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High-throughput sequencing data enables the comprehensive study of genomes and the variation therein. Essential for the interpretation of this genomic data is a thorough understanding of the computational methods used for processing and analysis. Whereas “gold-standard” empirical datasets exist for this purpose in humans, synthetic (i.e., simulated) sequencing data can offer important insights into the capabilities and limitations of computational pipelines for any arbitrary species and/or study design—yet, the ability of read simulator software to emulate genomic characteristics of empirical datasets remains poorly understood. We here compare the performance of six popular short-read simulators—ART, DWGSIM, InSilicoSeq, Mason, NEAT, and wgsim—and discuss important considerations for selecting suitable models for benchmarking.

 

ABSTRACT We characterized the complete genome sequence of Chako, an obligate lytic bacteriophage with siphovirus morphology from subcluster EA1 that infects Microbacterium foliorum NRRL B-24224. Its 41.6-kb genome contains 62 putative protein-coding genes and is highly similar to that of bacteriophage HanSolo (99.26% nucleotide identity). 

Bacteriophages are being widely harnessed as an alternative to antibiotics due to the global emergence of drug-resistant pathogens. To guide the usage of these bactericidal agents, characterization of their host specificity is vital—however, host range information remains limited for many bacteriophages. This is particularly the case for bacteriophages infecting the Microbacterium genus, despite their importance in agriculture, biomedicine, and biotechnology. Here, we elucidate the phylogenomic relationships between 125 Microbacterium cluster EA bacteriophages—including members from 11 sub-clusters (EA1 to EA11)—and infer their putative host ranges using insights from codon usage bias patterns as well as predictions from both exploratory and confirmatory computational methods. Our computational analyses suggest that cluster EA bacteriophages have a shared infection history across the Microbacterium clade. Interestingly, bacteriophages of all sub-clusters exhibit codon usage preference patterns that resemble those of bacterial strains different from ones used for isolation, suggesting that they might be able to infect additional hosts. Furthermore, host range predictions indicate that certain sub-clusters may be better suited in prospective biotechnological and medical applications such as phage therapy. 

Co-option of transposable elements (TEs) to become part of existing or new enhancers is an important mechanism for evolution of gene regulation. However, contributions of lineage-specific TE insertions to recent regulatory adaptations remain poorly understood. Gibbons present a suitable model to study these contributions as they have evolved a lineage-specific TE calledLAVA(LINE-AluSz-VNTR-Alu_LIKE), which is still active in the gibbon genome. The LAVA retrotransposon is thought to have played a role in the emergence of the highly rearranged structure of the gibbon genome by disrupting transcription of cell cycle genes. In this study, we investigated whether LAVA may have also contributed to the evolution of gene regulation by adopting enhancer function. We characterized fixed and polymorphic LAVA insertions across multiple gibbons and found 96 LAVA elements overlapping enhancer chromatin states. Moreover, LAVA was enriched in multiple transcription factor binding motifs, was bound by an important transcription factor (PU.1), and was associated with higher levels of gene expression incis. We found gibbon-specific signatures of purifying/positive selection at 27 LAVA insertions. Two of these insertions were fixed in the gibbon lineage and overlapped with enhancer chromatin states, representing putative co-opted LAVA enhancers. These putative enhancers were located within genes encoding SETD2 and RAD9A, two proteins that facilitate accurate repair of DNA double-strand breaks and prevent chromosomal rearrangement mutations. Co-option of LAVA in these genes may have influenced regulation of processes that preserve genome integrity. Our findings highlight the importance of considering lineage-specific TEs in studying evolution of gene regulatory elements.