Random regression models to account for the effect of genotype by environment interaction due to heat stress on the milk yield of Holstein cows under tropical conditions

Reaction norm for genomic prediction of plant growth: modeling drought stress response in soybean

KEY MESSAGE

We proposed models to predict the effects of genomic and environmental factors on daily soybean growth and applied them to soybean growth data obtained with unmanned aerial vehicles. Advances in high-throughput phenotyping technology have made it possible to obtain time-series plant growth data in field trials, enabling genotype-by-environment interaction (G × E) modeling of plant growth. Although the reaction norm is an effective method for quantitatively evaluating G × E and has been implemented in genomic prediction models, no reaction norm models have been applied to plant growth data. Here, we propose a novel reaction norm model for plant growth using spline and random forest models, in which daily growth is explained by environmental factors one day prior. The proposed model was applied to soybean canopy area and height to evaluate the influence of drought stress levels. Changes in the canopy area and height of 198 cultivars were measured by remote sensing using unmanned aerial vehicles. Multiple drought stress levels were set as treatments, and their time-series soil moisture was measured. The models were evaluated using three cross-validation schemes. Although accuracy of the proposed models did not surpass that of single-trait genomic prediction, the results suggest that our model can capture G × E, especially the latter growth period for the random forest model. Also, significant variations in the G × E of the canopy height during the early growth period were visualized using the spline model. This result indicates the effectiveness of the proposed models on plant growth data and the possibility of revealing G × E in various growth stages in plant breeding by applying statistical or machine learning models to time-series phenotype data.

Effect of transgenerational environmental condition on genetics parameters of Italian Brown Swiss

The aim of this study was to infer the effects of heat stress (HS) of dams during late gestation on direct and maternal genetic parameters for traits related to milk production and milk quality parameters (90,558 records) in Italian Brown Swiss cattle (12,072 cows in 617 herds). Daily average temperature-humidity indices (THI) during the last 56 d of pregnancy were calculated, using the climate data from the nearest public weather station for each herd. Heat load effects were considered as the average across the entire periods considering a thermoneutrality condition for data below the THI 60. For parameter estimation a random regression model using the second-order Legendre polynomial regression coefficient for THI considering both animal and maternal effect for heat load. Direct heritability increased sharply from THI 60 to 65, then decreased gradually up to THI ∼72, and sharply thereafter. Maternal heritability showed a different trend, with values close to 0 up until to THI 65 and slightly increasing toward extreme THI values. The study suggests a lower threshold of THI 60 for the onset of HS. Higher heritability values indicate greater selective efficiency in the THI range of 65 to 70, even if a higher standard deviation value have been detected. The effects of high THI during intrauterine life varied among traits with different heritability levels. Genetic correlations for milk, fat, and protein content at 60 THI with increasing value of environmental variable, remained constant (∼0.90) until THI >75, where they slightly decreased (∼0.85). Fat and protein yields, as well as milk and energy-corrected milk, showed correlations dropping to 0.80 around THI 67 to 68 and stabilizing between 0.75 and 0.85 at extreme THI values. Maternal component correlations dropped close to zero, with negative values for protein content at THI 65 to 70. Antagonism between direct and maternal components was stronger for intermediate THI values but less divergent for extremes. Genotype by environment interaction was observed, indicating the selection of resilient animals would be theoretically possible. In the future, the application of climate variables in selection schemes first should take into account the dimensions of the genetic correlations to be able to decide between the simple inclusion of the environmental effect in the statistical models, rather than a real parallel genetic evaluation.

Candidate genes associated with heat stress and breeding strategies to relieve its effects in dairy cattle: a deeper insight into the genetic architecture and immune response to heat stress

The need for food products of animal origin is increasing worldwide. Satisfying these needs in a way that has minimal impact on the environment requires cutting-edge technologies and techniques to enhance the genetic quality of cattle. Heat stress (HS), in particular, is affecting dairy cattle with increasing frequency and severity. As future climatic challenges become more evident, identifying dairy cows that are more tolerant to HS will be important for breeding dairy herds that are better adapted to future environmental conditions and for supporting the sustainability of dairy farming. While research into the genetics of HS in the context of the effect of global warming on dairy cattle is gaining momentum, the specific genomic regions involved in heat tolerance are still not well documented. Advances in omics information, QTL mapping, transcriptome profiling and genome-wide association studies (GWAS) have identified genomic regions and variants associated with tolerance to HS. Such studies could provide deeper insights into the genetic basis for response to HS and make an important contribution to future breeding for heat tolerance, which will help to offset the adverse effects of HS in dairy cattle. Overall, there is a great interest in identifying candidate genes and the proportion of genetic variation associated with heat tolerance in dairy cattle, and this area of research is currently very active worldwide. This review provides comprehensive information pertaining to some of the notable recent studies on the genetic architecture of HS in dairy cattle, with particular emphasis on the identified candidate genes associated with heat tolerance in dairy cattle. Since effective breeding programs require optimal knowledge of the impaired immunity and associated health complications caused by HS, the underlying mechanisms by which HS modulates the immune response and renders animals susceptible to various health disorders are explained. In addition, future breeding strategies to relieve HS in dairy cattle and improve their welfare while maintaining milk production are discussed.

