BackgroundThe development of next-generation sequencing technologies (NGS) has made the use of whole-genome sequence data for routine genetic evaluations possible, which has triggered a considerable interest in animal and plant breeding fields. Here, we investigated whether complete or partial sequence data can improve upon existing SNP (single nucleotide polymorphism) array-based selection strategies by simulation using a mixed coalescence - gene-dropping approach.ResultsWe simulated 20 or 100 causal mutations (quantitative trait nucleotides, QTN) within 65 predefined ‘gene’ regions, each 10 kb long, within a genome composed of ten 3-Mb chromosomes. We compared prediction accuracy by cross-validation using a medium-density chip (7.5 k SNPs), a high-density (HD, 17 k) and sequence data (335 k). Genetic evaluation was based on a GBLUP method. The simulations showed: (1) a law of diminishing returns with increasing number of SNPs; (2) a modest effect of SNP ascertainment bias in arrays; (3) a small advantage of using whole-genome sequence data vs. HD arrays i.e. ~4%; (4) a minor effect of NGS errors except when imputation error rates are high (≥20%); and (5) if QTN were known, prediction accuracy approached 1. Since this is obviously unrealistic, we explored milder assumptions. We showed that, if all SNPs within causal genes were included in the prediction model, accuracy could also dramatically increase by ~40%. However, this criterion was highly sensitive to either misspecification (including wrong genes) or to the use of an incomplete gene list; in these cases, accuracy fell rapidly towards that reached when all SNPs from sequence data were blindly included in the model.ConclusionsOur study shows that, unless an accurate prior estimate on the functionality of SNPs can be included in the predictor, there is a law of diminishing returns with increasing SNP density. As a result, use of whole-genome sequence data may not result in a highly increased selection response over high-density genotyping.

Control of negative emotions (e.g., anger and fear) by political cues perpetuate intractable conflict by mobilizing public support for aggressive actions. Halperin et al. (2013) found that reappraisal – an adaptive form of emotion regulation – decreased negative emotions triggered by anger-inducing information related to the Israeli–Palestinian conflict, and increased support for conciliatory statements. We tested these effects in the context of the conflict between the Colombian government and the Fuerzas Armadas Revolucionarias de Colombia-Ejército del Pueblo (FARC-EP). Reappraisal training reduced negative emotions produced by a presentation that illustrated FARC’s violent actions, and increased support for conciliatory statements (with overall moderate effect magnitudes). We also found that negative emotions mediated the effects of reappraisal on the support for aggressive and conciliatory statements. These findings indicate a high degree of generality of the phenomena, especially considering the differences between the Israeli–Palestinian conflict and the Colombian conflict. Our findings also show promise for replicating these effects on other types of intergroup conflicts and guiding effective public policy.

Blanco Orejinegro (BON) cattle have 500 years of adaptation to the Colombian tropic, but little is known about their genetic history. Our aim was to estimate levels of linkage disequilibrium (LD), effective population size (Ne), genomic inbreeding for runs of homozygosity (FROH), genomic relation matrix (FGRM), excess of homozygotes (FHOM) and pedigree information (FPEDCOMP) and to characterize the runs of homozygosity (ROH), searching for selection signatures. A total of 419 BON animals were genotyped, 70 with a 150K chip and 349 with a 50K chip. Next, an imputation to 50K was performed, and, after editing, databases of 40K were obtained. The PLINK v1.90 and R programs were used to estimate LD, ROH, FROH and FHOM. The SNeP v1.1 program was used to obtain Ne, and PreGSf90 was used to elaborate the scaled G matrix. The MTDFNRM program was used to estimate FPEDCOMP. The LD mean as r2 at 1 Mb was 0.21 (r2 > 0.30 at a distance of 96.72kb), and Ne was 123 ± 1. A total of 7,652 homozygous segments were obtained, with a mean of 18.35 ± 0.55 ROH/animal. Most of the genome was covered by long ROHs (ROH>8 Mb = 4.86%), indicating significant recent inbreeding. The average inbreeding coefficient for FPEDCOM, FGRM, FHOM and FROH was 4.41%, 4.18%, 5.58% and 6.78%, respectively. The highest correlation was observed between FHOM and FROH (0.95). ROH hotspots/islands were defined using the extreme values of a box plot that was generated, and correspond to QTLs related to milk yield (55.11%), external appearance (13.47%), production (13.30%), reproduction (8.15%), health (5.24%) and meat carcass (4.74%).

r e s u M e n Esta investigación tiene por objeto identificar las representaciones y estereotipos de género utilizados en los comerciales transmitidos por televisión, así como las posibles relaciones entre estos, las categorías de producto, los roles, el género y el nivel de sexismo de los comerciales. Se diseñó un instrumento basado en la Escala de Sexismo en Publicidad de Pingree, Parker, Butler y Paisley (1976), incorporando además las categorías de análisis de McArthur y Resko (1975), el cual se aplicó en una muestra de 80 comerciales. Los resultados evidencian diferencias en el trato del género dentro de los comerciales, apareciendo más figuras femeninas en escenarios privados (hogar) y masculinas en escenarios públicos. En cuanto al nivel de sexismo, el 48% evidenció alto nivel de sexismo, utilizando estereotipos de mujer sexi y ama de casa, con representaciones femeninas de objeto decorativo o en roles de dependencia. Palabras clave Roles de género; sexismo en publicidad, comerciales de televisión; roles de género; estereotipos; psicología del consumidor; psicología social Palabras clave descriptores roles de genero; psicología del consumidor; comerciales de tv; sexismo; estereotipos A b s t r A C t This research aims to identify the representations and stereotypes that are used in commercial broadcast on television, as well as the possible relationships among these product categories, roles, gender and the level of sexism in commercials. The data-gathering instrument was designed based on the Scale of Sexism in Advertising from Pingree, Parker, Butler and Paisley (1976), which also incorporated the analysis categories defined by McArthur and Resko (1975). This tool was applied in a sample of 80 commercials. The results show differences in the treatment of gender within commercials. Thus, female figures appear in the commercials, which occur in private settings (home), while in the public settings are mostly male figures. Regarding the level of sexism, half of the commercials showed high level of sexism. The most stereotypes are sexy woman and housewife, with representations of women like sex object or in dependency roles.