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Friedreich’s ataxia is an incurable disease caused by frataxin (FXN) protein deficiency, which is mostly induced by GAA repeat expansion in intron 1 of the FXN gene. Here, we identified antisense oligonucleotides (ASOs), complementary to two regions within the first intron of FXN pre-mRNA, which could increase FXN mRNA by ∼2-fold in patient fibroblasts. The increase in FXN mRNA was confirmed by the identification of multiple overlapping FXN-activating ASOs at each region, two independent RNA quantification assays, and normalization by multiple housekeeping genes. Experiments on cells with the ASO-binding sites deleted indicate that the ASO-induced FXN activation was driven by indirect effects. RNA sequencing analyses showed that the two ASOs induced similar transcriptome-wide changes, which did not resemble the transcriptome of wild-type cells. This RNA-seq analysis did not identify directly base-paired off-target genes shared across ASOs. Mismatch studies identified two guanosine-rich motifs (CCGG and G4) within the ASOs that were required for FXN activation. The phosphorodiamidate morpholino oligomer analogs of our ASOs did not activate FXN, pointing to a PS-backbone-mediated effect. Our study demonstrates the importance of multiple, detailed control experiments and target validation in oligonucleotide studies employing novel mechanisms such as gene activation.

SUMMARYCohesin-mediated loop extrusion folds interphase chromosomes at the ten to hundreds kilobases scale. This process produces structural features such as loops and topologically associating domains. We identify three types of cis-elements that define the chromatin folding landscape generated by loop extrusion. First, CTCF sites form boundaries by stalling extruding cohesin, as shown before. Second, transcription termination sites form boundaries by acting as cohesin unloading sites. RNA polymerase II contributes to boundary formation at transcription termination sites. Third, transcription start sites form boundaries that are mostly independent of cohesin, but are sites where cohesin can pause. Together with cohesin loading at enhancers, and possibly other cis-elements, these loci create a dynamic pattern of cohesin traffic along the genome that guides enhancer-promoter interactions. Disturbing this traffic pattern, by removing CTCF barriers, renders cells sensitive to knock-out of genes involved in transcription initiation, such as the SAGA and TFIID complexes, and RNA processing such DEAD-Box RNA helicases. In the absence of CTCF, several of these factors fail to be efficiently recruited to active promoters. We propose that the complex pattern of cohesin movement along chromatin contributes to appropriate promoter-enhancer interactions and localization of transcription and RNA processing factors to active genes.HIGHLIGHTSAt least three types of chromatin boundaries regulate a cohesin traffic pattern.The cohesin traffic pattern guides enhancer-promoter interactions.Removing CTCF renders cells sensitive to deletion of RNA processing and gene regulation genes.Depleting CTCF affects localization of RNA processing and gene regulatory proteins.

The antisense non-coding RNA in the INK locus (ANRIL) is a hotspot for genetic variants associated with cardiometabolic disease. We recently found increased ANRIL abundance in human pancreatic islets from donors with certain Type II Diabetes (T2D) risk-SNPs, including a T2D risk-SNP located within ANRIL exon 2 associated with beta cell proliferation. Recent studies have found that expression of circular species of ANRIL is linked to the regulation of cardiovascular phenotypes. Less is known about how the abundance of circular ANRIL may influence T2D phenotypes. Herein, we sequence circular RNA in pancreatic islets to characterize circular isoforms of ANRIL. We identify several consistently expressed circular ANRIL isoforms whose expression is correlated across dozens of individuals and characterize ANRIL splice sites that are commonly involved in back-splicing. We find that samples with the T2D risk allele in ANRIL exon 2 had higher ratios of circular to linear ANRIL compared to protective-allele carriers, and that higher circular:linear ANRIL was associated with decreased beta cell proliferation. Our study points to a combined involvement of both linear and circular ANRIL species in T2D phenotypes and opens the door for future studies of the molecular mechanisms by which ANRIL impacts cellular function in pancreatic islets.