Impact of Heat Stress on Blood, Production, and Physiological Indicators in Heat-Tolerant and Heat-Sensitive Dairy Cows

Heat stress affects production and health in cows severely. Since it is difficult to define heat-tolerant animals, studies of response to heat stress are important for understanding dairy cows' health and production. However, information on the impact of heat stress on various indicators in heat-tolerant and heat-sensitive cows is sparse. This study aimed to investigate the effects of heat stress (HS) on blood, production, and physiological indicators in heat-tolerant and heat-sensitive cows. A total of 43 dairy cows were used from 9 May to 7 August 2021, under Temperature-Humidity Index (THI) measurements that ranged from 65.9 to 86.7. We identified cows that were tolerant or sensitive to HS based on the slope of the response of physiological and production traits against THI during the HS period by using a clustering method. After HS, serum glucose (Glu), cortisol (COR), 5-hydroxytryptamine (5-HT), and interleukin-6 (IL-6) levels of cows in the heat-tolerant group were lower than in the heat-sensitive group (p < 0.05). With THI as the predictor, the R2 for predicting respiration rate (RR) and body surface temperature (BT) in heat-tolerant cows was 0.15 and 0.16, respectively, whereas the R2 for predicting RR and BT in heat-sensitive cows was 0.19 and 0.18, respectively. There were low to moderate, positive correlations between RR, BT, and MY with THI, with Pearson correlation coefficients ranging from r = 0.11 to 0.4 in the heat-tolerant group, and from r = 0.24 to 0.43 in the heat-sensitive group. There was a low positive correlation between VT and THI, with a Spearman correlation coefficient of r = 0.07 in the heat-sensitive group. The heat-tolerant dairy cows had lower MY losses and had lower MY (p = 0.0007) in mixed models. Heat-tolerant cows with low-stress levels, through upregulating RR rapidly, increased their adaptability to thermal environments. They have better thermoregulation capability; the hypothalamic-pituitary-adrenal (HPA) axis regulated the thermoregulatory in animals by releasing a variety of neurotransmitters and hormones.

Heat stress effects on milk yield traits and metabolites and mitigation strategies for dairy cattle breeds reared in tropical and sub-tropical countries

Heat stress is an important problem for dairy industry in many parts of the world owing to its adverse effects on productivity and profitability. Heat stress in dairy cattle is caused by an increase in core body temperature, which affects the fat production in the mammary gland. It reduces milk yield, dry matter intake, and alters the milk composition, such as fat, protein, lactose, and solids-not-fats percentages among others. Understanding the biological mechanisms of climatic adaptation, identifying and exploring signatures of selection, genomic diversity and identification of candidate genes for heat tolerance within indicine and taurine dairy breeds is an important progression toward breeding better dairy cattle adapted to changing climatic conditions of the tropics. Identifying breeds that are heat tolerant and their use in genetic improvement programs is crucial for improving dairy cattle productivity and profitability in the tropics. Genetic improvement for heat tolerance requires availability of genetic parameters, but these genetic parameters are currently missing in many tropical countries. In this article, we reviewed the HS effects on dairy cattle with regard to (1) physiological parameters; (2) milk yield and composition traits; and (3) milk and blood metabolites for dairy cattle reared in tropical countries. In addition, mitigation strategies such as physical modification of environment, nutritional, and genetic development of heat tolerant dairy cattle to prevent the adverse effects of HS on dairy cattle are discussed. In tropical climates, a more and cost-effective strategy to overcome HS effects is to genetically select more adaptable and heat tolerant breeds, use of crossbred animals for milk production, i.e., crosses between indicine breeds such as Gir, white fulani, N'Dama, Sahiwal or Boran to taurine breeds such as Holstein-Friesian, Jersey or Brown Swiss. The results of this review will contribute to policy formulations with regard to strategies for mitigating the effects of HS on dairy cattle in tropical countries.

