Coastal current convergence structures in the Bay of Biscay from optimized high-frequency radar and satellite data.

The southeastern Bay of Biscay has been described as a "dead end" for floating marine litter, often accumulating along small-scale linear streaks. Coastal Current Convergence Structures (CCS), often associated with vertical motions at river plume edges, estuarine fronts, or other physical processes, can be at the origin of the accumulation. Understanding the formation of CCS and their role in the transport of marine litter is essential to better quantify and to help mitigate marine litter pollution. The Lagrangian framework, used to estimate the absolute dispersion, and the finite-size Lyapunov exponents (FSLE), have proved very effective for identifying CCS in the current velocity field. However, the quality of CCS identification depends strongly on the Eulerian fields. Two surface current velocity data sets were used in the analysis: the remotely sensed velocities from the EuskOOS High-Frequency Radar (HFR) network and velocities from three-dimensional model outputs. They were complemented by drifting buoy velocity measurements. An optimization method, involving the fusion of drifting buoys and HFR velocities is proposed to better reconstruct the fine-scale structure of the current velocity field. Merging these two sources of velocity data reduced the mean Lagrangian error and the Root Mean Square Error (RMSE) by 50 % and 30 % respectively, significantly improving velocity reconstruction. FSLE ridgelines obtained from the Lagrangian analysis of optimized velocities were compared with remotely sensed concentrations of Chlorophyll-a. It was shown that ridgelines control the spatial distribution of phytoplankton. They fundamentally represent the CCS which can potentially affect marine litter aggregation. Analysis of the absolute dispersion revealed large stirring in the alongshore direction which was also confirmed by spatial distribution of FSLE ridgelines. The alignment between FSLE ridgelines and patterns of high Chlorophyll-a concentration was observed, often determining the limits of river plume expansion in the study area.

Multi-Agent System Based Cooperative Control for Speed Convergence of Virtually Coupled Train Formation.

This paper investigates the problem of spacing control between adjacent trains in train formation and proposes a distributed train-formation speed-convergence cooperative-control algorithm based on barrier Lyapunov function. Considering practical limitations such as communication distance and bandwidth constraints during operation, not all trains can directly communicate with the leader and obtain the expected trajectory it sends, making it difficult to maintain formation consistency as per the predetermined ideal state. Furthermore, to address the challenge of unknown external disturbances encountered by trains during operation, this paper designs a distributed observer deployed on each train in the formation. This observer can estimate and dynamically compensate for unknown reference trajectories and disturbances solely based on the states of adjacent trains. Additionally, to ensure that the spacing between adjacent trains remains within a predefined range, a safety hard constraint, this paper encodes the spacing hard constraint using barrier Lyapunov function. By integrating nonlinear adaptive control theory to handle model parameter uncertainties, a barrier Lyapunov function-based adaptive control method is proposed, which enables all trains to track the reference trajectory while ensuring that the spacing between them remains within the preset interval, therefore guaranteeing the asymptotic stability of the closed-loop system. Finally, a practical example using data from the Guangzhou Metro Line 22, specifically the route from Shiguang Road Station to Chentougang Station over three stations and two sections, is utilized to validate the effectiveness and robustness of the proposed algorithm.

The homogenized dynamical model of a thermoelastic composite stitched with reinforcing filaments.

The dynamical problem of linear thermoelasticity for a body with incorporated thin rectilinear inclusions is studied. It is assumed that the inclusions (i.e. filaments and threads) are parallel to each other and the problem contains a small parameter [Formula: see text], which characterizes the distance between two neighbouring inclusions. Using the two-scale convergence approach, we find the limiting problem as [Formula: see text]. As a result, we get a well-posed homogenized model of an anisotropic inhomogeneous body with effective characteristics inheriting thermomechanical properties of inclusions.This article is part of the theme issue 'Non-smooth variational problems with applications in mechanics'.

Prescribed-time command filtered control for a class uncertain nonlinear systems.

This article delves into the intricate challenge of implementing prescribed-time command filtered control in the context of uncertain nonlinear systems. Firstly, a prescribed-time function is defined to lay the groundwork for subsequent controller design. Subsequently, a novel prescribed-time command Filtered controller is proposed for high-order nonlinear systems featuring unknown parameters. This controller guarantees swift error convergence within a predefined time range, with the added capability of periodic error convergence to zero during subsequent controller operations. A pivotal innovation in this study lies in the controller's design, which remains unaffected by the system's initial conditions. This unique feature enables the prescribed time to be flexibly set within physical constraints, diverging markedly from conventional finite-time control theory. Theoretical analysis has conclusively shown that the controller achieves full-state tracking error convergence within the specified time frame. The efficacy of the research findings is substantiated through two simulation cases, underscoring a substantial contribution to the refinement and adaptability of nonlinear system control theory.

