Genetic effects of sequence-conserved enhancer-like elements on human complex traits.

BACKGROUND: The vast majority of findings from human genome-wide association studies (GWAS) map to non-coding sequences, complicating their mechanistic interpretations and clinical translations. Non-coding sequences that are evolutionarily conserved and biochemically active could offer clues to the mechanisms underpinning GWAS discoveries. However, genetic effects of such sequences have not been systematically examined across a wide range of human tissues and traits, hampering progress to fully understand regulatory causes of human complex traits. RESULTS: Here we develop a simple yet effective strategy to identify functional elements exhibiting high levels of human-mouse sequence conservation and enhancer-like biochemical activity, which scales well to 313 epigenomic datasets across 106 human tissues and cell types. Combined with 468 GWAS of European (EUR) and East Asian (EAS) ancestries, these elements show tissue-specific enrichments of heritability and causal variants for many traits, which are significantly stronger than enrichments based on enhancers without sequence conservation. These elements also help prioritize candidate genes that are functionally relevant to body mass index (BMI) and schizophrenia but were not reported in previous GWAS with large sample sizes. CONCLUSIONS: Our findings provide a comprehensive assessment of how sequence-conserved enhancer-like elements affect complex traits in diverse tissues and demonstrate a generalizable strategy of integrating evolutionary and biochemical data to elucidate human disease genetics.

Design of an image-based BRDF measurement method using a catadioptric multispectral capture and a real-time Lambert calibration.

By utilizing a catadioptric system and a calibration Lambertian sample, a compact measurement method of bidirectional reflectance distribution function (BRDF) has been proposed for rapid and accurate measurement. With the help of an ellipsoidal dome mirror, a hyperboloid mirror, and a high-resolution camera, spatial reflectance distributions from reflected directions with a large field of view (FOV) can be obtained. The built-in Lambertian standard allows for real-time calibration to account for fluctuations in the illumination spectrum, effectively reducing the measurement drift and achieving a high accuracy. Moreover, a multispectral camera captures images at 8 spectral bands for accurate spectral color reconstruction from different directions. To verify the method, a prototype capable of fast, high-resolution measurements with a large FOV has been developed for characterizing the scattering properties of objects. It achieves a measured angular range up to 160°. Multispectral BRDF data for each sample can be obtained within 5 minutes with an angular resolution of less than 0.6°. Eight ceramic samples with different colors were selected for the verification of measurement accuracy, and their mean relative bias of BRDF measurement was found to be as low as 2.5%.

Adaptation under dichromatic illumination.

Over the years, many CATs (chromatic adaptation transforms) have been developed, such as CMCCAT97, CAT02 and CAT16, to predict the corresponding colors under different illuminants. These CATs were derived from uniform simple stimuli surrounded by a uniform background with a single illuminant. Although some mixed adaptation models have been proposed in literature to predict the adaptation under more than one illuminant, these models are typically limited to a certain scene and exclude the impact of spatial complexity. To investigate chromatic adaptation under more complex conditions, an achromatic matching experiment was conducted with (simultaneously) spatially dichromatic illumination for three illumination color pairs and various spatial configurations. Spatial configuration was found to have an impact on both the degree of adaptation and the equivalent illuminant chromaticity, which is the chromaticity of a single uniform adapting illumination that results in the same corresponding colors as for the dichromatic lighting condition. A preliminary CAT model is proposed that considers the spatial and colorimetric complexity of the illumination.

Attenuated IL-2 muteins leverage the TCR signal to enhance regulatory T cell homeostasis and response in vivo.

Interleukin-2 (IL-2), along with T-cell receptor (TCR) signaling, are required to control regulatory T cell (Treg) homeostasis and function in vivo. Due to the heightened sensitivity to IL-2, Tregs retain the ability to respond to low-dose or attenuated forms of IL-2, as currently being developed for clinical use to treat inflammatory diseases. While attenuated IL-2 increases Treg selectivity, the question remains as to whether a weakened IL-2 signal sufficiently enhances Treg suppressive function(s) toward disease modification. To understand this question, we characterized the in vivo activity and transcriptomic profiles of two different attenuated IL-2 muteins in comparison with wildtype (WT) IL-2. Our study showed that, in addition to favoring Tregs, the attenuated muteins induced disproportionately robust effects on Treg activation and conversion to effector Treg (eTreg) phenotype. Our data furthermore suggested that Tregs activated by attenuated IL-2 muteins showed reduced dependence on TCR signal, at least in part due to the enhanced ability of IL-2 muteins to amplify the TCR signal in vivo. These results point to a new paradigm wherein IL-2 influences Tregs' sensitivity to antigenic signal, and that the combination effect may be leveraged for therapeutic use of attenuated IL-2 muteins.

