Highly parallel SNP genotyping platforms have been developed for some important crop species, but these platforms typically carry a high cost per sample for first-time or small-scale users. In contrast, recently developed genotyping by sequencing (GBS) approaches offer a highly cost effective alternative for simultaneous SNP discovery and genotyping. In the present investigation, we have explored the use of GBS in soybean. In addition to developing a novel analysis pipeline to call SNPs and indels from the resulting sequence reads, we have devised a modified library preparation protocol to alter the degree of complexity reduction. We used a set of eight diverse soybean genotypes to conduct a pilot scale test of the protocol and pipeline. Using ApeKI for GBS library preparation and sequencing on an Illumina GAIIx machine, we obtained 5.5 M reads and these were processed using our pipeline. A total of 10,120 high quality SNPs were obtained and the distribution of these SNPs mirrored closely the distribution of gene-rich regions in the soybean genome. A total of 39.5% of the SNPs were present in genic regions and 52.5% of these were located in the coding sequence. Validation of over 400 genotypes at a set of randomly selected SNPs using Sanger sequencing showed a 98% success rate. We then explored the use of selective primers to achieve a greater complexity reduction during GBS library preparation. The number of SNP calls could be increased by almost 40% and their depth of coverage was more than doubled, thus opening the door to an increase in the throughput and a significant decrease in the per sample cost. The approach to obtain high quality SNPs developed here will be helpful for marker assisted genomics as well as assessment of available genetic resources for effective utilisation in a wide number of species.

Conifers are characterized by a large genome size and a rapid decay of linkage disequilibrium, most often within gene limits. Genome scans based on noncoding markers are less likely to detect molecular adaptation linked to genes in these species. In this study, we assessed the effectiveness of a genome-wide single nucleotide polymorphism (SNP) scan focused on expressed genes in detecting local adaptation in a conifer species. Samples were collected from six natural populations of white spruce (Picea glauca) moderately differentiated for several quantitative characters. A total of 534 SNPs representing 345 expressed genes were analysed. Genes potentially under natural selection were identified by estimating the differentiation in SNP frequencies among populations (F ST ) and identifying outliers, and by estimating local differentiation using a Bayesian approach. Both average expected heterozygosity and population differentiation estimates (H E = 0.270 and F ST = 0.006) were comparable to those obtained with other genetic markers. Of all genes, 5.5% were identified as outliers with F ST at the 95% confidence level, while 14% were identified as candidates for local adaptation with the Bayesian method. There was some overlap between the two gene sets. More than half of the candidate genes for local adaptation were specific to the warmest population, about 20% to the most arid population, and 15% to the coldest and most humid higher altitude population. These adaptive trends were consistent with the genes' putative functions and the divergence in quantitative traits noted among the populations. The results suggest that an approach separating the locus and population effects is useful to identify genes potentially under selection. These candidates are worth exploring in more details at the physiological and ecological levels.

Outlier detection methods were used to scan the genome of the boreal conifer black spruce (Picea mariana [Mill.] B.S.P.) for gene single-nucleotide polymorphisms (SNPs) potentially involved in adaptations to temperature and precipitation variations. The scan involved 583 SNPs from 313 genes potentially playing adaptive roles. Differentiation estimates among population groups defined following variation in temperature and precipitation were moderately high for adaptive quantitative characters such as the timing of budset or tree height (Q(ST) = 0.189-0.314). Average differentiation estimates for gene SNPs were null, with F(ST) values of 0.005 and 0.006, respectively, among temperature and precipitation population groups. Using two detection approaches, a total of 26 SNPs from 25 genes distributed among 11 of the 12 linkage groups of black spruce were detected as outliers with F(ST) as high as 0.078. Nearly half of the outlier SNPs were located in exons and half of those were nonsynonymous. The functional annotations of genes carrying outlier SNPs and regression analyses between the frequencies of these SNPs and climatic variables supported their implication in adaptive processes. Several genes carrying outlier SNPs belonged to gene families previously found to harbour outlier SNPs in a reproductively isolated but largely sympatric congeneric species, suggesting differential subfunctionalization of gene duplicates. Selection coefficient estimates (S) were moderate but well above the magnitude of drift (>>1/N(e)), indicating that the signature of natural selection could be detected at the nucleotide level despite the recent establishment of these populations during the Holocene.

The International Pseudomonas aeruginosa Consortium is sequencing over 1000 genomes and building an analysis pipeline for the study of Pseudomonas genome evolution, antibiotic resistance and virulence genes. Metadata, including genomic and phenotypic data for each isolate of the collection, are available through the International Pseudomonas Consortium Database (http://ipcd.ibis.ulaval.ca/). Here, we present our strategy and the results that emerged from the analysis of the first 389 genomes. With as yet unmatched resolution, our results confirm that P. aeruginosa strains can be divided into three major groups that are further divided into subgroups, some not previously reported in the literature. We also provide the first snapshot of P. aeruginosa strain diversity with respect to antibiotic resistance. Our approach will allow us to draw potential links between environmental strains and those implicated in human and animal infections, understand how patients become infected and how the infection evolves over time as well as identify prognostic markers for better evidence-based decisions on patient care.

Numbers of substitutions per site for 15 protein-coding genes and six introns of the plant mitochondria were estimated to compare modes and tempos of evolution between exons and introns, and numbers of insertionsdeletions per site also were investigated in introns. Intra-gene homogeneity of numbers of substitutions per site was assessed further among different taxa and between mitochondrial and nuclear paralogs translocated from the mitochondrial genome. Gene-to-gene differences in numbers of substitutions per site were found to be higher for nonsynonymous than synonymous sites, and this could be due to differential selection if mutation rate is assumed constant for the genome. Some mitochondrial genes have evolved as fast as chloroplast genes, thus faster than previously thought. For coxI, relative rate tests showed that woody taxa evolved slower than annuals at synonymous sites. Generation time, population size, and speciation rate are likely factors involved in this rate heterogeneity. Introns were less constrained than their adjacent exons for both overall numbers of substitutions per site and indels, but, on average, overall numbers of substitutions per site for introns were similar to numbers of synonymous substitutions per site for exons. Correlations were generally high between numbers of substitutions and numbers of indels per site for the same intron. Mitochondrial genes transferred to the nucleus had an accelerated rate of substitution per site, which was most significant at synonymous sites. These differences between paralogs in two different genomes are likely the result of different mutation rates.