Genetic relationship of energy balance predicted from milk traits with fertility in Japanese Holsteins.

We predicted the energy balance of cows from milk traits and estimated the genetic correlations of predicted energy balance (PEB) with fertility traits for the first three lactations. Data included 9,646,606 test-day records of 576,555 Holstein cows in Japan from 2015 to 2019. Genetic parameters were estimated with a multiple-trait model in which the records among lactation stages and parities were treated as separate traits. Fertility traits were conception rate at first insemination (CR), number of inseminations (NI), and days open (DO). Heritability estimates of PEB were 0.28-0.35 (first lactation), 0.15-0.29 (second), and 0.09-0.23 (third). Estimated genetic correlations among lactation stages were 0.85-1.00 (first lactation), 0.73-1.00 (second), and 0.64-1.00 (third). Estimated genetic correlations among parities were 0.82-0.96 (between first and second), 0.97-0.99 (second and third), and 0.69-0.92 (first and third). Estimated genetic correlations of PEB in early lactation with fertility were 0.04 to 0.19 for CR, -0.03 to -0.19 for NI, and -0.01 to -0.24 for DO. Genetic improvement of PEB is possible. Lower PEB in early lactation was associated with worse fertility, suggesting that improving PEB in early lactation may improve reproductive performance.

Genetic analysis of efficiency-related traits in Boer x Central Highland goats.

This study aimed to identify important non-genetic factors and estimate genetic parameters for efficiency-related traits in Boer x Central Highland goats. The genetic parameters were estimated using the Average Information Restricted Maximum Likelihood algorithm using the WOMBAT program fitting animal model. The least-squares means for growth efficiency from birth to 3 months (GE1), 3-6 months (GE2), 6-12 months (GE3), relative growth rate from birth to 3 months (RGR1), 3-6 months (RGR2) and 6-12 month (RGR3) were 294.0 ± 5.06, 36.6 ± 1.20, 44.9 ± 1.81, 1.46 ± 0.01, 0.32 ± 0.01 and 0.19 ± 0.01, respectively. Birth type, blood level, sex of the kid, and year of kidding had a sizable effect on efficiency-related traits. About 18, 3.0, 23, 20, and 12% of the phenotypic variation in GE2, GE3, RGR1, RGR2, and RGR3 was explained by the direct additive genetic effect. Except for RGR3, all investigated traits were under the influence of maternal genetic effect, and maternal heritability ranged from 0.09 to 0.17. The total heritability estimate depicts that slow genetic progress would be expected from selection. Nevertheless, even with this level of heritability, selection for efficiency-related traits would improve the efficiency of chevon production as these traits are economically important traits. Nearly six-months of age was when farmers sold Boer crossbred goats. Therefore, improving the growth efficiency till the marketing age (GE2) in such a scenario could increase the production efficiency.

Evaluation of heritability partitioning approaches in livestock populations.

BACKGROUND: Heritability partitioning approaches estimate the contribution of different functional classes, such as coding or regulatory variants, to the genetic variance. This information allows a better understanding of the genetic architecture of complex traits, including complex diseases, but can also help improve the accuracy of genomic selection in livestock species. However, methods have mainly been tested on human genomic data, whereas livestock populations have specific characteristics, such as high levels of relatedness, small effective population size or long-range levels of linkage disequilibrium. RESULTS: Here, we used data from 14,762 cows, imputed at the whole-genome sequence level for 11,537,240 variants, to simulate traits in a typical livestock population and evaluate the accuracy of two state-of-the-art heritability partitioning methods, GREML and a Bayesian mixture model. In simulations where a single functional class had increased contribution to heritability, we observed that the estimators were unbiased but had low precision. When causal variants were enriched in variants with low (< 0.05) or high (> 0.20) minor allele frequency or low (below 1st quartile) or high (above 3rd quartile) linkage disequilibrium scores, it was necessary to partition the genetic variance into multiple classes defined on the basis of allele frequencies or LD scores to obtain unbiased results. When multiple functional classes had variable contributions to heritability, estimators showed higher levels of variation and confounding between certain categories was observed. In addition, estimators from small categories were particularly imprecise. However, the estimates and their ranking were still informative about the contribution of the classes. We also demonstrated that using methods that estimate the contribution of a single category at a time, a commonly used approach, results in an overestimation. Finally, we applied the methods to phenotypes for muscular development and height and estimated that, on average, variants in open chromatin regions had a higher contribution to the genetic variance (> 45%), while variants in coding regions had the strongest individual effects (> 25-fold enrichment on average). Conversely, variants in intergenic or intronic regions showed lower levels of enrichment (0.2 and 0.6-fold on average, respectively). CONCLUSIONS: Heritability partitioning approaches should be used cautiously in livestock populations, in particular for small categories. Two-component approaches that fit only one functional category at a time lead to biased estimators and should not be used.

