Introduction to Deep Sequencing and Its Application to Drug Addiction Research with a Focus on Rare Variants

Through linkage analysis, candidate gene approach, and genome-wide association studies (GWAS), many genetic susceptibility factors for substance dependence have been discovered such as the alcohol dehydrogenase gene (ALDH2) for alcohol dependence (AD) and nicotinic acetylcholine receptor (nAChR) subunit variants on chromosomes 8 and 15 for nicotine dependence (ND). However, these confirmed genetic factors contribute only a small portion of the heritability responsible for each addiction. Among many potential factors, rare variants in those identified and unidentified susceptibility genes are supposed to contribute greatly to the missing heritability. Several studies focusing on rare variants have been conducted by taking advantage of next-generation sequencing technologies, which revealed that some rare variants of nAChR subunits are associated with ND in both genetic and functional studies. However, these studies investigated variants for only a small number of genes and need to be expanded to broad regions/genes in a larger population. This review presents an update on recently developed methods for rare-variant identification and association analysis and on studies focused on rare-variant discovery and function related to addictions.     

Mutations and epimutations in the origin of cancer

Cancer is traditionally viewed as a disease of abnormal cell proliferation controlled by a series of mutations. Mutations typically affect oncogenes or tumor suppressor genes thereby conferring growth advantage. Genomic instability facilitates mutation accumulation. Recent findings demonstrate that activation of oncogenes and inactivation of tumor suppressor genes, as well as genomic instability, can be achieved by epigenetic mechanisms as well. Unlike genetic mutations, epimutations do not change the base sequence of DNA and are potentially reversible. Similar to genetic mutations, epimutations are associated with specific patterns of gene expression that are heritable through cell divisions. Knudson's hypothesis postulates that inactivation of tumor suppressor genes requires two hits, with the first hit occurring either in somatic cells (sporadic cancer) or in the germline (hereditary cancer) and the second one always being somatic. Studies on hereditary and sporadic forms of colorectal carcinoma have made it evident that, apart from genetic mutations, epimutations may serve as either hit or both. Furthermore, recent next-generation sequencing studies show that epigenetic genes, such as those encoding histone modifying enzymes and subunits for chromatin remodeling systems, are themselves frequent targets of somatic mutations in cancer and can act like tumor suppressor genes or oncogenes. This review discusses genetic vs. epigenetic origin of cancer, including cancer susceptibility, in light of recent discoveries. Situations in which mutations and epimutations occur to serve analogous purposes are highlighted.     

Network analysis of genome-wide association studies for drug target prioritisation

Over the past decades, genome-wide association studies (GWAS) have led to a dramatic expansion of genetic variants implicated with human traits and diseases. These advances are expected to result in new drug targets but the identification of causal genes and the cell biology underlying human diseases from GWAS remains challenging. Here, we review protein interaction network-based methods to analyse GWAS data. These approaches can rank candidate drug targets at GWAS-associated loci or among interactors of disease genes without direct genetic support. These methods identify the cell biology affected in common across diseases, offering opportunities for drug repurposing, as well as be combined with expression data to identify focal tissues and cell types. Going forward, we expect that these methods will further improve from advances in the characterisation of context specific interaction networks and the joint analysis of rare and common genetic signals.     

Copy Number Variation Analysis on a Non-Hodgkin Lymphoma Case-Control Study Identifies an 11q25 Duplication Associated with Diffuse Large B-Cell Lymphoma

Recent GWAS have identified several susceptibility loci for NHL. Despite these successes, much of the heritable variation in NHL risk remains to be explained. Common copy-number variants are important genomic sources of variability, and hence a potential source to explain part of this missing heritability. In this study, we carried out a CNV analysis using GWAS data from 681 NHL cases and 749 controls to explore the relationship between common structural variation and lymphoma susceptibility. Here we found a novel association with diffuse large B-cell lymphoma (DLBCL) risk involving a partial duplication of the C-terminus region of the LOC283177 long non-coding RNA that was further confirmed by quantitative PCR. For chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), known somatic deletions were identified on chromosomes 13q14, 11q22-23, 14q32 and 22q11.22. Our study shows that GWAS data can be used to identify germline CNVs associated with disease risk for DLBCL and somatic CNVs for CLL/SLL.     