Research on the coupling coordination characteristics and convergence of digital finance and regional sustainable development: evidence from Chinese city clusters.

The study examines the digital finance (DF) and regional sustainable development (RSD) across 90 cities within six major city clusters in China over the period from 2011 to 2020. By constructing an evaluation index system for DF and RSD, we employed the entropy value method to assess their levels, and the coupling coordination degree (CCD) model to evaluate their interplay. Our analysis extended to temporal and spatial disparities, distribution dynamics, and the convergence of CCD through kernel density estimation, Markov chain analysis, σ -convergence, and ß -convergence techniques. The results indicate a consistent upward trend in CCD, yet it remains at a low level with pronounced regional disparities and temporal characteristics. The kernel density distribution's central tendency has shifted rightward progressively, albeit with a decelerating pace annually. The Markov transition probability matrix suggests a stable CCD across various levels, hinting at "club convergence". Furthermore, both σ -convergence and ß -convergence analyses reveal significant convergence trends in CCD, enhanced by economic growth factors. Using the Quadratic Assignment Procedure (QAP) method, we found that regional economic growth disparities significantly influence the CCD's regional variances.

Parallel evolution of integrated craniofacial traits in trophic specialist pupfishes.

Populations may adapt to similar environments via parallel or non-parallel genetic changes, but the frequency of these alternative mechanisms and underlying contributing factors are still poorly understood outside model systems. We used QTL mapping to investigate the genetic basis of highly divergent craniofacial traits between the scale-eater (Cyprinodon desquamator) and molluscivore (C. brontotheroides) pupfish adapting to two different hypersaline lake environments on San Salvador Island, Bahamas. We lab-reared F2 scale-eater x molluscivore intercrosses from two different lake populations, estimated linkage maps, scanned for significant QTL for 29 skeletal and craniofacial traits, female mate preference, and sex. We compared the location of QTL between lakes to quantify parallel and non-parallel genetic changes. We detected significant QTL for six craniofacial traits in at least one lake. However, nearly all shared QTL loci were associated with a different craniofacial trait within each lake. Therefore, our estimate of parallel evolution of craniofacial genetic architecture could range from one out of six identical trait QTL (low parallelism) to five out of six integrated trait QTL (high parallelism). We suggest that pleiotropy and trait integration can affect estimates of parallel evolution, particularly within rapid radiations. We also observed increased adaptive introgression in shared QTL regions, suggesting that gene flow contributed to parallel evolution. Overall, our results suggest that the same genomic regions may contribute to parallel adaptation across integrated suites of craniofacial traits, rather than specific traits, and highlight the need for a more expansive definition of parallel evolution.

Three cassava A20/AN1 family genes, Metip3 (5, and 7), can bestow on tolerance of plants to multiple abiotic stresses but show functional convergence and divergence.

A20/AN1 zinc-finger domain-containing genes are very promising candidates in improving plant tolerance to abiotic stresses, but considerably less is known about functions and mechanisms for many of them. In this study, Metip3 (5, and 7), cassava (Manihot esculenta) A20/AN1 genes carrying one A20 domain and one AN1 domain, were functionally characterized at different layers. Metip3 (5, and 7) proteins were all located in the nucleus. No interactions were found between these three proteins. Metip3 (5, and 7)-expressing Arabidopsis was more tolerant to multiple abiotic stresses by Na, Cd, Mn, Al, drought, high temperature, and low temperature. Metip3- and Metip5-expressing Arabidopsis was sensitive to Cu stress, while Metip7-expressing Arabidopsis was insensitive. The H2O2 production significantly decreased in all transgenic Arabidopsis, however, O2·- production significantly decreased in Metip3- and Metip5-expressing Arabidopsis but did not significantly changed in Metip7-expressing Arabidopsis under drought. Metip3 (5, and 7) expression-silenced cassava showed the decreased tolerance to drought and NaCl, presented significant decreases in superoxide dismutase and catalase activities and proline content, and displayed a significant increase in malondialdehyde content under drought. Taken together with transcriptome sequencing analysis, it is suggested that Metip5 gene can not only affect signal transduction related to plant hormone, mitogen activated protein kinases, and starch and sucrose metabolism, DRE-binding transcription factors, and antioxidants, conferring the drought tolerance, but also might deliver the signals from DREB2A INTERACTING PROTEIN1, E3 ubiquitin-protein ligases to proteasome, leading to the drought intolerance. The results are informative not only for further study on evolution of A20/AN1 genes but also for development of climate resilient crops.

