Evidence for Quantitative Trait Loci Affecting Ovulation Rate in Pigs

Fifty-five microsatellite markers were scored in an F2 population of pigs (n = 114 females) developed at the University of Nebraska. The population was produced by crossing a line previously selected for 10 generations using an index of ovulation rate and embryonal survival and a line selected at random. The lines were from a common base population and differed by 6.7 ovulations and 3.1 fetuses at 50 d of gestation. Ovulation rate and number of fully formed and mummified pigs were recorded for each female. Data were analyzed with regression models that included random animal effects. Likelihood-ratio tests were used to test for quantitative trait loci (QTL) effects by deviating the log-likelihood for the full model that included additive and dominance QTL effects from the log-likelihood for the reduced model that did not contain QTL effects. A QTL for ovulation rate was found on chromosome 8 (P \u3c .001) with an additive effect of 3.07 ovulations. Other evidence of potential QTL affecting ovulation rate was found on chromosomes 4 (P \u3c .10), 13, and 15 (P \u3c .05). Effects on chromosomes 4, 13, and 15 were not significant for an experiment-wise threshold value of P \u3c .001. No significant QTL for litter size or number of mummified pigs were found. Additional data are needed to confirm the location and the effect of QTL found for ovulation rate before markers associated with them can be used in marker-assisted selection

Evidence for Quantitative Trait Loci Affecting Ovulation Rate in Pigs

Fifty-five microsatellite markers were scored in an F2 population of pigs (n = 114 females) developed at the University of Nebraska. The population was produced by crossing a line previously selected for 10 generations using an index of ovulation rate and embryonal survival and a line selected at random. The lines were from a common base population and differed by 6.7 ovulations and 3.1 fetuses at 50 d of gestation. Ovulation rate and number of fully formed and mummified pigs were recorded for each female. Data were analyzed with regression models that included random animal effects. Likelihood-ratio tests were used to test for quantitative trait loci (QTL) effects by deviating the log-likelihood for the full model that included additive and dominance QTL effects from the log-likelihood for the reduced model that did not contain QTL effects. A QTL for ovulation rate was found on chromosome 8 (P \u3c .001) with an additive effect of 3.07 ovulations. Other evidence of potential QTL affecting ovulation rate was found on chromosomes 4 (P \u3c .10), 13, and 15 (P \u3c .05). Effects on chromosomes 4, 13, and 15 were not significant for an experiment-wise threshold value of P \u3c .001. No significant QTL for litter size or number of mummified pigs were found. Additional data are needed to confirm the location and the effect of QTL found for ovulation rate before markers associated with them can be used in marker-assisted selection

The impact of selective genotyping on the response to selection using single-step genomic best linear unbiased prediction

Across the majority livestock species, routinely collected genomic and pedigree information has been incorporated into evaluations using single-step methods. As a result, strategies that reduce genotyping costs without reducing the response to selection are important as they could have substantial economic impacts on breeding programs. Therefore, the objective of the current study was to investigate the impact of selectively genotyping selection candidates on the selection response using simulation. Populations were simulated to mimic the genome and population structure of a swine and cattle population undergoing selection on an index comprised of the estimated breeding values (EBV) for 2 genetically correlated quantitative traits. Ten generations were generated and genotyping began generation 7. Two phenotyping scenarios were simulated that assumed the first trait was recorded early in life on all individuals and the second trait was recorded on all versus a random subset of the individuals. The EBV were generated from a bivariate animal model. Multiple genotyping scenarios were generated that ranged from not genotyping any selection candidates, a proportion of the selection candidates based on either their index value or chosen at random, and genotyping all selection candidates. An interim index value was utilized to decide who to genotype for the selective genotype strategy. The interim value assumed only the first trait was observed and the only genotypic information available was on animals in previous generations. Within each genotyping scenario 25 replicates were generated. Within each genotyping scenario the mean response per generation and the degree to which EBV were inflated/deflated was calculated. Across both species and phenotyping strategies, the plateau of diminishing returns was observed when 60% of the selection candidates with the largest index values were genotyped. When randomly genotyping selection candidates, either 80 or 100% of the selection candidates needed to be genotyped for there not to be a reduction in the index response. Across both populations, no differences in the degree that EBV were inflated/deflated for either trait 1 or 2 were observed between nongenotyped and genotyped animals. The current study has shown that animals can be selectively genotyped in order to optimize the response to selection as a function of the cost to conduct a breeding program using single-step genomic best linear unbiased prediction

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

National identity predicts public health support during a global pandemic

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics

Social and moral psychology of COVID-19 across 69 countries

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables

Author Correction: National identity predicts public health support during a global pandemic

Correction to: Nature Communications https://doi.org/10.1038/s41467-021-27668-9, published online 26 January 2022

Persistent Place-Making in Prehistory: the Creation, Maintenance, and Transformation of an Epipalaeolithic Landscape

Most archaeological projects today integrate, at least to some degree, how past people engaged with their surroundings, including both how they strategized resource use, organized technological production, or scheduled movements within a physical environment, as well as how they constructed cosmologies around or created symbolic connections to places in the landscape. However, there are a multitude of ways in which archaeologists approach the creation, maintenance, and transformation of human-landscape interrelationships. This paper explores some of these approaches for reconstructing the Epipalaeolithic (ca. 23,000–11,500 years BP) landscape of Southwest Asia, using macro- and microscale geoarchaeological approaches to examine how everyday practices leave traces of human-landscape interactions in northern and eastern Jordan. The case studies presented here demonstrate that these Epipalaeolithic groups engaged in complex and far-reaching social landscapes. Examination of the Early and Middle Epipalaeolithic (EP) highlights that the notion of “Neolithization” is somewhat misleading as many of the features we use to define this transition were already well-established patterns of behavior by the Neolithic. Instead, these features and practices were enacted within a hunter-gatherer world and worldview