Fertility Traits In Dairy Cattle Research Articles

Genetic variation in bovine LAP3 and SIRT1 genes associated with fertility traits in dairy cattle.

The genetic progress of fertility and reproduction traits in dairy cattle has been constrained by the low heritability of these traits. Identifying candidate genes and variants associated with fertility and reproduction could enhance the accuracy of genetic selection and expedite breeding process of dairy cattle with low-heritability traits. While the bovine LAP3 and SIRT1 genes exhibit well-documented associations with milk production traits in dairy cattle, their effect on cow fertility have not yet been explored. Eleven single nucleotide polymorphisms (SNPs), comprising five in the promoter (rs717156555: C > G, rs720373055: T > C, rs516876447: A > G, rs461857269: C > T and rs720349928: G > A), two in 5'UTR (rs722359733: C > T and rs462932574: T > G), two in intron 12 (rs110932626: A > G and rs43702363: C > T), and one in 3'UTR of exon 13 (rs41255599: C > T) in LAP3 and one in SIRT1 (rs718329990:T > C) genes, have previously been reported to be associated with various traits of milk production and clinical mastitis in Sahiwal and Karan Fries dairy cattle. In this study, the analysis primarily aimed to assess the impact of SNPs within LAP3 and SIRT1 genes on fertility traits in Sahiwal and Karan Fries cattle. Association studies were conducted using mixed linear models, involving 125 Sahiwal and 138 Karan Fries animals in each breed. The analysis utilized a designated PCR-RFLP panel. In the promoter region of the LAP3 gene, all variants demonstrated significant (P < 0.05) associations with AFC, except for rs722359733: C > T. However, specific variants with the LAP3 gene's promoter region, namely rs722359733: C > T, rs110932626: A > G, rs43702363: C > T, and rs41255599: C > T, showed significant associations with CI and DO in Sahiwal and Karan Fries cows, respectively. The SNP rs718329990: T > C in the promoter region of SIRT1 gene exhibited a significant association with CI and DO in Sahiwal cattle. Haplotype-based association analysis revealed significant associations between haplotype combinations and AFC, CI and DO in the studied dairy cattle population. Animals with H2H3 and H2H4 haplotype combination exhibited higher AFC, CI and DO than other combinations. These results affirm the involvement of the LAP3 and SIRT1 genes in female fertility traits, indicating that polymorphisms within these genes are linked to the studied traits. Overall, the significant SNPs and haplotypes identified in this study could have the potential to enhance herd profitability and ensure long-term sustainability on dairy farms by enabling the selection of animals with early age first calving and enhance reproductive performance in the dairy cattle breeding program.

214 Association between oocyte grade, markers of oocyte competence, and fertility traits in dairy cattle

214 Association between oocyte grade, markers of oocyte competence, and fertility traits in dairy cattle

Análise multidimensional de escala para investigar as relações entre o rendimento do leite e os parâmetros de fertilidade

ABSTRACT Milk yield and fertility traits in dairy cattle and their relationship with the influencing factors were investigated using multidimensional scaling analysis (MDS) in this study. The study focused on the relationship between lactation length, 305-day milk yield, actual milk yield and peak remaining days from milk yield characteristics, and service period, dry period, insemination per conception and calving interval from fertility traits, as well as the influencing factors such as calving age, lactation number, birth season, and birth year. When the MDS results were examined, it was discovered that all the traits had close Euclidean distances from each other, save for the birth season and birth year. As a result of MDS analysis, R2 and Stress Coefficient were calculated as 88.4% and 0.099, respectively. Consequently, the selection direction was tried to be identified by determining the milk yield and fertility traits and the relationship between these traits and the influencing factors through the MDS analysis and it was concluded that the MDS method could be employed in this field.