Genome-wide association study for cashmere traits in Inner Mongolia cashmere goat population reveals new candidate genes and haplotypes.

BACKGROUND: The cashmere goat industry is one of the main pillars of animal husbandry in Inner Mongolia Autonomous Region, and plays an irreplaceable role in local economic development. With the change in feeding methods and environment, the cashmere produced by Inner Mongolia cashmere goats shows a tendency of coarser, and the cashmere yield can not meet the consumption demand of people. However, the genetic basis behind these changes is not fully understood. We measured cashmere traits, including cashmere yield (CY), cashmere diameter (CD), cashmere thickness (CT), and fleece length (FL) traits for four consecutive years, and utilized Genome-wide association study of four cashmere traits in Inner Mongolia cashmere goats was carried out using new genomics tools to infer genomic regions and functional loci associated with cashmere traits and to construct haplotypes that significantly affect cashmere traits. RESULTS: We estimated the genetic parameters of cashmere traits in Inner Mongolia cashmere goats. The heritability of cashmere yield, cashmere diameter, and fleece length traits of Inner Mongolia cashmere goats were 0.229, 0.359, and 0.250, which belonged to the medium heritability traits (0.2 ~ 0.4). The cashmere thickness trait has a low heritability of 0.053. We detected 151 genome-wide significantly associated SNPs with four cashmere traits on different chromosomes, which were very close to the chromosomes of 392 genes (located within the gene or within ± 500 kb). Notch3, BMPR1B, and CCNA2 have direct functional associations with fibroblasts and follicle stem cells, which play important roles in hair follicle growth and development. Based on GO functional annotation and KEGG enrichment analysis, potential candidate genes were associated with pathways of hair follicle genesis and development (Notch, P13K-Akt, TGF-beta, Cell cycle, Wnt, MAPK). We calculated the effective allele number of the Inner Mongolia cashmere goat population to be 1.109-1.998, the dominant genotypes of most SNPs were wild-type, the polymorphic information content of 57 SNPs were low polymorphism (0 < PIC < 0.25), and the polymorphic information content of 79 SNPs were moderate polymorphism (0.25 < PIC < 0.50). We analyzed the association of SNPs with phenotypes and found that the homozygous mutant type of SNP1 and SNP3 was associated with the highest cashmere yield, the heterozygous mutant type of SNP30 was associated with the lowest cashmere thickness, the wild type of SNP76, SNP77, SNP78, SNP80, and SNP81 was associated with the highest cashmere thickness, and the wild type type of SNP137 was associated with the highest fleece length. 21 haplotype blocks and 68 haplotype combinations were constructed. Haplotypes A2A2, B2B2, C2C2, and D4D4 were associated with increased cashmere yield, haplotypes E2E2, F1F1, G5G5, and G1G5 were associated with decreased cashmere fineness, haplotypes H2H2 was associated with increased cashmere thickness, haplotypes I1I1, I1I2, J1J4, L5L3, N3N2, N3N3, O2O1, P2P2, and Q3Q3 were associated with increased cashmere length. We verified the polymorphism of 8 SNPs by KASP, and found that chr7_g.102631194A > G, chr10_g.82715068 T > C, chr1_g.124483769C > T, chr24_g.12811352C > T, chr6_g.114111249A > G, and chr6_g.115606026 T > C were significantly genotyped in verified populations (P < 0.05). CONCLUSIONS: In conclusion, the genetic effect of single SNP on phenotypes is small, and SNPs are more inclined to be inherited as a whole. By constructing haplotypes from SNPs that are significantly associated with cashmere traits, it will help to reveal the complex and potential causal variations in cashmere traits of Inner Mongolia cashmere goats. This will be a valuable resource for genomics and breeding of the cashmere goat.

