Brian Dalley

Using VAAST to identify an X-linked disorder resulting in lethality in male infants due to N-terminal acetyltransferase deficiency.

We have identified two families with a previously undescribed lethal X-linked disorder of infancy; the disorder comprises a distinct combination of an aged appearance, craniofacial anomalies, hypotonia, global developmental delays, cryptorchidism, and cardiac arrhythmias. Using X chromosome exon sequencing and a recently developed probabilistic algorithm aimed at discovering disease-causing variants, we identified in one family a c.109T>C (p.Ser37Pro) variant in NAA10, a gene encoding the catalytic subunit of the major human N-terminal acetyltransferase (NAT). A parallel effort on a second unrelated family converged on the same variant. The absence of this variant in controls, the amino acid conservation of this region of the protein, the predicted disruptive change, and the co-occurrence in two unrelated families with the same rare disorder suggest that this is the pathogenic mutation. We confirmed this by demonstrating a significantly impaired biochemical activity of the mutant hNaa10p, and from this we conclude that a reduction in acetylation by hNaa10p causes this disease. Here we provide evidence of a human genetic disorder resulting from direct impairment of N-terminal acetylation, one of the most common protein modifications in humans.

Dynamic transcriptome of Schizosaccharomyces pombe shown by RNA-DNA hybrid mapping

We have determined the high-resolution strand-specific transcriptome of the fission yeast S. pombe under multiple growth conditions using a novel RNA-DNA hybridization mapping (HybMap) technique. HybMap uses an antibody against an RNA-DNA hybrid to detect RNA molecules hybridized to a high-density DNA oligonucleotide tiling microarray. HybMap showed exceptional dynamic range and reproducibility, and allowed us to identify strand-specific coding, noncoding and structural RNAs, as well as previously unknown RNAs conserved in distant yeast species. Notably, we found that virtually the entire euchromatic genome (including intergenics) is transcribed, with heterochromatin dampening intergenic transcription. We identified features including large numbers of condition-specific noncoding RNAs, extensive antisense transcription, new properties of antisense transcripts and induced divergent transcription. Furthermore, our HybMap data informed the efficiency and locations of RNA splicing genome-wide. Finally, we observed strand-specific transcription islands around tRNAs at heterochromatin boundaries inside centromeres. Here, we discuss these new features in terms of organism fitness and transcriptome evolution.

Next generation tools for genomic data generation, distribution, and visualization

BackgroundWith the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the laboratory and clinic is shifting to one of effectively managing, analyzing, and sharing genomic data.ResultsHere we present three open-source, platform independent, software tools for generating, analyzing, distributing, and visualizing genomic data. These include a next generation sequencing/microarray LIMS and analysis project center (GNomEx); an application for annotating and programmatically distributing genomic data using the community vetted DAS/2 data exchange protocol (GenoPub); and a standalone Java Swing application (GWrap) that makes cutting edge command line analysis tools available to those who prefer graphical user interfaces. Both GNomEx and GenoPub use the rich client Flex/Flash web browser interface to interact with Java classes and a relational database on a remote server. Both employ a public-private user-group security model enabling controlled distribution of patient and unpublished data alongside public resources. As such, they function as genomic data repositories that can be accessed manually or programmatically through DAS/2-enabled client applications such as the Integrated Genome Browser.ConclusionsThese tools have gained wide use in our core facilities, research laboratories and clinics and are freely available for non-profit use. See http://sourceforge.net/projects/gnomex/, http://sourceforge.net/projects/genoviz/, and http://sourceforge.net/projects/useq.

Age-related mutations and chronic myelomonocytic leukemia

Chronic myelomonocytic leukemia (CMML) is a hematologic malignancy nearly confined to the elderly. Previous studies to determine incidence and prognostic significance of somatic mutations in CMML have relied on candidate gene sequencing, although an unbiased mutational search has not been conducted. As many of the genes commonly mutated in CMML were recently associated with age-related clonal hematopoiesis (ARCH) and aged hematopoiesis is characterized by a myelomonocytic differentiation bias, we hypothesized that CMML and aged hematopoiesis may be closely related. We initially established the somatic mutation landscape of CMML by whole exome sequencing followed by gene-targeted validation. Genes mutated in ⩾10% of patients were SRSF2, TET2, ASXL1, RUNX1, SETBP1, KRAS, EZH2, CBL and NRAS, as well as the novel CMML genes FAT4, ARIH1, DNAH2 and CSMD1. Most CMML patients (71%) had mutations in ⩾2 ARCH genes and 52% had ⩾7 mutations overall. Higher mutation burden was associated with shorter survival. Age-adjusted population incidence and reported ARCH mutation rates are consistent with a model in which clinical CMML ensues when a sufficient number of stochastically acquired age-related mutations has accumulated, suggesting that CMML represents the leukemic conversion of the myelomonocytic-lineage-biased aged hematopoietic system.

