Integrated analysis of SNP, CNV and gene expression data in genetic association studies

Genome-wide analysis to uncover how Pocillopora acuta survives the challenging intertidal environment

Characterisation of genomic variation among corals can help uncover variants underlying trait differences and contribute towards genotype prioritisation in coastal restoration projects. For example, there is growing interest in identifying resilient genotypes for transplantation, and to better understand the genetic processes that allow some individuals to survive in specific conditions better than others. The coral species Pocillopora acuta is known to survive in a wide range of habitats, from reefs artificial coastal defences, suggesting its potential use as a starter species for ecological engineering efforts involving coral transplantation onto intertidal seawalls. However, the intertidal section of coastal armour is a challenging environment for corals, with conditions during periods of emersion being particularly stressful. Here, we scanned the entire genome of P. acuta corals to identify the regions harbouring single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) that separate intertidal colonies (n = 18) from those found in subtidal areas (n = 21). Findings revealed 74,391 high quality SNPs distributed across 386 regions of the P. acuta genome. While the majority of the detected SNPs were in non-coding regions, 12% were identified in exons (i.e. coding regions). Functional SNPs that were significantly associated with intertidal colonies were found in overrepresented genomic regions linked to cellular homeostasis, metabolism, and signalling processes, which may represent local environmental adaptation in the intertidal. Interestingly, regions that exhibited CNVs were also associated with metabolic and signalling processes, suggesting P. acuta corals living in the intertidal have a high capacity to perform biological functions critical for survival in extreme environments.

Copy number variations and their effect on the plasma proteome

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Copy number variation of the ZNF679 gene in cattle and its association analysis with growth traits

Copy number variation (CNV) is an important member of genetic structural variation that exists widely in animal genomes and is between 50 bp and several Mb in length and widely used in research's of animal genetics and breeding. ZNF679 is an important transcription factor, which has been found association with diseases in the human genome many times. This gene has also been found to be associated with cattle growth traits in previous re-sequencing studies. We tested the CNVs of the ZNF679 gene in 809 individuals from 7 Chinese cattle breeds and tested the association between the CNVs and growth traits in 552 individuals from 5 breeds. The results demonstrated the correlation the correlation between the CNVs of the ZNF679 gene and some Chinese cattle (QC cattle and XN cattle) growth traits. To sum up, this study indicated that ZNF679-CNVs can be used as a candidate gene for molecular genetic marker-assisted selection breeding for cattle growth traits to contribute to the development of genetic improvement of Chinese cattle.

Osteosarcoma Multi-Omics Landscape and Subtypes

Osteosarcoma (OS) is the most common primary bone malignancy that exhibits remarkable histologic diversity and genetic heterogeneity. The complex nature of osteosarcoma has confounded precise molecular categorization, prognosis, and prediction for this disease. In this study, we performed a comprehensive multiplatform analysis on 86 osteosarcoma tumors, including somatic copy-number alteration, gene expression and methylation, and identified three molecularly distinct and clinically relevant subtypes of osteosarcoma. The subgrouping criteria was validated on another cohort of osteosarcoma tumors. Previously unappreciated osteosarcoma-type-specific changes in specific genes' copy number, expression and methylation were revealed based on the subgrouping. The subgrouping and novel gene signatures provide insights into refining osteosarcoma therapy and relationships to other types of cancer.

Comprehensive prognostic and immunological analysis of Ubiquitin Specific Peptidase 28 in pan-cancers and identification of its role in hepatocellular carcinoma cell lines

BACKGROUND

Ubiquitin Specific Peptidase 28 (USP28), as a member of the DUBs family, has been reported to regulate the occurrence and development of some tumors, but its oncogenic role in tumor immunity is still unknown.

METHODS

The comprehensive view of USP28 expression in tumor and normal samples was obtained from public databases, including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE). We analyzed the genomic alterations of USP28 in various cancers using the cBioPortal dataset. Besides, gene set enrichment analysis was used to analyze the associated cancer hallmarks with USP28 expression, and TIMER2.0 was taken to investigate the immune cell infiltrations related to the USP28 level.

RESULTS

USP28 is highly expressed in most tumors and has prognostic value across various cancer types. Moreover, a significant correlation exists between USP28 and immune regulators, clinical staging, checkpoint inhibitor response, MSI, TMB, CNV, MMR defects, and DNA methylation. Additionally, USP28 expression is strongly associated with the infiltration levels of neutrophils and NK cells in most tumor types. One of the most significant findings of our study was that USP28 could serve as a significant predictor of anti-CTLA4 therapy response in melanoma patients. Additionally, our molecular biology experiments validated that the knockdown of USP28 substantially reduced the proliferative and invasive abilities of the HCC cell lines.