Evaluation of genomic prediction considering non-additive genetic effects on fatty acid traits of Japanese Black cattle.

Genomic prediction was conducted using 2494 Japanese Black cattle from Hiroshima Prefecture and both single-nucleotide polymorphism information and phenotype data on monounsaturated fatty acid (MUFA) and oleic acid (C18:1) analyzed with gas chromatography. We compared the prediction accuracy for four models (A, additive genetic effects; AD, as for A with dominance genetic effects; ADR, as for AD with the runs of homozygosity (ROH) effects calculated by ROH-based relationship matrix; and ADF, as for AD with the ROH-based inbreeding coefficient of the linear regression). Bayesian methods were used to estimate variance components. The narrow-sense heritability estimates for MUFA and C18:1 were 0.52-0.53 and 0.57, respectively; the corresponding proportions of dominance genetic variance were 0.04-0.07 and 0.04-0.05, and the proportion of ROH variance was 0.02. The deviance information criterion values showed slight differences among the models, and the models provided similar prediction accuracy.

Too hot to handle: temperature-induced plasticity influences pollinator behaviour and plant fitness.

Increased temperature can induce plastic changes in many plant traits. However, little is known about how these changes affect plant interactions with insect pollinators and herbivores, and what the consequences for plant fitness and selection are. We grew fast-cycling Brassica rapa plants at two temperatures (ambient and increased temperature) and phenotyped them (floral traits, scent, colour and glucosinolates). We then exposed plants to both pollinators (Bombus terrestris) and pollinating herbivores (Pieris rapae). We measured flower visitation, oviposition of P. rapae, herbivore development and seed output. Plants in the hot environment produced more but smaller flowers, with lower UV reflectance and emitted a different volatile blend with overall lower volatile emission. Moreover, these plants received fewer first-choice visits by bumblebees and butterflies, and fewer flower visits by butterflies. Seed production was lower in hot environment plants, both because of a reduction in flower fertility due to temperature and because of the reduced visitation of pollinators. The selection on plant traits changed in strength and direction between temperatures. Our study highlights an important mechanism by which global warming can change plant-pollinator interactions and negatively impact plant fitness, as well as potentially alter plant evolution through changes in phenotypic selection.

Breeding for resilience in finishing pigs can decrease tail biting, lameness and mortality.

BACKGROUND: Previous research showed that deviations in longitudinal data are heritable and can be used as a proxy for pigs' general resilience. However, only a few studies investigated the relationship between these resilience traits and other traits related to resilience and welfare. Therefore, this study investigated the relationship between resilience traits derived from deviations in longitudinal data and traits related to animal resilience, health and welfare, such as tail and ear biting wounds, lameness and mortality. RESULTS: In our experiment, 1919 finishing pigs with known pedigree (133 Piétrain sires and 266 crossbred dams) were weighed every 2 weeks and scored for physical abnormalities, such as lameness and ear and tail biting wounds (17,066 records). Resilience was assessed via deviations in body weight, deviations in weighing order and deviations in observed activity during weighing. The association between these resilience traits and physical abnormality traits was investigated and genetic parameters were estimated. Deviations in body weight had moderate heritability estimates (h2 = 25.2 to 36.3%), whereas deviations in weighing order (h2 = 4.2%) and deviations in activity during weighing (h2 = 12.0%) had low heritability estimates. Moreover, deviations in body weight were positively associated and genetically correlated with tail biting wounds (rg = 0.22 to 0.30), lameness (rg = 0.15 to 0.31) and mortality (rg = 0.19 to 0.33). These results indicate that events of tail biting, lameness and mortality are associated with deviations in pigs' body weight evolution. This relationship was not found for deviations in weighing order and activity during weighing. Furthermore, individual body weight deviations were positively correlated with uniformity at the pen level, providing evidence that breeding for these resilience traits might increase both pigs' resilience and within-family uniformity. CONCLUSIONS: In summary, our findings show that breeding for resilience traits based on deviations in longitudinal weight data can decrease pigs' tail biting wounds, lameness and mortality while improving uniformity at the pen level. These findings are valuable for pig breeders, as they offer evidence that these resilience traits are an indication of animals' general health, welfare and resilience. Moreover, these results will stimulate the quantification of resilience via longitudinal body weights in other species.