Adeno-associated virus (AAV) vectors are important delivery platforms for therapeutic genome editing but are severely constrained by cargo limits. Simultaneous delivery of multiple vectors can limit dose and efficacy and increase safety risks. Here, we describe single-vector, ~4.8-kb AAV platforms that express Nme2Cas9 and either two sgRNAs for segmental deletions, or a single sgRNA with a homology-directed repair (HDR) template. We also use anti-CRISPR proteins to enable production of vectors that self-inactivate via Nme2Cas9 cleavage. We further introduce a nanopore-based sequencing platform that is designed to profile rAAV genomes and serves as a quality control measure for vector homogeneity. We demonstrate that these platforms can effectively treat two disease models [type I hereditary tyrosinemia (HT-I) and mucopolysaccharidosis type I (MPS-I)] in mice by HDR-based correction of the disease allele. These results will enable the engineering of single-vector AAVs that can achieve diverse therapeutic genome editing outcomes., Long-term expression of Cas9 following precision genome editing in vivo may lead to undesirable consequences. Here we show that a single-vector, self-inactivating AAV system containing Cas9 nuclease, guide, and DNA donor can use homology-directed repair to correct disease mutations in vivo.

Sustained silencing of gene expression throughout the brain using small interfering RNAs (siRNAs) has not been achieved. Here we describe an siRNA architecture, divalent siRNA (di-siRNA), that supports potent, sustained gene silencing in the central nervous system (CNS) of mice and nonhuman primates following a single injection into the cerebrospinal fluid. Di-siRNAs are composed of two fully chemically modified, phosphorothioate-containing siRNAs connected by a linker. In mice, di-siRNAs induced the potent silencing of huntingtin, the causative gene in Huntington’s disease, reducing messenger RNA and protein throughout the brain. Silencing persisted for at least 6 months, with the degree of gene silencing correlating to levels of guide strand tissue accumulation. In cynomolgus macaques, a bolus injection of di-siRNA showed substantial distribution and robust silencing throughout the brain and spinal cord without detectable toxicity and with minimal off-target effects. This siRNA design may enable RNA interference-based gene silencing in the CNS for the treatment of neurological disorders. A divalent siRNA architecture enables sustained silencing of gene expression in deep regions of the brain.

Adeno-associated virus (AAV) vectors are important delivery platforms for therapeutic genome editing but are severely constrained by cargo limits, especially for large effectors like Cas9s. Simultaneous delivery of multiple vectors can limit dose and efficacy and increase safety risks. The use of compact effectors has enabled single-AAV delivery of Cas9s with 1-3 guides for edits that use end-joining repair pathways, but many precise edits that correct disease-causing mutations in vivo require homology-directed repair (HDR) templates. Here, we describe single-vector, ∼4.8-kb AAV platforms that express Nme2Cas9 and either two sgRNAs to produce segmental deletions, or a single sgRNA with an HDR template. We also examine the utility of Nme2Cas9 target sites in the vector for self-inactivation. We demonstrate that these platforms can effectively treat two disease models [type I hereditary tyrosinemia (HT-I) and mucopolysaccharidosis type I (MPS-I)] in mice. These results will enable single-vector AAVs to achieve diverse therapeutic genome editing outcomes.

RNA processing has emerged as a key mechanistic step in the regulation of the cellular response to environmental perturbation. Recent work has uncovered extensive remodeling of transcriptome composition upon environmental perturbation and linked the impacts of this molecular plasticity to health and disease outcomes. These isoform changes and their underlying mechanisms are varied-involving alternative sites of transcription initiation, alternative splicing, and alternative cleavage at the 3' end of the mRNA. The mechanisms and consequences of differential RNA processing have been characterized across a range of common environmental insults, including chemical stimuli, immune stimuli, heat stress, and cancer pathogenesis. In each case, there are perturbation-specific contributions of local (cis) regulatory elements or global (trans) factors and downstream consequences. Overall, it is clear that choices in isoform usage involve a balance between the usage of specific genetic elements (i.e., splice sites, polyadenylation sites) and the timing at which certain decisions are made (i.e., transcription elongation rate). Fine-tuned cellular responses to environmental perturbation are often dependent on the genetic makeup of the cell. Genetic analyses of interindividual variation in splicing have identified genetic effects on splicing that contribute to variation in complex traits. Finally, the increase in the number of tissue types and environmental conditions analyzed for RNA processing is paralleled by the need to develop appropriate analytical tools. The combination of large datasets, novel methods and conditions explored promises to provide a much greater understanding of the role of RNA processing response in human phenotypic variation. This article is categorized under: RNA Processing > RNA Editing and Modification RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Mechanisms RNA Processing > Splicing Regulation/Alternative Splicing.

