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OPENRosaceae is the most important fruit-producing clade, and its key commercially relevant genera (Fragaria, Rosa, Rubus and Prunus) show broadly diverse growth habits, fruit types and compact diploid genomes. Peach, a diploid Prunus species, is one of the best genetically characterized deciduous trees. Here we describe the high-quality genome sequence of peach obtained from a completely homozygous genotype. We obtained a complete chromosome-scale assembly using Sanger whole-genome shotgun methods. We predicted 27,852 protein-coding genes, as well as noncoding RNAs. We investigated the path of peach domestication through whole-genome resequencing of 14 Prunus accessions. The analyses suggest major genetic bottlenecks that have substantially shaped peach genome diversity. Furthermore, comparative analyses showed that peach has not undergone recent whole-genome duplication, and even though the ancestral triplicated blocks in peach are fragmentary compared to those in grape, all seven paleosets of paralogs from the putative paleoancestor are detectable.

BackgroundWorldwide, grapes and their derived products have a large market. The cultivated grape species Vitis vinifera has potential to become a model for fruit trees genetics. Like many plant species, it is highly heterozygous, which is an additional challenge to modern whole genome shotgun sequencing. In this paper a high quality draft genome sequence of a cultivated clone of V. vinifera Pinot Noir is presented.Principal FindingsWe estimate the genome size of V. vinifera to be 504.6 Mb. Genomic sequences corresponding to 477.1 Mb were assembled in 2,093 metacontigs and 435.1 Mb were anchored to the 19 linkage groups (LGs). The number of predicted genes is 29,585, of which 96.1% were assigned to LGs. This assembly of the grape genome provides candidate genes implicated in traits relevant to grapevine cultivation, such as those influencing wine quality, via secondary metabolites, and those connected with the extreme susceptibility of grape to pathogens. Single nucleotide polymorphism (SNP) distribution was consistent with a diffuse haplotype structure across the genome. Of around 2,000,000 SNPs, 1,751,176 were mapped to chromosomes and one or more of them were identified in 86.7% of anchored genes. The relative age of grape duplicated genes was estimated and this made possible to reveal a relatively recent Vitis-specific large scale duplication event concerning at least 10 chromosomes (duplication not reported before).ConclusionsSanger shotgun sequencing and highly efficient sequencing by synthesis (SBS), together with dedicated assembly programs, resolved a complex heterozygous genome. A consensus sequence of the genome and a set of mapped marker loci were generated. Homologous chromosomes of Pinot Noir differ by 11.2% of their DNA (hemizygous DNA plus chromosomal gaps). SNP markers are offered as a tool with the potential of introducing a new era in the molecular breeding of grape.

urum wheat (DW), Triticum turgidum L. ssp. durum (Desf.) Husn., genome BBAA, is a cereal grain mainly used for pasta production and evolved from domesticated emmer wheat (DEW), T. turgidum ssp. dicoccum (Schrank ex Schübl.) Thell. DEW itself derived from wild emmer wheat (WEW), T. turgidum ssp. dicoccoides (Körn. ex Asch. & Graebn.

The Bovine HapMap Consortium* The imprints of domestication and breed development on the genomes of livestock likely differ from those of companion animals. A deep draft sequence assembly of shotgun reads from a single Hereford female and comparative sequences sampled from six additional breeds were used to develop probes to interrogate 37,470 single-nucleotide polymorphisms (SNPs) in 497 cattle from 19 geographically and biologically diverse breeds. These data show that cattle have undergone a rapid recent decrease in effective population size from a very large ancestral population, possibly due to bottlenecks associated with domestication, selection, and breed formation. Domestication and artificial selection appear to have left detectable signatures of selection within the cattle genome, yet the current levels of diversity within breeds are at least as great as exists within humans.T he emergence of modern civilization was accompanied by adaptation, assimilation, and interbreeding of captive animals. In cattle (Bos taurus), this resulted in the development of individual breeds differing in, for example, milk yield, meat quality, draft ability, and tolerance or resistance to disease and pests. However, despite mapping and diversity studies (1-5) and the identification of mutations affecting some quantitative phenotypes (6-8), the detailed genetic structure and history of cattle are not known.Cattle occur as two major geographic types, the taurine (humpless-European, African, and Asian) and indicine (humped-South Asian, and East African), which diverged >250 thousand years ago (Kya) (3). We sampled individuals representing 14 taurine (n = 376), three indicine (n = 73) (table S1), and two hybrid breeds (n = 48), as well as two individuals each of Bubalus quarlesi and Bubalus bubalis, which diverged from Bos taurus~1.25 to 2.0 Mya (9, 10). All breeds except Red Angus (n = 12) were represented by at least 24 individuals. We preferred individuals that were unrelated for ≥4 generations; however, each breed had one or two sire, dam, and progeny trios to allow assessment of genotype quality.Single-nucleotide polymorphisms (SNPs) that were polymorphic in many populations were primarily derived by comparing whole-genome sequence reads representing five taurine and one indicine breed to the reference genome assembly obtained from a Hereford cow (10) (table S2). This led to the ascertainment of SNPs with high minor allele frequencies (MAFs) within the discovery breeds (table S5). Thus, as expected, with trio progeny removed, SNPs discovered within the taurine breeds had higher average MAFs