Genome-wide association analysis identify candidate genes for feed efficiency and growth traits in Wenchang chickens.

BACKGROUND: Wenchang chickens are one of the most popular local chicken breeds in the Chinese chicken industry. However, the low feed efficiency is the main shortcoming of this breed. Therefore, there is a need to find a more precise breeding method to improve the feed efficiency of Wenchang chickens. In this study, we explored important candidate genes and variants for feed efficiency and growth traits through genome-wide association study (GWAS) analysis. RESULTS: Estimates of genomic heritability for growth and feed efficiency traits, including residual feed intake (RFI) of 0.05, average daily food intake (ADFI) of 0.21, average daily weight gain (ADG) of 0.24, body weight (BW) at 87, 95, 104, 113 days of age (BW87, BW95, BW104 and BW113) ranged from 0.30 to 0.44. Important candidate genes related to feed efficiency and growth traits were identified, such as PLCE1, LAP3, MED28, QDPR, LDB2 and SEL1L3 genes. CONCLUSION: The results identified important candidate genes for feed efficiency and growth traits in Wenchang chickens and provide a theoretical basis for the development of new molecular breeding technology.

Leaf and twig traits predict habitat adaptation and demographic strategies in tropical freshwater swamp forest trees.

Differences in demographic and environmental niches facilitate plant species coexistence in tropical forests. However, the adaptations that enable species to achieve higher demographic rates (e.g. growth or survival) or occupy unique environmental niches (e.g. waterlogged conditions) remain poorly understood. Anatomical traits may better predict plant environmental and demographic strategies because they are direct measurements of structures involved in these adaptations. We collected 18 leaf and twig traits from 29 tree species in a tropical freshwater swamp forest in Singapore. We estimated demographic parameters of the 29 species from growth and survival models, and degree of association toward swamp habitats. We examined pairwise trait-trait, trait-demography and trait-environment links while controlling for phylogeny. Leaf and twig anatomical traits were better predictors of all demographic parameters than other commonly measured leaf and wood traits. Plants with wider vessels had faster growth rates but lower survival rates. Leaf and spongy mesophyll thickness predicted swamp association. These findings demonstrate the utility of anatomical traits as indicators of plant hydraulic strategies and their links to growth-mortality trade-offs and waterlogging stress tolerance that underlie species coexistence mechanisms in tropical forest trees.

Predictive ability of multi-population genomic prediction methods of phenotypes for reproduction traits in Chinese and Austrian pigs.

