Hundreds Of Loci Research Articles

Elevated variant density around SV breakpoints in germline lineage lends support to error-prone replication hypothesis.

Copy number variants (CNVs) are a class of structural variants that may involve complex genomic rearrangements (CGRs) and are hypothesized to have additional mutations around their breakpoints. Understanding the mechanisms underlying CNV formation is fundamental for understanding the repair and mutation mechanisms in cells, thereby shedding light on evolution, genomic disorders, cancer, and complex human traits. In this study, we used data from the 1000 Genomes Project to analyze hundreds of loci harboring heterozygous germline deletions in the subjects NA12878 and NA19240. By utilizing synthetic long-read data (longer than 2 kbp) in combination with high coverage short-read data and, in parallel, by comparing with parental genomes, we interrogated the phasing of these deletions with the flanking tens of thousands of heterozygous SNPs and indels. We found that the density of SNPs/indels flanking the breakpoints of deletions (in-phase variants) is approximately twice as high as the corresponding density for the variants on the haplotype without deletion (out-of-phase variants). This fold change was even larger for the subset of deletions with signatures of replication-based mechanism of formation. The allele frequency (AF) spectrum for deletions is enriched for rare events; and the AF spectrum for in-phase SNPs is shifted toward this deletion spectrum, thus offering evidence consistent with the concomitance of the in-phase SNPs/indels with the deletion events. These findings therefore lend support to the hypothesis that the mutational mechanisms underlying CNV formation are error prone. Our results could also be relevant for resolving mutation-rate discrepancies in human and to explain kataegis.

Will Benchtop Sequencers Resolve the Sequencing Trade-off in Plant Genetics?

Will Benchtop Sequencers Resolve the Sequencing Trade-off in Plant Genetics?

Ecological population genomics in the marine environment.

Marine species live in a wide diversity of environments and yet, because of their pelagic life stages, are thought to be well-connected: they have high migration rates that inhibit significant population structure. Recent innovations in sequencing technologies now provide information on nucleotide polymorphisms at thousands to tens of thousands of loci based on whole genomes, reduced representative portions of genomes (0.1-1%) or a majority of expressed mRNAs. Data from these genomic approaches are used to define and quantify single-nucleotide polymorphisms (SNPs). These SNP data tend to agree with data from older technologies (allozymes or microsatellites), which support well-connected populations with few genetic differences among populations. However, these studies also find few percentages of SNPs (1-5%) that readily distinguish genetic differences among populations on relatively small geographic scales. The magnitudes of the genetic differences (FST values) suggest that hundreds of loci with significant differences are due to positive selective pressures. Thus, these data suggest that natural selection is effectively altering allele frequencies at 100s of loci in marine populations. In this manuscript, we provide examples of these studies, the strengths and weaknesses of different genomic approaches as well as important technical aspects associated with genomic approaches.

Genetics of coronary heart disease: towards causal mechanisms, novel drug targets and more personalized prevention.

Coronary heart disease (CHD) is an archetypical multifactorial disorder that is influenced by genetic susceptibility as well as both modifiable and nonmodifiable risk factors, and their interactions. Advances during recent years in the field of multifactorial genetics, in particular genomewide association studies (GWASs) and their meta-analyses, have provided the statistical power to identify and replicate genetic variants in more than 50 risk loci for CHD and in several hundreds of loci for cardiometabolic risk factors for CHD such as blood lipids and lipoproteins. Although for a great majority of these loci both the causal variants and mechanisms remain unknown, progress in identifying the causal variants and underlying mechanisms has already been made for several genetic loci. Furthermore, identification of rare loss-of-function variants in genes such as PCSK9, NPC1L1, APOC3 and APOA5, which cause a markedly decreased risk of CHD and no adverse side effects, illustrates the power of translating genetic findings into novel mechanistic information and provides some optimism for the future of developing novel drugs, given the many genes associated with CHD in GWASs. Finally, Mendelian randomization can be used to reveal or exclude causal relationships between heritable biomarkers and CHD, and such approaches have already provided evidence of causal relationships between CHD and LDL cholesterol, triglycerides/remnant particles and lipoprotein(a), and indicated a lack of causality for HDL cholesterol, C-reactive protein and lipoprotein-associated phospholipase A2. Together, these genetic findings are beginning to lead to promising new drug targets and novel interventional strategies and thus have great potential to improve prevention, prediction and therapy of CHD.