Production of most eukaryotic mRNAs requires splicing of introns from pre-mRNA. The splicing reaction requires definition of splice sites, which are initially recognized in either intron-spanning (‘intron definition’) or exon-spanning (‘exon definition’) pairs. To understand how exon and intron length and splice site recognition mode impact splicing, we measured splicing rates genome-wide in Drosophila, using metabolic labeling/RNA sequencing and new mathematical models to estimate rates. We found that the modal intron length range of 60–70 nt represents a local maximum of splicing rates, but that much longer exon-defined introns are spliced even faster and more accurately. We observed unexpectedly low variation in splicing rates across introns in the same gene, suggesting the presence of gene-level influences, and we identified multiple gene level variables associated with splicing rate. Together our data suggest that developmental and stress response genes may have preferentially evolved exon definition in order to enhance the rate or accuracy of splicing., National Institutes of Health (U.S.) (Grant R01-GM085319)

Most human protein-coding genes can be transcribed into multiple distinct mRNA isoforms. These alternative splicing patterns encourage molecular diversity, and dysregulation of isoform expression plays an important role in disease etiology. However, isoforms are difficult to characterize from short-read RNA-seq data because they share identical subsequences and occur in different frequencies across tissues and samples. Here, we develop biisq, a Bayesian nonparametric model for isoform discovery and individual specific quantification from short-read RNA-seq data. biisq does not require isoform reference sequences but instead estimates an isoform catalog shared across samples. We use stochastic variational inference for efficient posterior estimates and demonstrate superior precision and recall for simulations compared to state-of-the-art isoform reconstruction methods. biisq shows the most gains for low abundance isoforms, with 36% more isoforms correctly inferred at low coverage versus a multi-sample method and 170% more versus single-sample methods. We estimate isoforms in the GEUVADIS RNA-seq data and validate inferred isoforms by associating genetic variants with isoform ratios., Alternative splicing leads to transcript isoform diversity. Here, Aguiar et al. develop biisq, a Bayesian nonparametric approach to discover and quantify isoforms from RNA-seq data.

Mammalian transcriptomes are complex and formed by extensive promoter activity. In addition, gene promoters are largely divergent and initiate transcription of reverse-oriented promoter upstream transcripts (PROMPTs). Although PROMPTs are commonly terminated early, influenced by polyadenylation sites, promoters often cluster so that the divergent activity of one might impact another. Here, we find that the distance between promoters strongly correlates with the expression, stability and length of their associated PROMPTs. Adjacent promoters driving divergent mRNA transcription support PROMPT formation, but due to polyadenylation site constraints, these transcripts tend to spread into the neighboring mRNA on the same strand. This mechanism to derive new alternative mRNA transcription start sites (TSSs) is also evident at closely spaced promoters supporting convergent mRNA transcription. We suggest that basic building blocks of divergently transcribed core promoter pairs, in combination with the wealth of TSSs in mammalian genomes, provides a framework with which evolution shapes transcriptomes.