Prevalent mutations in prostate cancer

Quantitative and structural genetic alterations cause the development and progression of prostate cancer. A number of genes have been implicated in prostate cancer by genetic alterations and functional consequences of the genetic alterations. These include the ELAC2 (HPC2), MSR1, and RNASEL (HPC1) genes that have germline mutations in familial prostate cancer; AR, ATBF1, EPHB2 (ERK), KLF6, mitochondria DNA, p53, PTEN, and RAS that have somatic mutations in sporadic prostate cancer; AR, BRCA1, BRCA2, CHEK2 (RAD53), CYP17, CYP1B1, CYP3A4, GSTM1, GSTP1, GSTT1, PON1, SRD5A2, and VDR that have germline genetic variants associated with either hereditary and/or sporadic prostate cancer; and ANXA7 (ANX7), KLF5, NKX3-1 (NKX3.1), CDKN1B (p27), and MYC that have genomic copy number changes affecting gene function. More genes relevant to prostate cancer remain to be identified in each of these gene groups. For the genes that have been identified, most need additional genetic, functional, and/or biochemical examination. Identification and characterization of these genes will be a key step for improving the detection and treatment of prostate cancer.     

Type 2 Diabetes Mellitus: New Genetic Insights will Lead to New Therapeutics

Type 2 diabetes is a disorder of dysregulated glucose homeostasis. Normal glucose homeostasis is a complex process involving several interacting mechanisms, such as insulin secretion, insulin sensitivity, glucose production, and glucose uptake. The dysregulation of one or more of these mechanisms due to environmental and/or genetic factors, can lead to a defective glucose homeostasis. Hyperglycemia is managed by augmenting insulin secretion and/or interaction with hepatic glucose production, as well as by decreasing dietary caloric intake and raising glucose metabolism through exercise. Although these interventions can delay disease progression and correct blood glucose levels, they are not able to cure the disease or stop its progression entirely. Better management of type 2 diabetes is sorely needed. Advances in genotyping techniques and the availability of large patient cohorts have made it possible to identify common genetic variants associated with type 2 diabetes through genome-wide association studies (GWAS). So far, genetic variants on 19 loci have been identified. Most of these loci contain or lie close to genes that were not previously linked to diabetes and they may thus harbor targets for new drugs. It is also hoped that further genetic studies will pave the way for predictive genetic screening. The newly discovered type 2 diabetes genes can be classified based on their presumed molecular function, and we discuss the relation between these gene classes and current treatments. We go on to consider whether the new genes provide opportunities for developing alternative drug therapies.Key Words: Type 2 diabetes, drug targets, genetics, personalized medicine.     

Germline and somatic mutations in hMSH6 and hMSH3 in gastrointestinal cancers of the microsatellite mutator phenotype

Hereditary and sporadic gastrointestinal cancer of the microsatellite mutator phenotype (MMP) is characterized by a remarkable genomic instability at simple repeated sequences. The genomic instability is often caused by germline and somatic mutations in DNA mismatch repair (MMR) genes hMSH2 and hMLH1. The MMP can be also caused by epigenetic inactivation of hMLH1. The MMP generates many somatic frameshift mutations in genes containing mononucleotide repeats. We previously reported that in MMP tumors the hMSH6 and hMSH3 MMR genes often carry frameshift mutations in their (C)(8) and (A)(8) tracks, respectively. We proposed that these 'secondary mutator mutations' contribute to a gradual manifestation of the MMP. Here we report the detection of other frameshift, nonsense, and missense mutations in these genes in colon and gastric cancers of the MMP. A germline frameshift mutation was found in hMSH6 in a colon tumor harboring another somatic frameshift mutation. Several germline sequence variants and somatic missense mutations at conserved residues were detected in hMSH6 and only one was detected in hMSH3. Of the three hMSH6 germline variants in conserved residues, one coexisted with a somatic mutation at the (C)(8) track and another had a somatic missense mutation. We suggest that some of these germline and somatic missense variants are pathogenic. While biallelic hMSH6 and hMSH3 frameshift mutations were found in some tumors, many tumors seemed to contain only monoallelic mutations. In some tumors, these somatic monoallelic frameshift mutations at the (C)(8) and (A)(8) tracks were found to coexist with other somatic mutations in the other allele, supporting their functionality during tumorigenesis. However, the low incidence of these additional somatic mutations in hMSH6 and hMSH3 leaves many tumors with only monoallelic mutations. The impact of the frameshift mutations in gene expression was studied by comparative analysis of RNA and protein expression in different tumor cell clones with different genotypes. The results show that the hMSH6 (C)(8) frameshift mutation abolishes protein expression, ruling out a dominant negative effect by a truncated protein. We suggest the functionality of these secondary monoallelic mutator mutations in the context of an accumulative haploinsufficiency model.     

