MTD: a unique pipeline for host and meta-transcriptome joint and integrative analyses of RNA-seq data.

Ribonucleic acid (RNA)-seq data contain not only host transcriptomes but also nonhost information that comprises transcripts from active microbiota in the host cells. Therefore, joint and integrative analyses of both host and meta-transcriptome can reveal gene expression of the microbial community in a given sample as well as the correlative and interactive dynamics of the host response to the microbiome. However, there are no convenient tools that can systemically analyze host-microbiota interactions through simultaneously quantifying the host and meta-transcriptome in the same sample at the tissue and the single-cell level. This poses a challenge for interested researchers with limited expertise in bioinformatics. Here, we developed a software pipeline that can comprehensively and synergistically analyze and correlate the host and meta-transcriptome in a single sample using bulk and single-cell RNA-seq data. This pipeline, named meta-transcriptome detector (MTD), can extensively identify and quantify microbiome, including viruses, bacteria, protozoa, fungi, plasmids and vectors, in the host cells and correlate the microbiome with the host transcriptome. MTD is easy to install and run, involving only a few lines of simple commands. It offers researchers with unique genomics insights into host responses to microorganisms.

Increased Proviral DNA in Circulating Cells Correlates with Plasma Viral Rebound in Simian Immunodeficiency Virus-Infected Rhesus Macaques after Antiretroviral Therapy Interruption.

The human immunodeficiency virus (HIV) reservoir is responsible for persistent viral infection, and a small number of mosaic latent cellular reservoirs promote viral rebound upon antiretroviral therapy interruption, which is the major obstacle to a cure. However, markers that determine effective therapy and viral rebound posttreatment interruption remain unclear. In this study, we comprehensively and longitudinally tracked dynamic decay of cell-associated viral RNA/DNA in systemic and lymphoid tissues in simian immunodeficiency virus (SIV)-infected rhesus macaques on prolonged combined antiretroviral therapy (cART) and evaluated predictors of viral rebound after treatment cessation. The results showed that suppressive ART substantially reduced plasma SIV RNA, cell-associated unspliced, and multiply spliced SIV RNA to undetectable levels, yet viral DNA remained detectable in systemic tissues and lymphoid compartments throughout cART. Intriguingly, a rapid increase of integrated proviral DNA in peripheral mononuclear cells was detected once treatment was withdrawn, accompanied by the emergence of detectable plasma viral load. Notably, the increase of peripheral proviral DNA after treatment interruption correlated with the emergence and degree of viral rebound. These findings suggest that measuring total viral DNA in SIV infection may be a relatively simple surrogate marker of reservoir size and may predict viral rebound after treatment interruption and inform treatment strategies.IMPORTANCE Viral reservoirs are involved in persistent HIV infection, and a small number of mosaic latent cellular reservoirs promote viral rebound upon analytical treatment interruption, which is the major obstacle to a cure. However, early indicators that can predict resurgence of viremia after treatment interruption may aid treatment decisions in people living with HIV. Utilizing the rhesus macaque model, we demonstrated that increased proviral DNA in peripheral cells after treatment interruption, rather than levels of proviral DNA, was a useful marker to predict the emergence and degree of viral rebound after treatment interruption, providing a rapid approach for monitoring HIV rebound and informing decisions.

Screen technical noise in single cell RNA sequencing data.

We proposed a data cleaning pipeline for single cell (SC) RNA-seq data, where we first screen genes (gene-wise screening) followed by screening cell libraries (library-wise screening). Gene-wise screening is based on the expectation that for a gene with a low technical noise, a gene's count in a library will tend to increase with the increase of library size, which was tested using negative binomial regression of gene count (as dependent variable) against library size (as independent variable). Library-wise screening is based on the expectation that across-library correlations for housekeeping (HK) genes is expected to be higher than the correlations for non-housekeeping (NHK) genes in those libraries with low technical noise. We removed those libraries, whose mean pairwise correlation for HK genes is NOT significantly higher than that for NHK genes. We successfully applied the pipeline to two large SC RNA-seq datasets. The pipeline was also developed into an R package.