BACKGROUND: Multi-population genomic prediction can rapidly expand the size of the reference population and improve genomic prediction ability. Machine learning (ML) algorithms have shown advantages in single-population genomic prediction of phenotypes. However, few studies have explored the effectiveness of ML methods for multi-population genomic prediction. RESULTS: In this study, 3720 Yorkshire pigs from Austria and four breeding farms in China were used, and single-trait genomic best linear unbiased prediction (ST-GBLUP), multitrait GBLUP (MT-GBLUP), Bayesian Horseshoe (BayesHE), and three ML methods (support vector regression (SVR), kernel ridge regression (KRR) and AdaBoost.R2) were compared to explore the optimal method for joint genomic prediction of phenotypes of Chinese and Austrian pigs through 10 replicates of fivefold cross-validation. In this study, we tested the performance of different methods in two scenarios: (i) including only one Austrian population and one Chinese pig population that were genetically linked based on principal component analysis (PCA) (designated as the "two-population scenario") and (ii) adding reference populations that are unrelated based on PCA to the above two populations (designated as the "multi-population scenario"). Our results show that, the use of MT-GBLUP in the two-population scenario resulted in an improvement of 7.1% in predictive ability compared to ST-GBLUP, while the use of SVR and KKR yielded improvements in predictive ability of 4.5 and 5.3%, respectively, compared to MT-GBLUP. SVR and KRR also yielded lower mean square errors (MSE) in most population and trait combinations. In the multi-population scenario, improvements in predictive ability of 29.7, 24.4 and 11.1% were obtained compared to ST-GBLUP when using, respectively, SVR, KRR, and AdaBoost.R2. However, compared to MT-GBLUP, the potential of ML methods to improve predictive ability was not demonstrated. CONCLUSIONS: Our study demonstrates that ML algorithms can achieve better prediction performance than multitrait GBLUP models in multi-population genomic prediction of phenotypes when the populations have similar genetic backgrounds; however, when reference populations that are unrelated based on PCA are added, the ML methods did not show a benefit. When the number of populations increased, only MT-GBLUP improved predictive ability in both validation populations, while the other methods showed improvement in only one population.

Research on the Effects of the Relationship between Agronomic Traits and Dwarfing Genes on Yield in Colored Wheat.

This research focuses on 72 approved varieties of colored wheat from different provinces in China. Utilizing coefficients of variation, structural equation models, and correlation analyses, six agronomic traits of colored wheat were comprehensively evaluated, followed by further research on different dwarfing genes in colored wheat. Using the entropy method revealed that among the 72 colored wheat varieties, 10 were suitable for cultivation. Variety 70 was the top-performing variety, with a comprehensive index of 87.15%. In the final established structural equation model, each agronomic trait exhibited a positive direct effect on yield. Notably, plant height, spike length, and flag leaf width had significant impacts on yield, with path coefficients of 0.55, 0.40, and 0.27. Transcriptome analysis and real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) validation were used to identify three dwarfing genes controlling plant height: Rht1, Rht-D1, and Rht8. Subsequent RT-qPCR validation clustering heatmap results indicated that Rht-D1 gene expression increased with the growth of per-acre yield. Rht8 belongs to the semi-dwarf gene category and has a significant positive effect on grain yield. However, the impact of Rht1, as a dwarfing gene, on agronomic traits varies. These research findings provide crucial references for the breeding of new varieties.

Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets.

While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological interpretation of these findings remains challenging. Here we developed the GSA-MiXeR analytical tool for gene set analysis (GSA), which fits a model for the heritability of individual genes, accounting for linkage disequilibrium across variants and allowing the quantification of partitioned heritability and fold enrichment for small gene sets. We validated the method using extensive simulations and sensitivity analyses. When applied to a diverse selection of complex traits and disorders, including schizophrenia, GSA-MiXeR prioritizes gene sets with greater biological specificity compared to standard GSA approaches, implicating voltage-gated calcium channel function and dopaminergic signaling for schizophrenia. Such biologically relevant gene sets, often with fewer than ten genes, are more likely to provide insights into the pathobiology of complex diseases and highlight potential drug targets.

Genome-Wide Detection of Copy Number Variations and Their Potential Association with Carcass and Meat Quality Traits in Pingliang Red Cattle.

Copy number variation (CNV) serves as a significant source of genetic diversity in mammals and exerts substantial effects on various complex traits. Pingliang red cattle, an outstanding indigenous resource in China, possess remarkable breeding value attributed to their tender meat and superior marbling quality. However, the genetic mechanisms influencing carcass and meat quality traits in Pingliang red cattle are not well understood. We generated a comprehensive genome-wide CNV map for Pingliang red cattle using the GGP Bovine 100K SNP chip. A total of 755 copy number variable regions (CNVRs) spanning 81.03 Mb were identified, accounting for approximately 3.24% of the bovine autosomal genome. Among these, we discovered 270 potentially breed-specific CNVRs in Pingliang red cattle, including 143 gains, 73 losses, and 54 mixed events. Functional annotation analysis revealed significant associations between these specific CNVRs and important traits such as carcass and meat quality, reproduction, exterior traits, growth traits, and health traits. Additionally, our network and transcriptome analysis highlighted CACNA2D1, CYLD, UBXN2B, TG, NADK, and ITGA9 as promising candidate genes associated with carcass weight and intramuscular fat deposition. The current study presents a genome-wide CNV map in Pingliang red cattle, highlighting breed-specific CNVRs, and transcriptome findings provide valuable insights into the underlying genetic characteristics of Pingliang red cattle. These results offer potential avenues for enhancing meat quality through a targeted breeding program.

