Moderate Genetic Correlations Research Articles

Effects of anther-stigma position on cross-pollination efficiency in a hermaphroditic plant.

Evolution of cross-pollination efficiency depends on the genetic variation of flower traits, the pollen vector, and flower trait matching between pollen donors and recipients. Trait matching has been almost unexplored among nonheterostylous species, and we examined whether the match of anther length in pollen donors and stigma length in pollen recipients influences the efficiency of cross-pollination. To explore potential constraints for evolutionary response, we also quantified genetic variation and covariation among sepal length, petal length and width, stamen length, style length, and herkogamy. We created 58 experimental arrays of Turnera velutina that varied in the extent of mismatch in the position of anthers and stigmas between single-flowered plants. Genetic variation and correlations among flower traits were estimated under greenhouse conditions. Style length, but not herkogamy, influenced the efficiency of cross-pollination. Plants with stamen length that matched the style length of other plants were more efficient pollen donors, whereas those with the style protruding above the stamens of other plants were more efficient pollen recipients. Significant broad-sense heritability (0.22 > hB 2 < 0.42) and moderate genetic correlations (0.33 > r < 0.85) among floral traits were detected. Our results demonstrated that anther-stigma mismatch between flowers contributed to variation in the efficiency of cross-pollination. The genetic correlations between stamen length and other floral traits suggests that any change in cross-pollination efficiency would be driven by changes in style rather than in stamen length.

Genetic parameters and genome-wide association analyses for lifetime productivity in Chinese Holstein cattle

Lifetime productivity is a trait of great importance to dairy cattle populations as it combines information from production and longevity variables. Therefore, we investigated the genetic background of lifetime productivity in high-producing dairy cattle by integrating genomics and transcriptomics data sets. A total of 3,365,612 test-day milk yield records from 134,029 Chinese Holstein cows were used to define 6 lifetime productivity traits, including lifetime milk yield covering full lifespan and 5 cumulative milk yield traits covering partial lifespan. Genetic parameters were estimated based on univariate and bivariate linear animal models and the Restricted Maximum Likelihood (REML) method. Genome-wide association studies (GWAS) and weighted gene co-expression network analyses (WGCNA) were performed to identify candidate genes associated with lifetime productivity based on genomic data from 3,424 cows and peripheral blood RNA-seq data from 23 cows, respectively. Lifetime milk yield averaged 24,800.8 ± 14,396.6 kg (mean ± SD) across an average of 2.4 parities in Chinese Holstein population. The heritability estimates for lifetime productivity traits ranged from 0.05 (±0.01 for SE) to 0.10 (±0.02 for SE). The estimate of genetic correlation between lifetime milk yield and productive life is 0.88 (±0.3 for SE) while the genetic correlation with 305d milk yield in the first lactation was 0.49 (±0.08 for SE). Absolute values for most genetic correlation estimates between lifetime productivity and type traits were lower than 0.30. Moderate genetic correlations were found between udder related traits and lifetime productivity, such as with udder depth (0.33), rear udder attachment height (0.33), and udder system (0.34). Some single nucleotide polymorphisms and gene co-expression modules significantly associated with lifetime milk yield were identified based on GWAS and WGCNA analyses, respectively. Functional enrichment analyses of the candidate genes identified revealed important pathways related to immune system, longevity, energy utilization and metabolism, and FoxO signaling. The genes NTMT1, FNBP1, and S1PR1 were considered to be the most important candidate genes influencing lifetime productivity in Holstein cows. Overall, our findings indicate that lifetime productivity is heritable in Chinese Holstein cattle and important candidate genes were identified by integrating genomic and transcriptomic data sets.

Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia

Cognitive impairment is a major determinant of functional outcomes in schizophrenia, however, understanding of the biological mechanisms underpinning cognitive dysfunction in the disorder remains incomplete. Here, we apply Genomic Structural Equation Modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank. We identified three broad factors that underly the genetic correlations between the cognitive tests. We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). Global genetic correlations showed a significant moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found substantial polygenic overlap between each cognitive factor and schizophrenia and biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we show that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptoms in the Norwegian Thematically Organized Psychosis cohort. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.

Impact on prime animal beef merit from breeding solely for lighter dairy cows.

