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Background Over the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits. However, in general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. To address these questions, we applied a two-step, within-breed GWAS approach on 15 traits (5 linked with milk production, 2 with udder health, and 8 with udder morphology) in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) cattle. We detected the most-promising candidate variants (CV) using imputed WGS of 2515 MON, 2203 NOR, and 6321 HOL bulls, and validated their effects in three younger populations of 23,926 MON, 9400 NOR, and 51,977 HOL cows. Results Bull sequence-based GWAS detected 84 QTL: 13, 10, and 30 for milk production traits; 3, 0, and 2 for somatic cell score (SCS); and 8, 2 and 16 for udder morphology traits, in MON, NOR, and HOL respectively. Five genomic regions with effects on milk production traits were shared among the three breeds whereas six (2 for production and 4 for udder morphology and health traits) had effects in two breeds. In 80 of these QTL, 855 CV were highlighted based on the significance of their effects and functional annotation. The subsequent GWAS on MON, NOR, and HOL cows validated 8, 9, and 23 QTL for production traits; 0, 0, and 1 for SCS; and 4, 1, and 8 for udder morphology traits, respectively. In 47 of the 54 confirmed QTL, the CV identified in bulls had more significant effects than single nucleotide polymorphisms (SNPs) from the standard 50K chip. The best CV for each validated QTL was located in a gene that was functionally related to production (36 QTL) or udder (9 QTL) traits. Conclusions Using this two-step GWAS approach, we identified and validated 54 QTL that included CV mostly located within functional candidate genes and explained up to 6.3% (udder traits) and 37% (production traits) of the genetic variance of economically important dairy traits. These CV are now included in the chip used to evaluate French dairy cattle and can be integrated into routine genomic evaluation.

Background The search for quantitative trait loci (QTL) affecting traits of interest in mammals is frequently limited to autosomes, with the X chromosome excluded because of its hemizygosity in males. This study aimed to assess the importance of the X chromosome in the genetic determinism of 11 complex traits related to milk production, milk composition, mastitis resistance, fertility, and stature in 236,496 cows from three major French dairy breeds (Holstein, Montbéliarde, and Normande) and three breeds of regional importance (Abondance, Tarentaise, and Vosgienne). Results Estimates of the proportions of heritability due to autosomes and X chromosome (h² X ) were consistent among breeds. On average over the 11 traits, h² X =0.008 and the X chromosome explained ~ 3.5% of total genetic variance. GWAS was performed within-breed at the sequence level (~ 200,000 genetic variants) and then combined in a meta-analysis. QTL were identified for most breeds and traits analyzed, with the exception of Tarentaise and Vosgienne and two fertility traits. Overall, 3, 74, 59, and 71 QTL were identified in Abondance, Montbéliarde, Normande, and Holstein, respectively, and most were associated with the most-heritable traits (milk traits and stature). The meta-analyses, which assessed a total of 157 QTL for the different traits, highlighted new QTL and refined the positions of some QTL found in the within-breed analyses. Altogether, our analyses identified a number of functional candidate genes, with the most notable being GPC3 , MBNL3 , HS6ST2 , and DMD for dairy traits; TMEM164 , ACSL4 , ENOX2 , HTR2C , AMOT , and IRAK1 for udder health; MAMLD1 and COL4A6 for fertility; and NRK , ESX1 , GPR50 , GPC3 , and GPC4 for stature. Conclusions This study demonstrates the importance of the X chromosome in the genetic determinism of complex traits in dairy cattle and highlights new functional candidate genes and variants for these traits. These results could potentially be extended to other species as many X-linked genes are shared among mammals.