抑郁症易感基因和抗抑郁药物靶点相关[]神经细胞类型及相互作用网络分析

基于抑郁症的全基因组关联分析研究(GWAS),对于获得的单核苷酸多态性位点(SNP)使用Haploreg软件进行基因注释,得到SNP注释的102个易感基因.。使用MAGMA软件对GWAS的汇总统计数据做基因水平的分析,获得了270个校正之后显著的基因,两者合并共得到320个抑郁症易感基因。通过药物数据库Drugbank获取133个抗抑郁药物靶点基因。使用EWCE包对抑郁症易感基因和抗抑郁药物靶点在三套脑组织单细胞测序数据中,分别进行神经细胞类型富集分析。结果发现大脑皮质的GABA神经元(抑制性神经元)和谷氨酸能神经元(兴奋性神经元)是抑郁症易感基因和抗抑郁药物靶点共同的神经元。这两种类型的神经细胞可能是抗抑郁药物与抑郁症易感基因相互作用的神经细胞,另外少突胶质前体细胞可能是抑郁症特有的易感神经细胞。使用Network Calculator软件构建网络并进行进行网络拓扑学参数分析。结果表明抑郁症易感基因与抗抑郁药物靶点组成了一个具有显著的相互连接的网络。本研究从单细胞层面揭示抑郁症的遗传机制,在网络层面为寻找新的抗抑郁药物靶点提供了一定的启示。     

Allelic Selection of Amplicons in Glioblastoma Revealed by Combining Somatic and Germline Analysis

Cancer is a disease driven by a combination of inherited risk alleles coupled with the acquisition of somatic mutations, including amplification and deletion of genomic DNA. Potential relationships between the inherited and somatic aspects of the disease have only rarely been examined on a genome-wide level. Applying a novel integrative analysis of SNP and copy number measurements, we queried the tumor and normal-tissue genomes of 178 glioblastoma patients from the Cancer Genome Atlas project for preferentially amplified alleles, under the hypothesis that oncogenic germline variants will be selectively amplified in the tumor environment. Selected alleles are revealed by allelic imbalance in amplification across samples. This general approach is based on genetic principles and provides a method for identifying important tumor-related alleles. We find that SNP alleles that are most significantly overrepresented in amplicons tend to occur in genes involved with regulation of kinase and transferase activity, and many of these genes are known contributors to gliomagenesis. The analysis also implicates variants in synapse genes. By incorporating gene expression data, we demonstrate synergy between preferential allelic amplification and expression in DOCK4 and EGFR. Our results support the notion that combining germline and tumor genetic data can identify regions relevant to cancer biology.     

Nonheritable cellular variability accelerates the evolutionary processes of cancer

Recent cancer studies emphasize that genetic and heritable epigenetic changes drive the evolutionary rate of cancer progression and drug resistance. We discuss the ways in which nonheritable aspects of cellular variability may significantly increase evolutionary rate. Nonheritable variability arises by stochastic fluctuations in cells and by physiological responses of cells to the environment. New approaches to drug design may be required to control nonheritable variability and the evolution of resistance to chemotherapy.     

