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Shea, D. J.

Publications and source records attributed to Shea, D. J..

2 recordsLinked to original sources

Genome-wide analysis of long noncoding RNAs, 24-nt siRNAs, DNA methylation and H3K27me3 marks in Brassica rapa and related species

Long noncoding RNAs (lncRNAs) are RNA fragments that generally do not code for a protein but are involved in epigenetic gene regulation. In this study, lncRNAs of Brassica rapa were classified into long intergenic noncoding RNAs, natural antisense RNAs, and intronic noncoding RNAs and their expression were analyzed in relation to genome-wide 24-nt small interfering RNAs (siRNAs), DNA methylation, and histone H3 lysine 27 trimethylation marks (H3K27me3). More than 65% of the lncRNAs analyzed consisted of one exon, and more than 55% overlapped with inverted repeat regions (IRRs). Overlap of lncRNAs with IRRs or genomic regions encoding for 24-nt siRNAs resulted in increased DNA methylation levels and when both were present, there were further increase in DNA methylation levels. LncRNA did not overlap greatly with H3K27me3 marks, but the expression level of intronic noncoding RNAs that did coincide with H3K27me3 marks was higher than without H3K27me3 marks. The Brassica genus comprises important vegetables and oil seed crops grown across the world. Brassica rapa is a diploid (AA genome) thought to be one of the ancestral species of both B. juncea (AABB genome) and B. napus (AACC) through genome merging (allotetrapolyploidization). Complex genome restructuring and epigenetic alterations are thought to be involved in these allotetrapolyploidization events, but the detailed mechanism is not known. Comparison of lncRNAs between B. rapa and B. nigra, B. oleracea, B. juncea, and B. napus showed the highest conservation with B. oleracea. This study presents a comprehensive analysis of the epigenome structure of the B. rapa at multi-epigenetic levels (siRNAs, DNA methylation, H3K27me3, and lncRNAs) and offers insights into the function of lncRNA in the Brassica genus.

plant biology

High-performance pipeline for MutMap and QTL-seq

Bulked segregant analysis implemented in MutMap and QTL-seq is a powerful and efficient method to identify agronomically important loci. However, the previous pipelines were not user-friendly to install and run. Here, we describe new pipelines for MutMap and QTL-seq. These updated pipelines are approximately 5-8 times faster than the previous pipeline, are easier for novice users to use and can be easily installed through bioconda with all dependencies.

bioinformatics