Semiparametric procedures for prediction of total genetic value for quantitative traits, which make use of phenotypic and genomic data simultaneously, are presented. The methods focus on the treatment of massive information provided by, e.g., single-nucleotide polymorphisms. It is argued that standard parametric methods for quantitative genetic analysis cannot handle the multiplicity of potential interactions arising in models with, e.g., hundreds of thousands of markers, and that most of the assumptions required for an orthogonal decomposition of variance are violated in artificial and natural populations. This makes nonparametric procedures attractive. Kernel regression and reproducing kernel Hilbert spaces regression procedures are embedded into standard mixed-effects linear models, retaining additive genetic effects under multivariate normality for operational reasons. Inferential procedures are presented, and some extensions are suggested. An example is presented, illustrating the potential of the methodology. Implementations can be carried out after modification of standard software developed by animal breeders for likelihood-based or Bayesian analysis.

The evolutionary basis of domestication has been a longstanding question and its genetic architecture is becoming more tractable as more domestic species become genome-enabled. Before becoming established worldwide, sheep and goats were domesticated in the fertile crescent 10,500 years before present (YBP) where their wild relatives remain. Here we sequence the genomes of wild Asiatic mouflon and Bezoar ibex in the sheep and goat domestication center and compare their genomes with that of domestics from local, traditional, and improved breeds. Among the genomic regions carrying selective sweeps differentiating domestic breeds from wild populations, which are associated among others to genes involved in nervous system, immunity and productivity traits, 20 are common to Capra and Ovis. The patterns of selection vary between species, suggesting that while common targets of selection related to domestication and improvement exist, different solutions have arisen to achieve similar phenotypic end-points within these closely related livestock species.

The genomics revolution has spurred the undertaking of HapMap studies of numerous species, allowing for population genomics to increase the understanding of how selection has created genetic differences between subspecies populations. The objectives of this study were to (1) develop an approach to detect signatures of selection in subsets of phenotypically similar breeds of livestock by comparing single nucleotide polymorphism (SNP) diversity between the subset and a larger population, (2) verify this method in breeds selected for simply inherited traits, and (3) apply this method to the dairy breeds in the International Bovine HapMap (IBHM) study. The data consisted of genotypes for 32,689 SNPs of 497 animals from 19 breeds. For a given subset of breeds, the test statistic was the parametric composite log likelihood (CLL) of the differences in allelic frequencies between the subset and the IBHM for a sliding window of SNPs. The null distribution was obtained by calculating CLL for 50,000 random subsets (per chromosome) of individuals. The validity of this approach was confirmed by obtaining extremely large CLLs at the sites of causative variation for polled (BTA1) and black-coat-color (BTA18) phenotypes. Across the 30 bovine chromosomes, 699 putative selection signatures were detected. The largest CLL was on BTA6 and corresponded to KIT, which is responsible for the piebald phenotype present in four of the five dairy breeds. Potassium channel-related genes were at the site of the largest CLL on three chromosomes (BTA14, -16, and -25) whereas integrins (BTA18 and -19) and serine/arginine rich splicing factors (BTA20 and -23) each had the largest CLL on two chromosomes. On the basis of the results of this study, the application of population genomics to farm animals seems quite promising. Comparisons between breed groups have the potential to identify genomic regions influencing complex traits with no need for complex equipment and the collection of extensive phenotypic records and can contribute to the identification of candidate genes and to the understanding of the biological mechanisms controlling complex traits.