Respiratory disease caused by the 2019 novel coronavirus (2019-nCoV) pneumonia first emerged in Wuhan, Hubei Province, China, in December 2019 and spread rapidly to other provinces and other countries. Angiotensin-converting enzyme 2 (ACE2) is the receptor for SARS-CoV and has been suggested to be also the receptor for 2019-nCoV. Paradoxically, ACE2

Genetic studies are traditionally based on single-gene analysis. The use of these analyses can pose tremendous challenges for elucidating complicated genetic interplays involved in complex human diseases. Modern pathway-based analysis provides a technique, which allows a comprehensive understanding of the molecular mechanisms underlying complex diseases. Extensive studies utilizing the methods and applications for pathway-based analysis have significantly advanced our capacity to explore large-scale omics data, which has rapidly accumulated in biomedical fields. This article is a comprehensive review of the pathway-based analysis methods—the powerful methods with the potential to uncover the biological depths of the complex diseases. The general concepts and procedures for the pathway-based analysis methods are introduced and then, a comprehensive review of the major approaches for this analysis is presented. In addition, a list of available pathway-based analysis software and databases is provided. Finally, future directions and challenges for the methodological development and applications of pathway-based analysis techniques are discussed. This review will provide a useful guide to dissect complex diseases.

Atrial fibrillation (AF) is the most common cardiac arrhythmia at the clinic. Recent GWAS identified several variants associated with AF, but they account for <10% of heritability. Gene-gene interaction is assumed to account for a significant portion of missing heritability. Among GWAS loci for AF, only three were replicated in the Chinese Han population, including SNP rs2106261 (G/A substitution) in ZFHX3, rs2200733 (C/T substitution) near PITX2c, and rs3807989 (A/G substitution) in CAV1. Thus, we analyzed the interaction among these three AF loci. We demonstrated significant interaction between rs2106261 and rs2200733 in three independent populations and combined population with 2,020 cases/5,315 controls. Compared to non-risk genotype GGCC, two-locus risk genotype AATT showed the highest odds ratio in three independent populations and the combined population (OR=5.36 (95% CI 3.87-7.43), P=8.00×10-24). The OR of 5.36 for AATT was significantly higher than the combined OR of 3.31 for both GGTT and AACC, suggesting a synergistic interaction between rs2106261 and rs2200733. Relative excess risk due to interaction (RERI) analysis also revealed significant interaction between rs2106261 and rs2200733 when exposed two copies of risk alleles (RERI=2.87, P<1.00×10-4) or exposed to one additional copy of risk allele (RERI=1.29, P<1.00×10-4). The INTERSNP program identified significant genotypic interaction between rs2106261 and rs2200733 under an additive by additive model (OR=0.85, 95% CI: 0.74-0.97, P=0.02). Mechanistically, PITX2c negatively regulates expression of miR-1, which negatively regulates expression of ZFHX3, resulting in a positive regulation of ZFHX3 by PITX2c; ZFHX3 positively regulates expression of PITX2C, resulting in a cyclic loop of cross-regulation between ZFHX3 and PITX2c. Both ZFHX3 and PITX2c regulate expression of NPPA, TBX5 and NKX2.5. These results suggest that cyclic cross-regulation of gene expression is a molecular basis for gene-gene interactions involved in genetics of complex disease traits.

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BackgroundAldolase A (ALDOA) is one of the glycolytic enzymes primarily found in the developing embryo and adult muscle. Recently, a new role of ALDOA in several cancers has been proposed. However, the underlying mechanism remains obscure and inconsistent. In this study, we tried to investigate ALDOA-associated (AA) genes using available microarray datasets to help elucidating the role of ALDOA in cancer.ResultsIn the dataset of patients with non-small-cell lung cancer (NSCLC, E-GEOD-19188), 3448 differentially expressed genes (DEGs) including ALDOA were identified, in which 710 AA genes were found to be positively associated with ALDOA. Then according to correlation coefficients between each pair of AA genes, ALDOA-associated gene co-expression network (GCN) was constructed including 182 nodes and 1619 edges. 11 clusters out of GCN were detected by ClusterOne plugin in Cytoscape, and only 3 of them have more than three nodes. These three clusters were functionally enriched. A great number of genes (43/79, 54.4%) in the biggest cluster (Cluster 1) primarily involved in biological process like cell cycle process (P a = 6.76E-26), mitotic cell cycle (P a = 4.09E-19), DNA repair (P a = 1.13E-04), M phase of meiotic cell cycle (P a = 0.006), positive regulation of ubiquitin-protein ligase activity during mitotic cell cycle (P a = 0.014). AA genes with highest degree and betweenness were considered as hub genes of GCN, namely CDC20, MELK, PTTG1, CCNB2, CDC45, CCNB1, TK1 and PSMB2, which could distinguish cancer from normal controls with ALDOA. Their positive association with ALDOA remained after removing the effect of HK2 and PKM, the two rate limiting enzymes in glycolysis. Further, knocking down ALDOA blocked breast cancer cells in the G0/G1 phase under minimized glycolysis. All suggested that ALDOA might affect cell cycle progression independent of glycolysis. RT-qPCR detection confirmed the relationship of ALDOA with CDC45 and CCNB2 in breast tumors. High expression of the hub genes indicated poor outcome in NSCLC. ALDOA could improve their predictive power.ConclusionsALDOA could contribute to the progress of cancer, at least partially through its association with genes relevant to cell cycle independent of glycolysis. AA genes plus ALDOA represent a potential new signature for development and prognosis in several cancers.