Polymorphisms in the NPY2R Gene Show Significant Associations With BMI That Are Additive to FTO, MC4R, and NPFFR2 Gene Effects

Neuropeptide Y (NPY) is an appetite hormone that acts centrally to control feeding behavior. The 5′ and exon 2 regions of NPY2R, one of five NPY receptor genes, have been weakly and inconsistently implicated with obesity. With the ATG start site of the gene at the beginning of exon 2, single‐nucleotide polymorphisms (SNPs) across intron 1 may show stronger associations with obesity than expected. Two 5′ SNPs, three intron 1 SNPs, and one synonymous exon 2 SNP were genotyped on 2,985 white Utah subjects. Previously associated FTO, NPY, NPY1R, MC4R, PPARGC1A, OR7D4, and four NPFFR2 SNPs were also genotyped and related to BMI. One NPY2R 5′ SNP (rs12649641, P = 0.008), an exon 2 SNP (rs2880415, P = 0.009), and an intron 1 SNP (rs17376826, P = 7 × 10−6) were each significantly associated with BMI. All three SNPs, plus FTO (rs9939609, P = 1.5 × 10−6) and two NPFFR2 SNPs (rs4129733, P = 3.7 × 10−13 and rs11940196, 4.2 × 10−10) remained significant in a multiple regression additive model. Diplotypes using the estimated haplotypes of NPY2R, NPFFR2, and MC4R were significantly associated with BMI (P = 1.0 × 10−10, 3.2 × 10−8, and 1.1 × 10−4, respectively). Haplotypes of NPY2R, NPFFR2, and MC4R, plus the FTO SNP, explained 9.6% of the BMI variance. SNP effect sizes per allele for the four genes ranged from 0.8 to 3.5 kg/m2. We conclude that haplotypes containing the rs17376826 SNP in intron 1 of NPY2R have strong associations with BMI, some NPFFR2 haplotypes are strongly protective against or increase risk of obesity, and both NPY2R and NPFFR2 play important roles in obesity predisposition independent of FTO and MC4R.

Combining quantitative genetic footprinting and trait enrichment analysis to identify fitness determinants of a bacterial pathogen.

Strains of Extraintestinal Pathogenic Escherichia c oli (ExPEC) exhibit an array of virulence strategies and are a major cause of urinary tract infections, sepsis and meningitis. Efforts to understand ExPEC pathogenesis are challenged by the high degree of genetic and phenotypic variation that exists among isolates. Determining which virulence traits are widespread and which are strain-specific will greatly benefit the design of more effective therapies. Towards this goal, we utilized a quantitative genetic footprinting technique known as transposon insertion sequencing (Tn-seq) in conjunction with comparative pathogenomics to functionally dissect the genetic repertoire of a reference ExPEC isolate. Using Tn-seq and high-throughput zebrafish infection models, we tracked changes in the abundance of ExPEC variants within saturated transposon mutant libraries following selection within distinct host niches. Nine hundred and seventy bacterial genes (18% of the genome) were found to promote pathogen fitness in either a niche-dependent or independent manner. To identify genes with the highest therapeutic and diagnostic potential, a novel Trait Enrichment Analysis (TEA) algorithm was developed to ascertain the phylogenetic distribution of candidate genes. TEA revealed that a significant portion of the 970 genes identified by Tn-seq have homologues more often contained within the genomes of ExPEC and other known pathogens, which, as suggested by the first axiom of molecular Kochs postulates, is considered to be a key feature of true virulence determinants. Three of these Tn-seq-derived pathogen-associated genes—a transcriptional repressor, a putative metalloendopeptidase toxin and a hypothetical DNA binding protein—were deleted and shown to independently affect ExPEC fitness in zebrafish and mouse models of infection. Together, the approaches and observations reported herein provide a resource for future pathogenomics-based research and highlight the diversity of factors required by a single ExPEC isolate to survive within varying host environments.

Zinc-dependent Regulation of the adh1 Antisense Transcript in Fission Yeast

Background: Antisense transcription can inhibit complementary strand gene expression. Results: Multiple mechanisms ensure that adh1 antisense transcripts preferentially accumulate in zinc-limited cells. Conclusion: Different mechanisms control the ratio of sense and antisense transcripts in response to changes in nutrient levels. Significance: Alterations in the environment may contribute to the aberrant expression of antisense transcripts in complex diseases. In yeast, Adh1 (alcohol dehydrogenase 1) is an abundant zinc-binding protein that is required for the conversion of acetaldehyde to ethanol. Through transcriptome profiling of the Schizosaccharomyces pombe genome, we identified a natural antisense transcript at the adh1 locus that is induced in response to zinc limitation. This antisense transcript (adh1AS) shows a reciprocal expression pattern to that of the adh1 mRNA partner. In this study, we show that increased expression of the adh1AS transcript in zinc-limited cells is necessary for the repression of adh1 gene expression and that the increased level of the adh1AS transcript in zinc-limited cells is a result of two mechanisms. At the transcriptional level, the adh1AS transcript is expressed at a high level in zinc-limited cells. In addition to this transcriptional control, adh1AS transcripts preferentially accumulate in zinc-limited cells when the adh1AS transcript is expressed from a constitutive promoter. This secondary mechanism requires the simultaneous expression of adh1. Our studies reveal how multiple mechanisms can synergistically control the ratio of sense to antisense transcripts and highlight a novel mechanism by which adh1 gene expression can be controlled by cellular zinc availability.