As the proportion of prime carcasses originating from dairy herds increases, the focus is shifting to the beef merit of the progeny from dairy herds. Several dairy cow total merit indexes include a negative weight on measures of cow size. However, there is a lack of knowledge on the impact of genetic selection, solely for lighter or smaller-sized dairy cows, on the beef performance of their progeny. Therefore, the objective of this study was to quantify the genetic correlations among cow size traits (i.e., cow body weight (BW), cow carcass weight (CW)), cow body condition score (BCS), cow carcass conformation (CC), and cow carcass fat cover (CF), as well as the correlations between these cow traits and a series of beef performance slaughter-related traits (i.e., CW, CC, CF, and age at slaughter (AS)) in their progeny. After data editing, there were 52,950 cow BW and BCS records, along with 57,509 cow carcass traits (i.e., CW, CC, and CF); carcass records from 346,350 prime animals along with AS records from 316,073 prime animals were also used. Heritability estimates ranged from moderate to high (0.18 to 0.62) for all cow and prime animal traits. The same carcass trait in cows and prime animals were strongly genetically correlated with each other (0.76 to 0.85), implying that they are influenced by very similar genomic variants. Selecting exclusively for cows with higher BCS (i.e., fatter) will, on average, produce more conformed prime animals carcasses, owing to a moderate genetic correlation (0.30) between both traits. Genetic correlations revealed that selecting exclusively for lighter BW or CW cows will, on average, result in lighter prime animal carcasses of poor CC, while also delaying slaughter age. Nonetheless, selective breeding through total merit indexes should be successful in breeding for smaller dairy cows, and desirable prime animal carcass traits concurrently, because of the non-unity genetic correlations between the cow and prime animal traits; this will help to achieve a more ethical, environmentally sustainable, and economically viable dairy-beef industry.

Genetic analysis of health traits and their associations with longevity, fertility, production, and conformation traits in Holstein cattle

Health traits have high economic values in dairy cattle breeding, which can cause considerable financial loss through involuntary culling. In this study, fourteen health traits were analysed, including five composite health traits: reproductive disorders, udder health (UH), digestive disorders, metabolic disorders, locomotory diseases (LD), and nine independent health traits: gestation disorders and peripartum disorders, irregular estrus cycle and sterility, metritis (ME), mastitis (MA), abomasal displacement (AD), enteritis (EN), and ketosis, claw diseases (CD), laminitis complex. This study analysed variance components for health traits through both single and bivariate repeatability animal models. All health traits showed low heritability, ranging from 0.001 to 0.025. Most of the health traits in five categories showed negative genetic correlations, ranging from −0.012 (CD and EN) to −0.634 (ME and EN). Strong positive genetic correlations appeared within the same category, ranging from 0.469 (EN and AD) to 0.994 (UH and MA, LD and CD). Furthermore, approximate genetic correlations were evaluated between health traits and routinely collected traits (longevity, fertility, production, and conformation). In general, the low to moderate approximate genetic correlations were estimated between health traits and routinely collected traits. The estimated correlations between health traits and longevity, fertility, production, and conformation traits could provide an indirect reference for disease−resistance breeding in Holstein cattle.

Genetic parameters for udder conformation traits derived from Cartesian coordinates generated by robotic milking systems in North American Holstein cattle

Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems have increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in a xyz plan, which can then be used to derive udder conformation traits. AMS generate a large amount of per milking visit data for individual cows, which contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multi-trait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 single nucleotide polymorphisms. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (±standard error, SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (±SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between the FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection sub-indexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms.

Falls, fracture and frailty risk in multiple sclerosis: a Mendelian Randomization study to identify shared genetics

IntroductionPatients with multiple sclerosis (MS) commonly present musculoskeletal disorders characterized by lower bone mineral density (BMD) and muscle weakness. However, the underlying etiology remains unclear. Our objective is to identify shared pleiotropic genetic effects and estimate the causal relationship between MS and musculoskeletal disorders.Materials and MethodsWe conducted linkage disequilibrium score regression (LDSR), colocalization, and Mendelian randomization (MR) analyses using summary statistics from recent large-scale genome-wide association studies (GWAS), encompassing MS, falls, fractures, and frailty. Additional MR analyses explored the causal relationship with musculoskeletal risk factors, such as BMD, lean mass, grip strength, and vitamin D.ResultsWe observed a moderate genetic correlation between MS and falls (RG = 0.10, P-value =0.01) but not between MS with fracture or frailty in the LDSR analyses. MR revealed MS had no causal association with fracture and frailty but a moderate association with falls (OR: 1.004, FDR q-value = 0.018). We further performed colocalization analyses using nine SNPs that exhibited significant associations with both MS and falls in MR. Two SNPs (rs7731626 on ANKRD55 and rs701006 on OS9 gene) showed higher posterior probability of colocalization (PP.H4 = 0.927), suggesting potential pleiotropic effects between MS and falls. The nine genes are associated with central nervous system development and inflammation signaling pathways.ConclusionWe found potential pleiotropic genetic effects between MS and falls. However, our analysis did not reveal a causal relationship between MS and increased risks of falls, fractures, or frailty. This suggests that the musculoskeletal disorders frequently reported in MS patients in clinical studies are more likely attributed to secondary factors associated with disease progression and treatment, rather than being directly caused by MS itself.

