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The inevitable has happened: genomic technologies have been added to our noninvasive genetic sampling repertoire. In this issue of Molecular Ecology, Perry et al. (2010) demonstrate how DNA extraction from chimpanzee faeces, followed by a series of steps to enrich for target loci, can be coupled with next-generation sequencing. These authors collected sequence and single-nucleotide polymorphism (SNP) data at more than 600 genomic loci (chromosome 21 and the X) and the complete mitochondrial DNA. By design, each locus was 'deep sequenced' to enable SNP identification. To demonstrate the reliability of their data, the work included samples from six captive chimps, which allowed for a comparison between presumably genuine SNPs obtained from blood and potentially flawed SNPs deduced from faeces. Thus, with this method, anyone with the resources, skills and ambition to do genome sequencing of wild, elusive, or protected mammals can enjoy all of the benefits of noninvasive sampling., (© 2010 Blackwell Publishing Ltd.)

In large part, the relevance of genetics to conservation rests on the premise that neutral marker variation in populations reflects levels of detrimental and adaptive genetic variation. Despite its prominence, this tenet has been difficult to evaluate, until now. As we discuss here, genome sequence information and new technological and bioinformatics platforms now enable comprehensive surveys of neutral variation and more direct inferences of detrimental and adaptive variation in species with sequenced genomes and in 'genome-enabled' endangered taxa. Moreover, conservation schemes could begin to consider specific pathological genetic variants. A new conservation genetic agenda would utilize data from enhanced surveys of genomic variation in endangered species to better manage functional genetic variation.

We report on a genome-wide scan for introgression between the house mouse (Mus musculus domesticus) and the Algerian mouse (Mus spretus), using samples from the ranges of sympatry and allopatry in Africa and Europe. Our analysis reveals wide variability in introgression signatures along the genomes, as well as across the samples. We find that fewer than half of the autosomes in each genome harbor all detectable introgression, whereas the X chromosome has none. Further, European mice carry more M. spretus alleles than the sympatric African ones. Using the length distribution and sharing patterns of introgressed genomic tracts across the samples, we infer, first, that at least three distinct hybridization events involving M. spretus have occurred, one of which is ancient, and the other two are recent (one presumably due to warfarin rodenticide selection). Second, several of the inferred introgressed tracts contain genes that are likely to confer adaptive advantage. Third, introgressed tracts might contain driver genes that determine the evolutionary fate of those tracts. Further, functional analysis revealed introgressed genes that are essential to fitness, including the Vkorc1 gene, which is implicated in rodenticide resistance, and olfactory receptor genes. Our findings highlight the extent and role of introgression in nature and call for careful analysis and interpretation of house mouse data in evolutionary and genetic studies. [ABSTRACT FROM AUTHOR]

One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on PhyloNet-HMM—a new comparative genomic framework for detecting introgression in genomes. PhyloNet-HMM combines phylogenetic networks with hidden Markov models (HMMs) to simultaneously capture the (potentially reticulate) evolutionary history of the genomes and dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detected a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgressed genomic regions. Based on our analysis, it is estimated that about 9% of all sites within chromosome 7 are of introgressive origin (these cover about 13 Mbp of chromosome 7, and over 300 genes). Further, our model detected no introgression in a negative control data set. We also found that our model accurately detected introgression and other evolutionary processes from synthetic data sets simulated under the coalescent model with recombination, isolation, and migration. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism. [ABSTRACT FROM AUTHOR]

Background: The biological dimensions of genes are manifold. These include genomic properties, (e.g., X/ autosomal linkage, recombination) and functional properties (e.g., expression level, tissue specificity). Multiple properties, each generally of subtle influence individually, may affect the evolution of genes or merely be (auto-) correlates. Results of multidimensional analyses may reveal the relative importance of these properties on the evolution of genes, and therefore help evaluate whether these properties should be considered during analyses. While numerous properties are now considered during studies, most work still assumes the stereotypical solitary gene as commonly depicted in textbooks. Here, we investigate the Drosophila melanogaster genome to determine whether deviations from the stereotypical gene architecture correlate with other properties of genes. Results: Deviations from the stereotypical gene architecture were classified as the following gene constellations: Overlapping genes were defined as those that overlap in the 5-prime, exonic, or intronic regions. Chromatin coclustering genes were defined as genes that co-clustered within 20 kb of transcriptional territories. If this scheme is applied the stereotypical gene emerges as a rare occurrence (7.5%), slightly varied schemes yielded between ~1%- 50%. Moreover, when following our scheme, paired-overlapping genes and chromatin co-clustering genes accounted for 50.1 and 42.4% of the genes analyzed, respectively. Gene constellation was a correlate of a number of functional and evolutionary properties of genes, but its statistical effect was ~1-2 orders of magnitude lower than the effects of recombination, chromosome linkage and protein function. Analysis of datasets on male reproductive proteins showed these were biased in their representation of gene constellations and evolutionary rate Ka/Ks estimates, but these biases did not overwhelm the biologically meaningful observation of high evolutionary rates of male reproductive genes. Conclusion: Given the rarity of the solitary stereotypical gene, and the abundance of gene constellations that deviate from it, the presence of gene constellations, while once thought to be exceptional in large Eukaryote genomes, might have broader relevance to the understanding and study of the genome. However, according to our definition, while gene constellations can be significant correlates of functional properties of genes, they generally are weak correlates of the evolution of genes. Thus, the need for their consideration would depend on the context of studies. [ABSTRACT FROM AUTHOR]