On convergence properties of the brain-state-in-a-convex-domain.

Convergence in the presence of multiple equilibrium points is one of the most fundamental dynamical properties of a neural network (NN). Goal of the paper is to investigate convergence for the classic Brain-State-in-a-Box (BSB) NN model and some of its relevant generalizations named Brain-State-in-a-Convex-Body (BSCB). In particular, BSCB is a class of discrete-time NNs obtained by projecting a linear system onto a convex body of Rn. The main result in the paper is that the BSCB is convergent when the matrix of the linear system is symmetric and positive semidefinite or, otherwise, it is symmetric and the step size does not exceed a given bound depending only on the minimum eigenvalue of the matrix. This result generalizes previous results in the literature for BSB and BSCB and it gives a solid foundation for the use of BSCB as a content addressable memory (CAM). The result is proved via Lyapunov method and LaSalle's Invariance Principle for discrete-time systems and by using some fundamental inequalities enjoyed by the projection operator onto convex sets as Bourbaki-Cheney-Goldstein inequality.

A static precise single-point positioning method based on carrier phase zero-baseline self-differencing.

Satellite navigation positioning has become an indispensable component of everyday life, where precise pinpointing and rapid convergence are crucial in delivering timely and accurate location information. However, due to the damping of integer ambiguities and system residual errors, the rapid convergence of Precise Point Positioning (PPP) implementation is a significant challenge. To address this, this paper proposes a novel Carrier Phase Zero-Baseline Self-Differencing Precise Point Positioning (CZS-PPP) technique and its ionosphere-free fusion model. By employing the proposed CZS-PPP approach in separate scenarios involving BDS-3, GPS, and dual-system settings, we systematically validate the efficacy of the method. The experimental results indicate that the convergence time of the method is less than 4 min in a single-system scenario. Furthermore, in a dual-system scenario, the method can achieve rapid convergence in less than 3 min. The CZS-PPP technique presented demonstrates the elimination of integer ambiguities and the effective suppression of system residuals, in comparison to the conventional method. The proposed approach has demonstrated remarkable performance across different systems, offering a promising new pathway for achieving PPP fast convergence in BDS/GNSS.

Improving Thermoelectric Performance of AgSbTe2 through Suppression of Ag2Te and Band Convergence via Mg and Ti Codoping.

In this study, the impact of codoping Mg and Ti on the thermoelectric performance of AgSbTe2 materials was investigated. Through a two-step synthesis process involving slow cooling and spark plasma sintering, AgSb0.98-xMg0.02TixTe2 samples were prepared. The introduction of Mg and Ti dopants effectively suppressed the formation of the undesirable Ag2Te phase. Density functional theory (DFT) calculations confirmed that Ti doping facilitated the band convergence, leading to a reduction in the effective mass of the carriers. This optimization enhanced carrier mobility and, consequently, electrical conductivity. Additionally, the codoping strategy resulted in the reinforcement of point defects, which contributed to a decrease in lattice thermal conductivity. The AgSb0.98-xMg0.02TixTe2 sample achieved a maximum figure of merit (ZT) value of 1.45 at 523 K, representing an 87% improvement over the undoped AgSbTe2 sample. The average ZT value over the temperature range of 323-573 K was 1.09, marking a significant enhancement in thermoelectric performance. This research demonstrates the potential of Mg and Ti codoping as a strategy to improve the thermoelectric properties of AgSbTe2-based materials.

Exploring the Influence of Initial Estimates on Iterative Maximum Likelihood Expectation-maximization in Tomographic Reconstruction.

