGF binding to NRP1, thereby inhibiting tumor growth without promoting metastasis in the mouse model. Our results show that NRP1-specific, high-affinity binding of Fc-TPP11, is useful to validate NRP1 signaling, independent of NRP2. Thus, Fc-TPP11 can be used as a tumor penetration-promoting agent with anti-angiogenic activity or directly adapted to mAb-TPP11 format for more potent anti-cancer antibody therapy.

Enhancement of the tumor penetration of monoclonal antibody by fusion of a neuropilin-targeting peptide improves the antitumor efficacy.

The limited localization and penetration of monoclonal antibodies (mAb) into solid tumors restricts their antitumor efficacy. Here, we describe a solid tumor-targeting antibody with enhanced tumor penetration activity. We designed a 22-residue peptide (A22p), which was extracted from the C-terminal basic region of semaphorin 3A (Sema3A) but modified to have higher affinity with neuropilin receptors (NRP), and genetically fused it to the C-terminus of Fc of human immunoglobulin G1 via a 15-residue (G4S)3 linker, generating Fc-A22p, for the bivalent binding to NRPs. In contrast to Fc or the monovalent A22p peptide alone, Fc-A22p homed to tumor vessels and induced vascular permeability through VE-cadherin downregulation and penetrated tumor tissues by interacting with NRPs in mice bearing human tumor xenografts. We extended the Fc-A22p platform by generating mAb-A22p antibodies of two clinically approved solid tumor-targeting mAbs, the anti-EGF receptor mAb cetuximab (erbitux), and the anti-Her2 mAb trastuzumab (herceptin). The mAb-A22p antibodies retained the intrinsic antigen binding, natural Fc-like biophysical properties, and productivity in mammalian cell cultures, comparable with those of the parent mAbs. In mouse xenograft tumor models, the mAb-A22p antibodies more efficiently homed to tumor vessels and spread into the extravascular tumor parenchyma, which significantly enhanced antitumor efficacy compared with the parent mAbs. Our results suggest that mAb-A22p is a superior format for solid tumor-targeting antibodies due to its enhanced tumor tissue penetration and greater antitumor efficacy compared with conventional mAbs.

Cellular internalization mechanism and intracellular trafficking of filamentous M13 phages displaying a cell-penetrating transbody and TAT peptide.

Cellular internalization of bacteriophage by surface-displayed cell penetrating peptides has been reported, though the underlying mechanism remains elusive. Here we describe in detail the internalization mechanism and intracellular trafficking and stability of filamentous M13 phages, the cellular entry of which is mediated by surface-displayed cell-penetrating light chain variable domain 3D8 VL transbody (3D8 VL-M13) or TAT peptide (TAT-M13). Recombinant 3D8 VL-M13 and TAT-M13 phages were efficiently internalized into living mammalian cells via physiologically relevant, energy-dependent endocytosis and were recovered from the cells in their infective form with the yield of 3D8 VL-M13 being higher (0.005 ≈ 0.01%) than that of TAT-M13 (0.001 ≈ 0.005%). Biochemical and genetic studies revealed that 3D8 VL-M13 was internalized principally by caveolae-mediated endocytosis via interaction with heparan sulfate proteoglycans as cell surface receptors, whereas TAT-M13 was internalized by clathrin- and caveolae-mediated endocytosis utilizing chondroitin sulfate proteoglycans as cell surface receptors, suggesting that phage internalization occurs by physiological endocytotic mechanism through specific cell surface receptors rather than non-specific transcytotic pathways. Internalized 3D8 VL-M13 phages routed to the cytosol and remained stable for more than 18 h without further trafficking to other subcellular compartments, whereas TAT-M13 phages routed to several subcellular compartments before being degraded in lysosomes even after 2 h of internalization. Our results suggest that the internalizing mechanism and intracellular trafficking of filamentous M13 bacteriophages largely follow the attributes of the displayed cell-penetrating moiety. Efficient internalization and cytosolic localization of 3D8 VL transbody-displayed phages will provide a useful tool for intracellular delivery of polar macromolecules such as proteins, peptides, and siRNAs.