Proportions of resting memory T cells and monocytes in blood have prognostic significance in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by progressive decline of lung function. Here, we tested the importance of differential proportions of blood immune cells to IPF clinical outcomes. We used Cibersort to deconvolute immune cell components based on PBMCs or whole blood IPF genomics datasets. We found that a higher proportion of resting memory (RM) T cells was associated with a better survival and a higher DLco (diffusing capacity for carbon monoxide) in IPF patients. The association was also found in opposite direction for monocytes. Additionally, in IPF patients as compared to healthy controls, proportions of monocytes were observed to be higher, yet RM T cells were observed to be lower. Taken together, our result suggests a beneficial effect of RM T cells and a detrimental effect of monocytes for IPF. Future genomics studies of IPF should be more focused on these two types of cells.

Rheumatoid arthritis-associated DNA methylation sites in peripheral blood mononuclear cells.

OBJECTIVES: To identify novel DNA methylation sites significant for rheumatoid arthritis (RA) and comprehensively understand their underlying pathological mechanism. METHODS: We performed (1) genome-wide DNA methylation and mRNA expression profiling in peripheral blood mononuclear cells from RA patients and health controls; (2) correlation analysis and causal inference tests for DNA methylation and mRNA expression data; (3) differential methylation genes regulatory network construction; (4) validation tests of 10 differential methylation positions (DMPs) of interest and corresponding gene expressions; (5) correlation between PARP9 methylation and its mRNA expression level in Jurkat cells and T cells from patients with RA; (6) testing the pathological functions of PARP9 in Jurkat cells. RESULTS: A total of 1046 DNA methylation positions were associated with RA. The identified DMPs have regulatory effects on mRNA expressions. Causal inference tests identified six DNA methylation-mRNA-RA regulatory chains (eg, cg00959259-PARP9-RA). The identified DMPs and genes formed an interferon-inducible gene interaction network (eg, MX1, IFI44L, DTX3L and PARP9). Key DMPs and corresponding genes were validated their differences in additional samples. Methylation of PARP9 was correlated with mRNA level in Jurkat cells and T lymphocytes isolated from patients with RA. The PARP9 gene exerted significant effects on Jurkat cells (eg, cell cycle, cell proliferation, cell activation and expression of inflammatory factor IL-2). CONCLUSIONS: This multistage study identified an interferon-inducible gene interaction network associated with RA and highlighted the importance of PARP9 gene in RA pathogenesis. The results enhanced our understanding of the important role of DNA methylation in pathology of RA.

Integrative multi-omics analysis revealed SNP-lncRNA-mRNA (SLM) networks in human peripheral blood mononuclear cells.

Long non-coding RNAs (lncRNAs) serve as important controller of cellular functions via regulating RNA transcription, degradation and translation. However, what are the regulation patterns of lncRNAs on downstream mRNA and how the upstream genetic variants regulate lncRNAs are largely unknown. We first performed a comprehensive expression quantitative trait locus (eQTL) analysis (MatrixeQTL package, R) using genome-wide lncRNA expression and SNP genotype data from human peripheral blood mononuclear cells (PBMCs) of 43 unrelated individuals. Subsequently, multi-omics integrative network analysis was applied to construct SNP-lncRNA-mRNA (SLM) interaction networks. The causal inference test (CIT) was used to identify lncRNA-mediated (epi-) genetic regulation on mRNA expressions. Our eQTL analysis detected 707 pairs of cis-effect associations (p < 5.64E-06) and 6657 trans-effect associations (p < 3.51E-08), respectively. We also found that top significant cis-eSNPs were enriched around the lncRNA transcription start site regions, and that enrichment patterns of cis-eSNPs differs among different lncRNA sizes (small, medium and large).The constructed SLM interaction networks (1 primary networks and four small separate networks) showed various complex interaction patterns. Especially, the in-depth CIT detected 50 significant lncRNA-mediated SLM trios, and some hotspots (e.g., SNPs: rs926370, rs7716167 and rs16880521; lncRNAs: HIT000061975 and ENST00000579057.1). This study represents the first effort of dissecting the SLM interaction patterns in PBMCs by multi-omics integrative network analysis and causal inference test for clearing the regulation chain. The results provide novel insights into the regulation patterns of lncRNA, and may facilitate investigations of PBMC-related immune physiological process and immunological diseases in the future.