Germline polymorphisms are linked with differential survival outcomes in cancers but are not well studied in nasopharyngeal carcinoma (NPC). Here, a two-phase association study is conducted to discover germline polymorphisms that are associated with the prognosis of NPC. The discovery phase includes two consecutive hospital cohorts of patients with NPC from Southern China. Exome-wide genotypes at 246 173 single nucleotide polymorphisms (SNPs) are determined, followed by survival analysis for each SNP under Cox proportional hazard regression model. Candidate SNP is replicated in another two independent cohorts from Southern China and Singapore. Meta-analysis of all samples (n = 5553) confirms that the presence of rs1131636-T, located in the 3′-UTR of RPA1, confers an inferior overall survival (HR = 1.33, 95% CI = 1.20-1.47, P = 6.31 × 10 −8 ). Bioinformatics and biological assays show that rs1131636 has regulatory effects on upstream RPA1. Functional studies further demonstrate that RPA1 promotes the growth, invasion, migration, and radioresistance of NPC cells. Additionally, miR-1253 is identified as a suppressor for RPA1 expression, likely through regulation of its binding affinity to rs1131636 locus. Collectively, these findings provide a promising biomarker aiding in stratifying patients with poor survival, as well as a potential drug target for NPC.

L-Ascorbate (Asc) plays important roles in cell growth and plant development, and its de novo biosynthesis was catalyzed by the first rate-limiting enzyme VTC1. However, the function and regulatory mechanism of VTC1 involved in cell development is obscure in Gossypium hirsutum. Herein, the Asc content and AsA/DHA ratio were accumulated and closely linked with fiber development. The GhVTC1 encoded a typical VTC1 protein with functional conserved domains and expressed preferentially during fiber fast elongation stages. Functional complementary analysis of GhVTC1 in the loss-of-function Arabidopsis vtc1-1 mutants indicated that GhVTC1 is genetically functional to rescue the defects of mutants to normal or wild type (WT). The significant shortened primary root in vtc1-1 mutants was promoted to the regular length of WT by the ectopic expression of GhVTC1 in the mutants. Additionally, GhVTC1 expression was induced by ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC), and the GhVTC1 promoter showed high activity and included two ethylene-responsive elements (ERE). Moreover, the 5′-truncted promoters containing the ERE exhibited increased activity by ACC treatment. Our results firstly report the cotton GhVTC1 function in promoting cell elongation at the cellular level, and serve as a foundation for further understanding the regulatory mechanism of Asc-mediated cell growth via the ethylene signaling pathway.

Rates of gastroesophageal junction adenocarcinomas (GEJAs) have shown an alarming increase; however, the genetic background of GEJA and its Siewert classification have yet to be uncovered. Here, 60 paired tumor and normal DNA samples from GEJA patients were analyzed by whole-exome sequencing. Among them, 13 were Siewert type I, 14 were type II, and 33 were type III. A predominance of C/G>T/A substitutions was discovered in GEJA, followed by C/G>A/T substitutions. Notably, Siewert type I and type II/III display distinct sets of driver genes, mutational spectrum, and recurrently disrupted pathways. Siewert type I showed similarity to esophageal adenocarcinomas (EACs) and the chromosomal instability subtype of stomach adenocarcinomas, while Siewert type II/III showed similarity to the genomic stable subtype of stomach adenocarcinoma. We also found that mutation of FBXW7, a driver gene of GEJA, was enriched in Siewert type I. Our data identify differences between GEJA and stomach/EACs at the genomic level and provide evidence for differential treatment based on Siewert classification of GEJA.