Mutations in human DNA methyltransferase DNMT1 induce specific genome-wide epigenomic and transcriptomic changes in neurodevelopment.

DNA methyltransferase type 1 (DNMT1) is a major enzyme involved in maintaining the methylation pattern after DNA replication. Mutations in DNMT1 have been associated with autosomal dominant cerebellar ataxia, deafness and narcolepsy (ADCA-DN). We used fibroblasts, induced pluripotent stem cells (iPSCs) and induced neurons (iNs) generated from patients with ADCA-DN and controls, to explore the epigenomic and transcriptomic effects of mutations in DNMT1. We show cell type-specific changes in gene expression and DNA methylation patterns. DNA methylation and gene expression changes were negatively correlated in iPSCs and iNs. In addition, we identified a group of genes associated with clinical phenotypes of ADCA-DN, including PDGFB and PRDM8 for cerebellar ataxia, psychosis and dementia and NR2F1 for deafness and optic atrophy. Furthermore, ZFP57, which is required to maintain gene imprinting through DNA methylation during early development, was hypomethylated in promoters and exhibited upregulated expression in patients with ADCA-DN in both iPSC and iNs. Our results provide insight into the functions of DNMT1 and the molecular changes associated with ADCA-DN, with potential implications for genes associated with related phenotypes.

Effect of surrounding objects in the adapting scene on chromatic adaptation.

Most of the existing chromatic adaptation transforms (CATs) were developed for flat uniform stimuli presented in a uniform background, which substantially simplifies the complexity of the real scene by excluding surrounding objects from the viewing field. The impact of the background complexity, in terms of the spatial properties of the objects surrounding the stimulus, on chromatic adaptation is ignored in most CATs. This study systematically investigated how the background complexity and color distribution affect the adaptation state. Achromatic matching experiments were conducted in an immersive lighting booth, with the illumination varying in chromaticity and the adapting scene varying in surrounding objects. Results show that compared to the uniform adapting field, increasing the scene complexity can significantly improve the degree of adaptation for the Planckian illuminations with low CCT levels. In addition, the achromatic matching points are substantially biased by the color of the surrounding object, implying the interactive effect of the illumination color and the dominant scene color on the adapting white point.

NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding the mechanisms of gene expression regulation. Although deep convolutional neural networks (CNNs) have achieved great success in predicting cis-regulatory elements, the discovery of motifs and their combinatorial patterns from these CNN models has remained difficult. We show that the main difficulty is due to the problem of multifaceted neurons which respond to multiple types of sequence patterns. Since existing interpretation methods were mainly designed to visualize the class of sequences that can activate the neuron, the resulting visualization will correspond to a mixture of patterns. Such a mixture is usually difficult to interpret without resolving the mixed patterns. We propose the NeuronMotif algorithm to interpret such neurons. Given any convolutional neuron (CN) in the network, NeuronMotif first generates a large sample of sequences capable of activating the CN, which typically consists of a mixture of patterns. Then, the sequences are "demixed" in a layer-wise manner by backward clustering of the feature maps of the involved convolutional layers. NeuronMotif can output the sequence motifs, and the syntax rules governing their combinations are depicted by position weight matrices organized in tree structures. Compared to existing methods, the motifs found by NeuronMotif have more matches to known motifs in the JASPAR database. The higher-order patterns uncovered for deep CNs are supported by the literature and ATAC-seq footprinting. Overall, NeuronMotif enables the deciphering of cis-regulatory codes from deep CNs and enhances the utility of CNN in genome interpretation.

Transition type influences the adaptation state under dichromatic illuminations.

The CATs models proposed over these years (such as CMCCAT97, CAT02 and CAT16) were derived from simple stimuli surrounded by a uniform background with a single illuminant. However, the real scene always consists of more than one illumination, especially in many artificially lit environments. Some previous studies indicate an influence of the transition type between two illuminations on the adaptation state, but the visual data is insufficient to conclude a general trend applicable for any color pair. To systematically investigate how the transition type and illumination color pair interactively influence the adapted white point and degree of adaptation, a series of achromatic matching experiments were conducted under (simultaneously) spatially dichromatic illuminations. Transition type was found to have an impact on the adaptation state, but it is significant only for an illumination pair with a large color difference. In addition, for those sharp-transitioned dichromatic illuminations, the illumination that more easily gets adapted tends to have a higher contribution to the adapted white point than the other one. A more comprehensive CAT model for dichromatic illuminations was derived from the collected visual data.