Natural allelic variation confers diversity in the regulation of flag leaf traits in wheat.

Flag leaf (FL) dimension has been reported as a key ecophysiological aspect for boosting grain yield in wheat. A worldwide winter wheat panel consisting of 261 accessions was tested to examine the phenotypical variation and identify quantitative trait nucleotides (QTNs) with candidate genes influencing FL morphology. To this end, four FL traits were evaluated during the early milk stage under two growing seasons at the Leibniz Institute of Plant Genetics and Crop Plant Research. The results showed that all leaf traits (Flag leaf length, width, area, and length/width ratio) were significantly influenced by the environments, genotypes, and environments × genotypes interactions. Then, a genome-wide association analysis was performed using 17,093 SNPs that showed 10 novel QTNs that potentially play a role in modulating FL morphology in at least two environments. Further analysis revealed 8 high-confidence candidate genes likely involved in these traits and showing high expression values from flag leaf expansion until its senescence and also during grain development. An important QTN (wsnp_RFL_Contig2177_1500201) was associated with FL width and located inside TraesCS3B02G047300 at chromosome 3B. This gene encodes a major facilitator, sugar transporter-like, and showed the highest expression values among the candidate genes reported, suggesting their positive role in controlling flag leaf and potentially being involved in photosynthetic assimilation. Our study suggests that the detection of novel marker-trait associations and the subsequent elucidation of the genetic mechanism influencing FL morphology would be of interest for improving plant architecture, light capture, and photosynthetic efficiency during grain development.

Genetic parameters for novel climatic resilience indicators derived from automatically-recorded vaginal temperature in lactating sows under heat stress conditions.

BACKGROUND: Longitudinal records of automatically-recorded vaginal temperature (TV) could be a key source of data for deriving novel indicators of climatic resilience (CR) for breeding more resilient pigs, especially during lactation when sows are at an increased risk of suffering from heat stress (HS). Therefore, we derived 15 CR indicators based on the variability in TV in lactating sows and estimated their genetic parameters. We also investigated their genetic relationship with sows' key reproductive traits. RESULTS: The heritability estimates of the CR traits ranged from 0.000 ± 0.000 for slope for decreased rate of TV (SlopeDe) to 0.291 ± 0.047 for sum of TV values below the HS threshold (HSUB). Moderate to high genetic correlations (from 0.508 ± 0.056 to 0.998 ± 0.137) and Spearman rank correlations (from 0.431 to 1.000) between genomic estimated breeding values (GEBV) were observed for five CR indicators, i.e. HS duration (HSD), the normalized median multiplied by normalized variance (Nor_medvar), the highest TV value of each measurement day for each individual (MaxTv), and the sum of the TV values above (HSUA) and below (HSUB) the HS threshold. These five CR indicators were lowly to moderately genetically correlated with shoulder skin surface temperature (from 0.139 ± 0.008 to 0.478 ± 0.048) and respiration rate (from 0.079 ± 0.011 to 0.502 ± 0.098). The genetic correlations between these five selected CR indicators and sow reproductive performance traits ranged from - 0.733 to - 0.175 for total number of piglets born alive, from - 0.733 to - 0.175 for total number of piglets born, and from - 0.434 to - 0.169 for number of pigs weaned. The individuals with the highest GEBV (most climate-sensitive) had higher mean skin surface temperature, respiration rate (RR), panting score (PS), and hair density, but had lower mean body condition scores compared to those with the lowest GEBV (most climate-resilient). CONCLUSIONS: Most of the CR indicators evaluated are heritable with substantial additive genetic variance. Five of them, i.e. HSD, MaxTv, HSUA, HSUB, and Nor_medvar share similar underlying genetic mechanisms. In addition, individuals with higher CR indicators are more likely to exhibit better HS-related physiological responses, higher body condition scores, and improved reproductive performance under hot conditions. These findings highlight the potential benefits of genetically selecting more heat-tolerant individuals based on CR indicators.

