Genome-wide mapping of transcriptional enhancer candidates using DNA and chromatin features in maize


Rurika Oka, Johan Zicola, Blaise Weber, Sarah N. Anderson, Charlie Hodgman, Jonathan I. Gent, Jan-Jaap Wesselink, Nathan M. Springer, Huub C. J. Hoefsloot, Franziska Turck and Maike Stam




Background: While most cells in multicellular organisms carry the same genetic information, in each cell type only a subset of genes is being transcribed. Such differentiation in gene expression depends, for a large part, on the activation and repression of regulatory sequences, including transcriptional enhancers. Transcriptional enhancers can be located tens of kilobases from their target genes, but display characteristic chromatin and DNA features, allowing their identification by genome-wide profiling. Here we show that integration of chromatin characteristics can be applied to predict distal enhancer candidates in Zea mays, thereby providing a basis for a better understanding of gene regulation in this important crop plant.

Result: To predict transcriptional enhancers in the crop plant maize (Zea mays L. ssp. mays), we integrated available genome-wide DNA methylation data with newly generated maps for chromatin accessibility and histone 3 lysine 9 acetylation (H3K9ac) enrichment in young seedling and husk tissue. Approximately 1500 intergenic regions, displaying low DNA methylation, high chromatin accessibility and H3K9ac enrichment, were classified as enhancer candidates. Based on their chromatin profiles, candidate sequences can be classified into four subcategories. Tissue-specificity of enhancer candidates is defined based on the tissues in which they are identified and putative target genes are assigned based on tissue-specific expression patterns of flanking genes.

Conclusions: Our method identifies three previously identified distal enhancers in maize, validating the new set of enhancer candidates and enlarging the toolbox for the functional characterization of gene regulation in the highly repetitive maize genome.


Characterization of background noise in capture-based targeted sequencing data


Gahee Park, Joo Kyung Park, Seung-Ho Shin, Hyo-Jeong Jeon, Nayoung K. D. Kim, Yeon Jeong Kim, Hyun-Tae Shin, Eunjin Lee, Kwang Hyuck Lee, Dae-Soon Son, Woong-Yang Park and Donghyun Park




Background: Targeted deep sequencing is increasingly used to detect low-allelic fraction variants; it is therefore essential that errors that constitute baseline noise and impose a practical limit on detection are characterized. In the present study, we systematically evaluate the extent to which errors are incurred during specific steps of the capture-based targeted sequencing process.

Results: We removed most sequencing artifacts by filtering out low-quality bases and then analyze the remaining background noise. By recognizing that plasma DNA is naturally fragmented to be of a size comparable to that of mono-nucleosomal DNA, we were able to identify and characterize errors that are specifically associated with acoustic shearing. Two-thirds of C:G > A:T errors and one quarter of C:G > G:C errors were attributed to the oxidation of guanine during acoustic shearing, and this was further validated by comparative experiments conducted under different shearing conditions. The acoustic shearing step also causes A > G and A > T substitutions localized to the end bases of sheared DNA fragments, indicating a probable association of these errors with DNA breakage. Finally, the hybrid selection step contributes to one-third of the remaining C:G > A:T and one-fifth of the C > T errors.

Conclusions: The results of this study provide a comprehensive summary of various errors incurred during targeted deep sequencing, and their underlying causes. This information will be invaluable to drive technical improvements in this sequencing method, and may increase the future usage of targeted deep sequencing methods for low-allelic fraction variant detection.


Methicillin-resistant Staphylococcus aureus emerged long before the introduction of methicillin into clinical practice


Catriona P. Harkins, Bruno Pichon, Michel Doumith, Julian Parkhill, Henrik Westh, Alexander Tomasz, Herminia de Lencastre, Stephen D. Bentley, Angela M. Kearns and Matthew T. G. Holden




Background: The spread of drug-resistant bacterial pathogens poses a major threat to global health. It is widely recognised that the widespread use of antibiotics has generated selective pressures that have driven the emergence of resistant strains. Methicillin-resistant Staphylococcus aureus (MRSA) was first observed in 1960, less than one year after the introduction of this second generation beta-lactam antibiotic into clinical practice. Epidemiological evidence has always suggested that resistance arose around this period, when the mecA gene encoding methicillin resistance carried on an SCCmec element, was horizontally transferred to an intrinsically sensitive strain of S. aureus.

Results: Whole genome sequencing a collection of the first MRSA isolates allows us to reconstruct the evolutionary history of the archetypal MRSA. We apply Bayesian phylogenetic reconstruction to infer the time point at which this early MRSA lineage arose and when SCCmec was acquired. MRSA emerged in the mid-1940s, following the acquisition of an ancestral type I SCCmec element, some 14 years before the first therapeutic use of methicillin.

Conclusions: Methicillin use was not the original driving factor in the evolution of MRSA as previously thought. Rather it was the widespread use of first generation beta-lactams such as penicillin in the years prior to the introduction of methicillin, which selected for S. aureus strains carrying the mecA determinant. Crucially this highlights how new drugs, introduced to circumvent known resistance mechanisms, can be rendered ineffective by unrecognised adaptations in the bacterial population due to the historic selective landscape created by the widespread use of other antibiotics.