Investigating the shared genetic basis and causal relationships between mucosa-associated lymphoid tissue inflammation and psychiatric disorders.

Chronic and acute inflammation of the mucosa-associated lymphoid tissue have been positively linked to the development of psychiatric disorders in observational studies. However, it remains unclear whether this association is causal. In the present study, we investigated this association, using as proxies genetically predicted tonsillectomy, appendectomy and appendicitis on psychiatric disorders including major depressive disorder (MDD), schizophrenia (SCZ), bipolar depression (BD) and anxiety (ANX) via a two-sample Mendelian randomization (MR) analysis. Genetic association summary statistics for tonsillectomy, appendectomy and appendicitis were sourced from FinnGen Consortium, comprising data from 342,000 participants. Genetic correlations between all exposures and outcome were calculated with Linkage Disequilibrium Score (LDSC) Regression analysis. MR estimates were then calculated to assess their impact on the risk of developing psychiatric disorders. Sensitivity analysis was employed to test for any directional pleiotropy. Our results suggest that there is no direct causal association between tonsillectomy, appendectomy or appendicitis with a heightened risk for development of psychiatric disorders. The robustness of the results of the main MR analysis was further confirmed with additional sensitivity analyses. However, a moderate inverse genetic correlation was observed between tonsillectomy and MDD traits (rg=-0.39, p-value (P)=7.5x10-5). Our findings provide, for the first time, evidence that there is no causal association between tonsillectomy or appendectomy on subsequent vulnerability of developing psychiatric disorders. Future studies using larger sample size GWAS should focus on unraveling the confounding factors and mediators to investigate this relationship further.

Genetic analysis of feed efficiency and novel feeding behavior traits measured in group-housed broilers using electronic feeders

This study aimed to estimate genetic parameters for feeding behavior (FB) traits and to assess their genetic relationship with performance traits in group-housed broilers. In total, 99,472,151 visits were recorded for 95,711 birds between 2017 and 2022 using electronic feeders. The visits were first clustered into 2,667,617 daily observations for ten FB traits: daily feed intake (DFI), daily number of visits (NVIS), time spent at the feeders (TSF), number of visited feeders (NVF), visiting activity interval (VAI), feeding rate (FR), daily number of meals (NMEAL), average intake per meal (INTMEAL), number of visits per meal (VISMEAL) and interval between meals (MEALIVL). All FB traits were then considered as the average per bird across the feeding test period. Three growth traits (body weight at the start - SBW and at the end of the feeding test - FBW, and weight gain over the test period - BWG), and 2 feed efficiency (FE) traits (Feed Conversion Rate - FCR and Residual Feed Intake - RFI) were also recorded. The (co)variance components were estimated using multitrait animal mixed models. For growth and FE, the heritability (h2) estimates were moderate, ranging from 0.20 ± 0.01 (BWG) to 0.32 ± 0.02 (RFI). Overall, the h2 estimates for FB traits were higher than for productive traits, ranging from 0.31 ± 0.01 (DFI) to 0.56 ± 0.02 (TSF). DFI presented high genetic correlations (0.53-0.86) with all performance traits. Conversely, the remaining FB traits presented null to moderate genetic correlations with these traits, ranging from -0.38 to 0.42 for growth traits and between -0.14 and 0.25 for FE traits. Genetic selection for favorable feeding behavior is expected to exhibit a fast genetic response. The results suggest that it is possible to consider different feeding strategies without compromising the genetic progress of FE. Conversely, breeding strategies prioritizing a higher bird activity might result in lighter broiler lines in the long term, given the negative genetic correlations between visit-related traits (NV, NVF, and NMEAL) and growth traits (SBW and FBW).