Combating subclonal evolution of resistant cancer phenotypes

Metastatic breast cancer remains challenging to treat, and most patients ultimately progress on therapy. This acquired drug resistance is largely due to drug-refractory sub-populations (subclones) within heterogeneous tumors. Here, we track the genetic and phenotypic subclonal evolution of four breast cancers through years of treatment to better understand how breast cancers become drug-resistant. Recurrently appearing post-chemotherapy mutations are rare. However, bulk and single-cell RNA sequencing reveal acquisition of malignant phenotypes after treatment, including enhanced mesenchymal and growth factor signaling, which may promote drug resistance, and decreased antigen presentation and TNF-α signaling, which may enable immune system avoidance. Some of these phenotypes pre-exist in pre-treatment subclones that become dominant after chemotherapy, indicating selection for resistance phenotypes. Post-chemotherapy cancer cells are effectively treated with drugs targeting acquired phenotypes. These findings highlight cancer’s ability to evolve phenotypically and suggest a phenotype-targeted treatment strategy that adapts to cancer as it evolves.In metastatic breast cancer, subclonal evolution can drive drug resistance. Here, the authors genetically and transcriptionally follow the evolution of four breast cancers over time and treatment, and suggest a phenotype-targeted treatment strategy to adapt to cancer as it evolves.

Antibody detection of translocations in Ewing sarcoma.

The detection of chromosomal translocations has important implications in the diagnosis, prognosis and treatment of patients with cancer. Current approaches to translocation detection have significant shortcomings, including limited sensitivity and/or specificity, and difficulty in application to formalin‐fixed paraffin‐embedded (FFPE) clinical samples. We developed a new approach called antibody detection of translocations (ADOT) that avoids the shortcomings of current techniques. ADOT combines a transcriptional microarray‐based approach with a novel antibody‐based detection method. ADOT allows for the accurate and sensitive identification of translocations and provides exon‐level information about the fusion transcript. ADOT can detect translocations in poor‐quality unprocessed total ribonucleic acid (RNA). Furthermore, the technique is readily generalizable to detect any potential fusion transcript, including previously undescribed fusions. We demonstrate the feasibility of ADOT by examples in which both known and unknown Ewing sarcoma translocations are identified from cell lines, tumour xenografts and FFPE primary tumours. These results demonstrate that ADOT may be an effective approach for translocation analysis in clinical specimens with significant RNA degradation and may offer a novel diagnostic tool for translocation‐based cancers.

A comprehensive multi-omics approach uncovers adaptations for growth and survival of Pseudomonas aeruginosa on n-alkanes.

BackgroundExamination of complex biological systems has long been achieved through methodical investigation of the system’s individual components. While informative, this strategy often leads to inappropriate conclusions about the system as a whole. With the advent of high-throughput “omic” technologies, however, researchers can now simultaneously analyze an entire system at the level of molecule (DNA, RNA, protein, metabolite) and process (transcription, translation, enzyme catalysis). This strategy reduces the likelihood of improper conclusions, provides a framework for elucidation of genotype-phenotype relationships, and brings finer resolution to comparative genomic experiments. Here, we apply a multi-omic approach to analyze the gene expression profiles of two closely related Pseudomonas aeruginosa strains grown in n-alkanes or glycerol.ResultsThe environmental P. aeruginosa isolate ATCC 33988 consumed medium-length (C10–C16) n-alkanes more rapidly than the laboratory strain PAO1, despite high genome sequence identity (average nucleotide identity >99%). Our data shows that ATCC 33988 induces a characteristic set of genes at the transcriptional, translational and post-translational levels during growth on alkanes, many of which differ from those expressed by PAO1. Of particular interest was the lack of expression from the rhl operon of the quorum sensing (QS) system, resulting in no measurable rhamnolipid production by ATCC 33988. Further examination showed that ATCC 33988 lacked the entire lasI/lasR arm of the QS response. Instead of promoting expression of QS genes, ATCC 33988 up-regulates a small subset of its genome, including operons responsible for specific alkaline proteases and sphingosine metabolism.ConclusionThis work represents the first time results from RNA-seq, microarray, ribosome footprinting, proteomics, and small molecule LC-MS experiments have been integrated to compare gene expression in bacteria. Together, these data provide insights as to why strain ATCC 33988 is better adapted for growth and survival on n-alkanes.