Effect of synchronized breeding on genetic evaluations of fertility traits in dairy cattle

Estrus detection has become more difficult over the years due to decreases in the estrus expression of high-producing dairy cows, and increased herd sizes and animal density. Through the use of hormonal synchronization protocols, also known as timed artificial insemination (TAI) protocols, it is possible to alleviate some of the challenges associated with estrus detection. However, TAI masks cows' fertility performance, resulting in an unfair comparison of treated animals and innately fertile animals. Consequently, genetically inferior and superior cows show similar phenotypes, making it difficult to distinguish between them. As genetic programs rely on the collection of accurate phenotypic data, phenotypes collected on treated animals likely add bias to genetic evaluations. In this study, to assess the effect of TAI, the rank correlation of bulls for a given trait using only TAI records were compared with the same trait using only heat detection records. A total of 270,434 records from 192,539 animals split across heifers, first and second parity cows were analyzed for the traits: calving to first service, first service to conception, and days open. Results showed large reranking across all traits and parities between bulls compared based on either having only TAI records or only heat detection records, suggesting that a bias does indeed exist. Large reranking was also observed for both the heat detection and TAI groups among the top 100 bulls in the control group, which included all records. Furthermore, breeding method was added to the model to assess its effect on bull ranking. However, there were only minor changes in the rank correlations between scenario groups. Therefore, more complex methods to account for the apparent bias created by TAI should be investigated; for this, the method by which these data are collected needs to be improved through creating a standardized way of recording breeding codes. Though the results of this study suggest the presence of bias within current fertility evaluations, additional research is required to confirm the findings of this study, including looking at high-reliability bulls specifically, to determine if the levels of reranking remain. Future studies should also aim to understand the potential genetic differences between the fertility traits split via management technology, possibly in a multiple-trait analysis.

Potential effects of hormonal synchronized breeding on genetic evaluations of fertility traits in dairy cattle: A simulation study

About 30% of producers use hormone protocols to synchronize ovulation and perform timed artificial insemination (AI) in Canada. Days from calving to first service (CTFS) and first service to conception (FSTC) become masked phenotypes leading to biased genetic evaluations of cows for these fertility traits. The objectives of this study were to (1) demonstrate and quantify the potential amount of bias in genetic evaluations, and (2) find a procedure that could remove the bias. Simulation was used for both objectives. The proposed solution was to identify cows that have been treated by hormone protocols, make their CTFS and FSTC missing, and perform a multiple trait analysis including traits that have high genetic correlations with CTFS and FSTC, and which are not affected by the hormone protocols themselves. A total of 12 scenarios (S1-S12) were tested, changing the percentage of herds and cows that were randomly selected to be under timed AI. Cows that were given hormone protocols had CTFS of 86 d and FSTC of 0, which were used in genetic evaluation. Four criteria were used to indirectly measure the presence of bias: (1) the correlation between true (TBV) and estimated (EBV) breeding values (accuracy); (2) the differences in the mean EBV of top 25, 50, and 75 sires; (3) changes in correlation between TBV and EBV rankings; and (4) the changes in mean EBV over the simulated generations. All criteria changed unfavorably and proportionally to the increased use of timed AI. The accuracy within each class of animals (cows, dams, or sires) decreased proportionally with increased use of timed AI, varying from 0.32 (S12) to 0.52 (S1) for bull EBV for CTFS. The average EBV of the top sires (best 25, 50, 75, or 100 sires) approached population average EBV values when increasing the number of treated animals. The sire rank correlation between EBV and TBV within simulated scenarios was smaller for scenarios with more synchronized animals, going from 0.38 (S12) to 0.67 (S1). The long-term use of hormonal synchronized cows clearly decreased the mean EBV over generations in the population for CTFS and FSTC. The inclusion of genetically correlated traits in a multiple trait model was effective in removing the bias due to the presence of hormonal synchronized cows. However, given the constraints within the simulation, it is important that further investigation with real data is conducted to determine the true effect of including timed AI records within genetic evaluations of fertility traits in dairy cattle.

Association of lipid-related genes implicated in conceptus elongation with female fertility traits in dairy cattle