Design of a dual focal-plane near-eye display using diffractive waveguides and multiple lenses.

We propose a method to construct a compact dual focal-plane optical see-through near-eye display using diffractive waveguides and multiple lenses. A virtual image from a display device is projected into a three-grating waveguide using an objective lens, and a virtual image can be shown at a far distance with an extended eye box. One negative lens is employed to reduce the focus distance of the virtual image, and a corresponding positive lens is used to compensate for the distortion and accommodation errors. Thus, not only can a virtual image with a near distance be achieved, but also a virtual plane with a further distance can be generated by introducing another projection module and waveguide. Only two waveguides and two pieces of lenses are used in front of one eye to obtain a lightweight outlook. To verify the proposed method, a proof-of-concept prototype was developed to provide vivid virtual images at different depths in front of the human eye.

Design, analysis and optimization of a waveguide-type near-eye display using a pin-mirror array and a concaved reflector.

Waveguides have become one of the most promising optical combiners for see-through near-eye displays due to the thickness, weight, and transmittance. In this study, we propose a waveguide-type near-eye display using a pin-mirror array and a concaved reflector with a compact outlook, optimized image uniformity and stray light. Issues have been discussed in detail, which include field of view (FOV), eye-box, resolution, depth of field (DOF), display uniformity and stray light artifacts. It can be shown that the DOF can be extended (when compared with traditional waveguide-type near-eye displays) to alleviate the vergence-accommodation conflict (VAC) problem, and the uniformity & stray light can be improved with an optimal structure. Moreover, reflective surfaces have been introduced as the input and output coupling with a compact outlook, an easy-processing structure and the achromatic performance. A prototype based on the proposed method have been successfully developed, and virtual images with an extended DOF can be shown along with the real-world.

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

Predictive performance of the standard and the modified von Kries chromatic adaptation transforms.

To investigate chromatic adaptation and develop chromatic adaptation transforms (CATs), many psychophysical experiments have been conducted to collect corresponding colors (CC) under various illumination conditions. Most modern CATs have been developed based on a database of CC sets collected in the 20th century. More recently, several additional CC sets have been collected by Smet et al., Wei et al., and Ma et al. using memory color matching or achromatic matching methods. The analysis of these CC data indicates that for yellowish (located on or close to the Planckian locus) and greenish illuminations, the short-wave (S) sensitive cones show a lower degree of adaptation compared to the long-wave (L) and medium-wave (M) sensitive cones. This can result in a large prediction error of the standard von Kries CAT, which adopts a single degree of adaptation value for all three cone types. A modified von Kries CAT is proposed that accounts for these differences between the L-, M- and S-cone signals by applying a compression to the rescaling factor for the S-cones. It outperforms the standard von Kries CAT for the Breneman-C, Smet, Wei, and Ma data, while for other data sources the two CATs have similar performance.

Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is a common degenerative cardiovascular disease whose pathobiology is not clearly understood. The cellular heterogeneity and cell-type-specific gene regulation of vascular cells in human AAA have not been well-characterized. Here, we performed analysis of whole-genome sequencing data in AAA patients versus controls with the aim of detecting disease-associated variants that may affect gene regulation in human aortic smooth muscle cells (AoSMC) and human aortic endothelial cells (HAEC), two cell types of high relevance to AAA disease. To support this analysis, we generated H3K27ac HiChIP data for these cell types and inferred cell-type-specific gene regulatory networks. We observed that AAA-associated variants were most enriched in regulatory regions in AoSMC, compared with HAEC and CD4+ cells. The cell-type-specific regulation defined by this HiChIP data supported the importance of ERG and the KLF family of transcription factors in AAA disease. The analysis of regulatory elements that contain noncoding variants and also are differentially open between AAA patients and controls revealed the significance of the interleukin-6-mediated signaling pathway. This finding was further validated by including information from the deleteriousness effect of nonsynonymous single-nucleotide variants in AAA patients and additional control data from the Medical Genome Reference Bank dataset. These results shed important insights into AAA pathogenesis and provide a model for cell-type-specific analysis of disease-associated variants.

Network Effects of the 15q13.3 Microdeletion on the Transcriptome and Epigenome in Human-Induced Neurons.