A Non-Synonymous HMGA2 Variant Decreases Height in Shetland Ponies and Other Small Horses

The identification of quantitative trait loci (QTL) such as height and their underlying causative variants is still challenging and often requires large sample sizes. In humans hundreds of loci with small effects control the heritable portion of height variability. In domestic animals, typically only a few loci with comparatively large effects explain a major fraction of the heritability. We investigated height at withers in Shetland ponies and mapped a QTL to ECA 6 by genome-wide association (GWAS) using a small cohort of only 48 animals and the Illumina equine SNP70 BeadChip. Fine-mapping revealed a shared haplotype block of 793 kb in small Shetland ponies. The HMGA2 gene, known to be associated with height in horses and many other species, was located in the associated haplotype. After closing a gap in the equine reference genome we identified a non-synonymous variant in the first exon of HMGA2 in small Shetland ponies. The variant was predicted to affect the functionally important first AT-hook DNA binding domain of the HMGA2 protein (c.83G>A; p.G28E). We assessed the functional impact and found impaired DNA binding of a peptide with the mutant sequence in an electrophoretic mobility shift assay. This suggests that the HMGA2 variant also affects DNA binding in vivo and thus leads to reduced growth and a smaller stature in Shetland ponies. The identified HMGA2 variant also segregates in several other pony breeds but was not found in regular-sized horse breeds. We therefore conclude that we identified a quantitative trait nucleotide for height in horses.

Antarctic krill population genomics: apparent panmixia, but genome complexity and large population size muddy the water.

Antarctic krill (Euphausiasuperba; hereafter krill) are an incredibly abundant pelagic crustacean which has a wide, but patchy, distribution in the Southern Ocean. Several studies have examined the potential for population genetic structuring in krill, but DNA-based analyses have focused on a limited number of markers and have covered only part of their circum-Antarctic range. We used mitochondrial DNA and restriction site-associated DNA sequencing (RAD-seq) to investigate genetic differences between krill from five sites, including two from East Antarctica. Our mtDNA results show no discernible genetic structuring between sites separated by thousands of kilometres, which is consistent with previous studies. Using standard RAD-seq methodology, we obtained over a billion sequences from >140krill, and thousands of variable nucleotides were identified at hundreds of loci. However, downstream analysis found that markers with sufficient coverage were primarily from multicopy genomic regions. Careful examination of these data highlights the complexity of the RAD-seq approach in organisms with very large genomes. To characterize the multicopy markers, we recorded sequence counts from variable nucleotide sites rather than the derived genotypes; we also examined a small number of manually curated genotypes. Although these analyses effectively fingerprinted individuals, and uncovered a minor laboratory batch effect, no population structuring was observed. Overall, our results are consistent with panmixia of krill throughout their distribution. This result may indicate ongoing gene flow. However, krill's enormous population size creates substantial panmictic inertia, so genetic differentiation may not occur on an ecologically relevant timescale even if demographically separate populations exist.

Genetic and functional analyses demonstrate a role for abnormal glycinergic signaling in autism.