Background Due to their contribution to global warming, methane emissions from ruminants have been the subject of considerable scientific interest. It has been proposed that such emissions might be reduced using genetic selection; proposed phenotypes differ in the measurement methods used (direct or predicted methane emissions) and in the unit under consideration (g/d, g/kg of milk, g/kg of intake, residual methane emissions). Identifying the quantitative trait loci (QTLs) and candidate genes responsible for genetic variation in methane emissions allows a better understanding of the underlying genetic architecture of these phenotypes. Therefore, the aim of this study was to identify the genomic regions associated with six methane traits predicted from milk mid-infrared (MIR) spectra (0.33 ≤ R 2  ≤ 0.88) in French Holstein dairy cows using genome-wide association studies at the whole-genome-sequence level. Results Six methane emission traits—in g/d, in g/kg of fat- and protein-corrected milk, and in g/kg of dry matter intake—were predicted from milk MIR spectra routinely collected by French milk recording companies. A genome-wide association study of the predicted methane emissions of 40,609 primiparous Holstein cows was conducted using imputed whole-genome-sequence data. This analysis revealed 57 genomic regions of interest; between 1 and 8 QTLs were identified on each of the autosomes except 4, 12, 21, 24 and 26. We identified multiple genomic regions that were shared by two or more predicted methane traits, illustrating their common genetic basis. Functional annotation revealed potential candidate genes, in particular FASN , DGAT1 , ACSS2 , and KCNIP4 , which could be involved in biological pathways possibly related to methane production. Conclusions The methane traits studied here, which were predicted from milk MIR spectra, appear to be highly polygenic. Several genomic regions associated with these traits contain candidate genes previously associated with milk traits. Functional annotation and comparisons with studies using direct methane measurements support some potential candidate genes involved in biological pathways related to methane production. However, the overlap with genes influencing milk traits highlights the challenge of distinguishing whether these regions genuinely influence methane emissions or reflect the use of milk MIR spectra to predict the phenotypes.

Background Sequence-based genome-wide association studies (GWAS) provide high statistical power to identify candidate causal mutations when a large number of individuals with both sequence variant genotypes and phenotypes is available. A meta-analysis combines summary statistics from multiple GWAS and increases the power to detect trait-associated variants without requiring access to data at the individual level of the GWAS mapping cohorts. Because linkage disequilibrium between adjacent markers is conserved only over short distances across breeds, a multi-breed meta-analysis can improve mapping precision. Results To maximise the power to identify quantitative trait loci (QTL), we combined the results of nine within-population GWAS that used imputed sequence variant genotypes of 94,321 cattle from eight breeds, to perform a large-scale meta-analysis for fat and protein percentage in cattle. The meta-analysis detected (p ≤ 10 −8 ) 138 QTL for fat percentage and 176 QTL for protein percentage. This was more than the number of QTL detected in all within-population GWAS together (124 QTL for fat percentage and 104 QTL for protein percentage). Among all the lead variants, 100 QTL for fat percentage and 114 QTL for protein percentage had the same direction of effect in all within-population GWAS. This indicates either persistence of the linkage phase between the causal variant and the lead variant across breeds or that some of the lead variants might indeed be causal or tightly linked with causal variants. The percentage of intergenic variants was substantially lower for significant variants than for non-significant variants, and significant variants had mostly moderate to high minor allele frequencies. Significant variants were also clustered in genes that are known to be relevant for fat and protein percentages in milk. Conclusions Our study identified a large number of QTL associated with fat and protein percentage in dairy cattle. We demonstrated that large-scale multi-breed meta-analysis reveals more QTL at the nucleotide resolution than within-population GWAS. Significant variants were more often located in genic regions than non-significant variants and a large part of them was located in potentially regulatory regions.

Background DNA methylation (DNAm) plays an important functional role and is influenced by genetic variants known as methylation QTLs (meQTLs). The majority of meQTL studies have been conducted in human blood. Despite its unique landscape, the genetic regulation of sperm DNAm remains largely unexplored. In this study, we leveraged DNAm measured in sperm from 405 Holstein bulls using reduced representation bisulfite sequencing (RRBS) and performed sequence-level genome-wide association studies for 166,985 variable CpGs (s.d. >5%). We reported heritability estimates and have mapped both cis- meQTLs and trans- meQTLs. Results Heritability estimates ranged from 0 to 1 and averaged 0.26 across all selected CpGs, with 76% of estimates above 0.1. The meQTL mapping revealed that 32.9% of the CpGs had a cis- meQTL, 3.6% had a trans- meQTL and 1.0% had both cis- and trans- meQTLs. The cis- CpGs were located on average 261 kb (absolute mean) from their cis- meQTL top SNPs (defined by the most significant association). MeQTLs were enriched in featured genomic annotations, including regions surrounding transcription start sites and ATAC-seq peaks. We also identified spurious trans- associations by analyzing data across multiple genome assemblies, including the construction of a partial pangenome. Additionally, eight trans- meQTL hotspots, defined as variants associated with at least 30 trans- CpGs, were identified and overlapped with genes involved in epigenetic regulation. Using peripheral blood mononuclear cell DNAm from 54 out of the 405 bulls, we did not observe a similar effect of the trans- meQTL hotspots to that one observed in sperm. Conclusions For the first time, meQTLs have been detected and characterized in bovine sperm, contributing to a better understanding of the transmission of paternally inherited DNAm marks. These findings provide useful information for further research aimed at integrating epigenetic information into the prediction of performance traits.