Network-based proteomic analysis for postmenopausal osteoporosis in Caucasian females.

Menopause is one of the crucial physiological events during the life of a woman. Transition of menopause status is accompanied by increased risks of various health problems such as osteoporosis. Peripheral blood monocytes can differentiate into osteoclasts and produce cytokines important for osteoclast activity. With quantitative proteomics LC-nano-ESI-MS(E) (where MS(E) is elevated-energy MS), we performed protein expression profiling of peripheral blood monocytes in 42 postmenopausal women with discordant bone mineral density (BMD) levels. Traditional comparative analysis showed proteins encoded by four genes (LOC654188, PPIA, TAGLN2, YWHAB) and three genes (LMNB1, ANXA2P2, ANXA2) were significantly down- and upregulated, respectively, in extremely low- versus high-BMD subjects. To study functionally orchestrating groups of detected proteins in the form of networks, we performed weighted gene coexpression network analysis and gene set enrichment analysis. Weighted gene coexpression network analysis showed that the module including the annexin gene family was most significantly correlated with low BMD, and the lipid-binding related GO terms were enriched in this identified module. Gene set enrichment analysis revealed that two significantly enriched gene sets may be involved in postmenopausal BMD variation by regulating pro-inflammatory cytokines activities. To gain more insights into the proteomics data generated, we performed integrative analyses of the datasets available to us at the genome (DNA level), transcriptome (RNA level), and proteome levels jointly.

Meta-analysis of genome-wide association data identifies novel susceptibility loci for obesity.

Obesity is a major public health problem with strong genetic determination. Multiple genetic variants have been implicated for obesity by conducting genome-wide association (GWA) studies, primarily focused on body mass index (BMI). Fat body mass (FBM) is phenotypically more homogeneous than BMI and is more appropriate for obesity research; however, relatively few studies have been conducted on FBM. Aiming to identify variants associated with obesity, we carried out meta-analyses of seven GWA studies for BMI-related traits including FBM, and followed these analyses by de novo replication. The discovery cohorts consisted of 21 969 individuals from diverse ethnic populations and a total of over 4 million genotyped or imputed SNPs. The de novo replication cohorts consisted of 6663 subjects from two independent samples. To complement individual SNP-based association analyses, we also carried out gene-based GWA analyses in which all variations within a gene were considered jointly. Individual SNP-based association analyses identified a novel locus 1q21 [rs2230061, CTSS (Cathepsin S)] that was associated with FBM after the adjustment of lean body mass (LBM) (P = 3.57 × 10(-8)) at the genome-wide significance level. Gene-based association analyses identified a novel gene NLK (nemo-like kinase) in 17q11 that was significantly associated with FBM adjusted by LBM. In addition, we confirmed three previously reported obesity susceptibility loci: 16q12 [rs62033400, P = 1.97 × 10(-14), FTO (fat mass and obesity associated)], 18q22 [rs6567160, P = 8.09 × 10(-19), MC4R (melanocortin 4 receptor)] and 2p25 [rs939583, P = 1.07 × 10(-7), TMEM18 (transmembrane protein 18)]. We also found that rs6567160 may exert pleiotropic effects to both FBM and LBM. Our results provide additional insights into the molecular genetic basis of obesity and may provide future targets for effective prevention and therapeutic intervention.

Multistage genome-wide association meta-analyses identified two new loci for bone mineral density.