Autism spectrum disorder (ASD) is a common neurodevelopmental condition characterized by marked genetic heterogeneity. Recent studies of rare structural and sequence variants have identified hundreds of loci involved in ASD, but our knowledge of the overall genetic architecture and the underlying pathophysiological mechanisms remains incomplete. Glycine receptors (GlyRs) are ligand-gated chloride channels that mediate inhibitory neurotransmission in the adult nervous system but exert an excitatory action in immature neurons. GlyRs containing the α2 subunit are highly expressed in the embryonic brain, where they promote cortical interneuron migration and the generation of excitatory projection neurons. We previously identified a rare microdeletion of the X-linked gene GLRA2, encoding the GlyR α2 subunit, in a boy with autism. The microdeletion removes the terminal exons of the gene (GLRA2(Δex8-9)). Here, we sequenced 400 males with ASD and identified one de novo missense mutation, p.R153Q, absent from controls. In vitro functional analysis demonstrated that the GLRA2(Δex8)(-)(9) protein failed to localize to the cell membrane, while the R153Q mutation impaired surface expression and markedly reduced sensitivity to glycine. Very recently, an additional de novo missense mutation (p.N136S) was reported in a boy with ASD, and we show that this mutation also reduced cell-surface expression and glycine sensitivity. Targeted glra2 knockdown in zebrafish induced severe axon-branching defects, rescued by injection of wild type but not GLRA2(Δex8-9) or R153Q transcripts, providing further evidence for their loss-of-function effect. Glra2 knockout mice exhibited deficits in object recognition memory and impaired long-term potentiation in the prefrontal cortex. Taken together, these results implicate GLRA2 in non-syndromic ASD, unveil a novel role for GLRA2 in synaptic plasticity and learning and memory, and link altered glycinergic signaling to social and cognitive impairments.

Regulation of body growth.

Recent basic studies have yielded important new insights into the molecular mechanisms that regulate growth locally. Simultaneously, clinical studies have identified new molecular defects that cause growth failure and overgrowth, and genome-wide association studies have elucidated the genetic basis for normal human height variation. The Hippo pathway has emerged as one of the major mechanisms controlling organ size. In addition, an extensive genetic program has been described that allows rapid body growth in the fetus and infant but then causes growth to slow with age in multiple tissues. In human genome-wide association studies, hundreds of loci associated with adult stature have been identified; many appear to involve genes that function locally in the growth plate. Clinical genetic studies have identified a new genetic abnormality, microduplication of Xq26.3, that is responsible for growth hormone excess, and a gene, DNMT3A, in which mutations cause an overgrowth syndrome through epigenetic mechanisms. These recent advances in our understanding of somatic growth not only provide insight into childhood growth disorders but also have broader medical applications because disruption of these regulatory systems contributes to oncogenesis.

Genome-wide negative feedback drives transgenerational DNA methylation dynamics in Arabidopsis.

Epigenetic variations of phenotypes, especially those associated with DNA methylation, are often inherited over multiple generations in plants. The active and inactive chromatin states are heritable and can be maintained or even be amplified by positive feedback in a transgenerational manner. However, mechanisms controlling the transgenerational DNA methylation dynamics are largely unknown. As an approach to understand the transgenerational dynamics, we examined long-term effect of impaired DNA methylation in Arabidopsis mutants of the chromatin remodeler gene DDM1 (Decrease in DNA Methylation 1) through whole genome DNA methylation sequencing. The ddm1 mutation induces a drastic decrease in DNA methylation of transposable elements (TEs) and repeats in the initial generation, while also inducing ectopic DNA methylation at hundreds of loci. Unexpectedly, this ectopic methylation can only be seen after repeated self-pollination. The ectopic cytosine methylation is found primarily in the non-CG context and starts from 3’ regions within transcription units and spreads upstream. Remarkably, when chromosomes with reduced DNA methylation were introduced from a ddm1 mutant into a DDM1 wild-type background, the ddm1-derived chromosomes also induced analogous de novo accumulation of DNA methylation in trans. These results lead us to propose a model to explain the transgenerational DNA methylation redistribution by genome-wide negative feedback. The global negative feedback, together with local positive feedback, would ensure robust and balanced differentiation of chromatin states within the genome.

A new method for estimating species age supports the coexistence of malaria parasites and their Mammalian hosts.