Background The professional impact of upper limb lymphedema, which affects 15–20% of women after breast cancer treatment, has been poorly evaluated. Objective To analyze lymphedema characteristics and global lymphedema- and/or sleeve-attributed impact (mildly inconvenient to severely debilitating) on professional activities, workplace relationships, and workstation ergonomics. Methods Patients received a standardized, anonymous, self-administered questionnaire at consultation/hospitalization for treatment in a specialized lymphedema management center. Results All 134 consecutive women (March/2015–March/2017; median age 54), with 53-month median lymphedema duration and 34% median excess volume, were included; 35% considered global impact (arm-use impairment) high. For high vs. low global impact during occupational activities, univariate analyses identified global impairment as being associated with the low (23.8%), intermediate (60%), or high (63.2%) ( p  < 0.01) arm-use level, while multivariate analyses retained intermediate (OR 6.9 [95% CI 1.1–118.1], p  < 0.01) and high (OR 4.5 [95% CI 1.5–37.3], p  < 0.05) vs. low arm-use level. Lymphedema affected the careers of 70 (52.2%) patients, mostly those with severely impaired arm movement (53.8% vs. 10.2, p  < 0.001), without modifying their relationships with colleagues and superiors for 84 (62.7%). Highly impaired women reported changed relationships with colleagues (45% vs. 20%, p  < 0.01) and superiors (43.6% vs. 16.9%, p  < 0.01). Only 10 women’s (7.5%) job changes reflected lymphedema or its treatment. Workplace adaptations (53% ergonomic) were made for 36 (26.9%) patients, mostly those with greater arm-movement impairment (43.6% vs. 25.3%, p  < 0.05), who were highly satisfied (86%). Conclusion Upper limb lymphedema can significantly impact work, sometimes upending careers. The rare workstation adaptations were beneficial. Occupational physicians should assess lymphedema-attributed difficulties to improve working conditions.

Abstract GWAS conducted directly on imputed whole genome sequence have led to the identification of numerous genetic variants associated with agronomic traits in cattle. However, such variants are often simply markers in linkage disequilibrium with the actual causal variants, which is a limiting factor for the development of accurate genomic predictions. It is possible to identify causal variants by integrating information on how variants impact gene expression into GWAS output. RNA splicing plays a major role in regulating gene expression. Thus, assessing the effect of variants on RNA splicing may explain their function. Here, we use a high-throughput strategy to functionally analyse putative splice-disrupting variants in the bovine genome. Using GWAS, massively parallel reporter assay and deep learning algorithms designed to predict splice-disrupting variants, we identify 38 splice-disrupting variants associated with complex traits in cattle, three of which could be classified as causal. Our results indicate that splice-disrupting variants are widely found in the quantitative trait loci related to these phenotypes. Using our combined approach, we also assess the validity of splicing predictors originally developed to analyse human variants in the context of the bovine genome.