Common genetic factors for uncontrolled eating mechanisms.

Reward-based eating drives are putative mechanisms of uncontrolled eating implicated in obesity and disordered eating (e.g., binge eating). Uncovering the genetic and environmental contributions to reward-related eating, and their genetic correlation with BMI, could shed light on key mechanisms underlying eating and weight-related disorders. We conducted a classical twin study to examine how much variance in uncontrolled eating phenotypes and body mass index (BMI) was explained by genetic factors, and the extent that these phenotypes shared common genetic factors. 353 monozygotic twins and 128 dizygotic twins completed the Reward-based Eating Drive 13 scale, which measures three distinct uncontrolled eating phenotypes (loss of control over eating, preoccupation with thoughts about food, and lack of satiety), and a demographic questionnaire which included height and weight for BMI calculation. We estimated additive genetic (A), common environmental (C), and unique environmental (E) factors for each phenotype, as well as their genetic correlations, with a multivariate ACE model. A common pathway model also estimated whether genetic variance in the uncontrolled eating phenotypes was better explained by a common latent uncontrolled eating factor. There were moderate genetic correlations between uncontrolled eating phenotypes and BMI (.26-.41). Variance from the uncontrolled eating phenotypes was also best explained by a common latent uncontrolled eating factor that was explained by additive genetic factors (52%). These results suggest that uncontrolled eating phenotypes are heritable traits that also share genetic variance with BMI. This has implications for understanding the cognitive mechanisms that underpin obesity and disordered eating. Our study clarifies the degree to which uncontrolled eating phenotypes and BMI are influenced by shared genetics and shows that vulnerability to uncontrolled eating traits is impacted by common genetic factors.

Animal growth models as a tool to estimate resilience indicators in Bos indicus and Bos taurus heifers: Selection effects and genetics parameters

The aim of the study is to analyze different growth models for the estimation of resilience indicators and to assess the impacts of selection for yearling weight and breed on the resilience capacity of Nelore, Guzerá and Caracu heifers. Weight records of females (n = 38,937) from birth to the measurement of weight adjusted to 550 days of age (W550) were used to fit growth curves. Next, three resilience indicators were calculated based on weight deviations (residuals): natural logarithm of residual variance (LnVar), lag-one autocorrelation (rauto), and skewness of deviations. The means of the resilience indicators were compared between Nelore selection lines (NeC: selected based on the mean of the contemporary groups for W550; NeS: selected based on the highest selection differential for W550; and NeT: selected based on an index considering highest selection differential for W550 and lower residual feed intake) and breeds (Nelore, Guzerá, and Caracu). Additionally, the heritabilities of the resilience indicators were estimated, as well as the genetic correlations between these indicators and productive traits using blupf90+ program. The results indicated that selection for yearling weight had an impact on the resilience capacity of the animals, with NeS and NeT heifers exhibiting greater weight variability (mean LnVar: 6.09 ± 0.02 and 6.12 ± 0.02, respectively) but also the highest recovery rate (rauto: 0.04 ± 0.01 and 0.04 ± 0.01, respectively). Nelore heifers were the most resilient, with a fast recovery rate (rauto: 0.01 ± 0.05) and there was little influence of the environment on performance (skewness: 0.00 ± 0.01). Caracu was the breed most affected by environmental disturbances (LnVar: 6.46 ± 0.02), with inverse subsequent weight deviations (rauto: -0.12 ± 0.05). The heritabilities of the resilience indicators were low and moderate, with the highest estimates being observed for LnVar in the three breeds (0.05 ± 0.05 to 0.38 ± 0.07). LnVar and skewness showed moderate positive genetic correlations with W550 (0.29 ± 0.18 to 0.55 ± 0.12), while the genetic correlations of rauto with W550 were weak and negative (-0.19 ± 0.17 to -0.28 ± 0.20). Selection for yearling weight influenced the resilience capability to environmental challenges in heifers during the growth phase. The results reinforce the greater adaptation capacity of zebuine breeds (Bos indicus) to tropical environments when compared to taurine breeds (Bos taurus). LnVar showed enough genetic variability to be included in breeding programs for zebu breeds aiming selection for more resilient animals.

Genetic background of hematological parameters in Holstein cattle based on genome-wide association and RNA sequencing analyses

Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the Average Information Restricted Maximum Likelihood (AIREML) method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low to moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One-hundred-and-99 significant single nucleotide polymorphisms (SNP) located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle.

