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Reproductive traits of dairy cattle are bound to the actual efficiency of farm operation, which therefore show great economic importance. Among them, some traits were deemed to be simultaneously affected by service sire and mating cow. Service sires are proved to play an important role in reproduction process of cows. However, limited study explored the genetic effect of service sire (GESS), let alone the genomic prediction of this effect. In the present study, 2244 genotyped bulls together with phenotypic records were used to predict the GESS on conception rate, 56-day non-return rate, calving ease, stillbirth and gestation length. The feasibilities of multi-step genomic best linear unbiased predictor (msGBLUP) and single-step genomic best linear unbiased predictor (ssGBLUP) were investigated under different scenarios, that is, different marker densities and validation population. The predictive accuracies and unbiasedness for GESS ranged from 0.159 to 0.647 and from 0.202 to 2.018, respectively, when validated on young bulls, while the accuracies and unbiasedness ranged from 0.409 to 0.802 and 0.333 to 1.146 when validated on random split data sets. It is feasible to predict GESS on reproductive traits by using a linear mixed model and genomic data, and high-density marker panel had limited contribution to the prediction. This research investigated the potential factors that influence the genomic prediction of GESS on reproductive traits and indicated the possibility of genomic selection on GESS, both in ideal and practical circumstances.

The German Longhaired Pointer (GLP) breed is a versatile pointer dog breed. In the current study, we investigated the genetic diversity of these dogs based on SNP array data and compared it to 11 other pointer setter breeds. The results show that GLPs have a relatively low level of inbreeding among these pointer breeds. In addition, with the availability of pedigree information of the GLPs, we demonstrate that the correlation between pedigree-based inbreeding and genotype-based inbreeding coefficients was high (R = 0.89 and 0.85). By investigating population structure between these 12 pointer setter breeds we showed that GLP is a breed distinct from other pointers and shares common ancestry with a few other pointing breeds. Finally, we identified selection signatures in GLPs using the runs of homozygosity islands method. The most significant runs of homozygosity island was detected on chromosome 30 harboring the genes RYR3, FMN1, and GREM1. The RYR3 gene plays a role in skeletal muscle contraction while the FMN1 and GREM1 genes are involved in limb development. The selection on these three genes could have contributed to the excellent athletic performance of GLPs, which is an extremely important characteristic for this hunting dog.

Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9 cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.

Background Structural variants (SVs) are chromosomal segments that differ between genomes, such as deletions, duplications, insertions, inversions and translocations. The genomics revolution enabled the discovery of sub-microscopic SVs via array and whole-genome sequencing (WGS) data, paving the way to unravel the functional impact of SVs. Recent human expression QTL mapping studies demonstrated that SVs play a disproportionally large role in altering gene expression, underlining the importance of including SVs in genetic analyses. Therefore, this study aimed to generate and explore a high-quality bovine SV catalogue exploiting a unique cattle family cohort data (total 266 samples, forming 127 trios). Results We curated 13,731 SVs segregating in the population, consisting of 12,201 deletions, 1,509 duplications, and 21 multi-allelic CNVs (> 50-bp). Of these, we validated a subset of copy number variants (CNVs) utilising a direct genotyping approach in an independent cohort, indicating that at least 62% of the CNVs are true variants, segregating in the population. Among gene-disrupting SVs, we prioritised two likely high impact duplications, encompassing ORM1 and POPDC3 genes, respectively. Liver expression QTL mapping results revealed that these duplications are likely causing altered gene expression, confirming the functional importance of SVs. Although most of the accurately genotyped CNVs are tagged by single nucleotide polymorphisms (SNPs) ascertained in WGS data, most CNVs were not captured by individual SNPs obtained from a 50K genotyping array. Conclusion We generated a high-quality SV catalogue exploiting unique whole genome sequenced bovine family cohort data. Two high impact duplications upregulating the ORM1 and POPDC3 are putative candidates for postpartum feed intake and hoof health traits, thus warranting further investigation. Generally, CNVs were in low LD with SNPs on the 50K array. Hence, it remains crucial to incorporate CNVs via means other than tagging SNPs, such as investigation of tagging haplotypes, direct imputation of CNVs, or direct genotyping as done in the current study. The SV catalogue and the custom genotyping array generated in the current study will serve as valuable resources accelerating utilisation of full spectrum of genetic variants in bovine genomes.