Purpose: To explore the influence of initial guess or estimate (uniform as "ones" and "zeros" vs. filtered back projection [FBP] image) as an input image for maximum likelihood expectation-maximization (MLEM) tomographic reconstruction algorithm and provide the curves of error or convergence for each of these three initial estimates. Methods: Two phantoms, created as digital images, were utilized: one was a simple noiseless object and the other was a more complicated, noise-degraded object of the section of lower thorax in a matrix of 256 × 256 pixels. Both underwent radon transform or forward projection process and the corresponding sinograms were generated. For filtering during tomographic image reconstruction, ramp and Butterworth filters, as high-pass and low-pass ones, were applied to images. The second phantom (lower thorax) was radon-transformed and the resulting sinogram was degraded by noise. As initial guess or estimate images, in addition to FBP tomographic image, two uniform images, one with all pixels having a value of 1 ("ones") and the other with all having zero ("zeros"), were created. The three initial estimates (FBP, ones, and zeros) were reconstructed with iterative MLEM tomographic reconstruction (with 1, 2, 4, 8, 16, 32, and 64 iterations). The difference between the object and the updated slice was calculated at the end of each iteration (as error matrix), and the mean squared error (MSE) was computed and plotted separately or in conjunction with the MSE curves of other initial estimates. All computations were implemented in MATLAB software. Results: The results of ones and zeros seemed strikingly similar. The curves of uniform ones and uniform zeros were so close to each other that overlap near-perfectly. However, in the FBP slice as an initial estimate, the resulting tomographic slice was similar with a much higher extent to the object even after 1 or 2 iterations. The pattern of convergence for all three curves was roughly similar. The normalized MSE decreased sharply up to 5 iterations and then, after 10 iterations, the curves reached a plateau until 32 iterations. For the phantom of the lower thorax section with its noise-degraded sinogram, similar to the pattern observed for simple disk-shaped phantom, the curves (normalized MSE) fell sharply up to 10 iterations and then rapidly converged thereafter until 64 iterations. Conclusion: Similar results are observed when choosing different initial guesses or estimates (uniform vs. FBP) as the starting point, based on the error calculation using MSE. The algorithm converges almost similarly for all initial estimates. Therefore, selecting a uniform initial guess image can be an appropriate choice and may be preferred over an FBP image. Reducing the processing time can be a valid reason for this choice.

Comparing clinical measures of near point of convergence and accommodation from the lateral canthus and browline in a paediatric and adolescent population.

PURPOSE: Clinicians measure the near point of convergence (NPC) and the amplitude of accommodation (AA) from the spectacle plane, the bridge of the nose or the lateral canthus when assessing visual function. These values are compared to standard clinical criteria to diagnose vergence and accommodation deficits, despite varying reference points. This prospective study explored measuring relative to the spectacle plane and from the lateral canthus for NPC and monocular AA, and the resulting clinical implications of diagnosing visual deficits. METHODS: Participants were seen by a single clinician for an eye examination. NPC was measured from the forehead and the lateral canthus of the right eye. Monocular AA was measured from the brow and the lateral canthus. Differences between measurements were analysed using non-parametric statistical tests including Wilcoxon Signed Rank, as well as linear regression and a linear mixed effects model to adjust for inter-eye correlation and repeated measures. Chi-square tests were used to assess differences in rates of abnormal findings. RESULTS: Data were collected from 70 participants (53% female, median age 13 [11-15] years). On average, measuring NPC from the lateral canthus yielded a value 1.8 cm higher than measuring from the forehead. Measuring AA from the lateral canthus resulted in an average difference of 1.5 cm compared to measuring from the brow. A total of 39% and 76% of subjects failed NPC compared to clinical norms when measured from the forehead or the lateral canthus, respectively, while 7% and 40% failed AA when measured from the brow or the lateral canthus, respectively. CONCLUSION: With the variable anatomy of the eye, it is imperative to account for the measurement point when assessing visual function. Measuring from the lateral canthus greatly increased the failure rates for NPC and AA compared with measuring from the forehead and brow, respectively.

Relationships between fusional convergence, suppression depth, and exotropia control in intermittent exotropia.

Purpose: To assess the correlation between the contribution rates of fusional convergence from the dominant and non-dominant eye and suppression depth and exotropia control. Study design: Cross-sectional prospective study. Methods: The fusional convergence of 25 participants with intermittent exotropia (mean age 10.8 ± 3.4; range 6-18 years) was measured with an eye-tracking system. The contribution rate was defined based on the amplitude of fusional convergence during refusion relative to the exo-deviation angle. The suppression depth was assessed, and exotropia control was evaluated using the intermittent exotropia Office Control Score. We analyzed the correlations between the contribution rate from the dominant and non-dominant eyes and the suppression depth or control score. Results: There was a negative correlation between the dominant eye's contribution rate and the suppression depth in both eyes (r = -0.85, 95% confidence interval [CI]: -0.97 to - 0.20 in the fixated dominant eye and r = -0.91, 95%CI: -0.95 to - 0.40 in the fixated non-dominant eye). There was a negative correlation between the dominant eye's contribution rate and the control score at a 4-meter distance (r = -0.53, 95%CI: -0.76 to - 0.17). Conclusion: Suppression in intermittent exotropia patients could affect the fusional convergence in the dominant eye.