Potential for quantifying general environmental resilience of dairy cattle in sub-Saharan Africa using deviations in milk yield.

Introduction: Genetic improvement of general resilience of dairy cattle is deemed as a part of the solution to low dairy productivity and poor cattle adaptability in sub-Saharan Africa (SSA). While indicators of general resilience have been proposed and evaluated in other regions, their applicability in SSA remains unexplored. This study sought to test the viability of utilizing log-transformed variance (LnVar), autocorrelation (rauto), and skewness (Skew) of deviations in milk yield as indicators of general resilience of dairy cows performing in the tropical environment of Kenya. Methods: Test-day milk yield records of 2,670 first-parity cows performing in three distinct agroecological zones of Kenya were used. To predict expected milk yield, quantile regression was used to model lactation curve for each cow. Subsequently, resilience indicators were defined based on actual and standardized deviations of observed milk yield from the expected milk yield. The genetic parameters of these indicators were estimated, and their associations with longevity and average test-day milk yield were examined. Results: All indicators were heritable except skewness of actual and standardized deviation. The log-transformed variance of actual (LnVar1) and standardized (LnVar2) deviations had the highest heritabilities of 0.19 ± 0.04 and 0.17 ± 0.04, respectively. Auto-correlation of actual (rauto1) and standardized (rauto2) deviations had heritabilities of 0.05 ± 0.03 and 0.07 ± 0.03, respectively. Weak to moderate genetic correlations were observed among resilience indicators. Both rauto and Skew indicators had negligible genetic correlations with both longevity and average test-day milk yield. LnVar1 and LnVar2 were genetically associated with better longevity (rg = -0.47 ± 0.26 and -0.49 ± 0.26, respectively). Whereas LnVar1 suggested that resilient animals produce lower average test-day milk yield, LnVar2 revealed a genetic association between resilience and higher average test-day milk yield. Discussion: Log transformed variance of deviations in milk yield holds a significant potential as a robust resilience indicator for dairy animals performing in SSA. Moreover, standardized as opposed to actual deviations should be employed in defining resilience indicators because the resultant indicator does not inaccurately infer that low-producing animals are inherently resilient. This study offers an opportunity for enhancing the productivity of dairy cattle performing in SSA through selective breeding for resilience to environmental stressors.

Laying performance, genetic parameters, and the expression of FSHβ, LHβ, FSHR, and LHR genes in Japanese quails selected for early egg production

Investigating the impact of early egg production selection (the first 90 d of laying) on egg production features, cumulative selection response (CSR), and the mRNA expression of gonadotropins (FSHβ and LHβ), and their receptors (FSHR and LHR), in Japanese quails was the goal. The selection experiment involved 1293 females in all, 257 from the base group and 1036 from the 4 selected generations. Age and body weight at sexual maturity (ASM, BWSM), weight of the first egg (WFE), days to the first 10 eggs (DF10E), egg mass for the first 10 eggs (EMF10E), egg weight (EW), egg number at the first 90 d of laying (EN90D), and egg mass at the first 90 d of laying (EM90D) were all recorded. Most egg production traits had heritability estimates that were low to moderate and ranged from 0.17 to 0.33., where the highest estimates were reported for EN90D (0.33) and BWSM (0.32). With the exception of EN90D, low to moderate positive genetic correlations were observed between ASM and other egg production traits (0.17-0.44). The fourth generation showed significantly (P < 0.05) lower ASM and DF10E but higher BWSM, WFE, EN90D, EM10E, and EM90D when compared with the base generation. CSR were significant (P < 0.05) for ASM (-6.67 d), BWSM (27.13 g), WFE (0.93 g), DF10E (-1.25 d), EN90D (7.24 egg), EM10E (10.57 g), and EM90D (140.0 g). FSHβ, LHβ, FSHR, and LHR gene mRNA expression was considerably (P < 0.05) greater in the fourth generation compared to the base generation. In conclusion, selection programs depending on the efficiency of egg production (EN90D) could improve the genetic gain of egg production traits and upregulate the mRNA expression of FSHβ, LHβ, FSHR, and LHR genes in selected quails (fourth generation). These findings might help to enhance breeding plans and create commercial lines of high egg production Japanese quails.