BACKGROUND: The 15q13.3 microdeletion is associated with several neuropsychiatric disorders, including autism and schizophrenia. Previous association and functional studies have investigated the potential role of several genes within the deletion in neuronal dysfunction, but the molecular effects of the deletion as a whole remain largely unknown. METHODS: Induced pluripotent stem cells, from 3 patients with the 15q13.3 microdeletion and 3 control subjects, were generated and converted into induced neurons. We analyzed the effects of the 15q13.3 microdeletion on genome-wide gene expression, DNA methylation, chromatin accessibility, and sensitivity to cisplatin-induced DNA damage. Furthermore, we measured gene expression changes in induced neurons with CRISPR (clustered regularly interspaced short palindromic repeats) knockouts of individual 15q13.3 microdeletion genes. RESULTS: In both induced pluripotent stem cells and induced neurons, gene copy number change within the 15q13.3 microdeletion was accompanied by significantly decreased gene expression and no compensatory changes in DNA methylation or chromatin accessibility, supporting the model that haploinsufficiency of genes within the deleted region drives the disorder. Furthermore, we observed global effects of the microdeletion on the transcriptome and epigenome, with disruptions in several neuropsychiatric disorder-associated pathways and gene families, including Wnt signaling, ribosome function, DNA binding, and clustered protocadherins. Individual gene knockouts mirrored many of the observed changes in an overlapping fashion between knockouts. CONCLUSIONS: Our multiomics analysis of the 15q13.3 microdeletion revealed downstream effects in pathways previously associated with neuropsychiatric disorders and indications of interactions between genes within the deletion. This molecular systems analysis can be applied to other chromosomal aberrations to further our etiological understanding of neuropsychiatric disorders.

Effect of adapting field size on chromatic adaptation.

The human visual system adapts to changes in white tone of the illumination to maintain approximately the same object color appearance. Chromatic adaptation transforms (CAT) were developed to predict corresponding colors, which are colors that look the same under a wide range of illuminants. However, existing CATs fail to accurately predict corresponding colors, particularly under colored illumination, because of an inaccurate estimation of the degree of adaptation. In this study, the impact of the adapting field size on the degree of adaptation was investigated. A memory color matching experiment was conducted, in a real scene, with the background adapting field varying in the field of view, luminance and chromaticity to provide data for the development of a more comprehensive CAT. Results show that a larger field of view leads to a more complete adaptation, despite a much lower background luminance.

Integrated functional genomic analyses of Klinefelter and Turner syndromes reveal global network effects of altered X chromosome dosage.

In both Turner syndrome (TS) and Klinefelter syndrome (KS) copy number aberrations of the X chromosome lead to various developmental symptoms. We report a comparative analysis of TS vs. KS regarding differences at the genomic network level measured in primary samples by analyzing gene expression, DNA methylation, and chromatin conformation. X-chromosome inactivation (XCI) silences transcription from one X chromosome in female mammals, on which most genes are inactive, and some genes escape from XCI. In TS, almost all differentially expressed escape genes are down-regulated but most differentially expressed inactive genes are up-regulated. In KS, differentially expressed escape genes are up-regulated while the majority of inactive genes appear unchanged. Interestingly, 94 differentially expressed genes (DEGs) overlapped between TS and female and KS and male comparisons; and these almost uniformly display expression changes into opposite directions. DEGs on the X chromosome and the autosomes are coexpressed in both syndromes, indicating that there are molecular ripple effects of the changes in X chromosome dosage. Six potential candidate genes (RPS4X, SEPT6, NKRF, CX0rf57, NAA10, and FLNA) for KS are identified on Xq, as well as candidate central genes on Xp for TS. Only promoters of inactive genes are differentially methylated in both syndromes while escape gene promoters remain unchanged. The intrachromosomal contact map of the X chromosome in TS exhibits the structure of an active X chromosome. The discovery of shared DEGs indicates the existence of common molecular mechanisms for gene regulation in TS and KS that transmit the gene dosage changes to the transcriptome.

Impact of the starting point chromaticity on memory color matching accuracy.

In this study, the impact of starting point chromaticity and number of observers on memory color matching results was investigated. Matching data were obtained for 3 objects (neutral grey cube, yellow lemon and green apple) under a neutral white and a yellow background illumination. Memory color matchings were made for ten starting points of which eight chromaticities were symmetrically distributed along the hue circle and centered at the equal energy white (EEW) chromaticity of the neutral white background illumination; one starting point at the EEW chromaticity and one with the same chromaticity as the background. The matching track from starting point to the memory matched chromaticity was also recorded. It did not tend to cross over the central region towards the complementary hue, especially for experienced observers. The results also demonstrated a significant starting point bias, whereby the matched chromaticities were biased towards the chromaticity of the starting point. Starting point bias can be minimized by selecting three starting points symmetrically distributed around the expected memory color chromaticity. Furthermore, at least, ten observers are needed to achieve stable results for the grey cube and yellow lemon. For the green apple, the results are less conclusive and around 40 observers would be needed to obtain a stable average estimate for the chromaticity of the memory color. The large inter-observer variation may result from cultural differences or from natural variations in the "green" apple appearance. This study provides a well-founded guidance for future application of the memory color matching method.