Species in the genus Plasmodium cause malaria in humans and infect a variety of mammals and other vertebrates. Currently, estimated ages for several mammalian Plasmodium parasites differ by as much as one order of magnitude, an inaccuracy that frustrates reliable estimation of evolutionary rates of disease-related traits. We developed a novel statistical approach to dating the relative age of evolutionary lineages, based on Total Least Squares regression. We validated this lineage dating approach by applying it to the genus Drosophila. Using data from the Drosophila 12 Genomes project, our approach accurately reconstructs the age of well-established Drosophila clades, including the speciation event that led to the subgenera Drosophila and Sophophora, and age of the melanogaster species subgroup. We applied this approach to hundreds of loci from seven mammalian Plasmodium species. We demonstrate the existence of a molecular clock specific to individual Plasmodium proteins, and estimate the relative age of mammalian-infecting Plasmodium. These analyses indicate that: 1) the split between the human parasite Plasmodium vivax and P. knowlesi, from Old World monkeys, occurred 6.1 times earlier than that between P. falciparum and P. reichenowi, parasites of humans and chimpanzees, respectively; and 2) mammalian Plasmodium parasites originated 22 times earlier than the split between P. falciparum and P. reichenowi. Calibrating the absolute divergence times for Plasmodium with eukaryotic substitution rates, we show that the split between P. falciparum and P. reichenowi occurred 3.0–5.5 Ma, and that mammalian Plasmodium parasites originated over 64 Ma. Our results indicate that mammalian-infecting Plasmodium evolved contemporaneously with their hosts, with little evidence for parasite host-switching on an evolutionary scale, and provide a solid timeframe within which to place the evolution of new Plasmodium species.

BBCA: Improving the scalability of *BEAST using random binning.

BackgroundSpecies tree estimation can be challenging in the presence of gene tree conflict due to incomplete lineage sorting (ILS), which can occur when the time between speciation events is short relative to the population size. Of the many methods that have been developed to estimate species trees in the presence of ILS, *BEAST, a Bayesian method that co-estimates the species tree and gene trees given sequence alignments on multiple loci, has generally been shown to have the best accuracy. However, *BEAST is extremely computationally intensive so that it cannot be used with large numbers of loci; hence, *BEAST is not suitable for genome-scale analyses.ResultsWe present BBCA (boosted binned coalescent-based analysis), a method that can be used with *BEAST (and other such co-estimation methods) to improve scalability. BBCA partitions the loci randomly into subsets, uses *BEAST on each subset to co-estimate the gene trees and species tree for the subset, and then combines the newly estimated gene trees together using MP-EST, a popular coalescent-based summary method. We compare time-restricted versions of BBCA and *BEAST on simulated datasets, and show that BBCA is at least as accurate as *BEAST, and achieves better convergence rates for large numbers of loci.ConclusionsPhylogenomic analysis using *BEAST is currently limited to datasets with a small number of loci, and analyses with even just 100 loci can be computationally challenging. BBCA uses a very simple divide-and-conquer approach that makes it possible to use *BEAST on datasets containing hundreds of loci. This study shows that BBCA provides excellent accuracy and is highly scalable.

Regulation of histone H3K4 methylation in brain development and disease.

The growing list of mutations implicated in monogenic disorders of the developing brain includes at least seven genes (ARX, CUL4B, KDM5A, KDM5C, KMT2A, KMT2C, KMT2D) with loss-of-function mutations affecting proper regulation of histone H3 lysine 4 methylation, a chromatin mark which on a genome-wide scale is broadly associated with active gene expression, with its mono-, di- and trimethylated forms differentially enriched at promoter and enhancer and other regulatory sequences. In addition to these rare genetic syndromes, dysregulated H3K4 methylation could also play a role in the pathophysiology of some cases diagnosed with autism or schizophrenia, two conditions which on a genome-wide scale are associated with H3K4 methylation changes at hundreds of loci in a subject-specific manner. Importantly, the reported alterations for some of the diseased brain specimens included a widespread broadening of H3K4 methylation profiles at gene promoters, a process that could be regulated by the UpSET(KMT2E/MLL5)-histone deacetylase complex. Furthermore, preclinical studies identified maternal immune activation, parental care and monoaminergic drugs as environmental determinants for brain-specific H3K4 methylation. These novel insights into the epigenetic risk architectures of neurodevelopmental disease will be highly relevant for efforts aimed at improved prevention and treatment of autism and psychosis spectrum disorders.

