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High-altitude adaptation of Tibetans represents a remarkable case of natural selection during recent human evolution. Previous genome-wide scans found many non-coding variants under selection, suggesting a pressing need to understand the functional role of non-coding regulatory elements (REs). Here, we generate time courses of paired ATAC-seq and RNA-seq data on cultured HUVECs under hypoxic and normoxic conditions. We further develop a variant interpretation methodology (vPECA) to identify active selected REs (ASREs) and associated regulatory network. We discover three causal SNPs of EPAS1 , the key adaptive gene for Tibetans. These SNPs decrease the accessibility of ASREs with weakened binding strength of relevant TFs, and cooperatively down-regulate EPAS1 expression. We further construct the downstream network of EPAS1 , elucidating its roles in hypoxic response and angiogenesis. Collectively, we provide a systematic approach to interpret phenotype-associated noncoding variants in proper cell types and relevant dynamic conditions, to model their impact on gene regulation. Tibetan adaptation to the high-altitude environment represents a case of natural selection during recent human evolution. Here the authors investigated the chromatin and transcriptional landscape of umbilical endothelial cells from Tibetan and Han Chinese donors and provide genome-wide characterization of the hypoxia regulatory network associated high-altitude adaptation.

Advances in single-cell technology enable large-scale generation of omics data, promising for clarifying gene regulatory networks governing different cell type/states. Nonetheless, prevailing methods fail to account for universal and reusable regulatory modules in GRNs, which are fundamental underpinnings of cell type landscape. We introduce cRegulon to infer regulatory modules by modeling combinatorial regulation of transcription factors based on diverse GRNs from single-cell multi-omics data. Through benchmarking and applications using simulated datasets and real datasets, cRegulon outperforms existing approaches in identifying TF combinatorial modules as regulatory units and annotating cell types. cRegulon offers new insights and methodology into combinatorial regulation.

Standard genome-wide association studies (GWASs) rely on analyzing a single trait at a time. However, many human phenotypes are complex and composed by multiple correlated traits. Here we introduce C-GWAS, a method for combining GWAS summary statistics of multiple potentially correlated traits. Extensive computer simulations demonstrated increased statistical power of C-GWAS compared to the minimal p -values of multiple single-trait GWASs (MinGWAS) and the current state-of-the-art method for combining single-trait GWASs (MTAG). Applying C-GWAS to a meta-analysis dataset of 78 single trait facial GWASs from 10,115 Europeans identified 56 study-wide suggestively significant loci with multi-trait effects on facial morphology of which 17 are novel loci. Using data from additional 13,622 European and Asian samples, 46 (82%) loci, including 9 (53%) novel loci, were replicated at nominal significance with consistent allele effects. Functional analyses further strengthen the reliability of our C-GWAS findings. Our study introduces the C-GWAS method and makes it available as computationally efficient open-source R package for widespread future use. Our work also provides insights into the genetic architecture of human facial appearance. Combining multiple related traits can increase power in genetic association studies. Here, the authors develop a method to integrate GWAS statistics for multiple traits and apply it to find genetic loci affecting human facial variation.

Systems genetics holds the promise to decipher complex traits by interpreting their associated SNPs through gene regulatory networks derived from comprehensive multi-omics data of cell types, tissues, and organs. Here, we propose SpecVar to integrate paired chromatin accessibility and gene expression data into context-specific regulatory network atlas and regulatory categories, conduct heritability enrichment analysis with genome-wide association studies (GWAS) summary statistics, identify relevant tissues, and estimate relevance correlation to depict common genetic factors acting in the shared regulatory networks between traits. Our method improves power upon existing approaches by associating SNPs with context-specific regulatory elements to assess heritability enrichments and by explicitly prioritizing gene regulations underlying relevant tissues. Ablation studies, independent data validation, and comparison experiments with existing methods on GWAS of six phenotypes show that SpecVar can improve heritability enrichment, accurately detect relevant tissues, and reveal causal regulations. Furthermore, SpecVar correlates the relevance patterns for pairs of phenotypes and better reveals shared SNP-associated regulations of phenotypes than existing methods. Studying GWAS of 206 phenotypes in UK Biobank demonstrates that SpecVar leverages the context-specific regulatory network atlas to prioritize phenotypes’ relevant tissues and shared heritability for biological and therapeutic insights. SpecVar provides a powerful way to interpret SNPs via context-specific regulatory networks and is available at https://github.com/AMSSwanglab/SpecVar , copy archived at swh:1:rev:cf27438d3f8245c34c357ec5f077528e6befe829 .

There are technical requirements for the assembly of thousands of separate flange joints on the radar panel. The use of traditional manual assembly has problems such as high labor intensity, low assembly efficiency, and difficulty in uniform assembly quality. Therefore, in response to the above problems, combined with the requirements of high precision of joint assembly position and attitude, and intelligent management and control of the operation process, a set of joint component assembly system based on dual vision positioning, robot + ground rail + multi-axis module drive multi-gripper and electric batch accurate assembly is proposed. The system uses a dual-vision precise guidance control robot + ground rail as the main actuator, and an end effector composed of a multi-gripper assembly module and a lock. Using PLC as the main control center, equipped with robot, host computer, vision and other sub-systems, In this way, a large-scale, high-precision, and high-reliability joint assembly for military products is realized.

