Systematic evaluation of factors influencing ChIP-seq fidelity.

We evaluated how variations in sequencing depth and other parameters influence interpretation of chromatin immunoprecipitation-sequencing (ChIP-seq) experiments. Using Drosophila melanogaster S2 cells, we generated ChIP-seq data sets for a site-specific transcription factor (Suppressor of Hairy-wing) and a histone modification (H3K36me3). We detected a chromatin-state bias: open chromatin regions yielded higher coverage, which led to false positives if not corrected. This bias had a greater effect on detection specificity than any base-composition bias. Paired-end sequencing revealed that single-end data underestimated ChIP-library complexity at high coverage. Removal of reads originating at the same base reduced false-positives but had little effect on detection sensitivity. Even at mappable-genome coverage depth of ∼1 read per base pair, ∼1% of the narrow peaks detected on a tiling array were missed by ChIP-seq. Evaluation of widely used ChIP-seq analysis tools suggests that adjustments or algorithm improvements are required to handle data sets with deep coverage.

Systematic identification of balanced transposition polymorphisms in Saccharomyces cerevisiae.

High-throughput techniques for detecting DNA polymorphisms generally do not identify changes in which the genomic position of a sequence, but not its copy number, varies among individuals. To explore such balanced structural polymorphisms, we used array-based Comparative Genomic Hybridization (aCGH) to conduct a genome-wide screen for single-copy genomic segments that occupy different genomic positions in the standard laboratory strain of Saccharomyces cerevisiae (S90) and a polymorphic wild isolate (Y101) through analysis of six tetrads from a cross of these two strains. Paired-end high-throughput sequencing of Y101 validated four of the predicted rearrangements. The transposed segments contained one to four annotated genes each, yet crosses between S90 and Y101 yielded mostly viable tetrads. The longest segment comprised 13.5 kb near the telomere of chromosome XV in the S288C reference strain and Southern blotting confirmed its predicted location on chromosome IX in Y101. Interestingly, inter-locus crossover events between copies of this segment occurred at a detectable rate. The presence of low-copy repetitive sequences at the junctions of this segment suggests that it may have arisen through ectopic recombination. Our methodology and findings provide a starting point for exploring the origins, phenotypic consequences, and evolutionary fate of this largely unexplored form of genomic polymorphism.

COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences.

BACKGROUND: As the world faced the pandemic caused by the novel coronavirus disease 2019 (COVID-19), medical professionals, technologists, community leaders, and policy makers sought to understand how best to leverage data for public health surveillance and community education. With this complex public health problem, North Carolinians relied on data from state, federal, and global health organizations to increase their understanding of the pandemic and guide decision-making. OBJECTIVE: We aimed to describe the role that stakeholders involved in COVID-19-related data played in managing the pandemic in North Carolina. The study investigated the processes used by organizations throughout the state in using, collecting, and reporting COVID-19 data. METHODS: We used an exploratory qualitative study design to investigate North Carolina's COVID-19 data collection efforts. To better understand these processes, key informant interviews were conducted with employees from organizations that collected COVID-19 data across the state. We developed an interview guide, and open-ended semistructured interviews were conducted during the period from June through November 2020. Interviews lasted between 30 and 45 minutes and were conducted by data scientists by videoconference. Data were subsequently analyzed using qualitative data analysis software. RESULTS: Results indicated that electronic health records were primary sources of COVID-19 data. Often, data were also used to create dashboards to inform the public or other health professionals, to aid in decision-making, or for reporting purposes. Cross-sector collaboration was cited as a major success. Consistency among metrics and data definitions, data collection processes, and contact tracing were cited as challenges. CONCLUSIONS: Findings suggest that, during future outbreaks, organizations across regions could benefit from data centralization and data governance. Data should be publicly accessible and in a user-friendly format. Additionally, established cross-sector collaboration networks are demonstrably beneficial for public health professionals across the state as these established relationships facilitate a rapid response to evolving public health challenges.

Genetic regulation of telomere-telomere fusions in the yeast Saccharomyces cerevisae.

Yeast strains with mutations in both TEL1 and MEC1 have short telomeres and elevated rates of chromosome deletions. By using a PCR assay, we demonstrate that mec1 tel1 strains also have telomere-telomere fusions (T-TFs). T-TFs require Lig4p (a ligase required for nonhomologous end-joining DNA repair). The highest rates of T-TFs are found in strains with combination of mutations that affect telomere length and DNA damage checkpoints (mec1 tel1, mec3 tel1, mre11 mec1, and ddc1 tel1 strains). Examining many mutant genotypes, we find good agreement between the level of T-TFs and the rate of chromosomal deletions. In addition, if telomeres are elongated in a mec1 tel1 strain, we eliminate T-TFs and reduce the deletion rate. The correlation between the level of T-TFs and the rate of deletions argues that many of these deletions reflect a cycle of T-TF formation (resulting in dicentric chromosomes), followed by chromosome breakage.