Searching for phenotypic causal networks involving complex traits: an application to European quail

<p>Abstract</p> <p>Background</p> <p>Structural equation models (SEM) are used to model multiple traits and the casual links among them. The number of different causal structures that can be used to fit a SEM is typically very large, even when only a few traits are studied. In recent applications of SEM in quantitative genetics mixed model settings, causal structures were pre-selected based on prior beliefs alone. Alternatively, there are algorithms that search for structures that are compatible with the joint distribution of the data. However, such a search cannot be performed directly on the joint distribution of the phenotypes since causal relationships are possibly masked by genetic covariances. In this context, the application of the Inductive Causation (IC) algorithm to the joint distribution of phenotypes conditional to unobservable genetic effects has been proposed.</p> <p>Methods</p> <p>Here, we applied this approach to five traits in European quail: birth weight (BW), weight at 35 days of age (W35), age at first egg (AFE), average egg weight from 77 to 110 days of age (AEW), and number of eggs laid in the same period (NE). We have focused the discussion on the challenges and difficulties resulting from applying this method to field data. Statistical decisions regarding partial correlations were based on different Highest Posterior Density (HPD) interval contents and models based on the selected causal structures were compared using the Deviance Information Criterion (DIC). In addition, we used temporal information to perform additional edge orienting, overriding the algorithm output when necessary.</p> <p>Results</p> <p>As a result, the final causal structure consisted of two separated substructures: BW→AEW and W35→AFE→NE, where an arrow represents a direct effect. Comparison between a SEM with the selected structure and a Multiple Trait Animal Model using DIC indicated that the SEM is more plausible.</p> <p>Conclusions</p> <p>Coupling prior knowledge with the output provided by the IC algorithm allowed further learning regarding phenotypic causal structures when compared to standard mixed effects SEM applications.</p

Dystocia in Friesian cows and its effects on postpartum reproductive performance and milk production

A total of 1,243 records for 585 dairy Friesian cows from 1997–2004 were used to study the factors affecting dystocia and its effects on reproductive performance and milk production. The overall incidence of dystocia was 6.9%. The percentage of dystocia decreased with increasing live body weight, age, and parity of cows (P < 0.05); however, it increased with increasing birth weight of calves (P < 0.05). The highest percentage of dystocia was detected in winter season, but the least percentage was in summer season (P < 0.05). The percentage of incidence of dystocia was significantly (P < 0.05) higher with winter feeding compared to summer ration (8.2% vs. 5.1%). The percentage of incidence of dystocia was significantly (P < 0.05) higher with twinning than single calving (15.5% vs. 6.5%), while not significantly affected by the sex of born calves. Incidence of dystocia had adverse effects on reproductive performance and milk yield. The service interval, service period, days open, and calving interval were significantly (P < 0.05) longer in cows afflicted with dystocia compared to normal cows. The conception rate was lower (P < 0.05), but the number of service per conception was higher (P < 0.05) in cows afflicted with dystocia compared to normal cows (60.5% vs. 73.0% and 3.4 vs. 2.7, respectively). Average daily milk yield was lower (P < 0.05) by 1 kg for cows with incidence of dystocia compared to normal cows

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

<p>Abstract</p> <p>Background</p> <p>The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle.</p> <p>Methods</p> <p>Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models.</p> <p>Results and discussion</p> <p>On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence.</p> <p>Conclusions</p> <p>For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.</p

Víctimas resistentes y perpetradores encubiertos

En esta comunicación, presentamos un análisis lingüístico-discursivo de la conceptualización de las víctimas y de los perpetradores del régimen de Pinochet. Para el análisis, comparamos un testimonio autoficcional (Formas de volver a casa, Alejandro Zambra, 2011) con el informe de la Comisión Nacional de Verdad y Reconciliación (Informe Rettig, 1991). Mostramos que la representación de la víctima y del perpetrador cambia como consecuencia del género discursivo y de la época en la que se construye la representación del evento. Además, describimos la evolución de la conceptualización de la víctima y del perpetrador entre la percepción del joven protagonista de Zambra y la narración posterior de los hechos. Para comparar la representación pasiva o resiliente de la víctima, y la del perpetrador como verdadero responsable o como una persona de responsabilidad encubierta, realizamos un análisis lingüístico cognitivo (Talmy 2000, Ibarretxe-Antuñano & Valenzuela 2012) y discursivo (Lamb 2013). Concretamente, desarrollamos un análisis de la víctima y del perpetrador en que se destacan diversos grados de agentividad según la expresión explícita o no del rasgo humano y de la intencionalidad de los agentes (De Cock & Michaud Maturana 2014). Mediante este análisis, pretendemos asimismo ilustrar el aporte de la lingüística al análisis de corpus literarios. La principal conclusión es que el análisis de la agentividad revela diversas conceptualizaciones de las mismas entidades en ambos testimonios. La diferencia radica esencialmente en que mientras en el Informe Rettig las víctimas se perfilan en su mayoría por lo que les acontece, en la obra de Zambra se identifican además como personas activas y resilientes. En cuanto al perpetrador, los resultados muestran que la responsabilidad colectiva de los perpetradores, tan evidente en el informe, en la novela está esencialmente ausente. El resultado de la investigación sugiere que se trata de versiones diversas pero complementarias de la memoria colectiva

Prediction of non-muscle invasive bladder cancer outcomes assessed by innovative multimarker prognostic models.

BACKGROUND: We adapted Bayesian statistical learning strategies to the prognosis field to investigate if genome-wide common SNP improve the prediction ability of clinico-pathological prognosticators and applied it to non-muscle invasive bladder cancer (NMIBC) patients. METHODS: Adapted Bayesian sequential threshold models in combination with LASSO were applied to consider the time-to-event and the censoring nature of data. We studied 822 NMIBC patients followed-up >10 years. The study outcomes were time-to-first-recurrence and time-to-progression. The predictive ability of the models including up to 171,304 SNP and/or 6 clinico-pathological prognosticators was evaluated using AUC-ROC and determination coefficient. RESULTS: Clinico-pathological prognosticators explained a larger proportion of the time-to-first-recurrence (3.1 %) and time-to-progression (5.4 %) phenotypic variances than SNPs (1 and 0.01 %, respectively). Adding SNPs to the clinico-pathological-parameters model slightly improved the prediction of time-to-first-recurrence (up to 4 %). The prediction of time-to-progression using both clinico-pathological prognosticators and SNP did not improve. Heritability (ĥ (2)) of both outcomes was <1 % in NMIBC. CONCLUSIONS: We adapted a Bayesian statistical learning method to deal with a large number of parameters in prognostic studies. Common SNPs showed a limited role in predicting NMIBC outcomes yielding a very low heritability for both outcomes. We report for the first time a heritability estimate for a disease outcome. Our method can be extended to other disease models.The work was partially supported by Red Temática de Investigación Cooperativa en Cáncer (#RD12/0036/0050), Fondo de Investigaciones Sanitarias (FIS), Instituto de Salud Carlos III, (Grant numbers #PI00–0745, #PI05–1436, and #PI06–1614), and Asociación Española Contra el Cáncer (AECC), Spain; the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, USA (Contract NCI NO2-CP-11015); and EU-FP7-HEALTH-F2–2008–201663-UROMOL and EU-7FP-HEALTH-TransBioBC #601933. ELM was funded by a Sara Borrell fellowship, Instituto de Salud Carlos III, Spain; and AML by a fellowship of the European Urological Scholarship Program for Research (EUSP Scholarship S-01–2013)