Long intergenic non-coding RNAs (lincRNA) are members of a class of non-protein-coding RNA transcript that has recently been shown to contribute to gene regulatory processes and disease etiology. It has been hypothesized that lincRNAs influence disease risk through the regulation of mRNA transcription, possibly by interacting with regulatory proteins such as chromatin-modifying complexes. The hypothesis of the regulation of mRNA by lincRNAs is based on a small number of specific lincRNAs analyses; the cellular roles of lincRNAs regulation have not been catalogued genome-wide. Relative to mRNAs, lincRNAs tend to be expressed at lower levels and in more tissue-specific patterns, making genome-wide studies of their regulatory capabilities difficult. Here we develop a method for Mendelian randomization leveraging expression quantitative trait loci (eQTLs) that regulate the expression levels of lincRNAs (linc-eQTLs) to perform such a study across four primary tissues. We find that linc-eQTLs are largely similar to protein-coding eQTLs (pc-eQTLs) in cis-regulatory element enrichment, which supports the hypothesis that lincRNAs are regulated by the same transcriptional machinery as protein-coding RNAs and validates our linc-eQTLs. We catalog 74 lincRNAs with linc-eQTLs that are in linkage disequilibrium with TASs and are in protein-coding gene deserts; the putative lincRNA-regulated traits are highly enriched for adipose-related traits relative to mRNA-regulated traits.

In human lymphoblastoid cell lines, 8,902 loci were identified at which genetic variation is significantly associated with local DNase I sensitivity; these variants are responsible for a large fraction of expression quantitative trait loci. Expression quantitative trait loci (eQTLs) are stretches of DNA that regulate gene transcription and expression and contribute to a particular phenotypic trait. eQTL mapping is an important tool for linking genetic variation to changes in gene regulation, but identifying the causal variants underlying eQTLs and the regulatory mechanisms involved remains a challenge. Degner et al. used DNaseI sequencing to measure genome-wide chromatin accessibility in 70 Yoruba lymphoblastoid cell lines to produce genome-wide maps of chromatin accessibility for each individual. They identify variants that they call DNaseI sensitivity quantitative trait loci (dsQTLs). The implication is that changes in chromatin accessibility or transcription-factor binding occur at many gene loci and are likely to be important contributors to phenotypic variation. The mapping of expression quantitative trait loci (eQTLs) has emerged as an important tool for linking genetic variation to changes in gene regulation1,2,3,4,5. However, it remains difficult to identify the causal variants underlying eQTLs, and little is known about the regulatory mechanisms by which they act. Here we show that genetic variants that modify chromatin accessibility and transcription factor binding are a major mechanism through which genetic variation leads to gene expression differences among humans. We used DNase I sequencing to measure chromatin accessibility in 70 Yoruba lymphoblastoid cell lines, for which genome-wide genotypes and estimates of gene expression levels are also available6,7,8. We obtained a total of 2.7 billion uniquely mapped DNase I-sequencing (DNase-seq) reads, which allowed us to produce genome-wide maps of chromatin accessibility for each individual. We identified 8,902 locations at which the DNase-seq read depth correlated significantly with genotype at a nearby single nucleotide polymorphism or insertion/deletion (false discovery rate = 10%). We call such variants ‘DNase I sensitivity quantitative trait loci’ (dsQTLs). We found that dsQTLs are strongly enriched within inferred transcription factor binding sites and are frequently associated with allele-specific changes in transcription factor binding. A substantial fraction (16%) of dsQTLs are also associated with variation in the expression levels of nearby genes (that is, these loci are also classified as eQTLs). Conversely, we estimate that as many as 55% of eQTL single nucleotide polymorphisms are also dsQTLs. Our observations indicate that dsQTLs are highly abundant in the human genome and are likely to be important contributors to phenotypic variation.

Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the ‘missing heritability problem’. Several sources for the missing heritability have been proposed, including the contribution of many common variants with small individual effect sizes, which cannot be reliably found using the standard GWAS approach. The goal of our study was to explore a complimentary approach, which combines GWAS results with functional data in order to identify novel genetic associations with small effect sizes. To do so, we conducted a GWAS for lymphocyte count, a physiologic quantitative trait associated with asthma, in 462 Hutterites. In parallel, we performed a genome-wide gene expression study in lymphoblastoid cell lines from 96 Hutterites. We found significant support for genetic associations using the GWAS data when we considered variants near the 193 genes whose expression levels across individuals were most correlated with lymphocyte counts. Interestingly, these variants are also enriched with signatures of an association with asthma susceptibility, an observation we were able to replicate. The associated loci include genes previously implicated in asthma susceptibility as well as novel candidate genes enriched for functions related to T cell receptor signaling and adenosine triphosphate synthesis. Our results, therefore, establish a new set of asthma susceptibility candidate genes. More generally, our observations support the notion that many loci of small effects influence variation in lymphocyte count and asthma susceptibility.

