Posterior SD Research Articles

Modeling feed efficiency over productive lifetime and integrating a submodel for body reserve management in Nordic dairy cattle.

Genetic enhancement of feed efficiency can improve the economic sustainability and environmental responsibility of dairy farming. Although genetic selection holds promise for improving feed efficiency across the lifespan of dairy cows, comprehensive data spanning whole lactations or even a productive lifetime are currently limited. To address this, we used production data and data from a camera-based feed intake and BW recording system, along with records of production, feed intake, and weight on Holstein cows from a research herd. We aimed to estimate variance components for a multivariate, multiparity model of production, feed intake, and BW data to calculate genetic residual feed intake (gRFI) for each of the Nordic breeds (Holstein, Jersey, and Red Dairy Cattle). Our approach included investigating a new definition of energy balance (EBbody) calculated from changes in body reserves, serving as an energy sink in gRFI. The data in our analysis consisted of 4,751 Holstein cows (7,851 lactations), 2,068 Jersey cows (3,486 lactations), and 3,235 Red Dairy Cattle cows (5,419 lactations). We used Gibbs sampling to estimate posterior means and SD for all model parameters. Our findings revealed moderate lactation-wise heritability of gRFI (0.15-0.38) across all breeds and parities. Moreover, gRFI genetic correlations varied (-0.2 to 0.4) between early- and mid- to late-lactation stages across all breeds, and for lactation-wise gRFI, there were moderately high genetic correlations (0.39-0.59) between primi- and multiparous lactations across the 3 breeds. Those results suggest the importance of recording phenotypes in most time periods within and across lactations. Our analysis indicated that improving gRFI with one genetic SD unit corresponded to a 2% to 3% gain in net return profit per cow-year, with no or minimal impact on production and body reserve management. We demonstrated the feasibility of incorporating EBbody into gRFI. Comparing gRFI calculated with EBbody or changes in BW as an energy sink trait for body reserve management were highly genetically correlated (>0.95). This result shows that the choice of the energy sink trait for body reserve management in gRFI will yield limited reranking among cows and sires when based on BW records only. However, EBbody offers an opportunity to incorporate BCS information without increasing the number of genetic parameters to be estimated, but it relies on parameters estimated in experimental settings. In conclusion, our study demonstrates the feasibility of developing a model for gRFI over most of the productive lifetime of dairy cattle, offering significant economic benefits without compromising productivity or body reserve management. Moving forward, comprehensive recording schemes covering whole lactations and productive lifetimes are advantageous for accurate selection indices of gRFI.

Genetic analysis of daily milk weights in U.S. Holsteins using pen-based contemporary groups

The availability of daily milk weights and pen location information provides an interesting opportunity to capture additional data and review how contemporary groups are defined for dairy cattle genetic evaluations. In the US, dairy cows in larger herds are grouped into pens according to various characteristics like parity, production level, reproductive status, lactation stage, and health status. Our data set included pen location information for each daily milk weight, so instead of using herd-year-season of calving to form contemporary groups, we used herd-pen-milking date to more precisely model the environmental effects cows experience at the pen level on a given day. Our data set included 21,000,951 aggregated daily milk records from 114,243 first parity Holstein cows milked 3 times daily in conventional parlor systems in 157 herds representing 29 US states. Our phenotype of interest was daily milk weight, and alternative repeatability animal models were used to estimate genetic parameters and predict breeding values. Age at first calving (6 levels) and days in milk (10 levels) were included as fixed effects and cow (114,243 levels) was included as a random effect. Contemporary group effects included a fixed or random herd-year-season of calving effect (1,492 levels) and/or a fixed or random herd-pen-milking date effect (285,592 levels). Genetic parameters (kg2; posterior SD) were estimated using GIBBSF90+ software. The additive genetic variance ranged from 10.48 (0.60) to 24.12 (0.66), herd-year-season variance was 10.34 (0.40), herd-pen-milking date variance ranged from 4.91 (0.02) to 4.96 (0.02), permanent environmental variance ranged from 10.65 (0.44) to 16.94 (0.30), and residual variance ranged from 11.81 (0.01) to 14.60 (0.01). Heritability estimates ranged from 0.21 (0.01) to 0.47 (0.01), while repeatability estimates ranged from 0.51 (0.01) to 0.71 (0.01), and mean reliability of sires' breeding value predictions ranged from 0.81 to 0.89. Although caution is needed when disentangling associations between genetic effects, permanent environmental effects, and herd-pen-milking date contemporary groups, our results suggest that using daily milk weights and pen locations may improve the precision of genetic evaluations through increased sire PTA reliabilities for milk production traits in dairy cattle.