NASA POWER satellite meteorological system is a good tool for obtaining estimates of the temperature-humidity index under Brazilian conditions compared to INMET weather stations data

Heat stress negatively affects livestock, with undesirable effects on animals' production and reproduction. Temperature and humidity index (THI) is a climatic variable used worldwide to study the effect of heat stress on farm animals. Temperature and humidity data can be obtained in Brazil through the National Institute of Meteorology (INMET), but complete data may not be available due to temporary failures on weather stations. An alternative to obtaining meteorological data is the National Aeronautics and Space Administration Prediction of Worldwide Energy Resources (NASA POWER) satellite-based weather system. We aimed to compare THI estimates obtained from INMET weather stations and NASA POWER meteorological information sources using Pearson correlation and linear regression. After quality check, data from 489 INMET weather stations were used. The hourly, average daily and maximum daily THI were evaluated. We found greater correlations and better regression evaluation metrics when average daily THI values were considered, followed by maximum daily THI, and hourly THI. NASA POWER satellite-based weather system is a suitable tool for obtaining the average and maximum THI values using information collected from Brazil, showing high correlations with THI estimates from INMET and good regression evaluation metrics, and can assist studies that aim to analyze the impact of heat stress on livestock production in Brazil, providing additional data to complement the existing information available in the INMET database.

Genotype by environment interaction due to heat stress in Brown Swiss cattle

Due to its geographical position and a highly variable orography, Italy is characterized by several climatic areas and thus, by many different dairy cow farming systems. Brown Swiss cattle, in this context, are a very appreciated genetic resource for their adaptability and low metabolic requirement. The significant heterogeneity in farming systems may consist of genotype by environment (G × E) interactions with neglected changes in animals' rank position. The objective of this study was to investigate G × E for heat tolerance in Brown Swiss cattle for several production traits (milk, fat, and protein yield in kilograms; fat, protein, and cheese yield in percentage) and 2 derivate traits (fat-corrected milk and energy-corrected milk). We used the daily maximum temperature-humidity index (THI) range, calculated according to weather stations' data from 2008 to 2018 in Italy, and 202,776 test-day records from 23,396 Brown Swiss cows from 639 herds. Two different methodologies were applied to estimate the effect of the environmental variable (THI) on genetic parameters: (1) the reaction norm model, which uses a continuous random covariate to estimate the animal additive effect, and (2) the multitrait model, which splits each production pattern as a distinct and correlated trait according to the first (a thermal comfort condition), third (a moderate heat stress condition), and fifth (a severe heat stress condition) mean THI value quintile. The results from the reaction norm model showed a descending trend of the additive genetic effect until THI reached the value of 80. Then we recorded an increase with high extreme THI values (THI 90). Permanent environmental variance at increasing THI values revealed an opposite trend: The plot of heritability and the ratio of animal permanent environmental variance to phenotypic variance showed that when the environmental condition worsens, the additive genetic and permanent environmental component for production traits play a growing role. The negative additive genetic correlation between slope and linear random coefficient indicates no linear relationship between the production traits or under heat stress conditions, except for milk yield and protein yield. In tridimensional wireframe plots, the extreme margin decreases until a minimum of ∼0.90 of genetic correlation in the ECM trait, showing that the magnitude of G × E interaction is greater than the other traits. Genetic correlation values in Brown Swiss suggest the possibility of moderate changes in animals' estimated breeding value in heat stress conditions. Results indicated a moderate G × E interaction but significant variability in sire response related to their production level.

Comparison of Marker Effects and Breeding Values at Two Levels at THI for Milk Yield and Quality Traits in Brazilian Holstein Cows

Genomic tools can help in the selection of animals genetically resistant to heat stress, especially the genome-wide association studies (GWAS). The objective of this study was to compare the variance explained by SNPs and direct genomic breeding values (DGVs) at two levels of a temperature and humidity index (THI). Records of milk yield (MY), somatic cell score (SCS), and percentages of casein (CAS), saturated fatty acids (SFA), and unsaturated fatty acids (UFA) in milk from 1157 Holstein cows were used. Traditional breeding values (EBV) were determined in a previous study and used as pseudo-phenotypes. Two levels of THI (heat comfort zone and heat stress zone) were used as environments and were treated as "traits" in a bi-trait model. The GWAS was performed using the genomic best linear unbiased prediction (GBLUP) method. Considering the top 50 SNPs, a total of 36 SNPs were not common between environments, eight of which were located in gene regions related to the evaluated traits. Even for those SNPs that had differences in their explained variances between the two environments, the differences were very small. The animals showed virtually no rank order, with rank correlation values of 0.90, 0.88, 1.00, 0.88, and 0.97 for MY, CAS, SCS, SFA, and UFA, respectively. The small difference between the environments studied can be attributed to the small difference in the pseudo-phenotypes used between the environments, on-farm acclimation, the polygenic nature of the traits, and the THI values studied near the threshold between comfort and heat stress. It is recommended that future studies be conducted with a larger number of animals and at more extreme THI levels.