Accurate functional annotation of regulatory elements is essential for understanding global gene regulation. Here, we report a genome-wide map of 827,000 transcription factor binding sites in human lymphoblastoid cell lines, which is comprised of sites corresponding to 239 position weight matrices of known transcription factor binding motifs, and 49 novel sequence motifs. To generate this map, we developed a probabilistic framework that integrates cell- or tissue-specific experimental data such as histone modifications and DNase I cleavage patterns with genomic information such as gene annotation and evolutionary conservation. Comparison to empirical ChIP-seq data suggests that our method is highly accurate yet has the advantage of targeting many factors in a single assay. We anticipate that this approach will be a valuable tool for genome-wide studies of gene regulation in a wide variety of cell types or tissues under diverse conditions.

Motivation: Next-generation sequencing has become an important tool for genome-wide quantification of DNA and RNA. However, a major technical hurdle lies in the need to map short sequence reads back to their correct locations in a reference genome. Here, we investigate the impact of SNP variation on the reliability of read-mapping in the context of detecting allele-specific expression (ASE). Results: We generated 16 million 35 bp reads from mRNA of each of two HapMap Yoruba individuals. When we mapped these reads to the human genome we found that, at heterozygous SNPs, there was a significant bias toward higher mapping rates of the allele in the reference sequence, compared with the alternative allele. Masking known SNP positions in the genome sequence eliminated the reference bias but, surprisingly, did not lead to more reliable results overall. We find that even after masking, ∼5–10% of SNPs still have an inherent bias toward more effective mapping of one allele. Filtering out inherently biased SNPs removes 40% of the top signals of ASE. The remaining SNPs showing ASE are enriched in genes previously known to harbor cis-regulatory variation or known to show uniparental imprinting. Our results have implications for a variety of applications involving detection of alternate alleles from short-read sequence data. Availability: Scripts, written in Perl and R, for simulating short reads, masking SNP variation in a reference genome and analyzing the simulation output are available upon request from JFD. Raw short read data were deposited in GEO (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE18156. Contact: jdegner@uchicago.edu; marioni@uchicago.edu; gilad@uchicago.edu; pritch@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online.

The Altaian Kazakhs, a Turkic speaking group, now reside in the southern part of the Altai Republic in south-central Russia. According to historical accounts, they are one of several ethnic and geographical subdivisions of the Kazakh nomadic group that migrated from China and Western Mongolia into the Altai region during the 19th Century. However, their population history of the Altaian Kazakhs and the genetic relationships with other Kazakh groups and neighboring Turkic-speaking populations is not well understood. To begin elucidating their genetic history, we analyzed the mtDNAs from 237 Altaian Kazakhs through a combination of SNP analysis and HVS1 sequencing. This analysis revealed that their mtDNA gene pool was comprised of roughly equal proportions of East (A-G, M7, M13, Y and Z) and West (H, HV, pre-HV, R, IK, JT, X, U) Eurasian haplogroups, with the haplotypic diversity within haplogroups C, D, H, and U being particularly high. This pattern of diversity likely reflects the complex interactions of the Kazakhs with other Turkic groups, Mongolians, and indigenous Altaians. Overall, these data have important implications for Kazakh population history, the genetic prehistory of the Altai-Sayan region, and the phylogeography of major mitochondrial lineages in Eurasia.