Epigenetic information regulates gene expression and development. However, our understanding of the evolution of epigenetic regulation on brain development in primates is limited. Here, we compared chromatin accessibility landscapes and transcriptomes during fetal prefrontal cortex (PFC) development between rhesus macaques and humans. A total of 304,761 divergent DNase I-hypersensitive sites (DHSs) are identified between rhesus macaques and humans, although many of these sites share conserved DNA sequences. Interestingly, most of the cis -elements linked to orthologous genes with dynamic expression are divergent DHSs. Orthologous genes expressed at earlier stages tend to have conserved cis -elements, whereas orthologous genes specifically expressed at later stages seldom have conserved cis -elements. These genes are enriched in synapse organization, learning and memory. Notably, DHSs in the PFC at early stages are linked to human educational attainment and cognitive performance. Collectively, the comparison of the chromatin epigenetic landscape between rhesus macaques and humans suggests a potential role for regulatory elements in the evolution of differences in cognitive ability between non-human primates and humans. The evolution of epigenetic regulation of brain development in primates is not well understood. Here, the authors perform a comparative study of epigenetic dynamics of early prefrontal cortex development between human and rhesus macaque, finding divergent regulatory elements that may be related to cognitive capacity.

As a vast number of 3D CAD models associated with NC process are generated each year, taking full advantage of them is an effective way to generate the NC process for query subparts with less time and lower cost. However, there has been little research on how to discover and utilize the valuable information imbedded in the NC process of multiple existing similar subparts. In this paper, a novel multi-source similar subparts-based NC process fusion and regrouping approach is proposed. Firstly, the multi-source similar subparts are described as multi-dimension vectors consisting of feature attributes and NC process. Secondly, the attribute similarities of query feature and similar features are calculated to establish the similarity matrix. Then, based on the multi-source similar features, the gray relational analysis is utilized to mine the association between feature attributes and NC process, and the relation matrix is constructed. Based on the multiplication of similarity matrix and relation matrix, the adaption matrix is calculated to represent the important degree of the NC process of similar features for query feature. Through the weighted sum of adaption values and adjustments, the NC process is obtained for the query subpart. Finally, based on the feature interactions in the query subpart, the NC process of the query subpart is regrouped to meet the requirements of NC machining.

Cranial Neural Crest Cells (CNCC) originate at the cephalic region from forebrain, midbrain and hindbrain, migrate into the developing craniofacial region, and subsequently differentiate into multiple cell types. The entire specification, delamination, migration, and differentiation process is highly regulated and abnormalities during this craniofacial development cause birth defects. To better understand the molecular networks underlying CNCC, we integrate paired gene expression & chromatin accessibility data and reconstruct the genome-wide human Regulatory network of CNCC (hReg-CNCC). Consensus optimization predicts high-quality regulations and reveals the architecture of upstream, core, and downstream transcription factors that are associated with functions of neural plate border, specification, and migration. hReg-CNCC allows us to annotate genetic variants of human facial GWAS and disease traits with associated cis-regulatory modules, transcription factors, and target genes. For example, we reveal the distal and combinatorial regulation of multiple SNPs to core TF ALX1 and associations to facial distances and cranial rare disease. In addition, hReg-CNCC connects the DNA sequence differences in evolution, such as ultra-conserved elements and human accelerated regions, with gene expression and phenotype. hReg-CNCC provides a valuable resource to interpret genetic variants as early as gastrulation during embryonic development. The network resources are available at https://github.com/AMSSwanglab/hReg-CNCC.Zhanying Feng et al. present hReg-CNCC, a high-quality gene regulatory network for human cranial neural crest cells (CNCCs) constructed by consensus optimization modeling. It may be useful in interpreting genetic variants involved in embryonic development by linking the cis-regulatory sequences in this network with GWAS SNPs, disease risk loci, and evolutionarily-conserved regions of the genome.

Tin-zinc solder alloys are considered to be appropriate for soldering of aluminum alloys at low-temperature in electronics and radiators applications. In this paper, the effects of different soldering parameters on the microstructure and interfacial reaction behaviors of 1070Al/Sn-9Zn/1070Al joints were investigated. The results show that the Al substrate was dissolved by the liquid solder, but Al-related intermetallic was not observed in the interface. Two kinds of Al-rich phases formed in the solder matrix. Large butterfly-shaped solid solution (Al)″ phases (about 10 μm) were formed in the liquid alloys, and compact-shaped precipitations (nano-size) were dissolved out from solders during solidification process. With increasing of the soldering time, Al″ phases were migrated upwards in the solders and the amount of this phase increased. In addition, with the increase of the soldering temperature, the dissolution rate of Al into the solder increased and the formation time of (Al)″ phases was reduced. Shear test results indicate when soldered at 250 °C, the shear strength increased from 48.6 MPa to a maximum 60.5 MPa and then decreased to a stable value (about 55 MPa) with increasing of the soldering time. Similar trends were also observed at 300 and 350 °C, while the soldering time needed to obtain maximum shear strength was shortened. The formation of these Al-rich phases improves the shear strength but deteriorates the ductility.

To compress and compact the crushed biomass material into a honeycomb shape and improve the combustion efficiency of biomass solidified fuel, a gear-rack biomass honeycomb coal forming machine was designed. This forming machine adopts a gear-rack meshing system, which can efficiently compress biomass materials such as sawdust, straw, and rice husks into standard honeycomb coal shapes, suitable for the production and processing of various biomass materials. The biomass solidification forming method proposed in this article has certain theoretical value and practical significance for promoting the promotion and application of biomass solidification forming equipment and fuels.