Individual-based morphological brain network changes in children with Rolandic epilepsy

ObjectiveTo investigate the local cortical morphology and individual-based morphological brain networks (MBNs) changes in children with Rolandic epilepsy (RE). MethodsBased on the structural MRI data of 56 children with RE and 56 healthy controls (HC), we constructed four types of individual-based MBNs using morphological indices (cortical thickness [CT], fractal dimension [FD], gyrification index [GI], and sulcal depth [SD]). The global and nodal properties of the brain networks were analyzed using graph theory. The between-group difference in local morphology and network topology was estimated, and partial correlation analysis was further analyzed. ResultsCompared with the HC, children with RE showed regional GI increases in the right posterior cingulate gyrus and SD increases in the right anterior cingulate gyrus and medial prefrontal cortex. Regarding the network level, RE exhibited increased characteristic path length in CT-based and FD-based networks, while decreased FD-based network node efficiency in the right inferior frontal gyrus. No significant correlation between altered morphological features and clinical variables was found in RE. ConclusionsThese findings indicated that children with RE have disrupted morphological brain network organization beyond local morphology changes. SignificanceThe present study could provide more theoretical basis for exploring the neuropathological mechanisms in RE.

Detecting Fast Progressors: Comparing a Bayesian Longitudinal Model to Linear Regression for Detecting Structural Changes in Glaucoma

PurposeDemonstrate that a novel Bayesian hierarchical spatial longitudinal (HSL) model identifies macular superpixels with rapidly deteriorating ganglion cell complex (GCC) thickness more efficiently than simple linear regression (SLR). DesignProspective cohort study. SettingTertiary glaucoma center. Subjects111 eyes (111 patients) with moderate to severe glaucoma at baseline and ≥4 macular optical coherence tomography scans and ≥2 years of follow-up. Observation ProcedureSuperpixel-patient-specific GCC slopes and their posterior variances in 49 superpixels were derived from our latest Bayesian HSL model and Bayesian SLR. A simulation cohort was created with known intercepts, slopes, and residual variances in individual superpixels. Main outcome measuresWe compared HSL and SLR in the fastest progressing deciles on i) proportion of superpixels identified as significantly progressing in the simulation study and compared to SLR slopes in cohort data; ii) root mean square error (RMSE), and SLR/HSL RMSE ratios. ResultsCohort- In the fastest decile of slopes per SLR, 77% and 80% of superpixels progressed significantly according to SLR and HSL, respectively. The SLR/HSL posterior SD ratio had a median of 1.83, with 90% of ratios favoring HSL. SimulationHSL identified 89% significant negative slopes in the fastest progressing decile vs. 64% for SLR. SLR/HSL RMSE ratio was 1.36 for the fastest decile of slopes, with 83% of RMSE ratios favoring HSL. ConclusionThe Bayesian HSL model improves the estimation efficiency of local GCC rates of change regardless of underlying true rates of change, particularly in fast progressors.

Considerations on effort, precision and accuracy for long-term monitoring of African lions (Panthera leo), when using Bayesian spatial explicit capture-recapture models, in fenced protected areas.

Intensive management is frequently required in fenced wildlife areas to reduce deleterious effects of isolation. Decisions on how best to manage such wildlife are ideally informed by regular and reliable estimates of spatiotemporal fluctuations in population size and structure. However, even in small, fenced areas, it is difficult and costly to regularly monitor key species using advanced methods. This is particularly the case for large carnivores, which typically occur at low density and are elusive yet are central to management decision-making due to their top-down effects in ecosystems and attracting tourism. In this study, we aimed to provide robust estimates of population parameters for African lions (Panthera leo) and use the data to inform a resource-efficient long-term monitoring programme. To achieve this, we used unstructured spatial sampling to collect data on lions in Pilanesberg National Park, a small (~550 km2) fenced protected area in South Africa. We used Bayesian spatial capture-recapture models to estimate density, abundance, sex ratio and home range size of lions over the age of 1 year. Finally, to provide guidance on resource requirements for regular monitoring, we rarefied our empirical data set incrementally and analysed the subsets. Lion density was estimated to be 8.8 per 100 km2 (posterior SD = 0.6), which was lower than anticipated by park management. Sex ratio was estimated close to parity (0.9♀:1♂), consistent with emerging evidence in fenced lion populations, yet discordant with unfenced populations, which are usually ~2♀:1♂ in healthy, source populations. Our rarefied data suggest that a minimum of 4000 km search effort needs to be invested in future monitoring to obtain accurate and precise estimates, while assuming similar detection rates. This study demonstrates an important utility of Bayesian spatial explicit capture-recapture methods for obtaining robust estimates of lion densities and other important parameters in fence-protected areas to inform decision-making.

