The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome

Efficient genotype compression and analysis of large genetic-variation data sets

Genotype Query Tools (GQT) is an indexing strategy that expedites analyses of genome-variation data sets in Variant Call Format based on sample genotypes, phenotypes and relationships. GQT's compressed genotype index minimizes decompression for analysis, and its performance relative to that of existing methods improves with cohort size. We show substantial (up to 443-fold) gains in performance over existing methods and demonstrate GQT's utility for exploring massive data sets involving thousands to millions of genomes. GQT can be accessed at https://github.com/ryanlayer/gqt

Patterns of genic intolerance of rare copy number variation in 59,898 human exomes.

Copy number variation (CNV) affecting protein-coding genes contributes substantially to human diversity and disease. Here we characterized the rates and properties of rare genic CNVs (<0.5% frequency) in exome sequencing data from nearly 60,000 individuals in the Exome Aggregation Consortium (ExAC) database. On average, individuals possessed 0.81 deleted and 1.75 duplicated genes, and most (70%) carried at least one rare genic CNV. For every gene, we empirically estimated an index of relative intolerance to CNVs that demonstrated moderate correlation with measures of genic constraint based on single-nucleotide variation (SNV) and was independently correlated with measures of evolutionary conservation. For individuals with schizophrenia, genes affected by CNVs were more intolerant than in controls. The ExAC CNV data constitute a critical component of an integrated database spanning the spectrum of human genetic variation, aiding in the interpretation of personal genomes as well as population-based disease studies. These data are freely available for download and visualization online

Current understanding of the human microbiome

Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature Medicine 24 (2018): 392–400, doi:10.1038/nm.4517.Our understanding of the link between the human microbiome and disease, including obesity, inflammatory bowel disease, arthritis and autism, is rapidly expanding. Improvements in the throughput and accuracy of DNA sequencing of the genomes of microbial communities associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes, and mechanistic experiments in model systems, have vastly improved our ability to understand the structure and function of the microbiome in both diseased and healthy states. However, many challenges remain. In this Review, we focus on studies in humans to describe these challenges, and propose strategies that leverage existing knowledge to move rapidly from correlation to causation, and ultimately to translation.Many of the studies described here in our laboratories were supported by the NIH, NSF, DOE, and the Alfred P. Sloan Foundation.2018-10-1

MKLN1 splicing defect in dogs with lethal acrodermatitis

Lethal acrodermatitis (LAD) is a genodermatosis with monogenic autosomal recessive inheritance in Bull Terriers and Miniature Bull Terriers. The LAD phenotype is characterized by poor growth, immune deficiency, and skin lesions, especially at the paws. Utilizing a combination of genome wide association study and haplotype analysis, we mapped the LAD locus to a critical interval of similar to 1.11 Mb on chromosome 14. Whole genome sequencing of an LAD affected dog revealed a splice region variant in the MKLN1 gene that was not present in 191 control genomes (chr14:5,731,405T>G or MKLN/:c.400+3A>C). This variant showed perfect association in a larger combined Bull Terrier/Miniature Bull Terrier cohort of 46 cases and 294 controls. The variant was absent from 462 genetically diverse control dogs of 62 other dog breeds. RT-PCR analysis of skin RNA from an affected and a control dog demonstrated skipping of exon 4 in the MKLN1 transcripts of the LAD affected dog, which leads to a shift in the MKLN1 reading frame. MKLN1 encodes the widely expressed intracellular protein muskelin 1, for which diverse functions in cell adhesion, morphology, spreading, and intracellular transport processes are discussed. While the pathogenesis of LAD remains unclear, our data facilitate genetic testing of Bull Terriers and Miniature Bull Terriers to prevent the unintentional production of LAD affected dogs. This study may provide a starting point to further clarify the elusive physiological role of muskelin 1 in vivo.Peer reviewe

Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes.

Multi-nucleotide variants (MNVs), defined as two or more nearby variants existing on the same haplotype in an individual, are a clinically and biologically important class of genetic variation. However, existing tools typically do not accurately classify MNVs, and understanding of their mutational origins remains limited. Here, we systematically survey MNVs in 125,748 whole exomes and 15,708 whole genomes from the Genome Aggregation Database (gnomAD). We identify 1,792,248 MNVs across the genome with constituent variants falling within 2 bp distance of one another, including 18,756 variants with a novel combined effect on protein sequence. Finally, we estimate the relative impact of known mutational mechanisms - CpG deamination, replication error by polymerase zeta, and polymerase slippage at repeat junctions - on the generation of MNVs. Our results demonstrate the value of haplotype-aware variant annotation, and refine our understanding of genome-wide mutational mechanisms of MNVs

Potential Relevance of α1-Adrenergic Receptor Autoantibodies in Refractory Hypertension

-AAB might have a mechanistic role and could represent a therapeutic target. in cardiomyocytes and induce mesentery artery segment contraction.-AAB in hypertensive patients, and the notion of immunity as a possible cause of hypertension

Variant curation expert panel recommendations for RYR1 pathogenicity classifications in malignant hyperthermia susceptibility

Purpose: As a ClinGen Expert Panel (EP) we set out to adapt the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) pathogenicity criteria for classification of RYR1 variants as related to autosomal dominantly inherited malignant hyperthermia (MH). Methods: We specified ACMG/AMP criteria for variant classification for RYR1 and MH. Proposed rules were piloted on 84 variants. We applied quantitative evidence calibration for several criteria using likelihood ratios based on the Bayesian framework. Results: Seven ACMG/AMP criteria were adopted without changes, nine were adopted with RYR1-specific modifications, and ten were dropped. The in silico (PP3 and BP4) and hotspot criteria (PM1) were evaluated quantitatively. REVEL gave an odds ratio (OR) of 23:1 for PP3 and 14:1 for BP4 using trichotomized cutoffs of ≥0.85 (pathogenic) and ≤0.5 (benign). The PM1 hotspot criterion had an OR of 24:1. PP3 and PM1 were implemented at moderate strength. Applying the revised ACMG/AMP criteria to 44 recognized MH variants, 29 were classified as pathogenic, 13 as likely pathogenic, and 2 as variants of uncertain significance. Conclusion: Curation of these variants will facilitate classification of RYR1/MH genomic testing results, which is especially important for secondary findings analyses. Our approach to quantitatively calibrating criteria is generalizable to other variant curation expert panels

Contribution of Transcription Factor Binding Site Motif Variants to Condition-Specific Gene Expression Patterns in Budding Yeast

It is now experimentally well known that variant sequences of a cis transcription factor binding site motif can contribute to differential regulation of genes. We characterize the relationship between motif variants and gene expression by analyzing expression microarray data and binding site predictions. To accomplish this, we statistically detect motif variants with effects that differ among environments. Such environmental specificity may be due to either affinity differences between variants or, more likely, differential interactions of TFs bound to these variants with cofactors, and with differential presence of cofactors across environments. We examine conservation of functional variants across four Saccharomyces species, and find that about a third of transcription factors have target genes that are differentially expressed in a condition-specific manner that is correlated with the nucleotide at variant motif positions. We find good correspondence between our results and some cases in the experimental literature (Reb1, Sum1, Mcm1, and Rap1). These results and growing consensus in the literature indicates that motif variants may often be functionally distinct, that this may be observed in genomic data, and that variants play an important role in condition-specific gene regulation