Genome-wide Identification of Structure-Forming Repeats as Principal Sites of Fork Collapse upon ATR Inhibition.

DNA polymerase stalling activates the ATR checkpoint kinase, which in turn suppresses fork collapse and breakage. Herein, we describe use of ATR inhibition (ATRi) as a means to identify genomic sites of problematic DNA replication in murine and human cells. Over 500 high-resolution ATR-dependent sites were ascertained using two distinct methods: replication protein A (RPA)-chromatin immunoprecipitation (ChIP) and breaks identified by TdT labeling (BrITL). The genomic feature most strongly associated with ATR dependence was repetitive DNA that exhibited high structure-forming potential. Repeats most reliant on ATR for stability included structure-forming microsatellites, inverted retroelement repeats, and quasi-palindromic AT-rich repeats. Notably, these distinct categories of repeats differed in the structures they formed and their ability to stimulate RPA accumulation and breakage, implying that the causes and character of replication fork collapse under ATR inhibition can vary in a DNA-structure-specific manner. Collectively, these studies identify key sources of endogenous replication stress that rely on ATR for stability.

AM Versus PM Postoperative Administration of Warfarin With a Mechanical Mitral Valve.

Background: Currently, there are no guidelines regarding the optimal daily timing of inpatient warfarin administration. Objective: The purpose of this study was to determine whether dosing warfarin in the morning will have a significant impact on therapeutic international normalized ratio (INR) achievement compared with evening administration in mechanical mitral valve patients initiated on warfarin following cardiac surgery. Methods: This was a single-center, pre- and post-retrospective cohort conducted between 2014 and 2018. One-hundred fifty-four adult patients who underwent a mechanical mitral valve replacement or alternative cardiac surgery with a history of a mechanical mitral valve were enrolled. The primary outcome was achievement of therapeutic INR at any time point after initiation of warfarin. Pre-intervention administration timing was 6 pm and post-intervention timing was 10 am. Results: Baseline characteristics including age, sex, and race were similar between the 2 groups (P = NS for each characteristic). Therapeutic INR achievement was significantly improved at all time points following 10 am warfarin administration compared with 6 pm (hazard ratio = 1.69; P = .005). Mean time-to-therapeutic INR was 7.37 days in the post-intervention group and 8.39 days in the pre-intervention group (P = .073). There were no significant differences in INR >4, bleeding, or thrombotic complications between groups. Conclusion and Relevance: This retrospective analysis suggests that there may be a postoperative benefit in therapeutic INR achievement in mechanical valve patients when dosing warfarin in the morning compared with evening administration. Large-scale studies should be conducted to further elucidate the potential benefit across more heterogeneous populations.

Comparing variant calling algorithms for target-exon sequencing in a large sample.

BACKGROUND: Sequencing studies of exonic regions aim to identify rare variants contributing to complex traits. With high coverage and large sample size, these studies tend to apply simple variant calling algorithms. However, coverage is often heterogeneous; sites with insufficient coverage may benefit from sophisticated calling algorithms used in low-coverage sequencing studies. We evaluate the potential benefits of different calling strategies by performing a comparative analysis of variant calling methods on exonic data from 202 genes sequenced at 24x in 7,842 individuals. We call variants using individual-based, population-based and linkage disequilibrium (LD)-aware methods with stringent quality control. We measure genotype accuracy by the concordance with on-target GWAS genotypes and between 80 pairs of sequencing replicates. We validate selected singleton variants using capillary sequencing. RESULTS: Using these calling methods, we detected over 27,500 variants at the targeted exons; >57% were singletons. The singletons identified by individual-based analyses were of the highest quality. However, individual-based analyses generated more missing genotypes (4.72%) than population-based (0.47%) and LD-aware (0.17%) analyses. Moreover, individual-based genotypes were the least concordant with array-based genotypes and replicates. Population-based genotypes were less concordant than genotypes from LD-aware analyses with extended haplotypes. We reanalyzed the same dataset with a second set of callers and showed again that the individual-based caller identified more high-quality singletons than the population-based caller. We also replicated this result in a second dataset of 57 genes sequenced at 127.5x in 3,124 individuals. CONCLUSIONS: We recommend population-based analyses for high quality variant calls with few missing genotypes. With extended haplotypes, LD-aware methods generate the most accurate and complete genotypes. In addition, individual-based analyses should complement the above methods to obtain the most singleton variants.

Initial investigation of molecular phenotypes of airway mast cells and cytokine profiles in equine asthma.