Germline fitness-based scoring of cancer mutations

A key goal in cancer research is to find the genomic alterations that underlie malignant cells. Genomics has proved successful in identifying somatic variants at a large scale. However, it has become evident that a typical cancer exhibits a heterogenous mutation pattern across samples. Cases where the same alteration is observed repeatedly seem to be the exception rather than the norm. Thus, pinpointing the key alterations (driver mutations) from a background of variations with no direct causal link to cancer (passenger mutations) is difficult. Here we analyze somatic missense mutations from cancer samples and their healthy tissue counterparts (germline mutations) from the viewpoint of germline fitness. We calibrate a scoring system from protein domain alignments to score mutations and their target loci. We show first that this score predicts to a good degree the rate of polymorphism of the observed germline variation. The scoring is then applied to somatic mutations. We show that candidate cancer genes prone to copy number loss harbor mutations with germline fitness effects that are significantly more deleterious than expected by chance. This suggests that missense mutations play a driving role in tumor suppressor genes. Furthermore, these mutations fall preferably onto loci in sequence neighborhoods that are high scoring in terms of germline fitness. In contrast, for somatic mutations in candidate onco genes we do not observe a statistically significant effect. These results help to inform how to exploit germline fitness predictions in discovering new genes and mutations responsible for cancer.     

RUNAWAY COEVOLUTION: ADAPTATION TO HERITABLE AND NONHERITABLE ENVIRONMENTS

Populations evolve in response to the external environment, whether abiotic (e.g., climate) or biotic (e.g., other conspecifics). We investigated how adaptation to biotic, heritable environments differs from adaptation to abiotic, nonheritable environments. We found that, for the same selection coefficients, the coadaptive process between genes and heritable environments is much faster than genetic adaptation to an abiotic nonheritable environment. The increased rate of adaptation results from the positive association generated by reciprocal selection between the heritable environment and the genes responding to it. These associations result in a runaway process of adaptive coevolution, even when the genes creating the heritable environment and genes responding to the heritable environment are unlinked. Although tightening the degree of linkage accelerates the coadaptive process, the acceleration caused by a comparable amount of inbreeding is greater, because inbreeding has a cumulative effect on reducing functional recombination over generations. Our results suggest that that adaptation to local abiotic environmental variation may result in the rapid diversification of populations and subsequent reproductive isolation not directly but rather via its effects on heritable environments and the genes responding to them.     

Mitochondrial DNA Polymerase POLG1 Disease Mutations and Germline Variants Promote Tumorigenic Properties

Germline mutations in mitochondrial DNA polymerase gamma (POLG1) induce mitochondrial DNA (mtDNA) mutations, depletion, and decrease oxidative phosphorylation. Earlier, we identified somatic mutations in POLG1 and the contribution of these mutations in human cancer. However, a role for germline variations in POLG1 in human cancers is unknown. In this study, we examined a role for disease associated germline variants of POLG1, POLG1 gene expression, copy number variation and regulation in human cancers. We analyzed the mutations, expression and copy number variation in POLG1 in several cancer databases and validated the analyses in primary breast tumors and breast cancer cell lines. We discovered 5-aza-2''-deoxycytidine led epigenetic regulation of POLG1, mtDNA-encoded genes and increased mitochondrial respiration. We conducted comprehensive race based bioinformatics analyses of POLG1 gene in more than 33,000 European-Americans and 5,000 African-Americans. We identified a mitochondrial disease causing missense variation in polymerase domain of POLG1 protein at amino acid 1143 (E1143G) to be 25 times more prevalent in European-Americans (allele frequency 0.03777) when compared to African-American (allele frequency 0.00151) population. We identified T251I and P587L missense variations in exonuclease and linker region of POLG1 also to be more prevalent in European-Americans. Expression of these variants increased glucose consumption, decreased ATP production and increased matrigel invasion. Interestingly, conditional expression of these variants revealed that matrigel invasion properties conferred by these germline variants were reversible suggesting a role of epigenetic regulators. Indeed, we identified a set of miRNA whose expression was reversible after variant expression was turned off. Together, our studies demonstrate altered genetic and epigenetic regulation of POLG1 in human cancers and suggest a role for POLG1 germline variants in promoting tumorigenic properties.     