CONCLUSIONS

Our study suggests that USP28 could potentially serve as a biomarker for cancer immunologic infiltration and poor prognosis, with potential applications in developing novel cancer treatment strategies.

An Integrative Co-localization (INCO) Analysis for SNV and CNV Genomic Features With an Application to Taiwan Biobank Data

Genomic studies have been a major approach to elucidating disease etiology and to exploring potential targets for treatments of many complex diseases. Statistical analyses in these studies often face the challenges of multiplicity, weak signals, and the nature of dependence among genetic markers. This situation becomes even more complicated when multi-omics data are available. To integrate the data from different platforms, various integrative analyses have been adopted, ranging from the direct union or intersection operation on sets derived from different single-platform analysis to complex hierarchical multi-level models. The former ignores the biological relationship between molecules while the latter can be hard to interpret. We propose in this study an integrative approach that combines both single nucleotide variants (SNVs) and copy number variations (CNVs) in the same genomic unit to co-localize the concurrent effect and to deal with the sparsity due to rare variants. This approach is illustrated with simulation studies to evaluate its performance and is applied to low-density lipoprotein cholesterol and triglyceride measurements from Taiwan Biobank. The results show that the proposed method can more effectively detect the collective effect from both SNVs and CNVs compared to traditional methods. For the biobank analysis, the identified genetic regions including the gene VNN2 could be novel and deserve further investigation.

A pan-cancer analysis of the expression of gasdermin genes in tumors and their relationship with the immune microenvironment

BACKGROUND

Gasdermins (GSDMs) are a class of proteins related to pyrolysis and in humans, consist of GSDMA, GSDMB, GSDMC, GSDMD, DFNA5, and DFNB59. The inflammatory factors and cell contents released during pyrolysis can recruit immune cells and change the microenvironment. However, to date, there is a paucity of studies examining the relationship between GSDMs and the immune microenvironment in tumors. Therefore, this current report analyzed the expression of GSDM genes in tumors and their relationship with the immune microenvironment.

METHODS

Apply GSCALite and GEPIA2 online analysis tools to analyze the gene expression levels and the Single nucleotide variant (SNV), copy number variation (CNV), and methylation characteristics of GSDM genes respectively. Use R software or TISIDB online analysis tool to carry out the correlation analysis required in the article. Furthermore, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to examine the role of these GSDM genes in various cancers.

RESULTS

The results demonstrated that CNV can cause an increase in GSDM gene expression, and methylation can inhibit GSDM gene expression. The elevated expression of GSDMA, GSDMB, GSDMC, GSDMD, and DFNA5 in some or most tumors was often accompanied by elevated immune scores, increased immune cell infiltration, and high expression of major histocompatibility complex (MHC) molecules, chemokines and their receptors, and immune checkpoint-related genes. However, DFNB59 was often negatively correlated with these indicators in tumors. GSDMD was the most highly expressed GSDM protein in various normal tissues and tumors, and showed the strongest correlation with immune microenvironment-related genes. Moreover, the methylation of GSDMD was accompanied by low immune cell infiltration, low expression of MHC molecule-related genes, low expression of chemokines and receptor-related genes, and low expression of immune checkpoint-related genes.

CONCLUSIONS

Therefore, the expression of GSDM-related genes is associated with the tumor immune microenvironment. The GSDM genes, especially GSDMD, may be used as therapeutic targets to predict or change the tumor microenvironment and as biomarkers to predict the therapeutic efficacy of immune checkpoint inhibitors.

Copy number variation: Characteristics, evolutionary and pathological aspects

Copy number variants (CNVs) were the subject of extensive research in the past years. They are common features of the human genome that play an important role in evolution, contribute to population diversity, development of certain diseases, and influence host–microbiome interactions. CNVs have found application in the molecular diagnosis of many diseases and in non-invasive prenatal care, but their full potential is only emerging. CNVs are expected to have a tremendous impact on screening, diagnosis, prognosis, and monitoring of several disorders, including cancer and cardiovascular disease. Here, we comprehensively review basic definitions of the term CNV, outline mechanisms and factors involved in CNV formation, and discuss their evolutionary and pathological aspects. We suggest a need for better defined distinguishing criteria and boundaries between known types of CNVs.