Aiming to identify novel genetic variants and to confirm previously identified genetic variants associated with bone mineral density (BMD), we conducted a three-stage genome-wide association (GWA) meta-analysis in 27 061 study subjects. Stage 1 meta-analyzed seven GWA samples and 11 140 subjects for BMDs at the lumbar spine, hip and femoral neck, followed by a Stage 2 in silico replication of 33 SNPs in 9258 subjects, and by a Stage 3 de novo validation of three SNPs in 6663 subjects. Combining evidence from all the stages, we have identified two novel loci that have not been reported previously at the genome-wide significance (GWS; 5.0 × 10(-8)) level: 14q24.2 (rs227425, P-value 3.98 × 10(-13), SMOC1) in the combined sample of males and females and 21q22.13 (rs170183, P-value 4.15 × 10(-9), CLDN14) in the female-specific sample. The two newly identified SNPs were also significant in the GEnetic Factors for OSteoporosis consortium (GEFOS, n = 32 960) summary results. We have also independently confirmed 13 previously reported loci at the GWS level: 1p36.12 (ZBTB40), 1p31.3 (GPR177), 4p16.3 (FGFRL1), 4q22.1 (MEPE), 5q14.3 (MEF2C), 6q25.1 (C6orf97, ESR1), 7q21.3 (FLJ42280, SHFM1), 7q31.31 (FAM3C, WNT16), 8q24.12 (TNFRSF11B), 11p15.3 (SOX6), 11q13.4 (LRP5), 13q14.11 (AKAP11) and 16q24 (FOXL1). Gene expression analysis in osteogenic cells implied potential functional association of the two candidate genes (SMOC1 and CLDN14) in bone metabolism. Our findings independently confirm previously identified biological pathways underlying bone metabolism and contribute to the discovery of novel pathways, thus providing valuable insights into the intervention and treatment of osteoporosis.

Perceived overqualification and knowledge sharing: The role of organizational identity and psychological entitlement.

BACKGROUND: Employees' perception of being overqualified is a critical factor in influencing their knowledge sharing behavior. However previous studies have not examined the internal mechanism by which perceived overqualification affects knowledge sharing. OBJECTIVE: Drawing on social exchange theory, the present study aimed to explore the relationship between perceived overqualification and knowledge sharing and to examine the mediating effect of organizational identity and the moderating role of psychological entitlement. METHODS: Participants were 284 full-time employees from different companies in China. They answered self-report questionnaires that assessed perceived overqualification, knowledge sharing, organizational identity, and psychological entitlement. Path analyses were conducted, and the latent moderated structural equations were used to judge the significance of the mediation and moderation. RESULTS: The results revealed that overqualified employees were less willing to share knowledge, and the mediating role of organizational identity was significant. Further, the presence of high psychological entitlement would diminish the beneficial effect of organizational identity on employee knowledge sharing. CONCLUSIONS: The findings of the study enrich and expand our knowledge on the relationship between overqualification and knowledge sharing and have theoretical and practical implications for promoting constructive behavior among overqualified employees.

SCFFBXW11 Complex Targets Interleukin-17 Receptor A for Ubiquitin-Proteasome-Mediated Degradation.

Interleukin-17 (IL-17) is a pro-inflammatory cytokine that participates in innate and adaptive immune responses and plays an important role in host defense, autoimmune diseases, tissue regeneration, metabolic regulation, and tumor progression. Post-translational modifications (PTMs) are crucial for protein function, stability, cellular localization, cellular transduction, and cell death. However, PTMs of IL-17 receptor A (IL-17RA) have not been investigated. Here, we show that human IL-17RA was targeted by F-box and WD repeat domain-containing 11 (FBXW11) for ubiquitination, followed by proteasome-mediated degradation. We used bioinformatics tools and biochemical techniques to determine that FBXW11 ubiquitinated IL-17RA through a lysine 27-linked polyubiquitin chain, targeting IL-17RA for proteasomal degradation. Domain 665-804 of IL-17RA was critical for interaction with FBXW11 and subsequent ubiquitination. Our study demonstrates that FBXW11 regulates IL-17 signaling pathways at the IL-17RA level.

Single cell RNA-sequencing identifies the effect of Normothermic ex vivo liver perfusion on liver-resident T cells.

