A complete Cannabis chromosome assembly and adaptive admixture for elevated cannabidiol (CBD) content, bioRxiv, 2018-10-31

AbstractCannabis has been cultivated for millennia with distinct cultivars providing either fiber and grain or tetrahydrocannabinol. Recent demand for cannabidiol rather than tetrahydrocannabinol has favored the breeding of admixed cultivars with extremely high cannabidiol content. Despite several draft Cannabis genomes, the genomic structure of cannabinoid synthase loci has remained elusive. A genetic map derived from a tetrahydrocannabinolcannabidiol segregating population and a complete chromosome assembly from a high-cannabidiol cultivar together resolve the linkage of cannabidiolic and tetrahydrocannabinolic acid synthase gene clusters which are associated with transposable elements. High-cannabidiol cultivars appear to have been generated by integrating hemp-type cannabidiolic acid synthase gene clusters into a background of marijuana-type cannabis. Quantitative trait locus mapping suggests that overall drug potency, however, is associated with other genomic regions needing additional study.Resources available online at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpcannabisgenome.org>httpcannabisgenome.org<jatsext-link>SummaryA complete chromosome assembly and an ultra-high-density linkage map together identify the genetic mechanism responsible for the ratio of tetrahydrocannabinol (THC) to cannabidiol (CBD) in Cannabis cultivars, allowing paradigms for the evolution and inheritance of drug potency to be evaluated.

biorxiv genomics 100-200-users 2018

Personalized and graph genomes reveal missing signal in epigenomic data, bioRxiv, 2018-10-31

AbstractBackgroundEpigenomic studies that use next generation sequencing experiments typically rely on the alignment of reads to a reference sequence. However, because of genetic diversity and the diploid nature of the human genome, we hypothesized that using a generic reference could lead to incorrectly mapped reads and bias downstream results.ResultsWe show that accounting for genetic variation using a modified reference genome (MPG) or a denovo assembled genome (DPG) can alter histone H3K4me1 and H3K27ac ChIP-seq peak calls by either creating new personal peaks or by the loss of reference peaks. MPGs are found to alter approximately 1% of peak calls while DPGs alter up to 5% of peaks. We also show statistically significant differences in the amount of reads observed in regions associated with the new, altered and unchanged peaks. We report that short insertions and deletions (indels), followed by single nucleotide variants (SNVs), have the highest probability of modifying peak calls. A counter-balancing factor is peak width, with wider calls being less likely to be altered. Next, because high-quality DPGs remain hard to obtain, we show that using a graph personalized genome (GPG), represents a reasonable compromise between MPGs and DPGs and alters about 2.5% of peak calls. Finally, we demonstrate that altered peaks have a genomic distribution typical of other peaks. For instance, for H3K4me1, 518 personal-only peaks were replicated using at least two of three approaches, 394 of which were inside or within 10Kb of a gene.ConclusionsAnalysing epigenomic datasets with personalized and graph genomes allows the recovery of new peaks enriched for indels and SNVs. These altered peaks are more likely to differ between individuals and, as such, could be relevant in the study of various human phenotypes.

biorxiv bioinformatics 100-200-users 2018

 

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