Biodiversity of 52 chicken populations assessed by microsatellite typing of DNA pools

In a project on the biodiversity of chickens funded by the European Commission (EC), eight laboratories collaborated to assess the genetic variation within and between 52 populations from a wide range of chicken types. Twenty-two di-nucleotide microsatellite markers were used to genotype DNA pools of 50 birds from each population. The polymorphism measures for the average, the least polymorphic population (inbred C line) and the most polymorphic population (Gallus gallus spadiceus) were, respectively, as follows: number of alleles per locus, per population: 3.5, 1.3 and 5.2; average gene diversity across markers: 0.47, 0.05 and 0.64; and proportion of polymorphic markers: 0.91, 0.25 and 1.0. These were in good agreement with the breeding history of the populations. For instance, unselected populations were found to be more polymorphic than selected breeds such as layers. Thus DNA pools are effective in the preliminary assessment of genetic variation of populations and markers. Mean genetic distance indicates the extent to which a given population shares its genetic diversity with that of the whole tested gene pool and is a useful criterion for conservation of diversity. The distribution of population-specific (private) alleles and the amount of genetic variation shared among populations supports the hypothesis that the red jungle fowl is the main progenitor of the domesticated chicken

Organizational Heterogeneity of Vertebrate Genomes

Genomes of higher eukaryotes are mosaics of segments with various structural, functional, and evolutionary properties. The availability of whole-genome sequences allows the investigation of their structure as “texts” using different statistical and computational methods. One such method, referred to as Compositional Spectra (CS) analysis, is based on scoring the occurrences of fixed-length oligonucleotides (k-mers) in the target DNA sequence. CS analysis allows generating species- or region-specific characteristics of the genome, regardless of their length and the presence of coding DNA. In this study, we consider the heterogeneity of vertebrate genomes as a joint effect of regional variation in sequence organization superimposed on the differences in nucleotide composition. We estimated compositional and organizational heterogeneity of genome and chromosome sequences separately and found that both heterogeneity types vary widely among genomes as well as among chromosomes in all investigated taxonomic groups. The high correspondence of heterogeneity scores obtained on three genome fractions, coding, repetitive, and the remaining part of the noncoding DNA (the genome dark matter - GDM) allows the assumption that CS-heterogeneity may have functional relevance to genome regulation. Of special interest for such interpretation is the fact that natural GDM sequences display the highest deviation from the corresponding reshuffled sequences

Evaluating the number of different genomes in a metagenome by means of the compositional spectra approach.

Determination of metagenome composition is still one of the most interesting problems of bioinformatics. It involves a wide range of mathematical methods, from probabilistic models of combinatorics to cluster analysis and pattern recognition techniques. The successful advance of rapid sequencing methods and fast and precise metagenome analysis will increase the diagnostic value of healthy or pathological human metagenomes. The article presents the theoretical foundations of the algorithm for calculating the number of different genomes in the medium under study. The approach is based on analysis of the compositional spectra of subsequently sequenced samples of the medium. Its essential feature is using random fluctuations in the bacteria number in different samples of the same metagenome. The possibility of effective implementation of the algorithm in the presence of data errors is also discussed. In the work, the algorithm of a metagenome evaluation is described, including the estimation of the genome number and the identification of the genomes with known compositional spectra. It should be emphasized that evaluating the genome number in a metagenome can be always helpful, regardless of the metagenome separation techniques, such as clustering the sequencing results or marker analysis

List of genomes used for analyses.

<p>*incomplete genome sequences.</p

Heterogeneity of different genome fractions (·10⁻²).

<p>The deviation of the sampled median values is less than 0.0001 in all genomes for each of the three scores.</p><p>*H_c, H_o and H_t – compositional, organizational and total heterogeneity scores. Note that H_c is calculated as median of differences in GC content while H_t and H_o scores are evaluated based on comparison of compositional spectra (see section <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032076#s2" target="_blank">Methods</a>);</p><p>**only large chromosomes 1–8 were taken into account.</p

Predicted and observed values of human intra- and inter-chromosomal heterogeneity estimates.

<p>Axes X: predicted values, axes Y: observed values. (A) intra-chromosomal H_t; (B) average inter-chromosomal H_t; (C) intra-chromosomal H_o; (D) average inter-chromosomal H_o.</p

The distribution histogram of human median inter-chromosomal CS-distances obtained with different permitted maximal levels of GC differences between scored 100 kb segments.

<p>The inter-chromosomal CS-distances obtained without restriction on inter-segmental GC differences contain both compositional and organizational components of inter-chromosomal heterogeneity (thereby coinciding with H_t). The stricter conditions on ΔGC reduce the influence of H_c on the estimate of H_o. All ΔGC thresholds that are ≤0.02 show just slightly different distributions of human inter-chromosomal H_o. Therefore, we believe that ΔGC≤0.02 condition permits us to assess organizational inter-chromosomal heterogeneity without the influence of compositional heterogeneity.</p