The contribution of pre-mRNA processing mechanisms to the regulation of immune responses remains poorly studied despite emerging examples of their role as regulators of immune defenses. We sought to investigate the role of mRNA processing in the cellular responses of human macrophages to live bacterial infections. Here, we used mRNA sequencing to quantify gene expression and isoform abundances in primary macrophages from 60 individuals, before and after infection with Listeria monocytogenes and Salmonella typhimurium. In response to both bacteria we identified thousands of genes that significantly change isoform usage in response to infection, characterized by an overall increase in isoform diversity after infection. In response to both bacteria, we found global shifts towards (i) the inclusion of cassette exons and (ii) shorter 3’ UTRs, with near-universal shifts towards usage of more upstream polyadenylation sites. Using complementary data collected in non-human primates, we show that these features are evolutionarily conserved among primates. Following infection, we identify candidate RNA processing factors whose expression is associated with individual-specific variation in isoform abundance. Finally, by profiling microRNA levels, we show that 3’ UTRs with reduced abundance after infection are significantly enriched for target sites for particular miRNAs. These results suggest that the pervasive usage of shorter 3’ UTRs is a mechanism for particular genes to evade repression by immune-activated miRNAs. Collectively, our results suggest that dynamic changes in RNA processing may play key roles in the regulation of innate immune responses., Author Summary Changes in gene regulation have long been known to play important roles in both innate and adaptive immune responses. While transcriptional responses to infection have been well-characterized, much less is known about the extent to which co-transcriptional mechanisms of mRNA processing are involved in the regulation of immune defenses. In this study, we sought to investigate the role of mRNA processing in the cellular responses of human macrophages to live bacterial infection. Using primary human macrophages derived from whole blood samples from 60 individuals, we sequenced mRNA both before and after infection with two live bacteria. We show that immune responses to infection are accompanied by pervasive changes in mRNA isoform usage, with systematic shifts towards increased cassette exon inclusion and shortening of Tandem 3’ UTRs post-infection. These patterns are conserved in nonhuman primates, supporting their functional importance across evolutionary time. Complementary microRNA profiling revealed that shortened 3’ UTRs are enriched for target sites of macrophage-expressed miRNAs, many of which are specifically activated after infection to regulate the innate immune response. Our results therefore provide the first genome-wide empirical support for the idea that actively regulated shifts towards shorter 3’ UTRs might allow specific genes to evade repression by immune-activated miRNAs.

DNA methylation is thought to be robust to environmental perturbations on a short time scale. Here, we challenge that view by demonstrating that the infection of human dendritic cells (DCs) with a pathogenic bacteria is associated with rapid changes in methylation at thousands of loci. Infection-induced changes in methylation occur primarily at distal enhancer elements, including those associated with the activation of key immune transcription factors and genes involved in the crosstalk between DCs and adaptive immunity. Active demethylation is associated with extensive epigenetic remodeling and is strongly predictive of changes in the expression levels of nearby genes. Collectively, our observations show that rapid changes in methylation play a previously unappreciated role in regulating the transcriptional response of DCs to infection.

Alagille syndrome (AGS) is caused by mutations in the gene for the Notch signaling pathway ligand Jagged1 (JAG1), which are found in 94% of patients. To identify the cause of disease in patients without JAG1 mutations, we screened 11 JAG1 mutation-negative probands with AGS for alterations in the gene for the Notch2 receptor (NOTCH2). We found NOTCH2 mutations segregating in two families and identified five affected individuals. Renal manifestations, a minor feature in AGS, were present in all the affected individuals. This demonstrates that AGS is a heterogeneous disorder and implicates NOTCH2 mutations in human disease.

The use of low quality RNA samples in whole-genome gene expression profiling remains controversial. It is unclear if transcript degradation in low quality RNA samples occurs uniformly, in which case the effects of degradation can be normalized, or whether different transcripts are degraded at different rates, potentially biasing measurements of expression levels. This concern has rendered the use of low quality RNA samples in whole-genome expression profiling problematic. Yet, low quality samples are at times the sole means of addressing specific questions – e.g., samples collected in the course of fieldwork. We sought to quantify the impact of variation in RNA quality on estimates of gene expression levels based on RNA-seq data. To do so, we collected expression data from tissue samples that were allowed to decay for varying amounts of time prior to RNA extraction. The RNA samples we collected spanned the entire range of RNA Integrity Number (RIN) values (a quality metric commonly used to assess RNA quality). We observed widespread effects of RNA quality on measurements of gene expression levels, as well as a slight but significant loss of library complexity in more degraded samples. While standard normalizations failed to account for the effects of degradation, we found that a simple linear model that controls for the effects of RIN can correct for the majority of these effects. We conclude that in instances where RIN and the effect of interest are not associated, this approach can help recover biologically meaningful signals in data from degraded RNA samples.