Predicting factors of echocardiographic super-response to cardiac resynchronization therapy.

To investigate the clinical and echocardiographic predictors of echocardiographic super-response to cardiac resynchronization therapy (CRT) in heart failure patients. We retrospectively collected data from 97 patients, who underwent CRT and were followed up (median time=20.33 months). All had left ventricular ejection fraction (LVEF) ≤35%, New-York-Heart-Association class 3 or 4, and Q wave, R wave and S wave (QRS) duration >120 ms. Time-to-peak systolic velocity was measured for individual LV segments by tissue Doppler imaging prior to CRT. Two-dimensional echocardiography was carried out before and at follow-up, and ≥12.5% increase in LVEF was defined as super-response. From the 97 patients, 23 (23.7%) were super-responders. Super-responders were more frequently female (52.2% vs. 24.3%, respectively; p value=0.012). Among super-responders, the mean of LV end-diastolic and end-systolic volumes were significantly lower. According to dyssynchrony indices, time delay between anteroseptal and posterior wall and SD of all LV segments timing showed significantly higher values in super-responders. By multivariate analysis, LV end-systolic volume and anteroseptal-to-posterior wall delay remained independently associated with echocardiographic super-response to CRT. About one-fourth of our patients with CRT were super-responder in that they had ≥12.5% increase in LVEF by echocardiography. Among all the clinical and echocardiographic measures, only lower LV end-systolic volume and higher anteroseptal-to-posterior wall delay predicted super-response.

Evidence for a critical leopard conservation stronghold from a large protected landscape on the island of Sri Lanka

The decline and extirpation of large carnivore populations can lead to cascading effects in natural ecosystems. An understanding of large carnivore population densities, distribution and dynamics is therefore critical for developing effective conservation strategies across landscapes. This is particularly important in island environments where species face increased extinction risk due to genetic isolation coupled with local losses of finite habitat. The Sri Lankan leopard Panthera pardus kotiya is one of two remaining island-living leopards on Earth and the only apex predator in Sri Lanka. Despite its iconic status in Sri Lanka, robust research on the species has been limited to only a handful of scientific studies, limiting meaningful scientific recommendations for the species’ conservation and management. In this study, we conducted a single season camera trap survey in Sri Lanka’s largest protected area, Wilpattu National Park (1317 km 2 ), located in the country’s northwest. Our objective was to estimate key ecological state variables of interest (density, abundance, sex-specific movement and spatial distribution) of this leopard subspecies. Our results indicate that Wilpattu National Park supports a density of 18 individuals/100 km 2 (posterior SD=1.5; 95% HPD interval=16–21) with a mean abundance of 144 (posterior SD=15) individual leopards and a healthy sex ratio (f:m=2.03:1). The estimated activity range for male leopards > 2 years old was 49.53 km 2 (Posterior SD=3.43; HPD interval=43.09–56.41) and for female leopards > 2 years old was 22.04 km 2 (Posterior SD=1.82; HPD interval=18.34–25.65). This density falls at the higher end of published estimates for the species anywhere in its global range, based on similar methods. Given Sri Lanka’s limited size, this national park system should be considered as a critical stronghold that maintains a source population of leopards, contributing to the long-term population viability of leopards in the larger landscape.

Associations between illness burden and care experiences among Medicare beneficiaries before or after a cancer diagnosis

IntroductionTo understand associations between a new measure of illness burden and care experiences in a large, national sample of Medicare beneficiaries surveyed before or after a cancer diagnosis. Materials and MethodsThe SEER-CAHPS Illness Burden Index (SCIBI) was previously developed using Surveillance, Epidemiology, and End Results (SEER)–Consumer Assessment of Healthcare Providers and Systems (CAHPS) linked data. The SCIBI provides a standardized morbidity score based on self- and other-reported information from 8 domains and proxies relative risk of 12-month, all-cause mortality among people surveyed before or after a cancer diagnosis. We analyzed a population of Medicare beneficiaries (n = 116,735; 49% fee-for-service and 51% Medicare Advantage [MA]; 73% post-cancer diagnosis) surveyed 2007–2013 to understand how their SCIBI scores were associated with 12 different care experience measures. Frequentist and Bayesian multivariable regression models adjusted for standard case-mix adjustors, enrollment type, timing of cancer diagnoses relative to survey, and survey year. Results and DiscussionSCIBl scores were associated (P < .001) in frequentist models with better ratings of Health Plan (coefficient ± standard error: 0.33 ± 0.08) and better Getting Care Quickly scores (0.51 ± 0.09). In Bayesian models, individuals with higher illness burden had similar results on the same two measures and also reported reliably worse Overall Care experiences (coefficient ± posterior SD: −0.17 ± 0.06). Illness burden may influence how people experience care or report those experiences. Individuals with greater illness burdens may need intensive care coordination and multilevel interventions before and after a cancer diagnosis.