Elongation of the preimplantation conceptus is a requirement for pregnancy success in ruminants, and failures in this process are highly associated with subfertility in dairy cattle. Identifying genetic markers that are related to early conceptus development and survival and utilizing these markers in selective breeding can improve the reproductive efficiency of dairy herds. Here, we evaluated the association of 1,679 SNP markers within or close to 183 candidate genes involved in lipid metabolism of the elongating conceptus with different fertility traits in US Holstein cattle. A total of 27,371 bulls with predicted transmitting ability records for daughter pregnancy rate, cow conception rate, and heifer conception rate were used as the discovery population. The associations found in the discovery population were validated using 2 female populations (1,122 heifers and 2,138 lactating cows) each with 4 fertility traits, including success to first insemination, number of services per conception, age at first conception for heifers, or days open for cows. Marker effects were estimated using a linear mixed model with SNP genotype as a linear covariate and a random polygenic effect. After multiple testing correction, 39 SNP flagging 27 candidate genes were associated with at least one fertility trait in the discovery population. Of these 39 markers, 3 SNP were validated in the heifer population and 4 SNP were validated in the cow population. The 3 SNP validated in heifers are located within or near genes CAT, MYOF, and RBP4, and the 4 SNP validated in lactating cows are located within or close to genes CHKA, GNAI1, and HMOX2. These validated genes seem to be relevant for reducing pregnancy losses, and the SNP within these genes are excellent candidates for inclusion in genomic tests to improve reproductive performance in dairy cattle.

Fertility traits of Holstein, Brown Swiss, Simmental, and Alpine Grey cows are differently affected by herd productivity and milk yield of individual cows

Milk yield has a strong effect on fertility, but it may vary across different herds and individual cows. Therefore, the aim of this study was to assess the effects of breed and its interaction with level of milk production at the herd level (Herd-L) and at a cow-within-herd level (Cow-L) on fertility traits in dairy cattle. Data were gathered from Holstein (n = 17,688), Brown Swiss (n = 32,697), Simmental (n = 27,791), and Alpine Grey (n = 13,689) cows in northeastern Italy. The analysis was based on records from the first 3 lactations in the years 2011 to 2014. A mixed model was fitted to establish milk production levels of the various herds (Herd-L) and individual cows (Cow-L) using milk as a response variable. The interval fertility traits were interval from calving to first service, interval from first service to conception, and number of days open. The success traits were nonreturn rate at 56 d after first service, pregnancy rate at first service, and the number of inseminations. The interval from calving to first service, interval from first service to conception, and number of days open were analyzed using a Cox's proportional hazards model. The nonreturn rate at 56 d after first service, pregnancy rate at first service, and the number of inseminations were analyzed using logistic regression. There was a strong interaction between breed and productivity class at both Herd-L and Cow-L on all traits. The effects of herd and cow productivity differed from each other and differed among breeds. The dual-purpose Simmental and Alpine Grey breeds had better fertility than the specialized Holstein and Brown Swiss dairy cows; this difference is only partly attributable to different milk yields. Greater herd productivity can result in higher fertility in cows, whereas higher milk yield of individual cows within a herd results in lower fertility. These effects at both Herd-L and Cow-L are curvilinear and are stronger in dual-purpose breeds, which was more evident from low to intermediate milk yield levels than from central to high productivity classes. Disentangling the effects of milk productivity on fertility at Herd-L and Cow-L and taking the nonlinearity of response into account could lead to better modeling of populations within breed. It could also help with management-for example, in precision dairy farming of dairy and dual-purpose cattle. Moreover, assessing the fertility of various breeds and their different responses to herd and individual productivity levels could be useful in devising more profitable crossbreeding programs in different dairy systems.

Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle.

BackgroundGenome-wide association studies (GWAS) are a powerful tool for detecting genomic regions explaining variation in phenotype. The objectives of the present study were to identify or refine the positions of genomic regions affecting milk production, milk components and fertility traits in Canadian Holstein cattle, and to use these positions to identify genes and pathways that may influence these traits.ResultSeveral QTL regions were detected for milk production (MILK), fat production (FAT), protein production (PROT) and fat and protein deviation (FATD, PROTD respectively). The identified QTL regions for production traits (including milk production) support previous findings and some overlap with genes with known relevant biological functions identified in earlier studies such as DGAT1 and CPSF1. A significant region on chromosome 21 overlapping with the gene FAM181A and not previous linked to fertility in dairy cattle was identified for the calving to first service interval and days open. A functional enrichment analysis of the GWAS results yielded GO terms consistent with the specific phenotypes tested, for example GO terms GO:0007595 (lactation) and GO:0043627 (response to estrogen) for milk production (MILK), GO:0051057 (positive regulation of small GTPase mediated signal transduction) for fat production (FAT), GO:0040019 (positive regulation of embryonic development) for first service to calving interval (CTFS) and GO:0043268 (positive regulation of potassium ion transport) for days open (DO). In other cases the connection between the enriched GO terms and the traits were less clear, for example GO:0003279 (cardiac septum development) for FAT and GO:0030903 (notochord development) for DO trait.ConclusionThe chromosomal regions and enriched pathways identified in this study confirm several previous findings and highlight new regions and pathways that may contribute to variation in production or fertility traits in dairy cattle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0386-1) contains supplementary material, which is available to authorized users.