Genetic influences on brain gene expression in rats selected for tameness and aggression.

Interindividual differences in many behaviors are partly due to genetic differences, but the identification of the genes and variants that influence behavior remains challenging. Here, we studied an F2 intercross of two outbred lines of rats selected for tame and aggressive behavior toward humans for >64 generations. By using a mapping approach that is able to identify genetic loci segregating within the lines, we identified four times more loci influencing tameness and aggression than by an approach that assumes fixation of causative alleles, suggesting that many causative loci were not driven to fixation by the selection. We used RNA sequencing in 150 F2 animals to identify hundreds of loci that influence brain gene expression. Several of these loci colocalize with tameness loci and may reflect the same genetic variants. Through analyses of correlations between allele effects on behavior and gene expression, differential expression between the tame and aggressive rat selection lines, and correlations between gene expression and tameness in F2 animals, we identify the genes Gltscr2, Lgi4, Zfp40, and Slc17a7 as candidate contributors to the strikingly different behavior of the tame and aggressive animals.

Following-up genome-wide association study signals: lessons learned from Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.

Family studies have for decades documented a critical role of both common and rare inherited variations contributing to interindividual differences in the risks of common heart, lung and blood diseases and their risk factors. Examples include Mendelian forms of disease such as familial hypercholesterolemia caused by low-density lipoprotein receptor mutations and hypertension resulting from epithelial sodium channel subunit mutations. For most conditions, however, the identity of the contributing loci and allelic variants has remained elusive. In the late 1990s, 2 unlikely scientific tools were combined to seed a revolution in gene and locus discovery for many common disease traits. First, the HapMap Project (www.hapmap.org) produced a collection of haplotype-tagging variants that could capture information across the entire genome in common variants potentially influencing risk to disease. Second, large deeply phenotyped cohort studies in both the United States and Europe formed collaborations that took advantage of available DNA, appropriate informed consent, and high-quality longitudinal information about multiple phenotypes.1 These tools formed the basis of many genome-wide association studies (GWAS) which have identified hundreds of loci underlying common chronic conditions, infectious diseases, and cancer susceptibilities (www.genome.gov/gwastudies/). Because of the small effect sizes expected for most loci of interest, the large number of marker loci measured, and thus the corresponding number of statistical tests, large sample sizes are the norm for most contemporary GWAS. To obtain such sample sizes, multiple groups and studies have combined to form collaborative consortia. For instance, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)1 Consortium, which focuses on the genetics of cardiovascular disease and aging, has produced more than 300 publications reporting the results of GWAS for many cardio-, renal-, and cerebrovascular disease-related traits, including metabolic and inflammation traits. Several commentators have raised questions about the utility of GWAS, which have been celebrated …