Gene expression differences are shaped by selective pressures and contribute to phenotypic differences between species. We identified 964 copy number differences (CNDs) of conserved sequences across three primate species and examined their potential effects on gene expression profiles. Samples with copy number different genes had significantly different expression than samples with neutral copy number. Genes encoding regulatory molecules differed in copy number and were associated with significant expression differences. Additionally, we identified 127 CNDs that were processed pseudogenes and some of which were expressed. Furthermore, there were copy number-different regulatory regions such as ultraconserved elements and long intergenic noncoding RNAs with the potential to affect expression. We postulate that CNDs of these conserved sequences fine-tune developmental pathways by altering the levels of RNA.

Nucleosomes are important for gene regulation because their arrangement on the genome can control which proteins bind to DNA. Currently, few human nucleosomes are thought to be consistently positioned across cells; however, this has been difficult to assess due to the limited resolution of existing data. We performed paired-end sequencing of micrococcal nuclease-digested chromatin (MNase–seq) from seven lymphoblastoid cell lines and mapped over 3.6 billion MNase–seq fragments to the human genome to create the highest-resolution map of nucleosome occupancy to date in a human cell type. In contrast to previous results, we find that most nucleosomes have more consistent positioning than expected by chance and a substantial fraction (8.7%) of nucleosomes have moderate to strong positioning. In aggregate, nucleosome sequences have 10 bp periodic patterns in dinucleotide frequency and DNase I sensitivity; and, across cells, nucleosomes frequently have translational offsets that are multiples of 10 bp. We estimate that almost half of the genome contains regularly spaced arrays of nucleosomes, which are enriched in active chromatin domains. Single nucleotide polymorphisms that reduce DNase I sensitivity can disrupt the phasing of nucleosome arrays, which indicates that they often result from positioning against a barrier formed by other proteins. However, nucleosome arrays can also be created by DNA sequence alone. The most striking example is an array of over 400 nucleosomes on chromosome 12 that is created by tandem repetition of sequences with strong positioning properties. In summary, a large fraction of nucleosomes are consistently positioned—in some regions because they adopt favored sequence positions, and in other regions because they are forced into specific arrangements by chromatin remodeling or DNA binding proteins., Author Summary Within the nucleus of the cell, the genome of eukaryotic organisms is tightly packaged into chromatin. Chromatin is composed of a repeating series of bead-like nucleosomes, each of which is encircled 1.7 times by a string of DNA. The organization of nucleosomes on the genome is fundamentally important because they can prevent other proteins from accessing the DNA. Previous studies of human nucleosomes concluded that most nucleosomes have fuzzy positioning and tend to occupy different locations in different cells. This interpretation, however, may be a consequence of the low resolution of existing data. Here we revisit the question of nucleosome positioning by generating the most precise map of nucleosome positions that has ever been created for a human cell line. We find that 8.7% of nucleosomes have very consistent positioning, and most nucleosomes are more consistently positioned than expected by chance. Additionally, we estimate that almost half of the genome contains regularly spaced arrays of nucleosomes. Much of this positioning is due to the intrinsic preference of nucleosomes for some DNA sequences over others; but in some regions of the genome, the sequence preferences of nucleosomes are overridden by proteins that out-compete them for binding or displace them using energy from ATP.

Tuberculosis (TB) is a major public health problem. One-third of the world's population is estimated to be infected with Mycobacterium tuberculosis (MTB), the etiological agent causing TB, and active disease kills nearly 2 million individuals worldwide every year. Several lines of evidence indicate that interindividual variation in susceptibility to TB has a heritable component, yet we still know little about the underlying genetic architecture. To address this, we performed a genome-wide mapping study of loci that are associated with functional variation in immune response to MTB. Specifically, we characterized transcript and protein expression levels and mapped expression quantitative trait loci (eQTL) in primary dendritic cells (DCs) from 65 individuals, before and after infection with MTB. We found 198 response eQTL, namely loci that were associated with variation in gene expression levels in either untreated or MTB-infected DCs, but not both. These response eQTL are associated with natural regulatory variation that likely affects (directly or indirectly) host interaction with MTB. Indeed, when we integrated our data with results from a genome-wide association study (GWAS) for pulmonary TB, we found that the response eQTL were more likely to be genetically associated with the disease. We thus identified a number of candidate loci, including the MAPK phosphatase DUSP14 in particular, that are promising susceptibility genes to pulmonary TB.