Explorations in genome-wide association studies and network analyses with dairy cattle fertility traits

The objective of this study was to identify single nucleotide polymorphisms and gene networks associated with 3 fertility traits in dairy cattle—daughter pregnancy rate, heifer conception rate, and cow conception rate—using different approaches. Deregressed predicted transmitting abilities were available for approximately 24,000 Holstein bulls and 36,000 Holstein cows sampled from the National Dairy Database with high-density genotypes. Of those, 1,732 bulls and 375 cows had been genotyped with the Illumina BovineHD Genotyping BeadChip (Illumina Inc., San Diego, CA). The remaining animals were genotyped with various chips of lower density that were imputed to high density. Univariate and trivariate genome-wide association studies (GWAS) with both medium- (60,671 markers) and high-density (312,614 markers) panels were performed for daughter pregnancy rate, heifer conception rate, and cow conception rate using GEMMA (version 0.94; http://www.xzlab.org/software.html). Analyses were conducted using bulls only, cows only, and a sample of both bulls and cows. The partial correlation and information theory algorithm was used to develop gene interaction networks. The most significant markers were further investigated to identify putatively associated genes. Little overlap in associated genes could be found between GWAS using different reference populations of bulls only, cows only, and combined bulls and cows. The partial correlation and information theory algorithm was able to identify several genes that were not identified by ordinary GWAS. The results obtained herein will aid in further dissecting the complex biology underlying fertility traits in dairy cattle, while also providing insight into the nuances of GWAS.

Validation of associations for female fertility traits in Nordic Holstein, Nordic Red and Jersey dairy cattle

BackgroundThe results obtained from genome-wide association studies (GWAS) often show pronounced disagreements. Validation of association studies is therefore desired before marker information is incorporated in selection decisions. A reliable way to confirm a discovered association between genetic markers and phenotypes is to validate the results in different populations. Therefore, the objective of this study was to validate single nucleotide polymorphism (SNP) marker associations to female fertility traits identified in the Nordic Holstein (NH) cattle population in the Nordic Red (NR) and Jersey (JER) cattle breeds. In the present study, we used data from 3,475 NH sires which were genotyped with the BovineSNP50 Beadchip to discover associations between SNP markers and eight female fertility-related traits. The significant SNP markers were then tested in NR and JER cattle.ResultsA total of 4,474 significant associations between SNP markers and eight female fertility traits were detected in NH cattle. These significant associations were then validated in the NR (4,998 sires) and JER (1,225 sires) dairy cattle populations. We were able to validate 836 of the SNPs discovered in NH cattle in the NR population, as well as 686 SNPs in the JER population. 152 SNPs could be confirmed in both the NR and JER populations.ConclusionsThe present study presents strong evidence for association of SNPs with fertility traits across three cattle breeds. We provide strong evidence that SNPs for many fertility traits are concentrated at certain areas on the genome (BTA1, BTA4, BTA7, BTA9, BTA11 and BTA13), and these areas would be highly suitable for further study in order to identify candidate genes for female fertility traits in dairy cattle.

Short communication: A missense mutation in the PROP1 (prophet of Pit 1) gene affects male fertility and milk production traits in the US Holstein population