Leopard and spotted hyena densities in the Lake Mburo National Park, southwestern Uganda.

Robust measures of animal densities are necessary for effective wildlife management. Leopards (Panthera pardus) and spotted hyenas (Crocuta Crocuta) are higher order predators that are data deficient across much of their East African range and in Uganda, excepting for one peer-reviewed study on hyenas, there are presently no credible population estimates for these species. A lack of information on the population status and even baseline densities of these species has ramifications as leopards are drawcards for the photo-tourism industry, and along with hyenas are often responsible for livestock depredations from pastoralist communities. Leopards are also sometimes hunted for sport. Establishing baseline density estimates for these species is urgently needed not only for population monitoring purposes, but in the design of sustainable management offtakes, and in assessing certain conservation interventions like financial compensation for livestock depredation. Accordingly, we ran a single-season survey of these carnivores in the Lake Mburo National Park of south-western Uganda using 60 remote camera traps distributed in a paired format at 30 locations. We analysed hyena and leopard detections under a Bayesian spatially explicit capture-recapture (SECR) modelling framework to estimate their densities. This small national park (370 km2) is surrounded by Bahima pastoralist communities with high densities of cattle on the park edge (with regular park incursions). Leopard densities were estimated at 6.31 individuals/100 km2 (posterior SD = 1.47, 95% CI [3.75–9.20]), and spotted hyena densities were 10.99 individuals/100 km2, but with wide confidence intervals (posterior SD = 3.35, 95% CI [5.63–17.37]). Leopard and spotted hyena abundance within the boundaries of the national park were 24.87 (posterior SD 7.78) and 39.07 individuals (posterior = SD 13.51) respectively. Leopard densities were on the middle end of SECR studies published in the peer-reviewed literature over the last 5 years while spotted hyena densities were some of the first reported in the literature using SECR, and similar to a study in Botswana which reported 11.80 spotted hyenas/100 km2. Densities were not noticeably lower at the park edge, and in the southwest of our study site, despite repeated cattle incursions into these areas. We postulate that the relatively high densities of both species in the region could be owed to impala Aepyceros melampus densities ranging from 16.6–25.6 impala/km2. Another, potential explanatory variable (albeit a speculative one) is the absence of interspecific competition from African lions (Panthera leo), which became functionally extinct (there is only one male lion present) in the park nearly two decades ago. This study provides the first robust population estimate of these species anywhere in Uganda and suggests leopards and spotted hyenas continue to persist in the highly modified landscape of Lake Mburo National Park.

The Effects of Mindfulness-Based Stress Reduction on the Association Between Autonomic Interoceptive Signals and Emotion Regulation Selection.

The ability to select the most adaptive regulatory strategy as a function of the emotional context plays a pivotal role in psychological health. Recently, we showed that mindfulness-based interventions (MBIs) can improve the sensitivity of regulatory strategy selection to emotional intensity. However, the mechanisms underlying this improvement are unclear. In this study, we tested the hypothesis that MBIs support adaptive regulatory selection by increasing sensitivity to interoceptive signals associated with the emotional stimuli. Participants (n = 84, mean [standard deviation {SD}] age = 30.9 [8.3] years; 54% women) were randomized to either a mindfulness-based stress reduction (MBSR) program or a wait-list control condition. Before and after the MBSR program, physiological measures for autonomic nervous system activity were obtained, and participants performed a task examining emotion regulation selections (reappraisal versus distraction) when confronted with low or high negative intensity images. They also completed a battery of mindfulness, interoception, and well-being self-report measures. A cross-classified model was used for the main analyses. The participants assigned to the MBSR were overall more likely to choose reappraisal than distraction (b = 0.26, posterior SD = 0.13, 95confidence interval = 0.02-0.52) after the program. Interoceptive signals in response to negative images were associated with subsequent regulatory selections (b = 0.02, posterior SD = 0.01, 95% confidence interval = 0.01-0.03) in the MBSR group. Specifically, lower cardiac reactivity was associated with the choice to reappraise, whereas higher cardiac reactivity was related to the choice to distract. Greater differences in cardiac reactivity between states that prompt reappraisal and states that prompt distraction were associated with higher well-being (Satisfaction With Life Scale, Pearson r (29) = 0.527, p = .003). Mindfulness seems to increase the sensitivity of regulatory selections to interoceptive signals, and this is associated with subjective well-being. This may be a central pathway through which MBIs exert their positive effects on mental health and resilience.