Estimation of Genetic Parameters of Heat Tolerance for Production Traits in Canadian Holsteins Cattle

Understanding how cows respond to heat stress has helped to provide effective herd management practices to tackle this environmental challenge. The possibility of selecting animals that are genetically more heat tolerant may provide additional means to maintain or even improve the productivity of the Canadian dairy industry, which is facing a shifting environment due to climate changes. The objective of this study was to estimate the genetic parameters for heat tolerance of milk, fat, and protein yields in Canadian Holstein cows. A total of 1.3 million test-day records from 195,448 first-parity cows were available. A repeatability test-day model fitting a reaction norm on the temperature-humidity index (THI) was used to estimate the genetic parameters. The estimated genetic correlations between additive genetic effect for production and for heat tolerance ranged from -0.13 to -0.21, indicating an antagonistic relationship between the level of production and heat tolerance. Heritability increased marginally as THI increased above its threshold for milk yield (0.20 to 0.23) and protein yield (0.14 to 0.16) and remained constant for fat yield (0.17). A Spearman rank correlation between the estimated breeding values under thermal comfort and under heat stress showed a potential genotype by environmental interaction. The existence of a genetic variability for heat tolerance allows for the selection of more heat tolerant cows.

Changes in the pattern of heat waves and the impacts on Holstein cows in a subtropical region

This study aimed to evaluate the change in the air temperature and the impacts of heat waves using Climate Change Indexes on the physiological and productive responses of lactating Holstein cows. Daily data of maximum and minimum air temperature for 1981-2021 were used. Heat waves were determined using six Climate Change Indexes. Individual data on respiratory rate, rectal temperature, and milk yield were collected in the summers of 2018, 2019, and 2021. The temperature trend analysis showed a significant (p < 0.0001) increase in maximum temperature, minimum temperature, and days in a heat wave. All six indexes increased significantly (p > 0.01). The increase in warm nights (> 20 °C) and the hottest days (> 35 °C) was the highest since 2010. Heat waves were classified into short (< 5 days) and long (> 5 days) of greater (> 36 °C) or lesser (< 36 °C) intensity. During the long and short heat waves of greater intensity, the respiratory rate increased (p < 0.05) until the fourth day. On the other hand, rectal temperature was higher (p < 0.05) from the fourth day until the end of the long heat waves. Therefore, the decrease in milk yield was significantly greater from the fourth or fifth day onwards. Finally, the evaluation method based on indexes was efficient to demonstrate the negative effects on physiological parameters and milk yield and can be indicated to evaluate heat stress in lactating cows.

Heteroscedastic Reaction Norm Models Improve the Assessment of Genotype by Environment Interaction for Growth, Reproductive, and Visual Score Traits in Nellore Cattle

The assessment of the presence of genotype by environment interaction (GxE) in beef cattle is very important in tropical countries with diverse climatic conditions and production systems. The present study aimed to assess the presence of GxE by using different reaction norm models for eleven traits related to growth, reproduction, and visual score in Nellore cattle. We studied five reaction norm models (RNM), fitting a linear model considering homoscedastic residual variance (RNM_homo), and four models considering heteroskedasticity, being linear (RNM_hete), quadratic (RNM_quad), linear spline (RNM_l-l), and quadratic spline (RNM_q-q). There was the presence of GxE for age at first calving (AFC), scrotal circumference (SC), weaning to yearling weight gain (WYG), and yearling weight (YW). The best models were RNM_l-l for YW and RNM_q-q for AFC, SC, and WYG. The heritability estimates for RNM_l-l ranged from 0.07 to 0.20, 0.42 to 0.61, 0.24 to 0.42, and 0.47 to 0.63 for AFC, SC, WYG, and YW, respectively. The heteroskedasticity in reaction norm models improves the assessment of the presence of GxE for YW, WYG, AFC, and SC. Additionally, the trajectories of reaction norms for these traits seem to be affected by a non-linear component, and selecting robust animals for these traits is an alternative to increase production and reduce environmental sensitivity.