In previous studies, we reported significant associations of the POU1F1 pathway genes with reproduction and production traits in several dairy cattle populations. Polymorphisms in genes of this pathway were found to be associated with both female and male fertility traits in dairy cattle. The POU1F1 gene is a direct downstream target for the regulation of the prophet of Pit1 (PROP1) gene, also known as PROP paired-like homeobox 1. Interestingly, the position of PROP1 coincides with a quantitative trait locus affecting ovulation rate in cattle. Therefore, the objective of this study was to investigate whether PROP1 affects fertility and milk production traits in Holstein cattle. Using the DNA pooling sequencing approach, a missense single nucleotide polymorphism that replaces a histidine amino acid with an arginine was detected in exon 3 of PROP1. The arginine allele was found to be associated with a decrease in sire conception rate and an increase in productive life, protein yield, and net merit index in a population of 1,951 Holstein bulls. The transcription factors produced from the histidine and arginine isoforms are known to have different transcription, DNA binding, and regulation activities. As such, we propose that the association of the arginine isoform with decreased bull fertility is likely caused by reduced activity of this allele in male functions. The findings of this study suggest PROP1 polymorphisms as candidates in selection programs for fertility, health, and milk production traits in dairy cattle.

Exploration of relationships between production and fertility traits in dairy cattle via association studies of SNPs within candidate genes derived by expression profiling

The objective of this work was to integrate findings from functional genomics studies with genome-wide association studies for fertility and production traits in dairy cattle. Association analyses of production and fertility traits with SNPs located within or close to 170 candidate genes derived from two gene expression studies and from the literature were performed. Data from 2294 Holstein bulls genotyped for 39557 SNPs were used. A total of 111 SNPs were located on chromosomal segments covered by a candidate gene. Allele substitution effects for each SNP were estimated using a mixed model with a fixed effect of marker and a random polygenic effect. Assumed covariance was derived either from marker or from pedigree information. Results from the analysis with the kinship matrix built from marker genotypes were more conservative than from the analysis with the pedigree-derived relationship matrix. From sixteen SNPs with significant effects on both classes of traits, ten provided evidence of an antagonistic relationship between productivity and fertility. However, we found four SNPs with favourable effects on fertility and on yield traits, one SNP with favourable effects on fertility and percentage traits, and one SNP with antagonistic effects on two fertility traits. While most quantitative genetic studies have proven genetic antagonisms between yield and functional traits, improvements in both production and functionality may be possible when focusing on a few relevant SNPs. Investigations combining input from quantitative genetics and functional genomics with association analysis may be applied for the identification of such SNPs.

Short communication: Validation of in vitro fertility genes in a Holstein bull population

Previously, we constructed an in vitro fertilization system for the identification of genes affecting fertility traits in dairy cattle. The efficiency of this system has been demonstrated by the identification of several genes affecting fertilization rate and early embryonic survival. However, to employ these genetic markers in marker- and gene-assisted selection programs, there is a need to validate in vitro results in phenotypic data sets collected in vivo. Thus, the objective of this study was to validate, in a population of Holstein bulls, the fertility trait genes we previously identified in an in vitro system. Estimated relative conception rate (ERCR) data from 222 Holstein bulls were obtained from 5 different artificial insemination companies in the United States. Bulls were genotyped for the genes FGF2, POU1F1, PRL, PRLR, GH, GHR, STAT5A, OPN, and UTMP, and the data were analyzed for association with ERCR using a mixed effects sire model. A stepwise model selection procedure revealed evidence of association with ERCR for FGF2 and STAT5A polymorphisms. The in vivo validation suggests that these genes can be used in gene-assisted selection programs for reproductive performance in dairy cattle. The genotypes found to be associated with low bull fertility in this study have been reported to be associated with high milk composition in previous studies. These findings provide molecular evidence for the antagonistic relationship between milk production and fertility observed for many years in different breeds of dairy cattle.

Associations between SNPs in the bovine GnRH receptor gene and breeding values for fertility traits in dairy cattle

Associations between SNPs in the bovine GnRH receptor gene and breeding values for fertility traits in dairy cattle

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

International genetic evaluation for fertility traits in dairy cattle

The objective of this study was to review and discuss the results of the first international evaluation for female fertility of Holstein dairy cattle. Fifteen countries, including Italy, provided breeding values of bulls and joined the evaluation. Four trait groups were used to analyze animal’s ability to became pregnant and animal’s abilityto recycle after calving. Italy submitted three traits: days to first service (DTFS), non-return rate at 56 days (NR56) and calving interval (CI). Genetic correlation between Italy and the other countries ranged from 0.72 to 0.94 for DTFS, from 0.25 to 0.90 for NR56 and from 0.67 to 0.87 for CI. Results represent another step forward in the international trade of dairy cattle genetic material.