Systems Genomics of Metabolic Phenotypes in Wild-TypeDrosophila melanogaster

Systems biology is an approach to dissection of complex traits that explicitly recognizes the impact of genetic, physiological, and environmental interactions in the generation of phenotypic variation. We describe comprehensive transcriptional and metabolic profiling in Drosophila melanogaster across four diets, finding little overlap in modular architecture. Genotype and genotype-by-diet interactions are a major component of transcriptional variation (24 and 5.3% of the total variation, respectively) while there were no main effects of diet (<1%). Genotype was also a major contributor to metabolomic variation (16%), but in contrast to the transcriptome, diet had a large effect (9%) and the interaction effect was minor (2%) for the metabolome. Yet specific principal components of these molecular phenotypes measured in larvae are strongly correlated with particular metabolic syndrome-like phenotypes such as pupal weight, larval sugar content and triglyceride content, development time, and cardiac arrhythmia in adults. The second principal component of the metabolomic profile is especially informative across these traits with glycine identified as a key loading variable. To further relate this physiological variability to genotypic polymorphism, we performed evolve-and-resequence experiments, finding rapid and replicated changes in gene frequency across hundreds of loci that are specific to each diet. Adaptation to diet is thus highly polygenic. However, loci differentially transcribed across diet or previously identified by RNAi knockdown or expression QTL analysis were not the loci responding to dietary selection. Therefore, loci that respond to the selective pressures of diet cannot be readily predicted a priori from functional analyses.

Comparative Species Divergence across Eight Triplets of Spiny Lizards (Sceloporus) Using Genomic Sequence Data

Species divergence is typically thought to occur in the absence of gene flow, but many empirical studies are discovering that gene flow may be more pervasive during species formation. Although many examples of divergence with gene flow have been identified, few clades have been investigated in a comparative manner, and fewer have been studied using genome-wide sequence data. We contrast species divergence genetic histories across eight triplets of North American Sceloporus lizards using a maximum likelihood implementation of the isolation–migration (IM) model. Gene flow at the time of species divergence is modeled indirectly as variation in species divergence time across the genome or explicitly using a migration rate parameter. Likelihood ratio tests (LRTs) are used to test the null model of no gene flow at speciation against these two alternative gene flow models. We also use the Akaike information criterion to rank the models. Hundreds of loci are needed for the LRTs to have statistical power, and we use genome sequencing of reduced representation libraries to obtain DNA sequence alignments at many loci (between 340 and 3,478; mean = 1,678) for each triplet. We find that current species distributions are a poor predictor of whether a species pair diverged with gene flow. Interrogating the genome using the triplet method expedites the comparative study of species divergence history and the estimation of genetic parameters associated with speciation.

Comprehensive Analysis of Human Endogenous Retrovirus Group HERV-W Locus Transcription in Multiple Sclerosis Brain Lesions by High-Throughput Amplicon Sequencing

Human endogenous retroviruses (HERVs) of the HERV-W group comprise hundreds of loci in the human genome. Deregulated HERV-W expression and HERV-W locus ERVWE1-encoded Syncytin-1 protein have been implicated in the pathogenesis of multiple sclerosis (MS). However, the actual transcription of HERV-W loci in the MS context has not been comprehensively analyzed. We investigated transcription of HERV-W in MS brain lesions and white matter brain tissue from healthy controls by employing next-generation amplicon sequencing of HERV-W env-specific reverse transcriptase (RT) PCR products, thus revealing transcribed HERV-W loci and the relative transcript levels of those loci. We identified more than 100 HERV-W loci that were transcribed in the human brain, with a limited number of loci being predominantly transcribed. Importantly, relative transcript levels of HERV-W loci were very similar between MS and healthy brain tissue samples, refuting deregulated transcription of HERV-W env in MS brain lesions, including the high-level-transcribed ERVWE1 locus encoding Syncytin-1. Quantitative RT-PCR likewise did not reveal differences in MS regarding HERV-W env general transcript or ERVWE1- and ERVWE2-specific transcript levels. However, we obtained evidence for interindividual differences in HERV-W transcript levels. Reporter gene assays indicated promoter activity of many HERV-W long terminal repeats (LTRs), including structurally incomplete LTRs. Our comprehensive analysis of HERV-W transcription in the human brain thus provides important information on the biology of HERV-W in MS lesions and normal human brain, implications for study design, and mechanisms by which HERV-W may (or may not) be involved in MS.

