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Drought response is coordinated through expression changes in a large suite of genes. Interspecific variation in this response is common and associated with drought-tolerant and -sensitive genotypes. The extent to which different genetic networks orchestrate the adjustments to water deficit in tolerant and sensitive genotypes has not been fully elucidated, particularly in non-model or woody plants. Differential expression analysis via RNA-seq was evaluated in root tissue exposed to simulated drought conditions in two loblolly pine ( Pinus taeda L.) clones with contrasting tolerance to drought. Loblolly pine is the prevalent conifer in southeastern U.S. and a major commercial forestry species worldwide. Significant changes in gene expression levels were found in more than 4,000 transcripts [drought-related transcripts (DRTs)]. Genotype by environment (GxE) interactions were prevalent, suggesting that different cohorts of genes are influenced by drought conditions in the tolerant vs. sensitive genotypes. Functional annotation categories and metabolic pathways associated with DRTs showed higher levels of overlap between clones, with the notable exception of GO categories in upregulated DRTs. Conversely, both differentially expressed transcription factors (TFs) and TF families were largely different between clones. Our results indicate that the response of a drought-tolerant loblolly pine genotype vs. a sensitive genotype to water limitation is remarkably different on a gene-by-gene level, although it involves similar genetic networks. Upregulated transcripts under drought conditions represent the most diverging component between genotypes, which might depend on the activation and repression of substantially different groups of TFs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Li, West, Hart, Wegrzyn, Smith, Domec, Loopstra and Casola.)

Copy number variants are duplications and deletions of the genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested Simulator of Exome Copy Number Variants (SECNVs), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs., (Copyright © 2020 Xing, Dabney, Li, Wang, Gill and Casola.)