Polygenic Analyses Show Important Differences Between Major Depressive Disorder Symptoms Measured Using Various Instruments

BackgroundSymptoms of major depressive disorder (MDD) are commonly assessed using self-rating instruments like the Patient Health Questionnaire-9 (PHQ-9) (current symptoms) and the Composite International Diagnostic Interview Short-Form (CIDI-SF) (worst-episode symptoms). We performed a systematic comparison between them for their genetic architecture and utility in investigating MDD heterogeneity. MethodsUsing data from the UK Biobank (n = 41,948–109,417), we assessed the single nucleotide polymorphism heritability and genetic correlation (rg) of both sets of MDD symptoms. We further compared their rg with non-MDD traits and used Mendelian randomization to assess whether either set of symptoms has more genetic sharing with non-MDD traits. We also assessed how specific each set of symptoms is to MDD using the metric polygenic risk score pleiotropy. Finally, we used genomic structural equation modeling to identify factors that explain the genetic covariance between each set of symptoms. ResultsCorresponding symptoms reported through the PHQ-9 and CIDI-SF have low to moderate genetic correlations (rg = 0.43–0.87), and this cannot be fully attributed to different severity thresholds or the use of a skip structure in the CIDI-SF. Both Mendelian randomization and polygenic risk score pleiotropy analyses showed that PHQ-9 symptoms are more associated with traits that reflect general dysphoria, whereas the skip structure in the CIDI-SF allows for the identification of heterogeneity among likely MDD cases. Finally, the 2 sets of symptoms showed different factor structures in genomic structural equation modeling, reflective of their genetic differences. ConclusionsMDD symptoms assessed using the PHQ-9 and CIDI-SF are not interchangeable; the former better indexes general dysphoria, while the latter is more informative about within-MDD heterogeneity.

Micro-genetic environmental sensitivity across macro-environments of chickens reared in Burkina Faso and France

BackgroundCommercial poultry production systems follow a pyramidal structure with a nucleus of purebred animals under controlled conditions at the top and crossbred animals under commercial production conditions at the bottom. Genetic correlations between the same phenotypes on nucleus and production animals can therefore be influenced by differences both in purebred-crossbred genotypes and in genotype-by-environment interactions across the two environments, known as macro-genetic environmental sensitivity (GES). Within each environment, genotype-by-environment interactions can also occur due to so-called micro-GES. Micro-GES causes heritable variation in phenotypes and decreases uniformity. In this study, genetic variances of body weight (BW) and of micro-GES of BW and the impacts of purebred-crossbred differences and macro-environmental differences on micro-GES of BW were estimated. The dataset contained three subpopulations of slow-growing broiler chickens: purebred chickens (PB) reared in France, and crossbred chickens reared in France (FR) under the same conditions as PB or reared in Burkina Faso (BF) under local conditions. The crossbred chickens were offspring of the same dam line and had PB as their sire line.ResultsEstimates of heritability of BW and micro-GES of BW were 0.54 (SE of 0.02) and 0.06 (0.01), 0.67 (0.03) and 0.03 (0.01), and 0.68 (0.04) and 0.02 (0.01) for the BF, FR, and PB subpopulations, respectively. Estimates of the genetic correlations for BW between the three subpopulations were moderately positive (0.37 to 0.53) and those for micro-GES were weakly to moderately positive (0.01 to 0.44).ConclusionsThe results show that the heritability of the micro-GES of BW varies with macro-environment, which indicates that responses to selection are expected to differ between macro-environments. The weak to moderate positive genetic correlations between subpopulations indicate that both macro-environmental differences and purebred-crossbred differences can cause re-ranking of sires based on their estimated breeding values for micro-GES of BW. Thus, the sire that produces the most variable progeny in one macro-environment may not be the one that produces the most variable offspring in another. Similarly, the sire that produces the most variable purebred progeny may not produce the most variable crossbred progeny. The results highlight the need for investigating micro-GES for all subpopulations included in the selection scheme, to ensure optimal genetic gain in all subpopulations.

