Efficient and accurate whole genome assembly and methylome profiling of E. coli.

BACKGROUND: With the price of next generation sequencing steadily decreasing, bacterial genome assembly is now accessible to a wide range of researchers. It is therefore necessary to understand the best methods for generating a genome assembly, specifically, which combination of sequencing and bioinformatics strategies result in the most accurate assemblies. Here, we sequence three E. coli strains on the Illumina MiSeq, Life Technologies Ion Torrent PGM, and Pacific Biosciences RS. We then perform genome assemblies on all three datasets alone or in combination to determine the best methods for the assembly of bacterial genomes. RESULTS: Three E. coli strains - BL21(DE3), Bal225, and DH5α - were sequenced to a depth of 100× on the MiSeq and Ion Torrent machines and to at least 125× on the PacBio RS. Four assembly methods were examined and compared. The previously published BL21(DE3) genome [GenBank:AM946981.2], allowed us to evaluate the accuracy of each of the BL21(DE3) assemblies. BL21(DE3) PacBio-only assemblies resulted in a 90% reduction in contigs versus short read only assemblies, while N50 numbers increased by over 7-fold. Strikingly, the number of SNPs in PacBio-only assemblies were less than half that seen with short read assemblies (~20 SNPs vs. ~50 SNPs) and indels also saw dramatic reductions (~2 indel >5 bp in PacBio-only assemblies vs. ~12 for short-read only assemblies). Assemblies that used a mixture of PacBio and short read data generally fell in between these two extremes. Use of PacBio sequencing reads also allowed us to call covalent base modifications for the three strains. Each of the strains used here had a known covalent base modification genotype, which was confirmed by PacBio sequencing. CONCLUSION: Using data generated solely from the Pacific Biosciences RS, we were able to generate the most complete and accurate de novo assemblies of E. coli strains. We found that the addition of other sequencing technology data offered no improvements over use of PacBio data alone. In addition, the sequencing data from the PacBio RS allowed for sensitive and specific calling of covalent base modifications.

The auxin-induced transcriptome for etiolated Arabidopsis seedlings using a structure/function approach.

To increase our understanding of the mode of action of auxin, we analyzed auxin-induced changes in the Arabidopsis transcriptome with microarrays representing 20426 Arabidopsis genes. Treatment of etiolated seedlings with low concentrations of the auxin, indole-3-acetic acid (IAA), decreased the expression levels of 23 genes, whereas it increased the expression levels of 47 genes within 20 min. After 40 min, the directional trend in genomic change was predominantly an increase in gene expression. Among the most rapidly induced changes are those in genes encoding transcription factors. Promoter regions of transiently induced genes contained DNA motifs that bind auxin response (ARFAT) and silence element binding factors whereas genes induced by IAA during the entire experimental period contained MYC and ARFAT DNA motifs at higher frequencies. Six structurally diverse auxins were analyzed to determine genes that are unique to a specific auxin, as well as a common set of genes that are rapidly regulated by all tested auxins, thus enabling the identification of shared DNA motifs. In addition to ARFAT, analysis of promoter regions of genes induced by all six auxins revealed the presence of an abscisic-acid-responsive DC3 promoter-binding factor and low temperature responsive elements suggesting a possible role for abscisic acid in modulating auxin-induced responses.