BACKGROUND Population history can be reflected in group genetic ancestry, where genomic variation captured by the mitochondrial DNA (mtDNA) and non-recombining portion of the Y chromosome (NRY) can separate female- and male-specific admixture processes. Genetic ancestry may influence genetic association studies due to differences in individual admixture within recently admixed populations like African Americans. PRINCIPAL FINDINGS We evaluated the genetic ancestry of Senegalese as well as European Americans and African Americans from Philadelphia. Senegalese mtDNA consisted of approximately 12% U haplotypes (U6 and U5b1b haplotypes, common in North Africa) while the NRY haplotypes belonged solely to haplogroup E. In Philadelphia, we observed varying degrees of admixture. While African Americans have 9-10% mtDNAs and approximately 31% NRYs of European origin, these results are not mirrored in the mtDNA/NRY pools of European Americans: they have less than 7% mtDNAs and less than 2% NRYs from non-European sources. Additionally, there is

Recent gene expression QTL (eQTL) mapping studies have provided considerable insight into the genetic basis for inter-individual regulatory variation. However, a limitation of all eQTL studies to date, which have used measurements of steady-state gene expression levels, is the inability to directly distinguish between variation in transcription and decay rates. To address this gap, we performed a genome-wide study of variation in gene-specific mRNA decay rates across individuals. Using a time-course study design, we estimated mRNA decay rates for over 16,000 genes in 70 Yoruban HapMap lymphoblastoid cell lines (LCLs), for which extensive genotyping data are available. Considering mRNA decay rates across genes, we found that: (i) as expected, highly expressed genes are generally associated with lower mRNA decay rates, (ii) genes with rapid mRNA decay rates are enriched with putative binding sites for miRNA and RNA binding proteins, and (iii) genes with similar functional roles tend to exhibit correlated rates of mRNA decay. Focusing on variation in mRNA decay across individuals, we estimate that steady-state expression levels are significantly correlated with variation in decay rates in 10% of genes. Somewhat counter-intuitively, for about half of these genes, higher expression is associated with faster decay rates, possibly due to a coupling of mRNA decay with transcriptional processes in genes involved in rapid cellular responses. Finally, we used these data to map genetic variation that is specifically associated with variation in mRNA decay rates across individuals. We found 195 such loci, which we named RNA decay quantitative trait loci (“rdQTLs”). All the observed rdQTLs are located near the regulated genes and therefore are assumed to act in cis. By analyzing our data within the context of known steady-state eQTLs, we estimate that a substantial fraction of eQTLs are associated with inter-individual variation in mRNA decay rates., Author Summary Recent studies of functional genetic variation in humans have identified numerous loci that are associated with variation in gene expression levels, called expression quantitative trait loci (eQTLs). The mechanisms by which these loci affect gene expression, however, are still largely unknown. Specifically, since most studies rely on measures of steady-state gene expression levels, they are unable to distinguish between the relative influences of either transcriptional- or decay-related processes. To address this gap, we examined the specific impact of mRNA decay processes on steady-state gene expression levels for over 16,000 genes in human lymphoblastoid cell lines. By characterizing decay rates in 70 individuals, we show that steady-state expression levels are significantly influenced by variation in decay rates for 10% of genes. Yet, for roughly half of these genes, we find that individuals with higher expression levels also have faster decay rates. This pattern points to a non-simple mechanistic interplay between transcriptional and decay processes, especially for genes involved in rapid cellular responses. Finally, we identify 195 genetic variants that are significantly associated with both gene expression variation and variation in mRNA decay rates. Using these data, we estimate that that a substantial fraction of eQTLs are associated with inter-individual variation in mRNA decay rates.