Genetic relationships between and within some Malawian cichlid genera.

Genetic relationships were examined for a total of 90 individuals of 90 species or species var. from 13 genera of Malawian cichlids based on the sequences of an amplified 991-bp fragment of the mtDNA control region (mtDNA-CR). In the network analysis, no exclusive clades were made by all the members of any genera in this study. However, congeneric clades were observed by genera Buccochromis, Copadichromis, Protomelas, and Sciaenochromis, whereas no congeneric clades were observed by genera Mylochromis, Nimbochromis, and Otopharynx. In non-mbuna, an Aulonocara-Lethrinops group was divided into two groups, and the mean genetic distance of the larger group was much lower from mbuna than from other non-mbuna. Overall mean genetic distance within a genus was generally low in mbuna, whereas it was relatively high in non-mbuna. In the genetic tree of each genus, two or more large clades were observed, and some clades, such as those of Aulonocara hansbaenschi and Aulonocara nyassae in genus Aulonocara, Lethrinops micrentodon and Lethrinops sp. "gold harbor" in Lethrinops, and Otopharynx ovatus and Otopharynx brooksi in Otopharynx, were very deeply differentiated. Besides, a mbuna species, Pseudotropheus crabro, was extremely deeply differentiated from other members of this genus. These results suggest a widespread morphological convergence across the taxa in parallel with deep genetic differentiation in the long evolutionary story and some possibility of generation of the species of Aulonocara-Lethrinops group by hybridization of small non-mbuna and mbuna species. Furthermore, taxonomical reexamination is necessary based on a strong support by genetic connection.

Screening of Klebsiella pneumoniae subsp. pneumoniae Strains with Multi-Drug Resistance and Virulence Profiles Isolated from an Italian Hospital between 2020 and 2023.

Klebsiella pneumoniae strains that are resistant to multiple drugs (KPMDRs), which are often acquired in hospital settings and lead to healthcare-associated infections, pose a serious public health threat, as does hypervirulent K. pneumoniae (hvKp), which can also cause serious infections in otherwise healthy individuals. The widespread and often unnecessary use of antibiotics seen during the recent COVID-19 pandemic has exacerbated the challenges posed by antibiotic resistance in clinical settings. There is growing concern that hypervirulent (hvKp) strains may acquire genes that confer antimicrobial resistance, thus combining an MDR profile with their increased ability to spread to multiple body sites, causing difficult-to-treat infections. This study aimed to compare resistance and virulence profiles in KPC-3-producing K. pneumoniae isolates collected over four years (2020-2023). A genome-based surveillance of all MDR CRE-K. pneumoniae was used to identify genetic differences and to characterize the virulence and resistance profiles. Our results provide a picture of the evolution of resistance and virulence genes and contribute to avoiding the possible spread of isolates with characteristics of multi-drug resistance and increased virulence, which are thought to be one of the main global challenges to public health, within our hospital.

The Utilization of Bacillus subtilis to Design Environmentally Friendly Living Paints with Anti-Mold Properties.

The anti-fungal properties of the probiotic bacterium Bacillus subtilis have been studied extensively in agriculture and ecology, but their applications in the built environment remain to be determined. Our work aims to utilize this biological component to introduce new diverse anti-mold properties into paint. "Mold" refers to the ubiquitous fungal species that generate visible multicellular filaments commonly found in household dust. The development of mold leads to severe health problems for occupants, including allergic response, hypersensitivity pneumonitis, and asthma, which have significant economic and clinical outcomes. We here demonstrate the robust effect of a commercial paint enhanced with Bacillus subtilis cells against the common mold agent, Aspergillus niger, and identify three biosynthetic clusters essential for this effect. Our results lay the foundation for bio-convergence and synthetic biology approaches to introduce renewable and environmentally friendly bio-anti-fungal agents into the built environment.

Iterative Chebyshev approximation method for optimal control problems.