Genetic parameter estimations and genomic insights for teat and udder structure in young and mature Canadian Angus cows.

Poor teat and udder structure, frequently associated with older cows, impact cow production and health as well as calf morbidity and mortality. However, producer culling, for reasons including age, production, feed availability, and beef markets, creates a bias in teat (TS) and udder scores (US) assessed and submitted to the Canadian Angus Association for genetic evaluations toward improved mammary structure. In addition, due to the infancy of the reporting program, repeated scores are rare. Prior to the adoption of genetic evaluations for TS and US in Canadian Angus cattle, it is imperative to verify that TS and US from young cows are the same traits as TS and US estimated on mature cows. Genetic parameters for TS and US from all cows (n = 4,192) and then from young cows (parities 1 and 2) and from mature cows (parity ≥ 4) were estimated using a single-trait animal model. Genetic correlations for the traits between the two cow age groups were estimated using a two-trait animal model. Estimates of heritability (posterior SD [PSD]) were 0.32 (0.07) and 0.45 (0.07) for young TS and US and 0.27 (0.07) and 0.31 (0.07) for mature TS and US, respectively. Genetic correlation (PSD) between the young and mature traits was 0.87 (0.13) for TS and 0.40 (0.17) for US. Genome-wide association studies were used to further explore the genetic and biological commonalities and differences between the two groups. Although there were no genes in common for the two USs, 12 genes overlapped for TS in the two cow age groups. Interestingly, there were also 23 genes in common between TS and US in mature cows. Based on these findings, it is recommended that producers collect TS and US on their cow herd annually.

Genetic analysis of pathogen-specific intramammary infections in dairy cows

Mastitis is one of the most common diseases in dairy cattle, causing severe economic losses to dairy farmers. Mastitis usually occurs due to intramammary infection (IMI) caused by a variety of pathogenic bacteria. Although good progress has been made in understanding genetics of pathogen-specific clinical mastitis, studies involving genetic analysis of pathogen-specific IMI are scarce. The overall objective of this study was, therefore, to assess genetic variation of overall and pathogen-specific IMI in nonclinical primiparous and multiparous cows using bacterial culture. Data and milk samples were collected over a 2-yr interval as part of the Canadian Bovine Mastitis Research Network. The final data set contained records of 46,900 quarter milk samples from 3,382 clinically healthy primiparous and multiparous Holstein cows from 84 dairy herds. For the genetic analysis, we considered the following 7 traits: overall IMI, non-aureus staphylococci (NAS) IMI, contagious pathogen IMI, environmental pathogen IMI, major pathogen IMI, minor pathogen IMI and somatic cell score (SCS). Data were analyzed at the quarter level using a threshold-probit model via Gibbs sampling in BLUPF90. Prevalence of IMI traits at the quarter level in multiparous cow from 0 to 400 DIM ranged from 6.8 to 45.5%. Posterior mean of quarter heritability estimates (on the underlying scale, posterior SD in brackets) of overall IMI and pathogen-specific IMI traits ranged from 0.017 to 0.073 (±0.009 to 0.030). Weak to strong genetic correlations [ranging from 0.18 to 0.97 (±0.01 to 0.29)] among pathogen-specific IMI traits and with overall IMI indicated that not all of these traits were genetically similar. Weak to moderate Spearman rank correlations between estimated breeding values for overall IMI and pathogen-specific IMI traits (from 0.31 to 0.87) indicated possible substantial reranking of sires. The percentage of daughters with IMI caused by various pathogen groups ranged from 13 to 80% and from 38 to 94% for the best (10% decile) and worst sires (90% decile) according to their IMI trait-specific estimated breeding values, respectively. Pathogen-specific IMI traits and overall IMI had weak to moderate positive genetic correlations [ranging from 0.11 to 0.81 (±0.11 to 0.22)] with SCS. Therefore, selection for lower SCS will improve resistance to IMI. However, based on the observed weak to moderate rank correlations (0.04 to 0.47) between pathogen-specific IMI traits and SCS, selection for lower SCC will not improve resistance to IMI from every pathogen-specific IMI group in the same manner. Therefore, despite low heritability estimates, there was sizeable genetic variation for pathogen-specific IMI traits, indicating that long-term direct genetic selection for pathogen-specific IMI can improve pathogen-specific IMI resistance.

