Timothy Vyse, Yong Cui, Wanling Yang and colleagues report a meta-analysis of genome-wide association studies for systemic lupus erythematosus (SLE) including European and Chinese individuals. They identify ten new loci associated with SLE and find evidence for increased genetic risk of disease among individuals of non-European ancestry. Systemic lupus erythematosus (SLE; OMIM 152700) is a genetically complex autoimmune disease. Genome-wide association studies (GWASs) have identified more than 50 loci as robustly associated with the disease in single ancestries, but genome-wide transancestral studies have not been conducted. We combined three GWAS data sets from Chinese (1,659 cases and 3,398 controls) and European (4,036 cases and 6,959 controls) populations. A meta-analysis of these studies showed that over half of the published SLE genetic associations are present in both populations. A replication study in Chinese (3,043 cases and 5,074 controls) and European (2,643 cases and 9,032 controls) subjects found ten previously unreported SLE loci. Our study provides further evidence that the majority of genetic risk polymorphisms for SLE are contained within the same regions across both populations. Furthermore, a comparison of risk allele frequencies and genetic risk scores suggested that the increased prevalence of SLE in non-Europeans (including Asians) has a genetic basis.

Objectives Systemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic component in its pathogenesis. Through genome-wide association studies (GWAS), we recently identified 10 novel loci associated with SLE and uncovered a number of suggestive loci requiring further validation. This study aimed to validate those loci in independent cohorts and evaluate the role of SLE genetics in drug repositioning. Methods We conducted GWAS and replication studies involving 12 280 SLE cases and 18 828 controls, and performed fine-mapping analyses to identify likely causal variants within the newly identified loci. We further scanned drug target databases to evaluate the role of SLE genetics in drug repositioning. Results We identified three novel loci that surpassed genome-wide significance, including ST3AGL4 (rs13238909, p_meta=4.40E-08), MFHAS1 (rs2428, p_meta=1.17E-08) and CSNK2A2 (rs2731783, p_meta=1.08E-09). We also confirmed the association of CD226 locus with SLE (rs763361, p_meta=2.45E-08). Fine-mapping and functional analyses indicated that the putative causal variants in CSNK2A2 locus reside in an enhancer and are associated with expression of CSNK2A2 in B-lymphocytes, suggesting a potential mechanism of association. In addition, we demonstrated that SLE risk genes were more likely to be interacting proteins with targets of approved SLE drugs (OR=2.41, p=1.50E-03) which supports the role of genetic studies to repurpose drugs approved for other diseases for the treatment of SLE. Conclusion This study identified three novel loci associated with SLE and demonstrated the role of SLE GWAS findings in drug repositioning.

Summary: Insertion and deletion (indels) have been recognized as an important source generating tumor-specific mutant peptides (neoantigens). The focus of indel-derived neoantigen identification has been on leveraging DNA sequencing such as whole exome sequencing, with the effort of using RNA-seq less well explored. Here we present ScanNeo, a fast-streamlined computational pipeline for analyzing RNA-seq to predict neoepitopes derived from small to large-sized indels. We applied ScanNeo in a prostate cancer cell line and validated our predictions with matched mass spectrometry data. Finally, we demonstrated that indel neoantigens predicted from RNA-seq were associated with checkpoint inhibitor response in a cohort of melanoma patients.Availability and implementation: ScanNeo is implemented in Python. It is freely accessible at the GitHub repository (https://github.com/ylab-hi/ScanNeo).Supplementary information: Supplementary data are available at Bioinformatics online.

The filamentous fungus Neurospora crassa is a leading model organism for circadian clock studies. Computational identification of a protein–protein interaction (PPI) network (also known as an interactome) in N. crassa can provide new insights into the cellular functions of proteins. Using two well-established bioinformatics methods (the interolog method and the domain interaction-based method), we predicted 27 588 PPIs among 3006 N. crassaproteins. To the best of our knowledge, this is the first identified interactome for N. crassa, although it remains problematic because of incomplete interactions and false positives. In particular, the established PPI network has provided clues to further decipher the molecular mechanism of circadian rhythmicity. For instance, we found that clock-controlled genes (ccgs) are more likely to act as bottlenecks in the established PPI network. We also identified an important module related to circadian oscillators, and some functional unknown proteins in this module may serve as potential candidates for new oscillators. Finally, all predicted PPIs were compiled into a user-friendly database server (NCPI), which is freely available at http://protein.cau.edu.cn/ncpi.

DNA repair dysregulation is a key driver of cancer development. Understanding the molecular mechanisms underlying DNA repair dysregulation in cancer cells is crucial for cancer development and therapies. Here, we report that enhancer of zeste homolog 2 (EZH2) directly methylates poly(adenosine diphosphate–ribose) polymerase-1 (PARP-1), an essential enzyme involved in DNA repair, and regulates its activity. Functionally, EZH2-catalyzed methylation represses PARP1 catalytic activity, down-regulates the recruitment of x-ray repair cross-complementing group-1 to DNA lesions and its associated DNA damage repair; on the other hand, it protects the cells from nicotinamide adenine dinucleotide overconsumption upon DNA damage formation. Meanwhile, EZH2-mediated methylation regulates PARP1 transcriptional and oncogenic activity, at least in part, through impairing PARP1-E2F1 interaction and E2F1 transcription factor activity. EZH2 and PARP1 inhibitors synergistically suppress prostate cancer growth. Collectively, our findings uncover an insight of EZH2 functions in fine-tuning PARP1 activity during DNA damage repair and cancer progression, which provides a rationale for combinational targeting EZH2 and PARP1 in cancer.

Sex is an important but understudied factor in the genetics of human diseases. Analyses using a combination of gene expression data, ENCODE data, and evolutionary data of sex-biased gene expression in human tissues can give insight into the regulatory and evolutionary forces acting on sex-biased genes. In this study, we analyzed the differentially expressed genes between males and females. On the X chromosome, we used a novel method and investigated the status of genes that escape X-chromosome inactivation (escape genes), taking into account the clonality of lymphoblastoid cell lines (LCLs). To investigate the regulation of sex-biased differentially expressed genes (sDEG), we conducted pathway and transcription factor enrichment analyses on the sDEGs, as well as analyses on the genomic distribution of sDEGs. Evolutionary analyses were also conducted on both sDEGs and escape genes. Genome-wide, we characterized differential gene expression between sexes in 462 RNA-seq samples and identified 587 sex-biased genes, or 3.2% of the genes surveyed. On the X chromosome, sDEGs were distributed in evolutionary strata in a similar pattern as escape genes. We found a trend of negative correlation between the gene expression breadth and nonsynonymous over synonymous mutation (dN/dS) ratios, showing a possible pleiotropic constraint on evolution of genes. Genome-wide, nine transcription factors were found enriched in binding to the regions surrounding the transcription start sites of female-biased genes. Many pathways and protein domains were enriched in sex-biased genes, some of which hint at sex-biased physiological processes. These findings lend insight into the regulatory and evolutionary forces shaping sex-biased gene expression and their involvement in the physiological and pathological processes in human health and diseases.