Project description:The experiment was conducted to examine the influence of non-chloroplast genomes rearangements on chloroplast transcription in cucumber
Project description:We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 maize inbreds that serve as the founders for the maize nested association mapping population. The data indicate that the number of pan-genes in maize exceeds 103,000 and that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres further revealed the locations and internal structures of major cytological landmarks. We show that combining structural variation with SNPs can improve the power of quantitative mapping studies. Finally, we document variation at the level of DNA methylation, and demonstrate that unmethylated regions are enriched for cis-regulatory elements that correlate with known QTLs and changes in gene expression.
Project description:We describe an application of deep sequencing and de novo assembly of short RNA reads to investigate small interfering (si)RNAs mediated immunity in leaf samples from eight tree taxa naturally occurring in Wytham Woods, Oxfordshire, UK. BLAST search for homologues of contigs in the GenBank identified siRNA populations against a number of RNA viruses and a Ty1-copia retrotransposons in these tree species. Small RNA sequencing and de novo assembly
Project description:We reported an atlas of de novo-defined, full-length macaque gene models on the basis of single molecule long-read transcriptome sequencing (Iso-seq).
Project description:Whole Genome Shotgun (WGS) sequences of plant species often contain an abundance of reads that are derived from the chloroplast genome. Up to now these reads have generally been identified and assembled into chloroplast genomes based on homology to chloroplasts from related species. This re-sequencing approach may select against structural differences between the genomes especially in non-model species for which no close relatives have been sequenced before. The alternative approach is to de novo assemble the chloroplast genome from total genomic DNA sequences. In this study, we used k-mer frequency tables to identify and extract the chloroplast reads from the WGS reads and assemble these using a highly integrated and automated custom pipeline. Our strategy includes steps aimed at optimizing assemblies and filling gaps which are left due to coverage variation in the WGS dataset. We have successfully de novo assembled three complete chloroplast genomes from plant species with a range of nuclear genome sizes to demonstrate the universality of our approach: Solanum lycopersicum (0.9 Gb), Aegilops tauschii (4 Gb) and Paphiopedilum henryanum (25 Gb). We also highlight the need to optimize the choice of k and the amount of data used. This new and cost-effective method for de novo short read assembly will facilitate the study of complete chloroplast genomes with more accurate analyses and inferences, especially in non-model plant genomes.
Project description:Assembling a large genome using next generation sequencing reads requires large computer memory and a long execution time. To reduce these requirements, we propose an extension-based assembler, called JR-Assembler, where J and R stand for "jumping" extension and read "remapping." First, it uses the read count to select good quality reads as seeds. Second, it extends each seed by a whole-read extension process, which expedites the extension process and can jump over short repeats. Third, it uses a dynamic back trimming process to avoid extension termination due to sequencing errors. Fourth, it remaps reads to each assembled sequence, and if an assembly error occurs by the presence of a repeat, it breaks the contig at the repeat boundaries. Fifth, it applies a less stringent extension criterion to connect low-coverage regions. Finally, it merges contigs by unused reads. An extensive comparison of JR-Assembler with current assemblers using datasets from small, medium, and large genomes shows that JR-Assembler achieves a better or comparable overall assembly quality and requires lower memory use and less central processing unit time, especially for large genomes. Finally, a simulation study shows that JR-Assembler achieves a superior performance on memory use and central processing unit time than most current assemblers when the read length is 150 bp or longer, indicating that the advantages of JR-Assembler over current assemblers will increase as the read length increases with advances in next generation sequencing technology.