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A large-scale epigenome-wide association study identifies changes in DNA methylation associated with body mass index in blood and adipose tissue, and correlates DNA methylation sites with high risk of incident type 2 diabetes. Body fat and diabetes risk Obesity is a major risk factor for type 2 diabetes and related metabolic disorders. Genetic association studies have identified genomic loci associated with obesity, and recent studies have also suggested associations with DNA methylation. These authors report an epigenome-wide association study for body mass index (BMI), identifying an association with DNA methylation at 187 loci in blood and adipose tissue. They find that these methylation changes are secondary to adiposity and are also associated with an increased risk of developing type 2 diabetes, independent of conventional risk factors. Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type 2 diabetes, cardiovascular disease and related metabolic and inflammatory disturbances 1 , 2 . Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation 3 , 4 , 5 , 6 , a key regulator of gene expression and molecular phenotype 7 . Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P  < 1 × 10 −7 , range P  = 9.2 × 10 −8 to 6.0 × 10 −46 ; n  = 10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find that methylation loci are enriched for functional genomic features in multiple tissues ( P  < 0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci ( P  < 9.0 × 10 −6 , range P  = 5.5 × 10 −6 to 6.1 × 10 −35 , n  = 1,785 samples). The methylation loci identify genes involved in lipid and lipoprotein metabolism, substrate transport and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future development of type 2 diabetes (relative risk per 1 standard deviation increase in methylation risk score: 2.3 (2.07–2.56); P  = 1.1 × 10 −54 ). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type 2 diabetes and other adverse clinical consequences of obesity.

The CNV analysis group of the Psychiatric Genomic Consortium analyzes a large schizophrenia cohort to examine genomic copy number variants (CNVs) and disease risk. They find an enrichment of CNV burden in cases versus controls and identify 8 genome-wide significant loci as well as novel suggestive loci conferring either risk or protection to schizophrenia. Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10 −15 ), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10 −6 ). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10 −11 ) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10 −5 ). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 ( NRXN1 ), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

Key Points New methods that make use of high-throughput sequencing are enabling the simultaneous discovery and sequencing of thousands of genetic markers across whole genomes. These methods can be used to study wild populations of tens or hundreds of individuals for which genomic resources were not previously available. They also enable the rapid genotyping of hundreds of individuals in a mapping cross, for quantitative trait locus (QTL) mapping and marker-assisted selection. We describe best practices and make recommendations for a group of methods involving the use of restriction enzymes, namely reduced-representation libraries, complexity reduction of polymorphic sequences, restriction-site-associated DNA sequencing, multiplexed shotgun genotyping and genotyping by sequencing. We discuss the impact of several factors — such as the availability of genomic resources, the levels of polymorphism, the pooling of samples and the choice of restriction enzyme — on the design and implementation of high-throughput marker discovery and genotyping experiments. The analysis of data from these methods can be challenging and new methods for processing high-throughput marker data are described. At present these methods are far more economical than whole-genome sequencing. We discuss how this situation is likely to change over the next few years, as sequencing costs continue to fall rapidly. The authors describe the best practices for a growing number of methods that use next-generation sequencing to rapidly discover and assess genetic markers across any genome, with applications from population genomics and quantitative trait locus mapping to marker-assisted selection. The advent of next-generation sequencing (NGS) has revolutionized genomic and transcriptomic approaches to biology. These new sequencing tools are also valuable for the discovery, validation and assessment of genetic markers in populations. Here we review and discuss best practices for several NGS methods for genome-wide genetic marker development and genotyping that use restriction enzyme digestion of target genomes to reduce the complexity of the target. These new methods — which include reduced-representation sequencing using reduced-representation libraries (RRLs) or complexity reduction of polymorphic sequences (CRoPS), restriction-site-associated DNA sequencing (RAD-seq) and low coverage genotyping — are applicable to both model organisms with high-quality reference genome sequences and, excitingly, to non-model species with no existing genomic data.