This article mainly focuses on the challenges associated with implementing mating control and is the next in line of the series on the concepts of honey bee breeding programs that puzzle many beekeepers around the globe.

Animal breeding techniques offer potential to reduce enteric emissions of ruminants to lower the environmental impact of dairy farming. The aim of this study was to estimate the heritability and repeatability of methane (CH4) concentrations, using the largest data set from long-term repeatedly recorded CH4 on cows to date, and to evaluate (1) the accuracy of breeding values for different CH4 traits, including using visits or weekly means, and (2) recording strategies (with varying numbers of records and recorded daughters per sire). The data comprised of long-term recording of CH4 and carbon dioxide (CO2), from 1,746 Holstein Friesian cows, on 14 commercial dairy farms throughout the Netherlands. Emissions were recorded in 10- to 35-s intervals, between 64 and 436 d, depending on farms. From each robot visit, CH4 and CO2 concentrations were summarized into various traits, averaged per visit and per week: mean, median, mean log, and mean CH4/CO2 ratio. Genetic parameters were estimated with animal repeatability models, using a restricted maximum likelihood procedure, and a relationship matrix based on genotypes and pedigree. The heritability was equal for mean and median CH4 per visit (0.13) but lower for logCH4 and CH4/CO2 (0.07 and 0.01, respectively). Phenotypic and genetic correlations were high (≥0.78) between the CH4 traits, apart from the genetic correlations with the CH4/CO2 trait, which were negative. To achieve a minimum reliability of 50% for the estimated breeding value of a bull, 25 records on mean CH4, measured on 10 different daughters, were sufficient. Although the heritability and repeatability were higher for weekly (0.32 and 0.68, respectively) than for visit mean CH4 (0.13 and 0.30, respectively), the reliabilities of estimated breeding values from visit or weekly means were equal; thus, we found no advantage in averaging records to weekly means for genetic evaluations.

Background In genomic prediction, it is common to centre the genotypes of single nucleotide polymorphisms based on the allele frequencies in the current population, rather than those in the base generation. The mean breeding value of non-genotyped animals is conditional on the mean performance of genotyped relatives, but can be corrected by fitting the mean performance of genotyped individuals as a fixed regression. The associated covariate vector has been referred to as a ‘J-factor’, which if fitted as a fixed effect can improve the accuracy and dispersion bias of sire genomic estimated breeding values (GEBV). To date, this has only been performed on populations with a single breed. Here, we investigated whether there was any benefit in fitting a separate J-factor for each breed in a three-way crossbred population, and in using pedigree-based expected or genome-based estimated breed fractions to define the J-factors. Results For body weight at 7 days, dispersion bias decreased when fitting multiple J-factors, but only with a low proportion of genotyped individuals with selective genotyping. On average, the mean regression coefficients of validation records on those of GEBV increased with one J-factor compared to none, and further increased with multiple J-factors. However, for body weight at 35 days this was not observed. The accuracy of GEBV remained unchanged regardless of the J-factor method used. Differences between the J-factor methods were limited with correlations approaching 1 for the estimated covariate vector, the estimated coefficients of the regression on the J-factors, and the GEBV. Conclusions Based on our results and in the particular design analysed here, i.e. all the animals with phenotype are of the same type of crossbreds, fitting a single J-factor should be sufficient, to reduce dispersion bias. Fitting multiple J-factors may reduce dispersion bias further but this depends on the trait and genotyping rate. For the crossbred population analysed, fitting multiple J-factors has no adverse consequences and if this is done, it does not matter if the breed fractions used are based on the pedigree-expectation or the genomic estimates. Finally, when GEBV are estimated from crossbred data, any observed bias can potentially be reduced by including a straightforward regression on actual breed proportions.