PSVII-9 Heterosis Effects on Reproductive Traits in a Multibreed Beef Cattle Herd in Panama

Abstract The aim of this study was to estimate the influence of heterosis and breed percentage on calving interval (CI) and gestation length (GL), and the correlation between age at first calving (AFC) and CI, in beef cows. Data included 1,291 repeated observations of CI and GL from 502 cows with 2,840 individuals in the pedigree, including 3 generations from the multi-breed herd of the livestock experimental station of the Panama Agricultural Innovation Institute (IDIAP) in Gualaca, Panama. The herd was composed of the following genetic groups based on their breed percentage: tropically adapted Brahman (BR), Nellore (Ne), Undefined Bos indicus (BI), Guaymi Creole (CR), Senepol (SP) and Romosinuano (RS); Bos taurus (BT), Simmental (SM), Angus (A), Red Angus (AR), Limousin (LM), Charolais (CH), Wagyu (Wa), and Others (Oth); crossbreeds (cx), Beefmaster (BF), Three CX (F1 x different BT), R1(Backcross BR), R2 (Backcross BT), Composite (combination of at least 4 different breeds with less than 25% of Zebu), Upgrade (87.5% BR 12.5% BT), B1 (62.5% Zebu + 37.5% BT), and B2 (62.5% BT + 37.5% Zebu). The Zebu influenced breed group represents 50.03% of this population, followed by the F1, the three CX, composites, and R1, representing 22%, 13.89%, 6.11%, and 5.34%, respectively. The other breed groups represented less than 2.5% of the population. A repeated records animal model was used to estimate variance components for both CI and GL. A bivariate animal model was used to estimate the genetic correlation between CI and age at first calving (AFC). Fixed effects for all models consisted of contemporary group, age of dam, calf sex, degree of outcross, and breed percentage. Contemporary group was defined by calving year and season of birth. The average CI was 572.6 ± 140 d, with a range of 315 d to 910 d; and the average GL was 284.2 ± 6.3 d. The estimated regression coefficient for CI on heterosis was -0.114 ± 0.10 d/heterosis % (P = 0.266), and for GL was -0.01 ± 0.052 d/heterosis %. A shorter CI was observed for the F1, and three CX, with 558.7 days and 567.2 days, representing a 2.3% and 1.3% reduction in CI, respectively, when compared with the Zebu group. A larger CI was observed for the Nellore and Romosinuano breeds % with 0.17 ± 1.23 d, (P = 0.373) and 0.64± 0.13 d (P = 0.406), respectively. A low heritability (0.037 ± 0.026) for CI was estimated, with a positive genetic trend over the duration of the study. The analysis between CI and AFC revealed a moderate genetic correlation (0.49 ± 0.36) that allows the establishment of a selection program to improve AFC and CI, which would improve the fertility of this multi-breed herd in Panama.

Genetic parameters for calf feeding traits derived from automated milk feeding machines and number of bovine respiratory disease treatments in North American Holstein calves

Precision livestock farming technologies, such as automatic milk feeding machines, have increased the availability of on-farm data collected from dairy operations. We analyzed feeding records from automatic milk feeding machines to evaluate the genetic background of milk feeding traits and bovine respiratory disease (BRD) in North American Holstein calves. Data from 10,076 preweaning female Holstein calves were collected daily over a period of 6 yr (3 yr included per-visit data), and daily milk consumption (DMC), per-visit milk consumption (PVMC), daily sum of drinking duration (DSDD), drinking duration per-visit, daily number of rewarded visits (DNRV), and total number of visits per day were recorded over a 60-d preweaning period. Additional traits were derived from these variables, including total consumption and duration variance (TCV and TDV), feeding interval, drinking speed (DS), and preweaning stayability. A single BRD-related trait was evaluated, which was the number of times a calf was treated for BRD (NTT). The NTT was determined by counting the number of BRD incidences before 60 d of age. All traits were analyzed using single-step genomic BLUP mixed-model equations and fitting either repeatability or random regression models in the BLUPF90+ suite of programs. A total of 10,076 calves with phenotypic records and genotypic information for 57,019 SNP after the quality control were included in the analyses. Feeding traits had low heritability estimates based on repeatability models (0.006 ± 0.0009 to 0.08 ± 0.004). However, total variance traits using an animal model had greater heritabilities of 0.21 ± 0.023 and 0.23 ± 0.024, for TCV and TDV, respectively. The heritability estimates increased with the repeatability model when using only the first 32 d preweaning (e.g., PVMC = 0.040 ± 0.003, DMC = 0.090 ± 0.009, DSDD = 0.100 ± 0.005, DS = 0.150 ± 0.007, DNRV = 0.020 ± 0.002). When fitting random regression models (RRM) using the full dataset (60-d period), greater heritability estimates were obtained (e.g., PVMC = 0.070 [range: 0.020, 0.110], DMC = 0.460 [range: 0.050, 0.680], DSDD = 0.180 [range: 0.010, 0.340], DS = 0.19 [range: 0.070, 0.430], DNRV = 0.120 [range: 0.030, 0.450]) for the majority of the traits, suggesting that RRM capture more genetic variability than the repeatability model with better fit being found for RRM. Moderate negative genetic correlations of -0.59 between DMC and NTT were observed, suggesting that automatic milk feeding machines records have the potential to be used for genetically improving disease resilience in Holstein calves. The results from this study provide key insights of the genetic background of early in-life traits in dairy cattle, which can be used for selecting animals with improved health outcomes and performance.

