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Objectives: Pistacia genus belongs to the flowering plants in the cashew family and contains at least 11 species. The whole-genome resequencing data of different species from Pistacia genus are described herein. The data reported here will be useful for better understand the adaptive evolution, demographic history, genetic diversity, population structure, and domestication of pistachio. Data description: Genomic DNA was isolated from fresh leaves and used to construct libraries with insert size of 350 bp. Sequence libraries were made and sequenced on the Illumina Hiseq 4000 platform to produce 150 bp paired-end reads. A total number of 4,851,118,730 billion reads (ranging from 33,305,900 to 34,990,618 reads per sample) were created across all samples. We produced a total of 727.67 Gbp data which have been deposited in the Genome Sequence Archive (GSA) database with the Accession of CRA000978. All of the data are also available as the sequence read archive (SRA) format in the National Center for Biotechnology Information (NCBI) with identifier of SRP189222, mirroring our deposited data in GSA. [ABSTRACT FROM AUTHOR]

Background: Genomic selection has been successfully implemented in plant and animal breeding programs to shorten generation intervals and accelerate genetic progress per unit of time. In practice, genomic selection can be used to improve several correlated traits simultaneously via multiple-trait prediction, which exploits correlations between traits. However, few studies have explored multiple-trait genomic selection. Our aim was to infer genetic correlations between three traits measured in broiler chickens by exploring kinship matrices based on a linear combination of measures of pedigree and marker-based relatedness. A predictive assessment was used to gauge genetic correlations. Methods: A multivariate genomic best linear unbiased prediction model was designed to combine information from pedigree and genome-wide markers in order to assess genetic correlations between three complex traits in chickens, i.e. body weight at 35 days of age (BW), ultrasound area of breast meat (BM) and hen-house egg production (HHP). A dataset with 1351 birds that were genotyped with the 600 K Affymetrix platform was used. A kinship kernel (K) was constructed as K = λG + (1 - λ)A, where A is the numerator relationship matrix, measuring pedigree-based relatedness, and G is a genomic relationship matrix. The weight (λ) assigned to each source of information varied over the grid λ = (0, 0.2, 0.4, 0.6, 0.8, 1). Maximum likelihood estimates of heritability and genetic correlations were obtained at each λ, and the "optimum" λ was determined using cross-validation. Results: Estimates of genetic correlations were affected by the weight placed on the source of information used to build K. For example, the genetic correlation between BW-HHP and BM-HHP changed markedly when λ varied from 0 (only A used for measuring relatedness) to 1 (only genomic information used). As λ increased, predictive correlations (correlation between observed phenotypes and predicted breeding values) increased and mean-squared predictive error decreased. However, the improvement in predictive ability was not monotonic, with an optimum found at some 0 < λ < 1, i.e., when both sources of information were used together. Conclusions: Our findings indicate that multiple-trait prediction may benefit from combining pedigree and marker information. Also, it appeared that expected correlated responses to selection computed from standard theory may differ from realized responses. The predictive assessment provided a metric for performance evaluation as well as a means for expressing uncertainty of outcomes of multiple-trait selection. [ABSTRACT FROM AUTHOR]

Background: Two separate domestication events gave rise to humped zebu cattle in India and humpless taurine cattle in the Fertile Crescent of the Near and Middle East. Iran covers the Eastern side of the Fertile Crescent and exhibits a variety of native cattle breeds, however, only little is known about the admixture patterns of Iranian cattle and their contribution to the formation of modern cattle breeds. Results: Genome-wide data (700 k chip) of eight Iranian cattle breeds (Sarabi N = 19, Kurdi N = 7, Taleshi N = 7, Mazandarani N = 10, Najdi N = 7, Pars N = 7, Kermani N = 9, and Sistani N = 9) were collected from across Iran. For a local assessment, taurine (Holstein and Jersey) and indicine (Brahman) outgroup samples were used. For the global perspective, 134 world-wide cattle breeds were included. Between breed variation amongst Iranian cattle explained 60 % (p < 0.001) of the total molecular variation and 82.88 % (p < 0.001) when outgroups were included. Several migration edges were observed within the Iranian cattle breeds. The highest indicine proportion was found in Sistani. All Iranian breeds with higher indicine ancestry were more admixed with a complex migration pattern. Nineteen founder populations most accurately explained the admixture of 44 selected representative cattle breeds (standard error 0.4617). Low levels of African ancestry were identified in Iranian cattle breeds (on average 7.5 %); however, the signal did not persist through all analyses. Admixture and migration analyses revealed minimal introgression from Iranian cattle into other taurine cattle (Holstein, Hanwoo, Anatolian breeds). Conclusion: The eight Iranian cattle breeds feature a discrete genetic composition which should be considered in conservation programs aimed at preserving unique species and genetic diversity. Despite a complex admixture pattern among Iranian cattle breeds, there was no strong introgression from other world-wide cattle breeds into Iranian cattle and vice versa. Considering Iran's central location of cattle domestication, Iranian cattle might represent a local domestication event that remained contained and did not contribute to the formation of modern breeds, or genetics of the ancestral population that gave rise to modern cattle is too diluted to be linked directly to any current cattle breeds. [ABSTRACT FROM AUTHOR]