The blind Mexican cave tetra, Astyanax mexicanus, is a unique model system for the study of parallelism and the evolution of cave-adapted traits. Understanding the genetic basis for these traits has recently become feasible thanks to production of a genome-wide linkage map and quantitative trait association analyses. The selection of suitable candidate genes controlling quantitative traits remains challenging, however, in the absence of a physical genome. Here, we describe the integration of multiple linkage maps generated in four separate crosses between surface, cave, and hybrid forms of A. mexicanus. We performed exhaustive BLAST analyses of genomic markers populating this integrated map against sequenced genomes of numerous taxa, ranging from yeast to amniotes. We found the largest number of identified sequences (228), with the most expect (E) values <10(-5) (95), in the zebrafish Danio rerio. The most significant hits were assembled into an "anchored" linkage map with Danio, revealing numerous regions of conserved synteny, many of which are shared across critical regions of identified quantitative trait loci (QTL). Using this anchored map, we predicted the positions of 21 test genes on the integrated linkage map and verified that 18 of these are found in locations homologous to their chromosomal positions in D. rerio. The anchored map allowed the identification of four candidate genes for QTL relating to rib number and eye size. The map we have generated will greatly accelerate the production of viable lists of additional candidate genes involved in the development and evolution of cave-specific traits in A. mexicanus.

The goals of the current work were to analyse the population structure of 11 Spanish ovine breeds and to detect genomic regions that may have been targeted by selection. A total of 141 individuals were genotyped with the Infinium 50 K Ovine SNP BeadChip (Illumina). We combined this dataset with Spanish ovine data previously reported by the International Sheep Genomics Consortium (N = 229). Multidimensional scaling and Admixture analyses revealed that Canaria de Pelo and, to a lesser extent, Roja Mallorquina, Latxa and Churra are clearly differentiated populations, while the remaining seven breeds (Ojalada, Castellana, Gallega, Xisqueta, Ripollesa, Rasa Aragonesa and Segureña) share a similar genetic background. Performance of a genome scan with BayeScan and hapFLK allowed us identifying three genomic regions that are consistently detected with both methods i.e. Oar3 (150–154 Mb), Oar6 (4–49 Mb) and Oar13 (68–74 Mb). Neighbor-joining trees based on polymorphisms mapping to these three selective sweeps did not show a clustering of breeds according to their predominant productive specialization (except the local tree based on Oar13 SNPs). Such cryptic signatures of selection have been also found in the bovine genome, posing a considerable challenge to understand the biological consequences of artificial selection.

The identification of QTL related to production traits that are relevant for the pig industry has been mostly performed by using divergent crosses. The main objective of the current study was to investigate whether these growth, fatness, and meat quality QTL, previously described in diverse experimental populations, were segregating in a Landrace commercial population selected for litter size, backfat thickness, and growth performance. We have found QTL for carcass weight (posterior P > 0.75), cutlet weight (posterior P > 0.99), weight of ham (posterior P > 0.75), shoulders weight (posterior probability > 0.99), and shear firm-ness (posterior P > 0.99) on pig Chromosome 2. Moreover, QTL with posterior P > 0.75 for fat thickness between the 3rd and 4th ribs (Chromosome 7), rib weights (Chromosome 8), backfat thickness (Chromosomes 8, 9, and 10), and b Minolta color component (Chromosome 7) were identified. These results indicate that commercial purebred populations retain a significant amount of genetic variation, even for traits that have been selected for many generations.