Familial co-aggregation and shared genetics of cardiometabolic disorders and traits: data from the multi-generational Lifelines Cohort Study

BackgroundIt is unclear to what extent genetics explain the familial clustering and the co-occurrence of distinct cardiometabolic disorders in the general population. We therefore aimed to quantify the familial (co-)aggregation of various cardiometabolic disorders and to estimate the heritability of cardiometabolic traits and their genetic correlations using the large, multi-generational Lifelines Cohort Study.MethodsWe used baseline data of 162,416 participants from Lifelines. Cardiometabolic disorders including type 2 diabetes (T2D), cardiovascular diseases, hypertension, obesity, hypercholesterolemia, and metabolic syndrome (MetS), were defined in adult participants. Fifteen additional cardiometabolic traits indexing obesity, blood pressure, inflammation, glucose regulation, and lipid levels were measured in all included participants. Recurrence risk ratios (λR) for first-degree relatives (FDR) indexed familial (co-)aggregation of cardiometabolic disorders using modified conditional Cox proportional hazards models and were compared to those of spouses. Heritability (h2), shared environment, and genetic correlation (rg) were estimated using restricted maximum likelihood variance decomposition methods, adjusted for age, age2, and sex.ResultsIndividuals with a first-degree relative with a cardiometabolic disorder had a higher risk of the same disorder, ranging from λFDR of 1.23 (95% CI 1.20–1.25) for hypertension to λFDR of 2.48 (95% CI 2.15–2.86) for T2D. Most of these were higher than in spouses (λSpouses < λFDR), except for obesity which was slightly higher in spouses. We found moderate heritability for cardiometabolic traits (from h2CRP: 0.26 to h2HDL: 0.50). Cardiometabolic disorders showed positive familial co-aggregation, particularly between T2D, MetS, and obesity (from λFDR obesity-MetS: 1.28 (95% CI 1.24–1.32) to λFDR MetS-T2D: 1.61 (95% CI 1.52–1.70)), consistent with the genetic correlations between continuous intermediate traits (ranging from rg HDL-Triglycerides: − 0.53 to rg LDL-Apolipoprotein B: 0.94).ConclusionsThere is positive familial (co-)aggregation of cardiometabolic disorder, moderate heritability of intermediate traits, and moderate genetic correlations between traits. These results indicate that shared genetics and common genetic architecture contribute to cardiometabolic disease.

Genetic parameters for health traits and their association with fertility and milk production in Chinese Holsteins.

Herd health is one of the key problems influencing the efficiency of the dairy industry. Genetic selection, with a focus on animal health, is important for herd improvement. This study aimed to estimate genetic parameters for health traits and their correlations with fertility and milk production traits in dairy cattle. Based on records from 58,549 lactating cows calved between 2015 and 2021, a total of 24 health traits (six composite health traits and 18 independent health traits), four fertility traits and five milk production traits were analysed. First, linear and threshold animal models were used to estimate the variance components and heritabilities of the health traits. Second, a bivariate linear animal model was used to estimate genetic correlations among all 24 health traits. Finally, a bivariate linear animal model based on records from the first lactation was used to estimate the correlations between health traits and fertility or milk production traits. The results showed that all health traits had low heritabilities, ranging from 0.002 (0.001) to 0.048 (0.004) in the linear model and from <0.001 (0.021) to 0.226 (0.035) in the threshold model. Genetic correlations between health traits across categories were generally low, whereas the relatively high genetic correlations were found between health traits within the same category. In this study, only a few significant and moderate genetic correlations were observed between health traits and fertility or milk production traits. Clinical mastitis showed relatively moderate correlations with fertility traits, ranging from 0.277 (0.113) (interval from first to last insemination) to 0.401 (0.104) (calving interval). Moreover, there were moderate genetic correlations between hoof health and milk production traits. The results from the current study will support balanced dairy breeding to genetically improve disease resistance in dairy cows.