Examination of Genome Homogeneity in Prokaryotes Using Genomic Signatures

BACKGROUND:DNA word frequencies, normalized for genomic AT content, are remarkably stable within prokaryotic genomes and are therefore said to reflect a "genomic signature." The genomic signatures can be used to phylogenetically classify organisms from arbitrary sampled DNA. Genomic signatures can also be used to search for horizontally transferred DNA or DNA regions subjected to special selection forces. Thus, the stability of the genomic signature can be used as a measure of genomic homogeneity. The factors associated with the stability of the genomic signatures are not known, and this motivated us to investigate further. We analyzed the intra-genomic variance of genomic signatures based on AT content normalization (0(th) order Markov model) as well as genomic signatures normalized by smaller DNA words (1(st) and 2(nd) order Markov models) for 636 sequenced prokaryotic genomes. Regression models were fitted, with intra-genomic signature variance as the response variable, to a set of factors representing genomic properties such as genomic AT content, genome size, habitat, phylum, oxygen requirement, optimal growth temperature and oligonucleotide usage variance (OUV, a measure of oligonucleotide usage bias), measured as the variance between genomic tetranucleotide frequencies and Markov chain approximated tetranucleotide frequencies, as predictors. PRINCIPAL FINDINGS:Regression analysis revealed that OUV was the most important factor (p<0.001) determining intra-genomic homogeneity as measured using genomic signatures. This means that the less random the oligonucleotide usage is in the sense of higher OUV, the more homogeneous the genome is in terms of the genomic signature. The other factors influencing variance in the genomic signature (p<0.001) were genomic AT content, phylum and oxygen requirement. CONCLUSIONS:Genomic homogeneity in prokaryotes is intimately linked to genomic GC content, oligonucleotide usage bias (OUV) and aerobiosis, while oligonucleotide usage bias (OUV) is associated with genomic GC content, aerobiosis and habitat

Reliability and applications of statistical methods based on oligonucleotide frequencies in bacterial and archaeal genomes

<p>Abstract</p> <p>Background</p> <p>The increasing number of sequenced prokaryotic genomes contains a wealth of genomic data that needs to be effectively analysed. A set of statistical tools exists for such analysis, but their strengths and weaknesses have not been fully explored. The statistical methods we are concerned with here are mainly used to examine similarities between archaeal and bacterial DNA from different genomes. These methods compare observed genomic frequencies of fixed-sized oligonucleotides with expected values, which can be determined by genomic nucleotide content, smaller oligonucleotide frequencies, or be based on specific statistical distributions. Advantages with these statistical methods include measurements of phylogenetic relationship with relatively small pieces of DNA sampled from almost anywhere within genomes, detection of foreign/conserved DNA, and homology searches. Our aim was to explore the reliability and best suited applications for some popular methods, which include relative oligonucleotide frequencies (ROF), di- to hexanucleotide zero'th order Markov methods (ZOM) and 2.order Markov chain Method (MCM). Tests were performed on distant homology searches with large DNA sequences, detection of foreign/conserved DNA, and plasmid-host similarity comparisons. Additionally, the reliability of the methods was tested by comparing both real and random genomic DNA.</p> <p>Results</p> <p>Our findings show that the optimal method is context dependent. ROFs were best suited for distant homology searches, whilst the hexanucleotide ZOM and MCM measures were more reliable measures in terms of phylogeny. The dinucleotide ZOM method produced high correlation values when used to compare real genomes to an artificially constructed random genome with similar %GC, and should therefore be used with care. The tetranucleotide ZOM measure was a good measure to detect horizontally transferred regions, and when used to compare the phylogenetic relationships between plasmids and hosts, significant correlation <it>(R</it>²= <it>0.4) </it>was found with genomic GC content and intra-chromosomal homogeneity.</p> <p>Conclusion</p> <p>The statistical methods examined are fast, easy to implement, and powerful for a number of different applications involving genomic sequence comparisons. However, none of the measures examined were superior in all tests, and therefore the choice of the statistical method should depend on the task at hand.</p

Investigations of Oligonucleotide Usage Variance Within and Between Prokaryotes

Oligonucleotide usage in archaeal and bacterial genomes can be linked to a number of properties, including codon usage (trinucleotides), DNA base-stacking energy (dinucleotides), and DNA structural conformation (di- to tetranucleotides). We wanted to assess the statistical information potential of different DNA ‘word-sizes’ and explore how oligonucleotide frequencies differ in coding and non-coding regions. In addition, we used oligonucleotide frequencies to investigate DNA composition and how DNA sequence patterns change within and between prokaryotic organisms. Among the results found was that prokaryotic chromosomes can be described by hexanucleotide frequencies, suggesting that prokaryotic DNA is predominantly short range correlated, i.e., information in prokaryotic genomes is encoded in short oligonucleotides. Oligonucleotide usage varied more within AT-rich and host-associated genomes than in GC-rich and free-living genomes, and this variation was mainly located in non-coding regions. Bias (selectional pressure) in tetranucleotide usage correlated with GC content, and coding regions were more biased than non-coding regions. Non-coding regions were also found to be approximately 5.5% more AT-rich than coding regions, on average, in the 402 chromosomes examined. Pronounced DNA compositional differences were found both within and between AT-rich and GC-rich genomes. GC-rich genomes were more similar and biased in terms of tetranucleotide usage in non-coding regions than AT-rich genomes. The differences found between AT-rich and GC-rich genomes may possibly be attributed to lifestyle, since tetranucleotide usage within host-associated bacteria was, on average, more dissimilar and less biased than free-living archaea and bacteria

Dairy farmer attitudes and empathy toward animals are associated with animal welfare indicators

Attitudes and empathy of farmers influence human–animal interaction, thereby affecting their behavior toward animals. The goal was to investigate how measures of attitude and empathy toward animals were associated with animal welfare indicators such as milk yield, mastitis incidence, fertility index, and the prevalence of skin lesions on cows. To assess empathy toward animals, a photo-based pain assessment instrument was developed depicting various conditions that could be associated with some degree of pain in cattle and included questions aimed at assessing attitudes toward animals. Photos of painful conditions are useful in eliciting measurable empathic responses to pain in humans. A total of 221 farmers were sampled via e-mail and 154 responses were obtained. In the first analysis, farmers were categorized into 2 groups according to their agreement or disagreement with the attitude statement “animals experience physical pain as humans do.” In the second analysis, farmers were assigned a median pain assessment score obtained from their estimates on the visual analog scale of 21 conditions assumed painful for cattle. In the third analysis, farmers were clustered in 3 groups according to their visual analog scale responses. Three conditions were ranked as the most painful: fracture of tuber coxae, dystocia, and serious mastitis. Farmers with positive attitudes toward animals scored 2 points higher on their empathy score compared with farmers with negative attitudes. Personal experience with each additional condition resulted in a 0.09 higher score. Cluster analysis revealed 3 groups. Farmers in group 3 had the highest median pain assessment score (6.7 ± 0.2), indicating a high level of empathy and a positive attitude toward animals. They had the lowest prevalence of skin lesions over the carpus (24 ± 6%) and the lowest milk production (6,705 ± 202 kg). The complex associations between indicators of empathy and attitudes with relevant welfare outcomes suggest that competence building to safeguard animal welfare could benefit from including both attitudes and empathy in human–animal interactions studies

The effect of vaccine-associated cross-stitch vertebrae pathology on growth of farmed Atlantic salmon

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Characterization of some Brucella species from Zimbabwe by biochemical profiling and AMOS-PCR

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