Project description:We carried out genomewide DNA methylation analysis by whole genome bisulfite sequencing to identify candidate genes involved in pear fruit semi-russet formation, by comparing the CK (russet) and bagging treated (green) ‘Cuiguan’ pear fruit skin 115 DAFB.
Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Primary endpoints: circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Project description:purpose:The purpose of this study was to compare the transcriptome data of the diseased and the non diseased pear to verify the changes of different physiological indexes of the diseased pear Methods:By sequencing the transcriptome of the treatment group and the control group, the differences of genes related to glycoalcohol metabolism and cell wall physiological pathway metabolism between the two groups were compared. Verification by fluorescence quantitative PCR
Project description:Comparative analyze at the transcriptomic level 1) of Venturia pyrina pear host resistance via the major apple resistance gene Rvi6, in Rvi6 overexpressing transgenic pear versus ‘conference’ susceptible variety; 2) of Venturia inaequalis pear nonhost resistance, in ‘Conference’ variety, 24 and 72 hours post inoculation.
Project description:Although the importance of host plant chemistry in plant-insect interactions is widely accepted, the genetic basis of adaptation to host plants is poorly understood. Here, we investigate transcriptional changes associated with a host plant shift in Drosophila mettleri. While D. mettleri is distributed mainly throughout the Sonoran Desert where it specializes on columnar cacti (Carnegiea gigantea and Pachycereus pringleii), a population on Santa Catalina Island has shifted to coastal prickly pear cactus (Opuntia littoralis). We compared gene expression of larvae from the Sonoran Desert and Santa Catalina Island when reared on saguaro (C. gigantea), coastal prickly pear, and laboratory food. Consistent with expectations based on the complexity and toxicity of cactus relative to laboratory food, within population comparisons between larvae reared on these food sources revealed transcriptional differences in detoxification and other metabolic pathways. The majority of transcriptional differences between populations on the cactus hosts were independent of the rearing environment, and included a disproportionate number of genes involved in processes relevant to host plant adaptation (e.g. detoxification, central metabolism, and chemosensory pathways). Comparisons of transcriptional reaction norms between the two populations revealed extensive shared plasticity that likely allowed colonization of coastal prickly pear on Santa Catalina Island. We also found that while plasticity may have facilitated subsequent adaptive divergence in gene expression between populations, the majority of genes that differed in expression on the novel host were not transcriptionally plastic in the presumed ancestral state. mRNA profiles of third instar larvae from two different populations reared on three food types was sequenced on two lanes of an Illumina HiSeq 2000 Please note that the de novo assembly gives names to transcripts with the following convention: compXXX_cX_seqX. The first two identifiers (compXX_cX) are equivalent to a gene while the 'seq' identifier might refer to different isoforms or splice variants, etc. Therefore, for example, a gene might be comp123_c0, and this could have multiple sequences corresponding to different isoforms or splice variants. Since the analysis was carried out at the gene level, the program internally merged the multiple sequences together for each gene to generate the count matrix (AllGenesint.counts.matrix.txt) (i.e. it only includes comp123_c0), while the file from the assembly (i.e. Trinity.fasta) also include the individual sequences with the 'seq' identifier.