Genetics of tolerance to heat stress in milk yield of dairy buffaloes assessed by a reaction norm model

The objectives of this study were to assess the effects of heat stress on the milk yield and investigate the presence of genotype × environment interaction (G × E) in Brazilian Murrah buffaloes reared under tropical conditions. With this, 58,070 test-day (TD) records for milk yield from 3,459 first lactations of buffaloes collected between 1987 and 2018 were evaluated. A mixed model considering days in milk (DIM) and temperature-humidity index (THI) was applied to quantify milk yield losses due to heat stress. The most detrimental effect of THI on TD milk yield was observed in the mid-stages of lactation, after lactation peak, in DIM 105-154 and 155-204 days (-0.020 and -0.015 kg/day per THI, respectively). The least-squares means of TD milk yield were used to identify a heat stress threshold using a piecewise linear regression model. A substantial reduction in TD milk yield due to heat stress was observed for THI values above 77.8 (-0.251 kg/day per increase of 1 THI unit). An analysis using a single-trait random regression animal model was carried out to estimate variance components and genetic parameters for TD milk yield over THI and DIM values. Increased additive genetic variance and heritability estimates were observed for extreme THI values (THI = 60 and 80) combined with mid-lactation stages. The lowest genetic correlation (0.50) was observed between TD records at opposite extremes of the THI scale (THI = 60 vs. THI = 80). The genetic trends observed for the regression coefficients related to the general level of production (0.02) and specific ability to respond to heat stress (-0.002) indicated that selection to increase milk yield did not affect the specific ability to respond to heat stress until the present moment. These trends reflect the low genetic correlation between these components (0.05 ± 0.14). In this sense, monitoring trends of genetic components related to response to heat stress is recommended.

Genotype by climate zone interactions for fertility, somatic cell score, and production in Iranian Holsteins

The objective of this study was to investigate genetic variation and genotype by environment (G × E) interactions for fertility (including age at first calving and calving interval), somatic cell score (SCS), and milk production traits for Iranian Holsteins. Different environments were defined based on the climatic zones (cold, semi-cold, and moderate) and considering the herd location. Data were collected between 2003 and 2018 by the National Animal Breeding Center of Iran (Karaj). Variance and covariance components and genetic correlations were estimated using 2 different models, which were analyzed using Bayesian methods. For both models, performance of traits in each climate were considered as different traits. Fertility traits were analyzed using a trivariate model. Furthermore, SCS and production traits were analyzed using trivariate random regression models (records in different climate zones considered as different traits). For the fertility traits, the largest estimates of heritability were observed in cold climate. Fertility performance was always better in cold environment. Genetic correlations between climatic zones ranged from 0.85 to 0.94. For daily measurements of SCS and production traits, heritability ranged from 0.031 to 0.037 and 0.069 to 0.209, respectively. Genetic variances were the highest in the semi-cold and moderate climates for the SCS and production traits, respectively. Furthermore, across the studied climates, 305-d genetic correlation ranged from 0.756 to 0.884 for SCS and from 0.925 to 0.957 for the production traits. The structure of genetic correlation within each climate indicated a negative correlation between early and late lactation for SCS, especially in the cold climate and for milk production in the moderate climate. For fat percentage, in all climatic zones, the lowest genetic correlations were observed between early and mid-lactation. In addition, for protein production in the cold climate, a negative correlation was observed between early and late lactation. Results indicated heterogeneous variance components for all the studied traits across various climatic zones. Estimated genetic correlations for SCS revealed that the genetic expression of animals may vary by climatic zone. Results indicated the existence of G × E interaction due to the climatic condition, only for SCS. Therefore, in Iranian Holsteins, the effect of G × E interactions should not be neglected, especially for SCS, as different sires might be optimal for use in different climatic zones.

Genetic parameters for milk yield and quality traits of Brazilian Holstein cows as a function of temperature and humidity index

Measurements of milk yield (MY), somatic cell score (SCS), percentage of fat (FP), protein (PP), lactose (LP), casein (CP) and percentage of palmitic (C16:0), stearic (C18:0), oleic (C18:1), total saturated (SFA), unsaturated (UFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids in milk from 5,224 Holstein cows were evaluated as a function of a temperature and humidity index (THI). Legendre orthogonal polynomials from second to seventh order were tested. The best fit order for MY, PP and C18:0 was the third, whereas the second for all other traits. The heritability estimates decreased for MY (0.31 to 0.14), FP (0.28 to 0.16), LP (0.43 to 0.30), SCS (0.14 to 0.09), SFA (0.33 to 0.22) and C16:0 (0.31 to 0.26), whereas increased for CP (0.32 to 0.42), MUFA (0.08 to 0.13), UFA (0.07 to 0.11) and C18:1 (0.07 to 0.11) as the THI level increased. For PP, heritabilities (0.26 to 0.39) presented larger values in intermediate THI. For PUFA and C18:0, heritabilities were approximately constant (0.13 to 0.14 and 0.15, respectively). However, the greatest variations may have been the result of the limitations of Legendre polynomials at the extreme points of the curve, and the pattern of heritabilities curves was approximately constant for the evaluated traits. Spearman's rank correlations between breeding values in extreme THI levels were greater than 0.80 for all traits considering all animals, only cows and only bulls. When considering the top 1% and the top 50% animals (only cows, only bulls and all), Spearman correlations smaller than 0.70 were found, suggesting reranking of the animals. Although there was little variation in the variance components over THI, it is possible that there is no heat stress in the animals studied, because, on average, there was no great impact of the thermal load on the traits. One possible explanation is the use of herds with little climatic difference among herds, as well as the use of fans and sprinklers into the barns. However, the THI levels may be important factors in the selection process, as reranking of animals was verified.