Investigating the impact of paternal age, paternal heat stress, and estimation of non-genetic paternal variance on dairy cow phenotype.

BACKGROUND: Linear models that are commonly used to predict breeding values in livestock species consider paternal influence solely as a genetic effect. However, emerging evidence in several species suggests the potential effect of non-genetic semen-mediated paternal effects on offspring phenotype. This study contributes to such research by analyzing the extent of non-genetic paternal effects on the performance of Holstein, Montbéliarde, and Normande dairy cows. Insemination data, including semen Batch Identifier (BI, a combination of bull identification and collection date), was associated with various traits measured in cows born from the insemination. These traits encompassed stature, milk production (milk, fat, and protein yields), udder health (somatic cell score and clinical mastitis), and female fertility (conception rates of heifers and cows). We estimated (1) the effects of age at collection and heat stress during spermatogenesis, and (2) the variance components associated with BI or Weekly aggregated BI (WBI). RESULTS: Overall, the non-genetic paternal effect estimates were small and of limited biological importance. However, while heat stress during spermatogenesis did not show significant associations with any of the traits studied in daughters, we observed significant effects of bull age at semen collection on the udder health of daughters. Indeed, cows born from bulls collected after 1500 days of age had higher somatic cell scores compared to those born from bulls collected at a younger age (less than 400 days old) in both Holstein and Normande breeds (+ 3% and + 5% of the phenotypic mean, respectively). In addition, across all breeds and traits analyzed, the estimates of non-genetic paternal variance were consistently low, representing on average 0.13% and 0.09% of the phenotypic variance for BI and WBI, respectively (ranging from 0 to 0.7%). These estimates did not significantly differ from zero, except for milk production traits (milk, fat, and protein yields) in the Holstein breed and protein yield in the Montbéliarde breed when WBI was considered. CONCLUSIONS: Our findings indicate that non-genetic paternal information transmitted through semen does not substantially influence the offspring phenotype in dairy cattle breeds for routinely measured traits. This lack of substantial impact may be attributed to limited transmission or minimal exposure of elite bulls to adverse conditions.

Domestication of rice may have changed its arbuscular mycorrhizal properties by modifying phosphorus nutrition-related traits and decreasing symbiotic compatibility.

Modern cultivated rice (Oryza sativa) typically experiences limited growth benefits from arbuscular mycorrhizal (AM) symbiosis. This could be due to the long-term domestication of rice under favorable phosphorus conditions. However, there is limited understanding of whether and how the rice domestication has modified AM properties. This study compared AM properties between a collection of wild (Oryza rufipogon) and domesticated rice genotypes and investigated the mechanisms underlying their differences by analyzing physiological, genomic, transcriptomic, and metabolomic traits critical for AM symbiosis. The results revealed significantly lower mycorrhizal growth responses and colonization intensity in domesticated rice compared to wild rice, and this change of AM properties may be associated with the domestication modifications of plant phosphorus utilization efficiency at physiological and genomic levels. Domestication also resulted in a decrease in the activity of the mycorrhizal phosphorus acquisition pathway, which may be attributed to reduced mycorrhizal compatibility of rice roots by enhancing defense responses like root lignification and reducing carbon supply to AM fungi. In conclusion, rice domestication may have changed its AM properties by modifying P nutrition-related traits and reducing symbiotic compatibility. This study offers new insights for improving AM properties in future rice breeding programs to enhance sustainable agricultural production.

Clinal variation in quantitative traits but not in evolutionary potential along elevational and latitudinal gradients in the widespread Anthyllis vulneraria.

