Browsing by Author "Cui, Chenming"
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- Integrating bioinformatic approaches to promote crop resilienceCui, Chenming (Virginia Tech, 2019-10-09)Even under the best management strategies contemporary crops face yield losses from diverse threats such as, pathogens, pests, and environmental stress. Adding to this management challenge is that under current global climate projections these impacts are predicted to become even greater. Natural genetic variation, long used by traditional plant breeders, holds great promise for adapting high performing agronomic lines to these stressors. Yet, efforts to bolster crop plant resilience using wild relatives have been hindered by time consuming efforts to develop genomic tools and/or identify the genetic basis for agronomic traits. Thus, increasing crop plant resilience requires developing and deploying approaches that leverage current high-throughput sequencing technologies to more rapidly and robustly develop genomic tools in these systems. Here we report the integration of bioinformatic and statistical tools to leverage high-throughput sequencing to 1) develop a machine learning approach to determine factors impacting transcriptome assembly and quantitatively evaluate transcriptome completeness, 2) dissect complex physiological pathway interactions in Solanum pimpinellifolium under combined stresses—using comparative transcriptomics, and 3) develop a genome assembly pipeline that can be deployed to rapidly assemble a more contiguous genome, unraveling previously hidden complexity, using Phytopthora capsici as a model. As a result, we have generated strategic guidelines for transcriptome assembly and developed an orthologue and reference free, machine learning based tool "WWMT" to quantitatively score transcriptome completeness from short read data. Secondly, we identified "hub genes" and describe genes involved with "cross-talk" between drought and herbivore stress response pathways. Finally, we demonstrate a protocol for combining long-read sequencing from the Oxford Nanopore Technologies MinION, and short-read data, to rapidly assembly a cost-effective, contiguous and relatively complete genome. Here we uncovered hidden variation in a well-known plant pathogen finding that the genome was 92% bigger than previous estimates with more than 39% of duplicated regions, supporting a hypothesized recent whole genome duplication in this clade. This community resource will support new functional and evolutionary studies in this economically important pathogen.
- siRNAs regulate DNA methylation and interfere with gene and lncRNA expression in the heterozygous polyploid switchgrassYan, Haidong; Bombarely, Aureliano; Xu, Bin; Frazier, Taylor P.; Wang, Chengran; Chen, Peilin; Chen, Jing; Hasing, Tomas; Cui, Chenming; Zhang, Xinquan; Zhao, Bingyu Y.; Huang, Linkai (2018-07-24)Background Understanding the DNA methylome and its relationship with non-coding RNAs, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), is essential for elucidating the molecular mechanisms underlying key biological processes in plants. Few studies have examined the functional roles of the DNA methylome in grass species with highly heterozygous polyploid genomes. Results We performed genome-wide DNA methylation profiling in the tetraploid switchgrass (Panicum virgatum L.) cultivar ‘Alamo’ using bisulfite sequencing. Single-base-resolution methylation patterns were observed in switchgrass leaf and root tissues, which allowed for characterization of the relationship between DNA methylation and mRNA, miRNA, and lncRNA populations. The results of this study revealed that siRNAs positively regulate DNA methylation of the mCHH sites surrounding genes, and that DNA methylation interferes with gene and lncRNA expression in switchgrass. Ninety-six genes covered by differentially methylated regions (DMRs) were annotated by GO analysis as being involved in stimulus-related processes. Functionally, 82% (79/96) of these genes were found to be hypomethylated in switchgrass root tissue. Sequencing analysis of lncRNAs identified two lncRNAs that are potential precursors of miRNAs, which are predicted to target genes that function in cellulose biosynthesis, stress regulation, and stem and root development. Conclusions This study characterized the DNA methylome in switchgrass and elucidated its relevance to gene and non-coding RNAs. These results provide valuable genomic resources and references that will aid further epigenetic research in this important biofuel crop.