FreePSI: an alignment-free approach to estimating exon-inclusion ratios without a reference transcriptome.

Alternative splicing plays an important role in many cellular processes of eukaryotic organisms. The exon-inclusion ratio, also known as percent spliced in, is often regarded as one of the most effective measures of alternative splicing events. The existing methods for estimating exon-inclusion ratios at the genome scale all require the existence of a reference transcriptome. In this paper, we propose an alignment-free method, FreePSI, to perform genome-wide estimation of exon-inclusion ratios from RNA-Seq data without relying on the guidance of a reference transcriptome. It uses a novel probabilistic generative model based on k-mer profiles to quantify the exon-inclusion ratios at the genome scale and an efficient expectation-maximization algorithm based on a divide-and-conquer strategy and ultrafast conjugate gradient projection descent method to solve the model. We compare FreePSI with the existing methods on simulated and real RNA-seq data in terms of both accuracy and efficiency and show that it is able to achieve very good performance even though a reference transcriptome is not provided. Our results suggest that FreePSI may have important applications in performing alternative splicing analysis for organisms that do not have quality reference transcriptomes. FreePSI is implemented in C++ and freely available to the public on GitHub.

Constructing tissue-specific transcriptional regulatory networks via a Markov random field.

BACKGROUND: Recent advances in sequencing technologies have enabled parallel assays of chromatin accessibility and gene expression for major human cell lines. Such innovation provides a great opportunity to decode phenotypic consequences of genetic variation via the construction of predictive gene regulatory network models. However, there still lacks a computational method to systematically integrate chromatin accessibility information with gene expression data to recover complicated regulatory relationships between genes in a tissue-specific manner. RESULTS: We propose a Markov random field (MRF) model for constructing tissue-specific transcriptional regulatory networks via integrative analysis of DNase-seq and RNA-seq data. Our method, named CSNets (cell-line specific regulatory networks), first infers regulatory networks for individual cell lines using chromatin accessibility information, and then fine-tunes these networks using the MRF based on pairwise similarity between cell lines derived from gene expression data. Using this method, we constructed regulatory networks specific to 110 human cell lines and 13 major tissues with the use of ENCODE data. We demonstrated the high quality of these networks via comprehensive statistical analysis based on ChIP-seq profiles, functional annotations, taxonomic analysis, and literature surveys. We further applied these networks to analyze GWAS data of Crohn's disease and prostate cancer. Results were either consistent with the literature or provided biological insights into regulatory mechanisms of these two complex diseases. The website of CSNets is freely available at http://bioinfo.au.tsinghua.edu.cn/jianglab/CSNETS/ . CONCLUSIONS: CSNets demonstrated the power of joint analysis on epigenomic and transcriptomic data towards the accurate construction of gene regulatory network. Our work provides not only a useful resource of regulatory networks to the community, but also valuable experiences in methodology development for multi-omics data integration.

Effect of Acupotomy on FAK-PI3K Signaling Pathways in KOA Rabbit Articular Cartilages.

OBJECTIVE: By observing the needle-knife of KOA rabbit morphology, knee joint cartilage p-FAK, p-PI3K, Aggrecan gene, and protein expression, to study the effect of needle-knife to promote cartilage cell synthesis metabolism mechanism. METHOD: 49 male New Zealand rabbits, randomly divided into normal group (Z), model group (M), model-inhibitors (MP), needle-knife group (D), needle-knife inhibitors group (DP), electroacupuncture group (E), and electroacupuncture inhibitors (EP). RT-PCR and Western Blot were used to test each animal cartilage p-FAK, p-PI3K, and Aggrecan gene and protein expression level. RESULTS: Compared with N group, p-FAK and p-PI3K protein and mRNA expression of M group, D group, and E group increased (P < 0.05), while the protein and mRNA expression of Aggrecan reduced (P < 0.05). Compared with M group, p-FAK, p-PI3K, Aggrecan protein, and mRNA of E and D group increased (P < 0.05). Compared with E group, p-FAK, p-PI3K, Aggrecan protein, and mRNA expression of D group increased (P < 0.05); after adding inhibitors, p-FAK, p-PI3K, Aggrecan protein, and mRNA expression reduced (P < 0.05). CONCLUSION: Needle-knife therapy can promote the repairment of cartilage cells by activating FAK-PI3K signaling pathways, promoting the synthesis of cartilage cell metabolism.