Genetic correlations among body condition score, body weight, and fertility in dairy cows

Interest is accruing in indicator traits as predictors of fertility which: 1) can be more easily recorded; 2) can be measured early in life; and, 3) possess a co-heritability that is larger than the heritability of the fertility traits. Potentially interesting indicator traits include body condition score (BCS) and body weight (BW). The objective of this study was to estimate genetic (co) variances between BCS, BCS change, BW, BW change, and fertility traits in dairy cattle.

Genotype and feeding system effects and interactions for health and fertility traits in dairy cattle

The effects of feeding system, genotype and genotype by feeding system interactions on a range of health and fertility traits were investigated in Holstein Friesian cows at the Langhill Dairy Cattle Research Centre. There were two genetic groups: a selection (S) and control (C) line, housed and managed as one herd. Animals from each group were assigned to either a high concentrate (HC) or low concentrate (LC) feeding system and offered approximately 2500 kg and 1000 kg of concentrate per lactation on the HC and LC diets respectively. Feeding system had a significant effect on milk fever, days to first service and days to first heat. Lactation number had a significant effect ( P<0.05) on the incidence of mastitis, ketosis, retained placentas, milk fever and lameness and conception at first service. Effects of genotype were investigated first by comparing the two genetic groups and then by regressions of the health and fertility traits on pedigree index for fat plus protein (PI). Significant effects of PI were found for oestrus not observed, conception at first service, days to first heat, calving interval, days open and days to first service. The regression coefficient for mastitis on PI was also significantly different from zero ( P<0.05). There were no statistically significant genetic line by feeding system interactions, indicating that the observed line differences applied to both dietary treatments. Heritabilities for the health traits ranged between 0.00 and 0.08 and for the fertility traits they ranged between 0.02 and 0.15. Selection for high genetic merit in this herd, seems to have led to a deterioration in fertility but not health traits (with the exception of mastitis). These results, in line with those from studies in large populations, suggest that as genetic merit for production rises, fertility and some aspects of health are deteriorating.

Embryo viability and development after prostaglandin E 2 (PGE 2) addition to the semen and progesterone (P 4), solcoseryl ® and PGE 2 to the transfer medium

Milk yield has a strong effect on fertility, but it may vary across different herds and individual cows. Therefore, the aim of this study was to assess the effects of breed and its interaction with level of milk production at the herd level (Herd-L) and at a cow-within-herd level (Cow-L) on fertility traits in dairy cattle. Data were gathered from Holstein (n = 17,688), Brown Swiss (n = 32,697), Simmental (n = 27,791), and Alpine Grey (n = 13,689) cows in northeastern Italy. The analysis was based on records from the first 3 lactations in the years 2011 to 2014. A mixed model was fitted to establish milk production levels of the various herds (Herd-L) and individual cows (Cow-L) using milk as a response variable. The interval fertility traits were interval from calving to first service, interval from first service to conception, and number of days open. The success traits were nonreturn rate at 56 d after first service, pregnancy rate at first service, and the number of inseminations. The interval from calving to first service, interval from first service to conception, and number of days open were analyzed using a Cox's proportional hazards model. The nonreturn rate at 56 d after first service, pregnancy rate at first service, and the number of inseminations were analyzed using logistic regression. There was a strong interaction between breed and productivity class at both Herd-L and Cow-L on all traits. The effects of herd and cow productivity differed from each other and differed among breeds. The dual-purpose Simmental and Alpine Grey breeds had better fertility than the specialized Holstein and Brown Swiss dairy cows; this difference is only partly attributable to different milk yields. Greater herd productivity can result in higher fertility in cows, whereas higher milk yield of individual cows within a herd results in lower fertility. These effects at both Herd-L and Cow-L are curvilinear and are stronger in dual-purpose breeds, which was more evident from low to intermediate milk yield levels than from central to high productivity classes. Disentangling the effects of milk productivity on fertility at Herd-L and Cow-L and taking the nonlinearity of response into account could lead to better modeling of populations within breed. It could also help with management—for example, in precision dairy farming of dairy and dual-purpose cattle. Moreover, assessing the fertility of various breeds and their different responses to herd and individual productivity levels could be useful in devising more profitable crossbreeding programs in different dairy systems.