BACKGROUND: Normothermic ex vivo liver perfusion (NEVLP) is an exciting strategy to preserve livers prior to transplant, however, the effects of NEVLP on the phenotype of tissue-resident immune cells is largely unknown. The presence of tissue-resident memory T cells (TRM) in the liver may protect against acute rejection and decrease allograft dysfunction. Therefore, we investigated the effects of NEVLP on liver TRMs and assessed the ability of anti-inflammatory cytokines to reduce TRM activation during NEVLP. METHODS: Rat livers underwent NEVLP with or without the addition of IL-10 and TGF-ß. Naïve and cold storage livers served as controls. Following preservation, TRM T cell gene expression profiles were assessed through single cell RNA sequencing (scRNA-seq). Differential gene expression analysis was performed with Wilcoxon rank sum test to identify differentially expressed genes (DEGs) associated with a specific treatment group. Using the online Database for Annotation, Visualization and Integrated Discovery (DAVID), gene set enrichment was then conducted with Fisher's exact test on DEGs to highlight differentially regulated pathways and functional terms associated with treatment groups. RESULTS: Through scRNA-seq analysis, an atlas of liver-resident memory T cell subsets was created for all livers. TRM T cells could be identified in all livers, and through scRNA-seq, DEG was identified with Wilcoxon rank sum test at FDR < 0.05. Based on the gene set enrichment analysis of DEGs using Fisher's exact test, NEVLP is associated with downregulation of multiple gene enrichment pathways associated with surface proteins. Furthermore, NEVLP with anti-inflammatory cytokines was associated with down regulation of 52 genes in TRM T cells when compared to NEVLP alone (FDR <0.05), most of which are pro-inflammatory. CONCLUSION: This is the first study to create an atlas of liver TRM T cells in the rat liver undergoing NEVLP and demonstrate the effects of NEVLP on liver TRM T cells at the single cell gene expression level.

Ultra-high photoelectric conversion efficiency and obvious carrier separation in photovoltaic ZnIn2X4 (X = S, Se, and Te) van der Waals heterostructures.

The need for low-carbon solar electricity production has become increasingly urgent for energy security and climate change mitigation. However, the bandgap and carrier separation critical requirements of high-efficiency solar cells are difficult to satisfy simultaneously in a single material. In this work, several van der Waals ZnIn2X4 (X = S, Se, and Te) heterostructures were designed based on density functional theory. Our results suggest that both ZnIn2S4/ZnIn2Se4 and ZnIn2Se4/ZnIn2Te4 heterostructures are direct bandgap semiconductors at the Γ point. Besides, obvious carrier spatial separations were observed in the ZnIn2S4/ZnIn2Se4 and ZnIn2Se4/ZnIn2Te4 heterostructures. Interestingly, the ZnIn2S4/ZnIn2Se4 heterostructure has a suitable bandgap of 1.43 eV with good optical absorption in the visible light range. The calculated maximum theoretical photoelectric conversion efficiency of ZnIn2S4/ZnIn2Se4 heterostructure was 32.1%, and it can be further enhanced to 32.9% under 2% tensile strain. Compared to single-layer ZnIn2X4 materials, the electron effective mass of the ZnIn2S4/ZnIn2Se4 heterostructure is relatively low, which results in high electron mobility in the heterostructure. The suitable bandgap, obvious carrier separation, high electron mobility, and excellent theoretical photoelectric conversion efficiency of the ZnIn2S4/ZnIn2Se4 heterostructure make it a promising candidate for novel 2D-based photoelectronic devices and solar cells.

Enhanced Complement Expression in the Tumor Microenvironment Following Neoadjuvant Therapy: Implications for Immunomodulation and Survival in Pancreatic Ductal Adenocarcinoma.

Background: Neoadjuvant therapy (NAT) is increasingly being used for pancreatic ductal adenocarcinoma (PDAC) treatment. However, its specific effects on carcinoma cells and the tumor microenvironment (TME) are not fully understood. This study aims to investigate how NAT differentially impacts PDAC's carcinoma cells and TME. Methods: Spatial transcriptomics was used to compare gene expression profiles in carcinoma cells and the TME between 23 NAT-treated and 13 NAT-naïve PDAC patients, correlating with their clinicopathologic features. Analysis of an online single-nucleus RNA sequencing (snRNA-seq) dataset was performed for validation of the specific cell types responsible for NAT-induced gene expression alterations. Results: NAT not only induces apoptosis and inhibits proliferation in carcinoma cells but also significantly remodels the TME. Notably, NAT induces a coordinated upregulation of multiple key complement genes (C3, C1S, C1R, C4B and C7) in the TME, making the complement pathway one of the most significantly affected pathways by NAT. Patients with higher TME complement expression following NAT exhibit improved overall survival. These patients also exhibit increased immunomodulatory and neurotrophic cancer-associated fibroblasts (CAFs); more CD4+ T cells, monocytes, and mast cells; and reduced immune exhaustion gene expression. snRNA-seq analysis demonstrates C3 complement was specifically upregulated in CAFs but not in other stroma cell types. Conclusions: NAT can enhance complement production and signaling within the TME, which is associated with reduced immunosuppression in PDAC. These findings suggest that local complement dynamics could serve as a novel biomarker for prognosis, evaluating treatment response and resistance, and guiding therapeutic strategies in NAT-treated PDAC patients.