Studying gene flow between different livestock breeds will benefit the discovery of genes related to production traits and provide insight into human historical breeding. Chinese pigs have played an indispensable role in the breeding of Western commercial pigs. However, the differences in the timing and volume of the contribution of pigs from different Chinese regions to Western pigs are not yet apparent. In this paper, we combine the whole-genome sequencing data of 592 pigs from different studies and illustrate patterns of gene flow from Chinese pigs into Western commercial pigs. We describe introgression patterns from four distinct Chinese indigenous groups into five Western commercial groups. There were considerable differences in the number and length of the putative introgressed segments from Chinese pig groups that contributed to Western commercial pig breeds. The contribution of pigs from different Chinese geographical locations to a given western commercial breed varied more than that from a specific Chinese pig group to different Western commercial breeds, implying admixture within Europe after introgression. Within different Western commercial lines from the same breed, the introgression patterns from a given Chinese pig group seemed highly conserved, suggesting that introgression of Chinese pigs into Western commercial pig breeds mainly occurred at an early stage of breed formation. Finally, based on analyses of introgression signals, allele frequencies, and selection footprints, we identified a ∼2.65 Mb Chinese-derived haplotype under selection in Duroc pigs (CHR14: 95.68–98.33 Mb). Functional and phenotypic studies demonstrate that this PRKG1 haplotype is related to backfat and loin depth in Duroc pigs. Overall, we demonstrate that the introgression history of domestic pigs is complex and that Western commercial pigs contain distinct traces of mixed ancestry, likely derived from various Chinese pig breeds.

The pig IPEC-J2 and chicken SL-29 cell lines are of interest because of their untransformed nature and wide use in functional studies. Molecular characterization of these cell lines is important to gain insight into possible molecular aberrations. The aim of this paper is to provide a molecular and epigenetic characterization of the IPEC-J2 and SL-29 cell lines, a cell-line reference for the FAANG community, and future biomedical research. Whole genome sequencing, gene expression, DNA methylation, chromatin accessibility, and ChIP-seq of four histone marks (H3K4me1, H3K4me3, H3K27ac, H3K27me3) and an insulator (CTCF) are used to achieve these aims. Heteroploidy (aneuploidy) of various chromosomes was observed from whole genome sequencing analysis in both cell lines. Furthermore, higher gene expression for genes located on chromosomes with aneuploidy in comparison to diploid chromosomes was observed. Regulatory complexity of gene expression, DNA methylation, and chromatin accessibility was investigated through an integrative approach.

Aneuploidy is the loss or gain of one or more chromosomes. Although it is a rare phenomenon in liveborn individuals, it is observed in livestock breeding populations. These breeding populations are often routinely genotyped and the genotype intensity data from single nucleotide polymorphism (SNP) arrays can be exploited to identify aneuploidy cases. This identification is a time-consuming and costly task, because it is often performed by visual inspection of the data per chromosome, usually done in plots of the intensity data by an expert. Therefore, we wanted to explore the feasibility of automated image classification to replace (part of) the visual detection procedure for any diploid species. The aim of this study was to develop a deep learning Convolutional Neural Network (CNN) classification model based on chromosome level plots of SNP array intensity data that can classify the images into disomic, monosomic and trisomic cases. A multispecies dataset enriched for aneuploidy cases was collected containing genotype intensity data of 3321 disomic, 1759 monosomic and 164 trisomic chromosomes. The final CNN model had an accuracy of 99.9%, overall precision was 1, recall was 0.98 and the F1 score was 0.99 for classifying images from intensity data. The high precision assures that cases detected are most likely true cases, however, some trisomy cases may be missed (the recall of the class trisomic was 0.94). This supervised CNN model performed much better than an unsupervised k-means clustering, which reached an accuracy of 0.73 and had especially difficult to classify trisomic cases correctly. The developed CNN classification model provides high accuracy to classify aneuploidy cases based on images of plotted X and Y genotype intensity values. The classification model can be used as a tool for routine screening in large diploid populations that are genotyped to get a better understanding of the incidence and inheritance, and in addition, avoid anomalies in breeding candidates.