Genotype by heat stress interactions for production and functional traits in dairy cows from an across-generation perspective

The aim of this study was to analyze time-lagged heat stress (HS) effects during late gestation on genetic co(variance) components in dairy cattle across generations for production, female fertility, and health traits. The data set for production and female fertility traits considered 162,492 Holstein Friesian cows from calving years 2003 to 2012, kept in medium-sized family farms. The health data set included 69,986 cows from calving years 2008 to 2016, kept in participating large-scale co-operator herds. Production traits were milk yield (MKG), fat percentage (fat%), and somatic cell score (SCS) from the first official test-day in first lactation. Female fertility traits were the nonreturn rate after 56 d (NRR56) in heifers and the interval from calving to first insemination (ICFI) in first-parity cows. Health traits included clinical mastitis (MAST), digital dermatitis (DD), and endometritis (EM) in the early lactation period in first-parity cows. Meteorological data included temperature and humidity from public weather stations in closest herd distance. The HS indicator was the temperature-humidity index (THI) during dams' late gestation, also defined as in utero HS. For the genetic analyses of production, female fertility, and health traits in the offspring generation, a sire-maternal grandsire random regression model with Legendre polynomials of order 3 for the production and of order 2 for the fertility and health traits on prenatal THI, was applied. All statistical models additionally considered a random maternal effect. THI from late gestation (i.e., prenatal climate conditions), influenced genetic parameter estimates in the offspring generation. For MKG, heritabilities and additive genetic variances decreased in a wave-like pattern with increasing THI. Especially for THI >58, the decrease was very obvious with a minimal heritability of 0.08. For fat% and SCS, heritabilities increased slightly subjected to prenatal HS conditions at THI >67. The ICFI heritabilities differed marginally across THI [heritability (h²) = 0.02-0.04]. For NRR56, MAST, and DD, curves for heritabilities and genetic variances were U-shaped, with largest estimates at the extreme ends of the THI scale. For EM, heritability increased from THI 25 (h² = 0.13) to THI 71 (h² = 0.39). The trait-specific alterations of genetic parameters along the THI gradient indicate pronounced genetic differentiation due to intrauterine HS for NRR56, MAST, DD, and EM, but decreasing genetic variation for MKG and ICFI. Genetic correlations smaller than 0.80 for NRR56, MAST, DD, and EM between THI 65 with corresponding traits at remaining THI indicated genotype by environment interactions. The lowest genetic correlations were identified when considering the most distant THI. For MKG, fat%, SCS, and ICFI, genetic correlations throughout were larger than 0.80, disproving concerns for any genotype by environment interactions. Variations in genetic (co)variance components across prenatal THI may be due to epigenetic modifications in the offspring genome, triggered by in utero HS. Epigenetic modifications have a persistent effect on phenotypic responses, even for traits recorded late in life. However, it is imperative to infer the underlying epigenetic mechanisms in ongoing molecular experiments.

Heat stress during late pregnancy and postpartum influences genetic parameter estimates for birth weight and weight gain in dual-purpose cattle offspring generations

Impact of direct heat stress (HS) on genetic parameter estimates, i.e., HS close to the trait recording date, was verified in several previous studies conducted in dairy and beef cattle populations. The aim of the present study was to analyze the impact of time-lagged HS at different recording periods during late pregnancy (a.p.) and postpartum (p.p.) on genetic parameter estimates for birth weight (BWT) and weight gain traits (200 d- and 365 d-weight gain (200dg, 365dg)) in offspring of the dual-purpose cattle breed "Rotes Höhenvieh" (RHV). Furthermore, we estimated genetic correlations within traits across time-lagged climatic indicators, in order to proof possible genotype by environment interactions (G×E). Trait recording included 5,434 observations for BWT, 3,679 observations for 200dg and 2,998 observations for 365dg. Time-lagged climatic descriptors were classes for the mean temperature humidity index (mTHI) and number of HS days (nHS) from the following periods: 7 d-period a.p. (BWT), 56 d-period a.p., and 56 d-period p.p. (200dg and 365dg). Genetic parameters were estimated via 2-trait animal models, i.e., defining the same trait in different climatic environments as different traits. Genetic variances and heritabilities for all traits increased with increasing mTHI- and nHS-classes for all recording periods, indicating pronounced genetic differentiation with regard to time-lagged in utero HS and HS directly after birth. Similarly, in low mTHI- and nHS-classes indicating cold stress, genetic variances, and heritabilities were larger than for temperate climates. Genetic correlations substantially smaller than 0.80 indicating G × E were observed when considering same traits from mTHI- and nHS-classes in greater distance. Estimated breeding values (EBV) of the 10 most influential sires with the largest number of offspring records fluctuated across mTHI- and nHS-classes. Correlations between sire EBV for same traits from distant climatic classes confirmed the genetic correlation estimates. Sires displaying stable EBV with climatic alterations were also identified. Selection of those sires might contribute to improved robustness in the RHV outdoor population genetically.