Background Bovine paratuberculosis is a contagious disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), with adverse effects on animal welfare and serious economic consequences. Published results on host genetic resistance to MAP are inconsistent, mainly because of difficulties in characterizing the infection status of cows. The objectives of this study were to identify quantitative trait loci (QTL) for resistance to MAP in Holstein and Normande cows with an accurately defined status for MAP. Results From MAP-infected herds, cows without clinical signs of disease were subjected to at least four repeated serum ELISA and fecal PCR tests over time to determine both infected and non-infected statuses. Clinical cases were confirmed using PCR. Only cows that had concordant results for all tests were included in further analyses. Positive and control cows were matched within herd according to their birth date to ensure a same level of exposure to MAP. Cows with accurate phenotypes, i.e. unaffected (control) or affected (clinical or non-clinical cases), were genotyped with the Illumina BovineSNP50 BeadChip. Genotypes were imputed to whole-genome sequences using the 1000 Bull Genomes reference population (run6). A genome-wide association study (GWAS) of MAP status of 1644 Holstein and 649 Normande cows, using either two (controls versus cases) or three classes of phenotype (controls, non-clinical and clinical cases), revealed three regions, on Bos taurus (BTA) chromosomes 12, 13, and 23, presenting significant effects in Holstein cows, while only one of those was identified in Normande cows (BTA23). The most significant effect was found on BTA13, in a short 8.5-kb region. Conditional analyses revealed that only one causal variant may be responsible for the effects observed on each chromosome with the ABCC4 (BTA12), CBFA2T2 (BTA13), and IER3 (BTA23) genes as good functional candidates. Conclusions A sequence-based GWAS on cows for which resistance to MAP was accurately defined, was able to identify candidate variants located in genes that were functionally related to resistance to MAP; these explained up to 28% of the genetic variance of the trait. These results are very encouraging for efforts towards implementation of a breeding strategy aimed at improving resistance to paratuberculosis in Holstein cows.

Background Milk quality in dairy cattle is routinely assessed via analysis of mid-infrared (MIR) spectra; this approach can also be used to predict the milk’s cheese-making properties (CMP) and composition. When this method of high-throughput phenotyping is combined with efficient imputations of whole-genome sequence data from cows’ genotyping data, it provides a unique and powerful framework with which to carry out genomic analyses. The goal of this study was to use this approach to identify genes and gene networks associated with milk CMP and composition in the Montbéliarde breed. Results Milk cheese yields, coagulation traits, milk pH and contents of proteins, fatty acids, minerals, citrate, and lactose were predicted from MIR spectra. Thirty-six phenotypes from primiparous Montbéliarde cows (1,442,371 test-day records from 189,817 cows) were adjusted for non-genetic effects and averaged per cow. 50 K genotypes, which were available for a subset of 19,586 cows, were imputed at the sequence level using Run6 of the 1000 Bull Genomes Project (comprising 2333 animals). The individual effects of 8.5 million variants were evaluated in a genome-wide association study (GWAS) which led to the detection of 59 QTL regions, most of which had highly significant effects on CMP and milk composition. The results of the GWAS were further subjected to an association weight matrix and the partial correlation and information theory approach and we identified a set of 736 co-associated genes. Among these, the well-known caseins, PAEP and DGAT1 , together with dozens of other genes such as SLC37A1 , ALPL , MGST1 , SEL1L3 , GPT , BRI3BP , SCD , GPAT4 , FASN , and ANKH , explained from 12 to 30% of the phenotypic variance of CMP traits. We were further able to identify metabolic pathways (e.g., phosphate and phospholipid metabolism and inorganic anion transport) and key regulator genes, such as PPARA , ASXL3, and bta - mir - 200c that are functionally linked to milk composition. Conclusions By using an approach that integrated GWAS with network and pathway analyses at the whole-genome sequence level, we propose candidate variants that explain a substantial proportion of the phenotypic variance of CMP traits and could thus be included in genomic evaluation models to improve milk CMP in Montbéliarde cows.

Structural variants (SVs) correspond to different types of genomic variants larger than 50 bp. Many findings suggest the use of long-read (LR) rather than short-read (SR) sequencing to improve the accuracy of SVs detection. Here, we present the results of an in-depth analysis for detection of SVs, mainly large insertions and deletions, in 14 French bovine breeds, based on whole-genome sequence (WGS) data comprising 176 LR and 571 SR samples, with 154 individuals having both LR and SR data available. We first investigated possible biases on the performances of well-known SVs detection tools, namely CUTESV, PBSV, and SNIFFLES, using LR from different technologies, including PacBio HiFi, Oxford ONT, and PacBio CLR. We subsequently highlighted the abilities of tools for detecting SVs (DELLY, LUMPY, and MANTA) and for genotyping known SVs (GRAPHTYPER, SVTYPER, PARAGRAPH, and VG toolkit) using SR data. We then show how the incremental composition of samples in the reference panel affected the SVs genotyping for six validation individuals sequenced in SR. We then searched for the optimal parameters and created the final SVs reference panel consisting of 25,191 deletions and 30,118 insertions. Finally, we emphasized the landscape of the genotyped SVs segregating across 571 SR individuals of 14 breeds.