Integrating multiple microarray dataset analysis and machine learning methods to reveal the key genes and regulatory mechanisms underlying human intervertebral disc degeneration

Intervertebral disc degeneration (IDD), a major cause of lower back pain, has multiple contributing factors including genetics, environment, age, and loading history. Bioinformatics analysis has been extensively used to identify diagnostic biomarkers and therapeutic targets for IDD diagnosis and treatment. However, multiple microarray dataset analysis and machine learning methods have not been integrated. In this study, we downloaded the mRNA, microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) expression profiles (GSE34095, GSE15227, GSE63492 GSE116726, GSE56081 and GSE67566) associated with IDD from the GEO database. Using differential expression analysis and recursive feature elimination, we extracted four optimal feature genes. We then used the support vector machine (SVM) to make a classification model with the four optimal feature genes. The ROC curve was used to evaluate the model's performance, and the expression profiles (GSE63492, GSE116726, GSE56081, and GSE67566) were used to construct a competitive endogenous RNA (ceRNA) regulatory network and explore the underlying mechanisms of the feature genes. We found that three miRNAs (hsa-miR-4728-5p, hsa-miR-5196-5p, and hsa-miR-185-5p) and three circRNAs (hsa_circRNA_100723, hsa_circRNA_104471, and hsa_circRNA_100750) were important regulators with more interactions than the other RNAs across the whole network. The expression level analysis of the three datasets revealed that BCAS4 and SCRG1 were key genes involved in IDD development. Ultimately, our study proposes a novel approach to determining reliable and effective targets in IDD diagnosis and treatment.

The Polymorphism rs2968 of LSS Gene Confers Susceptibility to Age-Related Cataract

Research showed that lanosterol can decrease protein aggregation in lens and reduce cataract formation. Lanosterol synthase (LSS) and 3-Hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) are the limiting enzymes in the process of synthesis of lanosterol. We demonstrate to investigate the association between functional single-nucleotide polymorphisms (SNPs) of LSS and HMGCR genes and age-related cataract (ARC) risks in Han Chinese population from Jiangsu Eye Study. This is a case-control study. We collected participants' venous blood for DNA genotyping and lens capsule samples for RNA. The SNPs of the genes were assayed with TaqMan RT-PCR genotyping. The quantitative RT-PCR was used to detect the LSS mRNA levels of lens epithelial cells (LECs) in individuals. The chi-square test was used to compare differences between ARC groups and controls of each SNP and to calculate the odds ratio (OR). We found that LSS-rs2968 of ARCs was different from controls (p = 0.018), but the significance was lost after Bonferroni correction (p = 0.072). We then further performed stratification analysis and found that LSS-rs2968 A allele was associated with nuclear type of ARC risk in Chinese population (p = 0.012, OR = 0.68). Consequently, we found that the mRNA expression of LSS was lower in LECs of all subtypes of ARC group than that of control group (p < 0.05). LSS-rs2968 A allele might play a role in the formation and development of nuclear type of ARC risk in Chinese population.

Copy Number Variation of the PIGY Gene in Sheep and Its Association Analysis with Growth Traits

Simple Summary

The PIGY (phosphatidylinositol glycan anchor biosynthesis class Y) gene is a member of the PIG gene family and encodes the glycosylphosphatidylinositol-N-acetylglucosaminyltransferase (GPI-GnT) complex. It initiates the biosynthesis of GPI and plays an important role in cell–cell interactions. Sequencing has revealed a 3600 bp copy number variation (CNV) in exon 2 of the PIGY gene in sheep, potentially altering a functional part of the protein. The CNV overlaps 28 quantitative trait loci that are relevant to some economic traits like muscle density and carcass weight. We screened for this CNV of the PIGY gene in 569 individuals, namely, 240 Chaka sheep (CKS), 168 Hu sheep (HS), and 161 small-tailed Han sheep (STHS), and analyzed the association between the presence of this CNV and sheep body size traits. The results showed that the loss-type CNV was more prevalent than other types in these three breeds, and there were significant effects of the PIGY gene CNV on body weight, chest circumference, and circumference of cannon bone of sheep. The results showed that sheep with gain-type CNV had better growth traits than those with other types. The findings reveal the relationship between the CNV of the PIGY gene and growth traits of sheep, suggesting that CNV could be utilized for improved molecular breeding of sheep.