Equine asthma is a naturally occurring lung disease characterized by chronic, partially reversible airway obstruction, pulmonary remodeling, and lower airway inflammation. Asthma is currently divided into two major groups, mild to moderate asthma (mEA) and severe asthma (sEA), but further subtyping by phenotype (i.e., clinical presentation) and/or endotype (i.e., cellular mechanisms) may be warranted. For this study, we were interested in further investigation of cellular and inflammatory characteristics of EA, including airway mast cells. The purpose of this study was to: (1) compare mast cell protease mRNA expression between healthy and asthmatic horses, (2) analyze the cytokine profile present in BALF of currently defined equine asthma groups, and (3) use these data to evaluate potential biomarkers of defined asthma groups. We hypothesized that there would be significant differences in the cellular mast cell phenotypes (i.e., mucosal vs. connective tissue) and cytokine profiles in the BALF of asthmatic vs. healthy horses and across asthma groups. We assert these characteristics may inform additional subtypes of equine asthma. Adult horses were recruited from the institution's teaching herd and clinical caseload. Mast cell protease gene expression of the BALF cellular component and multiplex bead immunoassay for cytokine concentrations in the BALF supernatant were investigated. Airway mast cells primarily expressed tryptase, with low levels of chymase. No significant changes in protease expression were detected across groups. Horses with severe asthma had increased TNF-α, CXCL-8, and IFN-γ concentrations in BALF supernatant. Multidimensional analysis demonstrated healthy and mEA horses have overlapping characteristics, with sEA separating from the other groups. This difference was primarily due to BALF neutrophil and lymphocyte concentrations. These study results further inform understanding of EA immunopathology, and future studies designed to investigate asthma phenotypes and endotypes. Ultimately, a better understanding of these groups could help identify novel therapeutic strategies.

Using Machine Learning on Home Health Care Assessments to Predict Fall Risk.

Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home health care (HHC) population. Existing standardized fall risk assessments often require supplemental data collection and tend to have low specificity. We applied a random forest algorithm on readily available HHC data from the mandated Outcomes and Assessment Information Set (OASIS) with over 100 items from 59,006 HHC patients to identify factors that predict and quantify fall risks. Our ultimate goal is to build clinical decision support for fall prevention. Our model achieves higher precision and balanced accuracy than the commonly used multifactorial Missouri Alliance for Home Care fall risk assessment. This is the first known attempt to determine fall risk factors from the extensive OASIS data from a large sample. Our quantitative prediction of fall risks can aid clinical discussions of risk factors and prevention strategies for lowering fall incidence.

Loci associated with skin pigmentation identified in African populations.

Despite the wide range of skin pigmentation in humans, little is known about its genetic basis in global populations. Examining ethnically diverse African genomes, we identify variants in or near SLC24A5, MFSD12, DDB1, TMEM138, OCA2, and HERC2 that are significantly associated with skin pigmentation. Genetic evidence indicates that the light pigmentation variant at SLC24A5 was introduced into East Africa by gene flow from non-Africans. At all other loci, variants associated with dark pigmentation in Africans are identical by descent in South Asian and Australo-Melanesian populations. Functional analyses indicate that MFSD12 encodes a lysosomal protein that affects melanogenesis in zebrafish and mice, and that mutations in melanocyte-specific regulatory regions near DDB1/TMEM138 correlate with expression of ultraviolet response genes under selection in Eurasians.

Going global by adapting local: A review of recent human adaptation.

The spread of modern humans across the globe has led to genetic adaptations to diverse local environments. Recent developments in genomic technologies, statistical analyses, and expanded sampled populations have led to improved identification and fine-mapping of genetic variants associated with adaptations to regional living conditions and dietary practices. Ongoing efforts in sequencing genomes of indigenous populations, accompanied by the growing availability of "-omics" and ancient DNA data, promises a new era in our understanding of recent human evolution and the origins of variable traits and disease risks.

Whole-genome sequencing of uropathogenic Escherichia coli reveals long evolutionary history of diversity and virulence.

Uropathogenic Escherichia coli (UPEC) are phenotypically and genotypically very diverse. This diversity makes it challenging to understand the evolution of UPEC adaptations responsible for causing urinary tract infections (UTI). To gain insight into the relationship between evolutionary divergence and adaptive paths to uropathogenicity, we sequenced at deep coverage (190×) the genomes of 19 E. coli strains from urinary tract infection patients from the same geographic area. Our sample consisted of 14 UPEC isolates and 5 non-UTI-causing (commensal) rectal E. coli isolates. After identifying strain variants using de novo assembly-based methods, we clustered the strains based on pairwise sequence differences using a neighbor-joining algorithm. We examined evolutionary signals on the whole-genome phylogeny and contrasted these signals with those found on gene trees constructed based on specific uropathogenic virulence factors. The whole-genome phylogeny showed that the divergence between UPEC and commensal E. coli strains without known UPEC virulence factors happened over 32 million generations ago. Pairwise diversity between any two strains was also high, suggesting multiple genetic origins of uropathogenic strains in a small geographic region. Contrasting the whole-genome phylogeny with three gene trees constructed from common uropathogenic virulence factors, we detected no selective advantage of these virulence genes over other genomic regions. These results suggest that UPEC acquired uropathogenicity long time ago and used it opportunistically to cause extraintestinal infections.