Genetic Parameters for Tolerance to Heat Stress in Crossbred Swine Carcass Traits

Data for loin and backfat depth, as well as carcass growth of 126,051 three-way crossbred pigs raised between 2015 and 2019, were combined with climate records of air temperature, relative humidity, and temperature-humidity index. Environmental covariates with the largest impact on the studied traits were incorporated in a random regression model that also included genomic information. Genetic control of tolerance to heat stress and the presence of genotype by environment interaction were detected. Its magnitude was more substantial for loin depth and carcass growth, but all the traits studied showed a different impact of heat stress and different magnitude of genotype by environment interaction. For backfat depth, heritability was larger under comfortable conditions (no heat stress), as compared to heat stress conditions. Genetic correlations between extreme values of environmental conditions were lower (∼0.5 to negative) for growth and loin depth. Based on the solutions obtained from the model, sires were ranked on their breeding value for general performance and tolerance to heat stress. Antagonism between overall performance and tolerance to heat stress was moderate. Still, the models tested can provide valuable information to identify genetic material that is resilient and can perform equally when environmental conditions change. Overall, the results obtained from this study suggest the existence of genotype by environment interaction for carcass traits, as a possible genetic contributor to heat tolerance in swine.

Selection for Test-Day Milk Yield and Thermotolerance in Brazilian Holstein Cattle

Simple Summary

Interest in selection for milk yield and thermotolerance in cattle has grown, since heat stress has caused great losses in milk yield. However, few studies on how to carry out concurrent selection are available. Milk yield was analyzed by traditional methods, including heat stress indicators, in genetic evaluation. The results showed that the best sires for milk yield are not the best for heat tolerance, and only a small proportion of individuals have the aptitude for joint selection. Despite a small population fraction allowed for joint selection, sufficient genetic variability for selecting more resilient sires was found, which promoted concomitant genetic gains in milk yield and thermotolerance.

Abstract

Intense selection for milk yield has increased environmental sensitivity in animals, and currently, heat stress is an expensive problem in dairy farming. The objectives were to identify the best model for characterizing environmental sensitivity in Holstein cattle, using the test-day milk yield (TDMY) combined with the temperature–humidity index (THI), and identify sires genetically superior for heat-stress (HS) tolerance and milk yield, through random regression. The data comprised 94,549 TDMYs of 11,294 first-parity Holstein cows in Brazil, collected from 1997 to 2013. The yield data were fitted to Legendre orthogonal polynomials, linear splines and the Wilmink function. The THI (the average of two days before the dairy control) was used as an environmental gradient. An animal model that fitted production using a Legendre polynomials of quartic order for the days in milk and quadratic equations for the THI presented a better quality of fit (Akaike’s information criterion (AIC) and Bayesian information criterion (BIC)). The Spearman correlation coefficient of greatest impact was 0.54, between the top 1% for TDMY and top 1% for HS. Only 9% of the sires showed plasticity and an aptitude for joint selection. Thus, despite the small population fraction allowed for joint selection, sufficient genetic variability for selecting more resilient sires was found, which promoted concomitant genetic gains in milk yield and thermotolerance.

Integrating High-Throughput Phenotyping and Statistical Genomic Methods to Genetically Improve Longitudinal Traits in Crops

The rapid development of remote sensing in agronomic research allows the dynamic nature of longitudinal traits to be adequately described, which may enhance the genetic improvement of crop efficiency. For traits such as light interception, biomass accumulation, and responses to stressors, the data generated by the various high-throughput phenotyping (HTP) methods requires adequate statistical techniques to evaluate phenotypic records throughout time. As a consequence, information about plant functioning and activation of genes, as well as the interaction of gene networks at different stages of plant development and in response to environmental stimulus can be exploited. In this review, we outline the current analytical approaches in quantitative genetics that are applied to longitudinal traits in crops throughout development, describe the advantages and pitfalls of each approach, and indicate future research directions and opportunities.