To reduce methane (CH4) emissions of dairy cows by animal breeding, CH4 measurements have to be recorded on thousands of individual cows. Currently, several techniques are used to phenotype cows for CH4, differing in costs and applicability. However, there is uncertainty about the agreement between techniques. To judge the similarity and repeatability between measurements of different recording techniques, the repeatability, heritability, and genetic correlation are useful metrics. Therefore, our objective was to estimate (1) the repeatability and heritability for CH4 and carbon dioxide production recorded by GreenFeed (GF) and for CH4 and carbon dioxide concentration measured by cost-effective but less accurate sniffers, and (2) the genetic correlation between CH4 recorded with these 2 different on farm and high throughput techniques. Data were available from repeated measurements of CH4 production (grams/day) by GF units and of CH4 concentration (ppm) by sniffers, recorded on commercial dairy farms in the Netherlands. The final data comprised 24,284 GF daily means from 822 cows, 170,826 sniffer daily means from 1,800 cows, and 1,786 daily means from 75 cows by both GF and sniffer (in the same period). Additionally, CH4 records were averaged per week. For daily and weekly mean GF CH4 the heritabilities were 0.19 ± 0.02 and 0.33 ± 0.04, and for daily and weekly mean sniffer CH4 the heritabilities were similar and were 0.18 ± 0.01 and 0.32 ± 0.02, respectively. Phenotypic correlations between GF CH4 production and sniffer CH4 concentration were moderate (0.39 ± 0.03 for daily means and 0.37 ± 0.05 for weekly means). However, genetic correlations were high; 0.71 ± 0.13 for daily means and 0.76 ± 0.15 for weekly means. The high genetic correlation indicates that selection on low CH4 concentrations (ppm) recorded by the cost-effective sniffer method, will result in reduced CH4 production (grams/day) as recorded with GF.

Commonly, female European eels are injected weekly with pituitary extract (PE) from carp (CPE) or salmon (SPE) to induce sexual maturation. However, a PE is a mixture of gonadotropins and other hormones that are not specific for eel and rapidly cleared from circulation. The aim of this study was therefore to test the effects of highly stable eel-specific recombinant gonadotropins (rGTHs) on oocyte development in vitro and in vivo in European eels. For the in vitro trial, the dose–effect responses of maturing eel oocytes on CPE and recombinant luteinizing hormone (rLH) were studied before and after 12 and 18 h of incubation. For the in vivo experiment, sexual maturation was stimulated by treatment with (i) CPE, (ii) recombinant follicle-stimulating hormone (rFSH) followed by CPE and (iii) rFSH followed by rLH. For the in vitro experiment, the expression of the nuclear progestin receptor 2 (pgr2) was induced by rLH, implying that rLH was preparing the oocyte for ovulation. For the in vivo experiment, the females treated with rGTHs had high gonadosomatic index (GSI) values (rFSH-CPE: 75, 77; rFSH-rLH: 80) in comparison with the females injected with CPE (50–60), suggesting that rFSH strongly induced vitellogenic growth. Larvae were produced for all treatment groups and for the first time by rGTH treatment alone but dose and timing still need optimization.

This article continues our series on the basics of honey bee breeding (Uzunov et al., Citation2017, Citation2022a, Citation2022b). Its purpose is to introduce the background and application of breeding values in honey bees to a readership that is not trained in quantitative genetics. Breeding values are currently not widely used in honey bee breeding. This is in contrast to farm animals, where nearly all breeding programs make use of breeding values. The limited use of breeding values in honey bees has various reasons. One reason is that many honey bee programs just aim at the multiplication of stock obtained from other breeders instead of gradually improving the population. However, for honey bee breeding programs that aim to improve the population, not using breeding values seems a missed opportunity. A second reason is that the use of breeding values is more complicated in honey bees than in farm animals. This is because controlled mating is a challenge (Uzunov et al., Citation2022b), and queens are mated to several drones from multiple queens. Moreover, traits like honey yield and varroa resistance are not measured on single bees but on colonies as a group of related individuals (known as superorganism) from two generations (mother and daughters). This paper starts by explaining the meaning of breeding values and finishes by discussing how to utilize estimated breeding values in honey bee breeding.