Abstract

Copy number variation (CNV) is a type of genomic variation with an important effect on animal phenotype. We found that the PIGY gene contains a 3600 bp copy number variation (CNV) region located in chromosome 6 of sheep (Oar_v4.0 36,121,601–36,125,200 bp). This region overlaps with multiple quantitative trait loci related to phenotypes like muscle density and carcass weight. Therefore, in this study, the copy number variation of the PIGY gene was screened in three Chinese sheep breeds, namely, Chaka sheep (CKS, May of 2018, Wulan County, Qinghai Province, China), Hu sheep (HS, May of 2015, Mengjin County, Henan Province, China), and small-tailed Han sheep (STHS, May of 2016, Yongjing, Gansu Province, China). Association analyses were performed on the presence of CNV and sheep body size traits. We used real-time quantitative PCR (qPCR) to detect the CNV for association analysis. According to the results, the loss-type CNV was more common than other types in the three breeds (global average: loss = 61.5%, normal = 17.5%, and gain = 21.0%). The association analysis also showed significant effects of the PIGY gene CNV on body weight, chest circumference, and circumference of the cannon bone of sheep. Sheep with gain-type CNV had better growth traits than those with other types. The results indicate a clear relationship between the PIGY gene CNV and growth traits of sheep, suggesting the use of CNV as a new molecular breeding marker.

Identification of Dysregulated Competitive Endogenous RNA Networks Driven by Copy Number Variations in Malignant Gliomas

Gliomas represent 80% of malignant brain tumors. Because of the high heterogeneity, the oncogenic mechanisms in gliomas are still unclear. In this study, we developed a new approach to identify dysregulated competitive endogenous RNA (ceRNA) interactions driven by copy number variation (CNV) in both lower-grade glioma (LGG) and glioblastoma multiforme (GBM). By analyzing genome and transcriptome data from The Cancer Genome Atlas (TCGA), we first found out the protein coding genes and long non-coding RNAs (lncRNAs) significantly affected by CNVs and further determined CNV-driven dysregulated ceRNA interactions by a customized pipeline. We obtained 13,776 CNV-driven dysregulated ceRNA pairs (including 3,954 mRNAs and 306 lncRNAs) in LGG and 262 pairs (including 221 mRNAs and 11 lncRNAs) in GBM, respectively. Our results showed that most of the ceRNA interactions were weakened by CNVs in both LGG and GBM, and many CNV-driven genes shared the same ceRNAs in the dysregulated ceRNA networks. Functional analysis indicated that the CNV-driven ceRNA network involved in some important mechanisms of tumorigenesis, such as cell cycle, p53 signaling pathway and TGF-beta signaling pathway. Further investigation of the ceRNA pairs in the communities from the dysregulated ceRNA network revealed more detailed biological functions related to the oncogenesis of malignant gliomas. Moreover, by exploring the association of CNV-driven ceRNAs with prognosis and histological subtype, we found that the copy number status of MTAP, KLHL9, and ELAVL2 related to the overall survival in LGG and showed high correlation with histological subtype. In conclusion, this study provided new insight into the molecular mechanisms and clinical biomarkers in gliomas.

MicroRNA binding mediated Functional sequence variant in 3'-UTR of DNA repair Gene XPC in Age-related Cataract

DNA oxidative damage repair is strongly involved in the pathogenesis of age-related cataract (ARC). The sequence variants of in coding region of DNA repair genes have been shown to be associated with ARC. It is known that single nucleotide polymorphisms (SNPs) in the 3′-terminal untranslated region (3′-UTR) can alter the gene expression by binding with microRNAs (miRNAs). We hypothesize that SNP(s) in miRNA binding site of certain DNA oxidative damage repair genes might associate with ARC risk. We examined 10 miRNA binding SNPs in 3′-UTR of 7 oxidative damage genes and revealed the XPC- rs2229090 C allele was associated with nuclear type of ARC (ARNC) risk in Chinese population. The individuals with the variant G allele (CG and GG) of XPC- rs2229090 had higher XPC mRNA expression compared to individuals carrying CC genotype. The in vitro assay showed that luciferase reporter gene expression can be down regulated by hsa-miR-589-5p in cells transfected with rs2229090 C allele compared to G allele. These results suggested that the C allele of XPC-2229090 increase the risk with ARNC. The mechanism underlying might be due to the stronger interation of the C allele with hsa-miR-589-5p, resulting in lower XPC expression and DNA repair capability than the individuals carring G allele in lens.