Main conclusionThe present review illustrates a comprehensive overview of the start codon targeted (SCoT) polymorphism marker and their utilization in various applications related to genetic and genomic studies.Start codon targeted (SCoT) polymorphism marker, a targeted fingerprinting marker technique, has gained considerable importance in plant genetics, genomics, and molecular breeding due to its many desirable features. SCoT marker targets the region flanking the start codon, a highly conserved region in plant genes. Therefore, it can distinguish genetic variations in a specific gene that link to a specific trait. It is a simple, novel, cost-effective, highly polymorphic, and reproducible molecular marker for which there is no need for prior sequence information. In the recent past, SCoT markers have been employed in many commercially important and underutilized plant species for a variety of applications, including genetic diversity analysis, interspecific/generic genetic relationships, cultivar/hybrid/species identification, sex determination, construction of linkage map, association mapping/analysis, differential gene expression, and genetic fidelity analysis of tissue culture-raised plants. The main aim of this review is to provide up-to-date information on SCoT markers and their application in many commercially important and underutilized plant species, mainly progress made in the last 8–10 years.

Lavinia Paternoster and colleagues report the results of a large, multi-ancestry genome-wide association study of atopic dermatitis. They identify ten new susceptibility loci harboring candidate genes involved in innate host defense and T cell function. Genetic association studies have identified 21 loci associated with atopic dermatitis risk predominantly in populations of European ancestry. To identify further susceptibility loci for this common, complex skin disease, we performed a meta-analysis of >15 million genetic variants in 21,399 cases and 95,464 controls from populations of European, African, Japanese and Latino ancestry, followed by replication in 32,059 cases and 228,628 controls from 18 studies. We identified ten new risk loci, bringing the total number of known atopic dermatitis risk loci to 31 (with new secondary signals at four of these loci). Notably, the new loci include candidate genes with roles in the regulation of innate host defenses and T cell function, underscoring the important contribution of (auto)immune mechanisms to atopic dermatitis pathogenesis.

The functional composition of microbial community samples from several environments is predicted based on 16S ribosomal RNA gene sequencing data. Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community's functional capabilities. Here we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.

Through drug exposure, a rare, transient transcriptional program characterized by high levels of expression of known resistance drivers can get ‘burned in’, leading to the selection of cells endowed with a transcriptional drug resistance and thus more chemoresistant cancers. Therapies that target signalling molecules that are mutated in cancers can often have substantial short-term effects, but the emergence of resistant cancer cells is a major barrier to full cures 1 , 2 . Resistance can result from secondary mutations 3 , 4 , but in other cases there is no clear genetic cause, raising the possibility of non-genetic rare cell variability 5 , 6 , 7 , 8 , 9 , 10 , 11 . Here we show that human melanoma cells can display profound transcriptional variability at the single-cell level that predicts which cells will ultimately resist drug treatment. This variability involves infrequent, semi-coordinated transcription of a number of resistance markers at high levels in a very small percentage of cells. The addition of drug then induces epigenetic reprogramming in these cells, converting the transient transcriptional state to a stably resistant state. This reprogramming begins with a loss of SOX10-mediated differentiation followed by activation of new signalling pathways, partially mediated by the activity of the transcription factors JUN and/or AP-1 and TEAD. Our work reveals the multistage nature of the acquisition of drug resistance and provides a framework for understanding resistance dynamics in single cells. We find that other cell types also exhibit sporadic expression of many of these same marker genes, suggesting the existence of a general program in which expression is displayed in rare subpopulations of cells.

We previously reported Agrobacterium-mediated transformation methods for the liverwort Marchantia polymorpha using the hygromycin phosphotransferase gene as a marker for selection with hygromycin. In this study, we developed three additional markers for M. polymorpha transformation: the gentamicin 3'-acetyltransferase gene for selection with gentamicin; a mutated acetolactate synthase gene for selection with chlorsulfuron; and the neomycin phosphotransferase II gene for selection with G418. Based on these four marker genes, we have constructed a series of Gateway binary vectors designed for transgenic experiments on M. polymorpha. The 35S promoter from cauliflower mosaic virus and endogenous promoters for constitutive and heat-inducible expression were used to create these vectors. The reporters and tags used were Citrine, 3×Citrine, Citrine-NLS, TagRFP, tdTomato, tdTomato-NLS, GR, SRDX, SRDX-GR, GUS, ELuc(PEST), and 3×FLAG. These vectors, designated as the pMpGWB series, will facilitate molecular genetic analyses of the emerging model plant M. polymorpha.