Robustness to Divergence Time Underestimation When Inferring Species Trees from Estimated Gene Trees

To infer species trees from gene trees estimated from phylogenomic data sets, tractable methods are needed that can handle dozens to hundreds of loci. We examine several computationally efficient approaches-MP-EST, STAR, STEAC, STELLS, and STEM-for inferring species trees from gene trees estimated using maximum likelihood (ML) and Bayesian approaches. Among the methods examined, we found that topology-based methods often performed better using ML gene trees and methods employing coalescent times typically performed better using Bayesian gene trees, with MP-EST, STAR, STEAC, and STELLS outperforming STEM under most conditions. We examine why the STEM tree (also called GLASS or Maximum Tree) is less accurate on estimated gene trees by comparing estimated and true coalescence times, performing species tree inference using simulations, and analyzing a great ape data set keeping track of false positive and false negative rates for inferred clades. We find that although true coalescence times are more ancient than speciation times under the multispecies coalescent model, estimated coalescence times are often more recent than speciation times. This underestimation can lead to increased bias and lack of resolution with increased sampling (either alleles or loci) when gene trees are estimated with ML. The problem appears to be less severe using Bayesian gene-tree estimates.

PAVIS: a tool for Peak Annotation and Visualization

We introduce a web-based tool, Peak Annotation and Visualization (PAVIS), for annotating and visualizing ChIP-seq peak data. PAVIS is designed with non-bioinformaticians in mind and presents a straightforward user interface to facilitate biological interpretation of ChIP-seq peak or other genomic enrichment data. PAVIS, through association with annotation, provides relevant genomic context for each peak, such as peak location relative to genomic features including transcription start site, intron, exon or 5'/3'-untranslated region. PAVIS reports the relative enrichment P-values of peaks in these functionally distinct categories, and provides a summary plot of the relative proportion of peaks in each category. PAVIS, unlike many other resources, provides a peak-oriented annotation and visualization system, allowing dynamic visualization of tens to hundreds of loci from one or more ChIP-seq experiments, simultaneously. PAVIS enables rapid, and easy examination and cross-comparison of the genomic context and potential functions of the underlying genomic elements, thus supporting downstream hypothesis generation.

The Role of Human Equilibrative Nucleoside Transporter 1 on the Cellular Transport of the DNA Methyltransferase Inhibitors 5-Azacytidine and CP-4200 in Human Leukemia Cells

The nucleoside analog 5-azacytidine is an archetypical drug for epigenetic cancer therapy, and its clinical effectiveness has been demonstrated in the treatment of myelodysplastic syndromes (MDS) and acute myelogenous leukemia (AML). However, therapy resistance in patients with MDS/AML remains a challenging issue. Membrane proteins that are involved in drug uptake are potential mediators of drug resistance. The responsible proteins for the transport of 5-azacytidine into MDS/AML cells are unknown. We have now systematically analyzed the expression and activity of various nucleoside transporters. We identified the human equilibrative nucleoside transporter 1 (hENT1) as the most abundant nucleoside transporter in leukemia cell lines and in AML patient samples. Transport assays using [¹⁴C]5-azacytidine demonstrated Na⁺-independent uptake of the drug into the cells, which was inhibited by S-(4-nitrobenzyl)-6-thioinosine (NBTI), a hENT1 inhibitor. The cellular toxicity of 5-azacytidine and its DNA demethylating activity were strongly reduced after hENT1 inhibition. In contrast, the cellular activity of the 5-azacytidine derivative 5-azacytidine-5'-elaidate (CP-4200), a nucleoside transporter-independent drug, persisted after hENT1 inhibition. A strong dependence of 5-azacytidine-induced DNA demethylation on hENT1 activity was also confirmed by array-based DNA methylation profiling, which uncovered hundreds of loci that became demethylated only when hENT1-mediated transport was active. Our data establish hENT1 as a key transporter for the cellular uptake of 5-azacytidine in leukemia cells and raise the possibility that hENT1 expression might be a useful biomarker to predict the efficiency of 5-azacytidine treatments. Furthermore, our data suggest that CP-4200 may represent a valuable compound for the modulation of transporter-related 5-azacytidine resistances.