Background The genetic correlation between purebred (PB) and crossbred (CB) performances ($${r}_{pc}$$ r pc ) partially determines the response in CB when selection is on PB performance in the parental lines. An earlier study has derived expressions for an upper and lower bound of $${r}_{pc}$$ r pc , using the variance components of the parental purebred lines, including e.g. the additive genetic variance in the sire line for the trait expressed in one of the dam lines. How to estimate these variance components is not obvious, because animals from one parental line do not have phenotypes for the trait expressed in the other line. Thus, the aim of this study was to propose and compare three methods for approximating the required variance components. The first two methods are based on (co)variances of genomic estimated breeding values (GEBV) in the line of interest, either accounting for shrinkage (VCGEBV-S) or not (VCGEBV). The third method uses restricted maximum likelihood (REML) estimates directly from univariate and bivariate analyses (VCREML) by ignoring that the variance components should refer to the line of interest, rather than to the line in which the trait is expressed. We validated these methods by comparing the resulting predicted bounds of $${r}_{pc}$$ r pc with the $${r}_{pc}$$ r pc estimated from PB and CB data for five traits in a three-way cross in pigs. Results With both VCGEBV and VCREML, the estimated $${r}_{pc}$$ r pc (plus or minus one standard error) was between the upper and lower bounds in 14 out of 15 cases. However, the range between the bounds was much smaller with VCREML (0.15–0.22) than with VCGEBV (0.44–0.57). With VCGEBV-S, the estimated $${r}_{pc}$$ r pc was between the upper and lower bounds in only six out of 15 cases, with the bounds ranging from 0.21 to 0.44. Conclusions We conclude that using REML estimates of variance components within and between parental lines to predict the bounds of $${r}_{pc}$$ r pc resulted in better predictions than methods based on GEBV. Thus, we recommend that the studies that estimate $${r}_{pc}$$ r pc with genotype data also report estimated genetic variance components within and between the parental lines.

Background In poultry, the population structure of local breeds is usually complex mainly due to unrecorded breeding. Local chicken breeds offer an interesting proxy to understand the complexity of population structure in the context of human-mediated development of diverse morphologies and varieties. We studied 37 traditional Dutch chicken breeds to investigate population structure and the corresponding genomic impact using whole-genome sequence data. Results Looking at the genetic differences between breeds, the Dutch chicken breeds demonstrated a complex and admixed subdivided structure. The dissection of this complexity highlighted the influence of selection adhering to management purposes, as well as the role of geographic distance within subdivided breed clusters. Identification of signatures of genetic differentiation revealed genomic regions that are associated with diversifying phenotypic selection between breeds, including dwarf size (bantam) and feather color. In addition, with a case study of a recently developed bantam breed developed by crossbreeding, we provide a genomic perspective on the effect of crossbreeding. Conclusions This study demonstrates the complex population structure of local traditional Dutch chicken, and provides insight into the genomic basis and the factors involved in the formation of this complexity.