The importance of reliable monitoring methods for the management of small, isolated populations

AbstractTo effectively manage wildlife populations, it is essential to reliably estimate their abundance. This is particularly the case for small, isolated populations, which are vulnerable to extirpation. Lake Nakuru National Park in Kenya is one such small, isolated area where an introduced population of African lions (Panthera leo) is vulnerable to genetic degradation and catastrophic events. A founder population of six individuals was introduced between 1984 and 1992, with no further recorded immigration. We used Bayesian spatially‐explicit capture–recapture models to estimate lion density and abundance based on unstructured spatial sampling. For individuals over the age of 1 year, posterior mean lion density was estimated to be 6.75 (mode = 5.93, posterior SD = 0.92) individuals/100 km2, with a mean abundance of 11.37 (mode = 10, posterior SD = 1.54), and a sex ratio of 1.38♀:1♂. Previous reports provided abundance figures much higher than ours. However, our estimates are the result of the first scientifically robust survey and we discuss why they should be viewed as a baseline rather than being suggestive of population decline, and how the discrepancy highlights the need for regular systematic surveys using a standardized framework. Given the small population size and prolonged genetic isolation, we provide long‐term management recommendations to secure this lion population.

Genetic parameters of sow feed efficiency during lactation and its underlying traits in a Duroc population

As a result of the genetic selection for prolificacy and the improvements in the environment and farms management, litter size has increased in the last few years so that energy requirements of the lactating sow are greater. In addition, selection for feed efficiency of growing pigs is also conducted in maternal lines, and this has led to a decrease in appetite and feed intake that is extended to the lactation period, so the females are not able to obtain the necessary energy and nutrients for milk production and they mobilize their energetic reserves. When this mobilization is excessive, reproductive and health problems occur which ends up in an early sow culling. In this context, it has been suggested to improve feed efficiency at lactation through genetic selection. The aim of this study is to know, in a Duroc population, the genetic determinism of sow feed efficiency during lactation and traits involved in its definition, as well as genetic and environmental associations between them. The studied traits are daily lactation feed intake (dLFI), daily sow weight balance (dSWB), backfat thickness balance (BFTB), daily litter weight gain (dLWG), sow residual feed intake (RFI) and sow restricted residual feed intake (RRFI) during lactation. Data corresponded to 851 parities from 581 Duroc sows. A Bayesian analysis was performed using Gibbs sampling. A four-trait repeatability animal model was implemented including the systematic factors of batch and parity order, the standardized covariates of sow weight (SWf) and litter weight (LWs) at farrowing for all traits and lactation length for BFTB. The posterior mean (posterior SD) of heritabilities were: 0.09 (0.03) for dLFI, 0.37 (0.07) for dSWB, 0.09 (0.03) for BFTB, 0.22 (0.05) for dLWG, 0.04 (0.02) for RFI and null for RRFI. The genetic correlation between dLFI and dSWB was high and positive (0.74 (0.11)) and null between dLFI and BFTB. Genetic correlation was favourable between RFI and dLFI and BFTB (0.71 (0.16) and −0.69 (0.18)), respectively. The other genetic correlations were not statistically different from zero. The phenotypic correlations were low and positive between dLFI and dSWB (0.27 (0.03), dSWB and BFTB (0.25 (0.04)), and between dLFI and dLWG (0.16 (0.03)). Therefore, in the population under study, the improvement of the lactation feed efficiency would be possible either using RFI, which would not have unfavourable correlated effects, or through an index including its component traits.

66 A genome-wide association study for gestation length in swine

Abstract The objective of the current study was to conduct a genome-wide association on gestation length (GL) in different parities in swine. Sows (n = 831) belonging to the University of Nebraska – Lincoln resource population (Landrace X Nebraska Index Line) were utilized. GL was defined as the number of days between the final insemination and farrowing. Four traits, GL at parity 1, 2, 3 and 4 (GL1, GL2, GL3 and GL4, respectively) were investigated. Animals which were induced 24h prior to a farrowing event were removed from the analysis. Sows were genotyped with the Illumina SNP60 BeadArray. A Bayes C model with π=0.995 was implemented with fixed effects of contemporary group, development pen, diet, linear and quadratic terms for age at puberty (GL1; P &lt; 0.01), and linear and quadratic terms for farrowing age (GL2; P &lt; 0.01). Results are posterior means of 55,000 samples.Single marker association analysis (SMA) was performed in R utilizing a linear model on SNP from 1-Mb windows (n = 10) which explained the largest proportion of genetic variation in GL1. Top 10 (0.5% of all windows) 1-Mb windows accounted for a limited proportion of genetic variance, 7.75, 4.66, 3.45 and 2.05% in GL1, GL2, GL3 and GL4, respectively. Posterior mean heritability estimates (posterior SD) for GL1, GL2, GL3 and GL4 were 0.33 (0.06), 0.34 (0.07), 0.32 (0.08) and 0.20 (0.08), respectively. The top SNP (ASGA0017859, SSC4, 7.8 Mb) located in one of the two top common genomic regions associated with GL1, GL2 and GL3 displayed a difference of 1.1d in GL1 between alternate homozygotes (P &lt; 0.01). The top SNP from nine of the ten regions were significant (P &lt; 0.05) in the SMA. Two of these regions were in common with GL2 and GL3 where SNP with potential functional effects were found in ZFAT, MAML2 and CCDC82. Results suggest GL is a largely polygenic trait.

