A new non-linear normalization method for reducing variability in DNA microarray experiments

BACKGROUND: Microarray data are subject to multiple sources of variation, of which biological sources are of interest whereas most others are only confounding. Recent work has identified systematic sources of variation that are intensity-dependent and non-linear in nature. Systematic sources of variation are not limited to the differing properties of the cyanine dyes Cy5 and Cy3 as observed in cDNA arrays, but are the general case for both oligonucleotide microarray (Affymetrix GeneChips) and cDNA microarray data. Current normalization techniques are most often linear and therefore not capable of fully correcting for these effects. RESULTS: We present here a simple and robust non-linear method for normalization using array signal distribution analysis and cubic splines. These methods compared favorably to normalization using robust local-linear regression (lowess). The application of these methods to oligonucleotide arrays reduced the relative error between replicates by 5-10% compared with a standard global normalization method. Application to cDNA arrays showed improvements over the standard method and over Cy3-Cy5 normalization based on dye-swap replication. In addition, a set of known differentially regulated genes was ranked higher by the t-test. In either cDNA or Affymetrix technology, signal-dependent bias was more than ten times greater than the observed print-tip or spatial effects. CONCLUSIONS: Intensity-dependent normalization is important for both high-density oligonucleotide array and cDNA array data. Both the regression and spline-based methods described here performed better than existing linear methods when assessed on the variability of replicate arrays. Dye-swap normalization was less effective at Cy3-Cy5 normalization than either regression or spline-based methods alone

Complete genome sequence of the industrial bacterium Bacillus licheniformis and comparisons with closely related Bacillus species

BACKGROUND: Bacillus licheniformis is a Gram-positive, spore-forming soil bacterium that is used in the biotechnology industry to manufacture enzymes, antibiotics, biochemicals and consumer products. This species is closely related to the well studied model organism Bacillus subtilis, and produces an assortment of extracellular enzymes that may contribute to nutrient cycling in nature. RESULTS: We determined the complete nucleotide sequence of the B. licheniformis ATCC 14580 genome which comprises a circular chromosome of 4,222,336 base-pairs (bp) containing 4,208 predicted protein-coding genes with an average size of 873 bp, seven rRNA operons, and 72 tRNA genes. The B. licheniformis chromosome contains large regions that are colinear with the genomes of B. subtilis and Bacillus halodurans, and approximately 80% of the predicted B. licheniformis coding sequences have B. subtilis orthologs. CONCLUSIONS: Despite the unmistakable organizational similarities between the B. licheniformis and B. subtilis genomes, there are notable differences in the numbers and locations of prophages, transposable elements and a number of extracellular enzymes and secondary metabolic pathway operons that distinguish these species. Differences include a region of more than 80 kilobases (kb) that comprises a cluster of polyketide synthase genes and a second operon of 38 kb encoding plipastatin synthase enzymes that are absent in the B. licheniformis genome. The availability of a completed genome sequence for B. licheniformis should facilitate the design and construction of improved industrial strains and allow for comparative genomics and evolutionary studies within this group of Bacillaceae

Analysis of the Phlebiopsis gigantea Genome, Transcriptome and Secretome Provides Insight into Its Pioneer Colonization Strategies of Wood

Peer reviewe

Aplied Mycology and biotechnology

Volume 6xiv, 336 p. : il.; 21 cm