Peripheral blood monocyte-expressed ANXA2 gene is involved in pathogenesis of osteoporosis in humans.

Low bone mineral density (BMD) is a risk factor of osteoporosis and has strong genetic determination. Genes influencing BMD and fundamental mechanisms leading to osteoporosis have yet to be fully determined. Peripheral blood monocytes (PBM) are potential osteoclast precursors, which could access to bone resorption surfaces and differentiate into osteoclasts to resorb bone. Herein, we attempted to identify osteoporosis susceptibility gene(s) and characterize their function(s), through an initial proteomics discovery study on PBM in vivo, and multiscale validation studies in vivo and in vitro. Utilizing the quantitative proteomics methodology LC-nano-ESI-MS(E), we discovered that a novel protein, i.e. ANXA2, was up-regulated twofold in PBM in vivo in Caucasians with extremely low BMD (cases) versus those with extremely high BMD (controls) (n = 28, p < 0.05). ANXA2 gene up-regulation in low BMD subjects was replicated at the mRNA level in PBM in vivo in a second and independent case-control sample (n = 80, p < 0.05). At the DNA level, we found that SNPs in the ANXA2 gene were associated with BMD variation in a 3(rd) and independent case-control sample (n = 44, p < 0.05), as well as in a random population sample (n = 997, p < 0.05). The above integrative evidence strongly supports the concept that ANXA2 is involved in the pathogenesis of osteoporosis in humans. Through a follow-up cellular functional study, we found that ANXA2 protein significantly promoted monocyte migration across an endothelial barrier in vitro (p < 0.001). Thus, elevated ANXA2 protein expression level, as detected in low BMD subjects, probably stimulates more PBM migration through the blood vessel walls to bone resorption surfaces in vivo, where they differentiate into higher number of osteoclasts and resorb bone at higher rates, thereby decreasing BMD. In conclusion, this study identified a novel osteoporosis susceptibility gene ANXA2, and suggested a novel pathophysiological mechanism, mediated by ANXA2, for osteoporosis in humans.

Five Critical Gene-Based Biomarkers With Optimal Performance for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most fatal cancers in the world. There is an urgent need to understand the molecular background of HCC to facilitate the identification of biomarkers and discover effective therapeutic targets. Published transcriptomic studies have reported a large number of genes that are individually significant for HCC. However, reliable biomarkers remain to be determined. In this study, built on max-linear competing risk factor models, we developed a machine learning analytical framework to analyze transcriptomic data to identify the most miniature set of differentially expressed genes (DEGs). By analyzing 9 public whole-transcriptome datasets (containing 1184 HCC samples and 672 nontumor controls), we identified 5 critical differentially expressed genes (DEGs) (ie, CCDC107, CXCL12, GIGYF1, GMNN, and IFFO1) between HCC and control samples. The classifiers built on these 5 DEGs reached nearly perfect performance in identification of HCC. The performance of the 5 DEGs was further validated in a US Caucasian cohort that we collected (containing 17 HCC with paired nontumor tissue). The conceptual advance of our work lies in modeling gene-gene interactions and correcting batch effect in the analytic framework. The classifiers built on the 5 DEGs demonstrated clear signature patterns for HCC. The results are interpretable, robust, and reproducible across diverse cohorts/populations with various disease etiologies, indicating the 5 DEGs are intrinsic variables that can describe the overall features of HCC at the genomic level. The analytical framework applied in this study may pave a new way for improving transcriptome profiling analysis of human cancers.

Enhanced optical absorption in two-dimensional Ruddlesden-Popper (C6H5CH2NH3)2PbI4 perovskites via biaxial strain and surface doping.