Indirect genetic effect model using feeding behaviour traits to define the degree of interaction between mates: an implementation in pigs growth rate

An alternative implementation of the animal model including indirect genetic effect (IGE) is presented considering pair-mate-specific interaction degrees to improve the performance of the model. Data consisted of average daily gain (ADG) records from 663 pigs kept in groups of 10 to 14 mates during the fattening period. Three types of models were used to fit ADG data: (i) animal model (AM); (ii) AM with classical IGE (AM-IGE); and (iii) AM fitting IGE with a specific degree of interaction between each pair of mates (AM-IGEi). Several feeding behavior phenotypes were used to define the pair-mate-specific degree of interaction in AM-IGEi: feeding rate (g/min), feeding frequency (min/day), the time between consecutive visits to the feeder (min/day), occupation time (min/day) and an index considering all these variables. All models included systematic effects batch, initial age (covariate), final age (covariate), number of pigs per pen (covariate), plus the random effect of the pen. Estimated posterior mean (posterior SD) of heritability was 0.47 (0.15) using AM. Including social genetic effects in the model, total heritable variance expressed as a proportion of total phenotypic variance (T2) was 0.54 (0.29) using AM-IGE, whereas it ranged from 0.51 to 0.55 (0.12 to 0.14) with AM-IGEi, depending on the behavior trait used to define social interactions. These results confirm the contribution of IGEs to the total heritable variation of ADG. Moreover, important differences between models were observed in EBV rankings. The percentage of coincidence of top 10% animals between AM and AM-IGEi ranged from 0.44 to 0.89 and from 0.41to 0.68 between AM-IGE and AM-IGEi. Based on the goodness of fit and predictive ability, social models are preferred for the genetic evaluation of ADG. Among models including IGEs, when the pair-specific degree of interaction was defined using feeding behavior phenotypes we obtained an increase in the accuracy of genetic parameters estimates, the better goodness of fit and higher predictive ability. We conclude that feeding behavior variables can be used to measure the interaction between pen mates and to improve the performance of models including IGEs.

The impact of individual patient data in a network meta-analysis: An investigation into parameter estimation and model selection.

The use of individual patient data (IPD) in network meta-analysis (NMA) is becoming increasingly popular. However, as most studies do not report IPD, most NMAs are performed using aggregate data for at least some, if not all, of the studies. We investigate the benefits of including varying proportions of IPD studies in an NMA. Several models have previously been developed for including both aggregate data and IPD in the same NMA. We performed a simulation study based on these models to examine the impact of additional IPD studies on the accuracy and precision of the estimates of both the treatment effect and the covariate effect. We also compared the deviance information criterion (DIC) between models to assess model fit. An increased proportion of IPD resulted in more accurate and precise estimates for most models and datasets. However, the coverage probability sometimes decreased when the model was misspecified. The use of IPD leads to greater differences in DIC, which allows us choose the correct model more often. We analysed a Hepatitis C network consisting of 3 IPD observational studies. The ranking of treatments remained the same for all models and datasets. We observed similar results to the simulation study: The use of IPD leads to differences in DIC and more precise estimates for the covariate effect. However, IPD sometimes increased the posterior SD of the treatment effect estimate, which may indicate between study heterogeneity. We recommend that IPD should be used where possible, especially for assessing model fit.

Genetic analysis of carcass and meat quality traits in Nelore cattle1.