PREMISE: Strong elevational and latitudinal gradients allow the study of genetic differentiation in response to similar environmental changes. However, it is uncertain whether the environmental changes along the two types of gradients result in similar genetically based changes in quantitative traits. Peripheral arctic and alpine populations are thought to have less evolutionary potential than more central populations do. METHODS: We studied quantitative traits of the widespread Anthyllis vulneraria in a common garden. Plants originated from 20 populations along a 2000-m elevational gradient from the lowlands to the elevational limit of the species in the Alps, and from 20 populations along a 2400-km latitudinal gradient from the center of the distribution of the species in Central Europe to its northern distributional margin. RESULTS: Most traits showed similar clinal variations with elevation and latitude of origin, and the magnitude of all measured traits in relation to mean annual temperature was similar. Higher QST values than FST values in several traits indicated diversifying selection, but for others QST was smaller than FST. Genetic diversity of quantitative traits and neutral molecular markers was not correlated. Plasticity in response to favorable conditions declined with elevation and less strongly with latitude of origin, but the evolvability of traits did not. CONCLUSIONS: The clinal variation suggests adaptive differentiation of quantitative traits along the two gradients. The evolutionary potential of peripheral populations is not necessarily reduced, but lower plasticity may threaten their survival under rapidly changing climatic conditions.

A scalable and robust variance components method reveals insights into the architecture of gene-environment interactions underlying complex traits.

Understanding the contribution of gene-environment interactions (GxE) to complex trait variation can provide insights into disease mechanisms, explain sources of heritability, and improve genetic risk prediction. While large biobanks with genetic and deep phenotypic data hold promise for obtaining novel insights into GxE, our understanding of GxE architecture in complex traits remains limited. We introduce a method to estimate the proportion of trait variance explained by GxE (GxE heritability) and additive genetic effects (additive heritability) across the genome and within specific genomic annotations. We show that our method is accurate in simulations and computationally efficient for biobank-scale datasets. We applied our method to common array SNPs (MAF ≥1%), fifty quantitative traits, and four environmental variables (smoking, sex, age, and statin usage) in unrelated white British individuals in the UK Biobank. We found 68 trait-E pairs with significant genome-wide GxE heritability (p<0.05/200) with a ratio of GxE to additive heritability of ≈6.8% on average. Analyzing ≈8 million imputed SNPs (MAF ≥0.1%), we documented an approximate 28% increase in genome-wide GxE heritability compared to array SNPs. We partitioned GxE heritability across minor allele frequency (MAF) and local linkage disequilibrium (LD) values, revealing that, like additive allelic effects, GxE allelic effects tend to increase with decreasing MAF and LD. Analyzing GxE heritability near genes highly expressed in specific tissues, we find significant brain-specific enrichment for body mass index (BMI) and basal metabolic rate in the context of smoking and adipose-specific enrichment for waist-hip ratio (WHR) in the context of sex.

Trait selection strategy in multi-trait GWAS: Boosting SNP discoverability.

Since the first genome-wide association studies (GWASs), thousands of variant-trait associations have been discovered. However, comprehensively mapping the genetic determinant of complex traits through univariate testing can require prohibitive sample sizes. Multi-trait GWAS can circumvent this issue and improve statistical power by leveraging the joint genetic architecture of human phenotypes. Although many methodological hurdles of multi-trait testing have been solved, the strategy to select traits has been overlooked. In this study, we conducted multi-trait GWAS on approximately 20,000 combinations of 72 traits using an omnibus test as implemented in the Joint Analysis of Summary Statistics. We assessed which genetic features of the sets of traits analyzed were associated with an increased detection of variants compared with univariate screening. Several features of the set of traits, including the heritability, the number of traits, and the genetic correlation, drive the multi-trait test gain. Using these features jointly in predictive models captures a large fraction of the power gain of the multi-trait test (Pearson's r between the observed and predicted gain equals 0.43, p < 1.6 × 10-60). Applying an alternative multi-trait approach (Multi-Trait Analysis of GWAS), we identified similar features of interest, but with an overall 70% lower number of new associations. Finally, selecting sets based on our data-driven models systematically outperformed the common strategy of selecting clinically similar traits. This work provides a unique picture of the determinant of multi-trait GWAS statistical power and outlines practical strategies for multi-trait testing.