Two-dimensional Ruddlesden-Popper (2D RP) perovskites can form layered protective materials using long organic cations as "barrier" caps, which is expected to solve the problem of instability of perovskites in the working environment. In this work, we systematically studied the 2D Ruddlesden-Popper (C6H5CH2NH3)2PbI4 hybrid perovskites using density functional theory. The results reveal that the 2D (C6H5CH2NH3)2PbI4 perovskites are semiconductors with band gaps of 2.22 eV. The optical absorption peak of the 2D (C6H5CH2NH3)2PbI4 perovskite structure is located at 532 nm in the visible region. Interestingly, the optical absorption spectrum of the 2D (C6H5CH2NH3)2PbI4 perovskite structure enhanced under suitable strains. The highest optical absorption peak appears in 2D (C6H5CH2NH3)2PbI4 under a -2% strain, and its theoretical photoelectric conversion efficiency is 28.5%. More interestingly, the replacement of surface I atoms with Br is another ways to enhance the optical absorption spectrum of the 2D (C6H5CH2NH3)2PbI4 perovskite structure. The optical absorption peak blue-shifts to the high energy region, which has higher solar energy flux density than the low energy region. The good stability, tuneable band gap and excellent theoretical photoelectric conversion efficiency of the 2D (C6H5CH2NH3)2PbI4 perovskite structure make it a promising candidate for novel 2D hybrid perovskite based photoelectronic devices and solar cells.

Genome-wide association study identifies HMGN3 locus for spine bone size variation in Chinese.

Bone size (BS) is one of the major risk factors for osteoporotic fractures. BS variation is genetically determined to a substantial degree with heritability over 50%, but specific genes underlying variation of BS are still largely unknown. To identify specific genes for BS in Chinese, initial genome-wide association scan (GWAS) study and follow-up replication study were performed. In initial GWAS study, a group of 12 contiguous single-nucleotide polymorphism (SNP)s, which span a region of ~25 kb and locate at the upstream of HMGN3 gene (high-mobility group nucleosomal binding domain 3), achieved moderate association signals for spine BS, with P values ranging from 6.2E-05 to 1.8E-06. In the follow-up replication study, eight of the 12 SNPs were detected suggestive replicate associations with BS in 1,728 unrelated female Caucasians, which have well-known differences from Chinese in ethnic genetic background. The SNPs in the region of HMGN3 gene formed a tightly combined haplotype block in both Chinese and Caucasians. The results suggest that the genomic region containing HMGN3 gene may be associated with spine BS in Chinese.

Genome-wide association and follow-up replication studies identified ADAMTS18 and TGFBR3 as bone mass candidate genes in different ethnic groups.

To identify and validate genes associated with bone mineral density (BMD), which is a prominent osteoporosis risk factor, we tested 379,319 SNPs in 1000 unrelated white U.S. subjects for associations with BMD. For replication, we genotyped the most significant SNPs in 593 white U.S. families (1972 subjects), a Chinese hip fracture (HF) sample (350 cases, 350 controls), a Chinese BMD sample (2955 subjects), and a Tobago cohort of African ancestry (908 males). Publicly available Framingham genome-wide association study (GWAS) data (2953 whites) were also used for in silico replication. The GWAS detected two BMD candidate genes, ADAMTS18 (ADAM metallopeptidase with thrombospondin type 1 motif, 18) and TGFBR3 (transforming growth factor, beta receptor III). Replication studies verified the significant findings by GWAS. We also detected significant associations with hip fracture for ADAMTS18 SNPs in the Chinese HF sample. Meta-analyses supported the significant associations of ADAMTS18 and TGFBR3 with BMD (p values: 2.56 x 10(-5) to 2.13 x 10(-8); total sample size: n = 5925 to 9828). Electrophoretic mobility shift assay suggested that the minor allele of one significant ADAMTS18 SNP might promote binding of the TEL2 factor, which may repress ADAMTS18 expression. The data from NCBI GEO expression profiles also showed that ADAMTS18 and TGFBR3 genes were differentially expressed in subjects with normal skeletal fracture versus subjects with nonunion skeletal fracture. Overall, the evidence supports that ADAMTS18 and TGFBR3 might underlie BMD determination in the major human ethnic groups.