The objective of this study was to estimate genetic parameters for carcass and meat quality traits, as well as their genetic correlations using pedigree and genomic information. A total of 3,716; 3,702; 3,439; 3,705; and 3,714 records of 12th-13th rib LM area (LMA), backfat thickness (BF), HCW, marbling score (MARB), and Warner-Bratzler peak shear force (WBSF), respectively, were used. Animals were genotyped with BovineHD BeadChip and GeneSeek Genomic Profiler Indicus HD - GGP75Ki panel. The (co)variance components were estimated by Bayesian inference using a multitrait ssGBLUP analysis. The animal model included fixed effects of contemporary group (defined by the combination of farm and year of birth, and management group at yearling) and age of animal at slaughtering as a covariate (linear). Direct additive genetic and residual effects were fitted as random. The posterior means and SD of heritabilities for LMA, BF, HCW, MARB, and WBSF were 0.28 (0.03), 0.21 (0.04), 0.21 (0.04), 0.12 (0.04), and 0.11 (0.03), respectively. The posterior means for genetic correlations between LMA and meat quality were positive and moderate with MARB (0.38 ± 0.12) and negative with WBSF (-0.47 ± 0.12). Low genetic correlations were estimated between BF and WBSF (-0.03 ± 0.16) and between HCW and MARB (-0.04 ± 0.14), indicating that these traits are not controlled by the same set or linked genes. Carcass traits (LMA, BF, and HCW) presented moderate heritability providing quick response to the selection purpose. The estimates of heritability for meat quality traits (MARB and WBSF) were low and indicate that the rate of genetic improvement for these traits would be slow. Genetic correlations indicated that selection for carcass traits would not be strongly antagonistic for improving meat quality.

Genome-wide association study for feed efficiency traits using SNP and haplotype models.

Feed costs comprise the majority of variable expenses in beef cattle systems making feed efficiency an important economic consideration within the beef industry. Due to the expense of recording individual feed-intake phenotypes, a genomic-enabled approach could be advantageous toward improving this economically relevant trait complex. A genome-wide association study (GWAS) was performed using 748 crossbred steers and heifers representing seven sire breeds with phenotypes for ADG and ADFI. Animals were genotyped with the BovineSNP50v2 BeadChip containing approximately 54,000 SNP. Both traits were analyzed using univariate SNP-based (BayesC) and haplotype-based (BayesIM) models and jointly using BayesIM to perform a bivariate GWAS. For BayesIM, a hidden Markov model (HMM) of haplotype segments of variable length was built where haplotypes were mapped to clusters based on local similarity. The estimated HMM was then used to assign haplotype cluster genotypes, instead of SNP genotypes, as latent covariates in a Bayesian mixture model. The number of haplotype clusters at each location was assumed to be either 8 (BayesIM8) or 16 (BayesIM16). A total of three univariate analyses for each trait and two bivariate analyses were performed. Posterior SD (PSD) for ADG were 0.28 (0.08), 0.37 (0.11), 0.37 (0.11), 0.35 (0.11), and 0.35 (0.12) for BayesC, BayesIM8, BayesIM16, BayesIM8 bivariate, and BayesIM16 bivariate, respectively. ADFI PSD were 0.30 (0.07), 0.44 (0.13), 0.42 (0.12), 0.38 (0.10), and 0.38 (0.10) for the same models. The top 1% of 1-Mb windows that explained the largest fraction of genetic variation in common between univariate SNP and haplotype models ranged from 24% to 40% and from 20% to 32% for ADG and ADFI, respectively. Spearmen rank correlations between molecular breeding values from SNP and haplotype-based models in the training data were similar for both traits (>0.96) suggesting that either model would lead to similar rankings of animals, although resolution of potential QTL appeared to be greater for BayesIM.

Predicting milk protein responses and the requirement of metabolizable protein by lactating dairy cows

The objective of this study was to develop a modeling framework to predict milk protein yield responses to varying metabolizable protein (MP) supplies and to determine the requirement of MP by lactating dairy cows. The logistic curve was used to model milk protein yield while accounting for a variable efficiency of MP utilization and between-study variability. Models were developed with databases from 2 recently published meta-analyses and based on either total MP supply or MP supply available for milk production. All models provided reasonable fit to data, with root mean square prediction error ranging from 18 to 20% of the average milk protein yield. The estimated horizontal asymptotes were 1.17 (posterior SD = 0.02) and 1.55 (posterior SD = 0.06) in the 2 databases, suggesting that the limiting milk protein yield, as MP supply increases, converges to 1.17 or 1.55 kg/d in the environments determined by the 2 databases. The observed efficiencies ranged from 0.75 to 0.18 when total MP supply was used as the denominator and above 1 to 0.24 when the MP supply available for milk production was used as the denominator. The predicted efficiencies were in good agreement with the data, decreasing nonlinearly with the MP supply. The MP requirement was calculated with a function constructed with the inverse of the logistic model and modified at regions of maximum marginal efficiency and minimum second derivative. This strategy assumes that the MP solution, or the MP needed to predict a given protein yield in the fitted logistic curve, determines the MP requirement for maintenance and lactation. Requirements calculated with the independent variable as total MP supply refer to the total requirement of maintenance plus lactation, whereas the requirement from models based on MP supply available for milk production are referent to the MP required only for lactation. The requirements were, on average, slightly smaller than the ones predicted by the current Northern American feeding system for dairy cows at lower protein yields and greater than currently recommended at high yields.