Structural variations disrupting the 3′ region of PD-L1 are shown to aid immune evasion in a number of human cancers, including adult T-cell leukaemia/lymphoma, and in a mouse tumour model, CRISPR/Cas9-mediated deletion of the 3'-UTR of Pd-l1 is also shown to result in immune escape, suggesting that PD-L1 3′-UTR disruption could provide a diagnostic marker to identify patients who will benefit from anti-PD-1/PD-L1 therapy. A marker for responsiveness to anti-PD-1/PD-L1 therapy In some patients, cancer therapy with antibodies against programmed cell death 1 (PD-1) and its ligand (PD-L1) is ineffective due to immune evasion. Here Seishi Ogawa and colleagues show that structural variations disrupting the 3′-region of PD-L1 lead to overexpression of the PD-L1 protein, promoting immune evasion in a number of human cancers, including adult T-cell leukaemia and diffuse large B-cell lymphoma. Crispr-Cas9-mediated deletion of the 3′-UTR of Pd-l1 is also shown to result in immune escape in a mouse tumour model, suggesting that PD-L1 3′-UTR disruption could provide a diagnostic marker to identify patients who will benefit from anti-PD-1/PD-L1 therapy. Successful treatment of many patients with advanced cancer using antibodies against programmed cell death 1 (PD-1; also known as PDCD1) and its ligand (PD-L1; also known as CD274) has highlighted the critical importance of PD-1/PD-L1-mediated immune escape in cancer development 1 , 2 , 3 , 4 , 5 , 6 . However, the genetic basis for the immune escape has not been fully elucidated, with the exception of elevated PD-L1 expression by gene amplification and utilization of an ectopic promoter by translocation, as reported in Hodgkin and other B-cell lymphomas, as well as stomach adenocarcinoma 6 , 7 , 8 , 9 , 10 . Here we show a unique genetic mechanism of immune escape caused by structural variations (SVs) commonly disrupting the 3′ region of the PD-L1 gene. Widely affecting multiple common human cancer types, including adult T-cell leukaemia/lymphoma (27%), diffuse large B-cell lymphoma (8%), and stomach adenocarcinoma (2%), these SVs invariably lead to a marked elevation of aberrant PD-L1 transcripts that are stabilized by truncation of the 3′-untranslated region (UTR). Disruption of the Pd-l1 3′-UTR in mice enables immune evasion of EG7-OVA tumour cells with elevated Pd-l1 expression in vivo , which is effectively inhibited by Pd-1/Pd-l1 blockade, supporting the role of relevant SVs in clonal selection through immune evasion. Our findings not only unmask a novel regulatory mechanism of PD-L1 expression, but also suggest that PD-L1 3′-UTR disruption could serve as a genetic marker to identify cancers that actively evade anti-tumour immunity through PD-L1 overexpression.

Ludmila Prokunina-Olsson, Thomas O'Brien and colleagues report the discovery of a new gene, INFL4 , encoding interferon-λ4, that is upstream of INFL3 ( IL28B ). A compound dinucleotide frameshift genetic variant in INFL4 creates the full-length INFL4 protein and is more strongly associated with hepatitis C virus clearance in individuals of African ancestry than rs12979860, a known variant associated with clearance. Chronic infection with hepatitis C virus (HCV) is a common cause of liver cirrhosis and cancer. We performed RNA sequencing in primary human hepatocytes activated with synthetic double-stranded RNA to mimic HCV infection. Upstream of IFNL3 ( IL28B ) on chromosome 19q13.13, we discovered a new transiently induced region that harbors a dinucleotide variant ss469415590 (TT or ΔG), which is in high linkage disequilibrium with rs12979860, a genetic marker strongly associated with HCV clearance. ss469415590[ΔG] is a frameshift variant that creates a novel gene, designated IFNL4 , encoding the interferon-λ4 protein (IFNL4), which is moderately similar to IFNL3. Compared to rs12979860, ss469415590 is more strongly associated with HCV clearance in individuals of African ancestry, although it provides comparable information in Europeans and Asians. Transient overexpression of IFNL4 in a hepatoma cell line induced STAT1 and STAT2 phosphorylation and the expression of interferon-stimulated genes. Our findings provide new insights into the genetic regulation of HCV clearance and its clinical management.