Genotype by environment interaction due to heat stress during gestation and postpartum for milk production of Holstein cattle

Remarkable increases in the production of dairy animals have negatively impacted their tolerance to heat stress (HS). The evaluation of the effect of HS on milk yield is based on the direct impact of HS on performance. However, in practical terms, HS also exerts its influence during gestation (indirect effect). The main purpose of this study was to identify and characterize the genotype by environment interaction (G × E) due to HS during the last 60 days of gestation (THI_g) and also the HS postpartum (THI_m) over first lactation milk production of Brazilian Holstein cattle. A total of 389 127 test day milk yield (TD) records from 1572 first lactation Holstein cows born in Brazil (daughters of 1248 dams and 70 sires) and the corresponding temperature-humidity index (THI) obtained between December 2007 and January 2013 were analyzed using different random regression models. Cows in the cold environment (THI_g = 64 to 73) during the last 60 days of gestation produced more milk than those cows in a hot environment (THI_g = 74 to 84), particularly during the first 150 days of lactation (DIM). The heritabilities (h2) of TD were similar throughout DIM for cows in THI_g hot (0.11 to 0.20) or (0.10 to 0.22), while the genetic correlations (rg) for TD between these two environments ranged from 0.11 to 0.52 along the first 250 DIM. The h2 estimates for TD across THI_m were similar for cows in THI_g hot (0.07 to 0.25) and THI_g cold (0.08 to 0.19). The rg estimates ranged from 0.17 to 0.42 along THI_m between TD of cows in cold and hot THI_g. The results were consistent in demonstrating the existence of an additional source of G × E for TD due to THI_g and THI_m. The present study is probably the first to provide evidence of this source of G × E; further research is needed because of its importance when the breeding objective is to select animals that are more tolerant to HS.

Dual-purpose Guzerá cattle exhibit high dairy performance under heat stress

The present study evaluated the heat stress response pattern of dual-purpose Guzerá cattle for test-day (TD) milk yield records of first lactation and estimated genetic parameters and trends related to heat stress. A total of 31,435 TD records from 4,486 first lactations of Guzerá cows, collected between 1986 and 2012, were analysed. Two random regression models considered days in milk (DIM) and/or temperature × humidity-dependent (THI) covariate. Impacts of -0.037, -0.019 and -0.006 kg/day/THI for initial and intermediate stages of lactation were observed when considering the mean maximum daily temperature and humidity to calculate THI. Heritability estimates ranged from 0.16 to 0.35 throughout lactation and THI values, suggesting the possibility to expect gains from selection for such trait. The variable trajectory of breeding values for dual-purpose Guzerá sires in response to changes in THI values confirms that the genotype × environment interaction due to heat stress can have some effect on TD milk yield. Despite the high dairy performance of Guzerá cattle under heat stress, estimated genetic trends showed a progressive reduction in heat tolerance. Therefore, new strategies should be adopted to prevent negative impacts of heat stress over milk production in Guzerá animals in future.

Thermotolerance indicators related to production and physiological responses to heat stress of holstein cows

Heat stress (HS) adversely influences dairy cattle welfare and productivity. This study aimed to investigate the effects of HS on production and physiological parameters of Holstein cows. Two experiments each lasted 6 weeks were conducted in four Tunisian farms, firstly during summer under HS (n = 80, THI = 77) and later during autumn under thermo-neutral (n = 80, THI = 54) conditions. Respiration rate (RR), skin temperature (ST), rectal temperature (RT) and milk yield were measured, and milk samples were collected on 2 days every week during each experimental period. Temperature and relative humidity were measured inside the barn to calculate the temperature-humidity index (THI). Mixed models were used to evaluate the effects of period and the relationships between THI and physiological and production traits. Reaction norm models were applied to quantify the individual responses of cows across the trajectory of THI during the HS period. A clustering methodology was developed to identify tolerant and sensitive cows to HS based on their slope for response of physiological and production traits during HS period. In summer, RR (61 breaths/min) and ST (37.7 °C) were 2.3- and 1.3-fold higher, whereas milk yield per milking was 24% lower compared with thermo-neutral conditions. Linear relationship between THI and RR, ST and RT was observed and showed increases by 2 breaths/min, 0.5 °C and 0.04 °C per increase in one THI unit, respectively. Inversely, milk, fat and protein yields showed a drop of 0.13 kg, 0.4 g and 0.3 g per milking per increase in one THI unit, respectively. Cows qualified to be heat tolerant by our work tended to have higher RR, ST, and RT and lower to almost no decay in milk yield compared to cows qualified to be heat sensitive. Specifically, RR could be used as a reliable indicator for thermotolerance. The results of this study deepen our understanding of different aspects of HS resilience.