We present a novel numerical approach for solving nonlinear constrained optimal control problems (NCOCPs). Instead of directly solving the NCOCPs, we start by linearizing the constraints and dynamic system, which results in a sequence of sub-problems. For each sub-problem, we use finite number of Chebyshev polynomials to estimate the control and state vectors. To eliminate the errors at non-collocation points caused by conventional collocation methods, we additionally estimate the coefficient functions involved in the linear constraints and dynamic system by Chebyshev polynomials. By leveraging the characteristics of Chebyshev polynomials, the approximate sub-problem is changed into an equivalent nonlinear optimization problem with linear equality constraints. Consequently, any feasible point of the approximate sub-problem will satisfy the constraints and dynamic system throughout the entire time scale. To validate the efficacy of the new method, we solve three examples and assess the accuracy of the method through the computation of its approximation error. Numerical results obtained show that our approach achieves lower approximation error when compared to the Chebyshev pseudo-spectral method. The proposed method is particularly suitable for scenarios that require high-precision approximation, such as aerospace and precision instrument production.

Convergence of inputs from the basal ganglia with layer 5 of motor cortex and cerebellum in mouse motor thalamus.

A key to motor control is the motor thalamus, where several inputs converge. One excitatory input originates from layer 5 of primary motor cortex (M1L5), while another arises from the deep cerebellar nuclei (Cb). M1L5 terminals distribute throughout the motor thalamus and overlap with GABAergic inputs from the basal ganglia output nuclei, the internal segment of the globus pallidus (GPi), and substantia nigra pars reticulata (SNr). In contrast, it is thought that Cb and basal ganglia inputs are segregated. Therefore, we hypothesized that one potential function of the GABAergic inputs from basal ganglia is to selectively inhibit, or gate, excitatory signals from M1L5 in the motor thalamus. Here, we tested this possibility and determined the circuit organization of mouse (both sexes) motor thalamus using an optogenetic strategy in acute slices. First, we demonstrated the presence of a feedforward transthalamic pathway from M1L5 through motor thalamus. Importantly, we discovered that GABAergic inputs from the GPi and SNr converge onto single motor thalamic cells with excitatory synapses from M1L5. Separately, we also demonstrate that, perhaps unexpectedly, GABAergic GPi and SNr inputs converge with those from the Cb. We interpret these results to indicate that a role of the basal ganglia is to gate the thalamic transmission of M1L5 and Cb information to cortex.

Genetic basis of phenotypic convergence in pig terminal sires using pathway-based selection signature detection methods.

The primary purpose of genetic improvement in lean pig breeds is to enhance production performance. Owing to their similar breeding directions, Duroc and Pietrain pigs are ideal models for investigating the phenotypic convergence underlying artificial selection. However, most important economic traits are controlled by a polygenic basis, so traditional strategies for detecting selection signatures may not fully reveal the genetic basis of complex traits. The pathway-based gene network analysis method utilizes each pathway as a unit, overcoming the limitations of traditional strategies for detecting selection signatures by revealing the selection of complex biological processes. Here, we utilized 13 122 398 high-quality SNPs from whole-genome sequencing data of 48 Pietrain pigs, 156 Duroc pigs and 36 European wild boars to detect selective signatures. After calculating FST and iHS scores, we integrated the pathway information and utilized the r/bioconductor graphite and signet packages to construct gene networks, identify subnets and uncover candidate genes underlying selection. Using the traditional strategy, a total of 47 genomic regions exhibiting parallel selection were identified. The enriched genes, including INO80, FZR1, LEPR and FAF1, may be associated with reproduction, fat deposition and skeletal development. Using the pathway-based selection signatures detection method, we identified two significant biological pathways and eight potential candidate genes underlying parallel selection, such as VTN, FN1 and ITGAV. This study presents a novel strategy for investigating the genetic basis of complex traits and elucidating the phenotypic convergence underlying artificial selection, by integrating traditional selection signature methods with pathway-based gene network analysis.

Five autism-associated transcriptional regulators target shared loci proximal to brain-expressed genes.

Many autism spectrum disorder (ASD)-associated genes act as transcriptional regulators (TRs). Chromatin immunoprecipitation sequencing (ChIP-seq) was used to identify the regulatory targets of ARID1B, BCL11A, FOXP1, TBR1, and TCF7L2, ASD-associated TRs in the developing human and mouse cortex. These TRs shared substantial overlap in the binding sites, especially within open chromatin. The overlap within a promoter region, 1-2,000 bp upstream of the transcription start site, was highly predictive of brain-expressed genes. This signature was observed in 96 out of 102 ASD-associated genes. In vitro CRISPRi against ARID1B and TBR1 delineated downstream convergent biology in mouse cortical cultures. After 8 days, NeuN+ and CALB+ cells were decreased, GFAP+ cells were increased, and transcriptomic signatures correlated with the postmortem brain samples from individuals with ASD. We suggest that functional convergence across five ASD-associated TRs leads to shared neurodevelopmental outcomes of haploinsufficient disruption.