Structural Principles Governing Disease-Causing Germline Mutations

Advancements in sequencing in the past decades enabled not only the determination of the human proteome but also the identification of a large number of genetic variations in the human population. The phenotypic effects of these mutations range from neutral for polymorphisms to severe for some somatic mutations. Disease-causing germline mutations (DCMs) represent a special and largely understudied class with relatively weak phenotypes. While for somatic mutations their effect on protein structure and regulation has been extensively studied in select cases, for germline mutations, this information is currently largely missing. In this analysis, a large amount of DCMs were analyzed and contrasted to polymorphisms from a structural point of view. Our results delineate the characteristic features of DCMs starting at the global level of partitioning proteins into globular, disordered and transmembrane classes, moving toward smaller structural units describing secondary structure elements and molecular surfaces, reaching down to the smallest structural entity, post-translational modifications. We show how these structural entities influence the emergence and possible phenotypic effects of DCMs.     

CCGD-ESCC: A Comprehensive Database for Genetic Variants Associated with Esophageal Squamous Cell Carcinoma in Chinese Population

Esophageal squamous-cell carcinoma (ESCC) is one of the most lethal malignancies in the world and occurs at particularly higher frequency in China. While several genome-wide association studies (GWAS) of germline variants and whole-genome or whole-exome sequencing studies of somatic mutations in ESCC have been published, there is no comprehensive database publically available for this cancer. Here, we developed the Chinese Cancer Genomic Database-Esophageal Squamous Cell Carcinoma (CCGD-ESCC) database, which contains the associations of 69,593 single nucleotide polymorphisms (SNPs) with ESCC risk in 2022 cases and 2039 controls, survival time of 1006 ESCC patients (survival GWAS) and gene expression (expression quantitative trait loci, eQTL) in 94 ESCC patients. Moreover, this database also provides the associations between 8833 somatic mutations and survival time in 675 ESCC patients. Our user-friendly database is a resource useful for biologists and oncologists not only in identifying the associations of genetic variants or somatic mutations with the development and progression of ESCC but also in studying the underlying mechanisms for tumorigenesis of the cancer. CCGD-ESCC is freely accessible at http://db.cbi.pku.edu.cn/ccgd/ESCCdb.     

Targeted deep resequencing of the human cancer genome using next-generation technologies

Next-generation sequencing technologies have revolutionized our ability to identify genetic variants, either germline or somatic point mutations, that occur in cancer. Parallelization and miniaturization of DNA sequencing enables massive data throughput and for the first time, large-scale, nucleotide resolution views of cancer genomes can be achieved. Systematic, large-scale sequencing surveys have revealed that the genetic spectrum of mutations in cancers appears to be highly complex with numerous low frequency bystander somatic variations, and a limited number of common, frequently mutated genes. Large sample sizes and deeper resequencing are much needed in resolving clinical and biological relevance of the mutations as well as in detecting somatic variants in heterogeneous samples and cancer cell sub-populations. However, even with the next-generation sequencing technologies, the overwhelming size of the human genome and need for very high fold coverage represents a major challenge for up-scaling cancer genome sequencing projects. Assays to target, capture, enrich or partition disease-specific regions of the genome offer immediate solutions for reducing the complexity of the sequencing libraries. Integration of targeted DNA capture assays and next-generation deep resequencing improves the ability to identify clinically and biologically relevant mutations.     

Germline and somatic mutation profile in Cancer patients revealed by a medium-sized pan-Cancer panel

Gene mutation detection and the resulted precision-medicine therapy is transforming clinical practice. Here, we report the use of a custom-developed, medium-sized, pan-cancer probe panel for the detection of somatic and germline mutations. We used a hybridization capture-based NGS assay for targeted deep sequencing of all exons and selected introns of 181 key cancer driver genes, covering both inherited risks and somatic mutations. We performed paired-variant calling on tumor samples and their matched normal samples. We processed clinical patient samples of formalin-fixed, paraffin embedded tumors (FFPE samples) and cell-free peripheral blood (cfDNA samples). We found germline mutations of inherited cancer risk at 9%; and discovered a novel germline mutation in BRCA1. Somatic mutation rate in driver genes is at 73.1%, much higher than previously reported. On recommending precision-medicine therapeutics, we achieved 91.6% for patients with FFPE samples.