With the development of genotyping and sequencing technology, researchers working in the area of conservation genetics are able to obtain the genotypes or even the sequences of a representative sample of individuals from the population. It is of great importance to examine the genomic variants and genes that are highly preferred or pruned during the process of adaptive introgression or long-term hybridization. To the best of our knowledge, we are the first to develop a platform with computational integration of a relative identity-by-descent (rIBD) scores algorithm for introgressive mapping. The rIBD algorithm is designed for mapping the fine-scaled genomic regions under adaptive introgression between the source breeds and the admixed breed. Our rIBD calculation platform provides compact functions including reading input information and uploading of files, rIBD calculation, and presentation of the rIBD scores. We analyzed the simulated data using the rIBD calculation platform and calculated the average IBD score of 0.061 with a standard deviation of 0.124. The rIBD scores generally follow a normal distribution, and a cut-off of 0.432 and −0.310 for both positive and negative rIBD scores is derived to enable the identification of genomic regions showing significant introgression signals from the source breed to the admixed breed. A list of genomic regions with detailed calculated rIBD scores is reported, and all the rIBD scores for each of the considered windows are presented in plots on the rIBD calculation platform. Our rIBD calculation platform provides a user-friendly tool for the calculation of fine-scaled rIBD scores for each of the genomic regions to map possible functional genomic variants due to adaptive introgression or long-term hybridization.

Accurate measurements of breeding traits on individuals are critical in aquaculture for obtaining breeding values and tracking the progress of the breeding program. Modern breeding programs prioritize not only production traits but also complex traits related to production, product quality, body composition, disease resistance, and fish health, such as slaughter traits. Slaughter traits can be selected indirectly and incorporated into breeding programs. Indirect selection is cost-effective, but there is often little genetic correlation between measured and target traits. Accurate phenotypic prediction of the target traits using modern phenotyping technology can be game-changing in indirect selection. This paper proposes an analytical framework for predicting slaughter traits using images. The framework demonstrated that using images in addition to body weight improved fat percentage prediction accuracy from 0.4 to 0.7 when compared to a model that only used body weight and its numerical derivations. The framework also allowed for the interpretation of the prediction by providing imaginal features. In the case study, the dorsal side, the upper edge of the pectoral fin, and operculum edge were discovered to be the three regions on seabream that have properties that are negatively correlated with fillet fat percentage. The framework showed that both body weight and visceral weight are highly correlated with total fish body area. The framework also revealed that the lower edge of the pectoral fin, operculum edge, and anal fin are the regions with properties that explain variation in the visceral percentage. Future research will be required to segment and quantify each predictive imaginal feature to calculate its heritability. The framework can potentially predict other harvest, post-slaughter, and metabolic traits for aquacultural study.

Preimplantation genetic testing for aneuploidy (PGT-A) is widespread, but controversial, in humans and improves pregnancy and live birth rates in cattle. In pigs, it presents a possible solution to improve in vitro embryo production (IVP), however, the incidence and origin of chromosomal errors remains under-explored. To address this, we used single nucleotide polymorphism (SNP)-based PGT-A algorithms in 101 in vivo-derived (IVD) and 64 IVP porcine embryos. More errors were observed in IVP vs. IVD blastocysts (79.7% vs. 13.6% p < 0.001). In IVD embryos, fewer errors were found at blastocyst stage compared to cleavage (4-cell) stage (13.6% vs. 40%, p = 0.056). One androgenetic and two parthenogenetic embryos were also identified. Triploidy was the most common error in IVD embryos (15.8%), but only observed at cleavage, not blastocyst stage, followed by whole chromosome aneuploidy (9.9%). In IVP blastocysts, 32.8% were parthenogenetic, 25.0% (hypo-)triploid, 12.5% aneuploid, and 9.4% haploid. Parthenogenetic blastocysts arose from just three out of ten sows, suggesting a possible donor effect. The high incidence of chromosomal abnormalities in general, but in IVP embryos in particular, suggests an explanation for the low success of porcine IVP. The approaches described provide a means of monitoring technical improvements and suggest future application of PGT-A might improve embryo transfer success.

Background Nitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment. Meanwhile, the increasing demand for dairy products will result in more pollution if N losses are not controlled. Therefore, a more efficient, and environmentally friendly production system is needed, in which nitrogen use efficiency (NUE) of dairy cows plays a key role. To genetically improve NUE, extensively recorded and cost-effective proxies are essential, which can be obtained by including mid-infrared (MIR) spectra of milk in prediction models for NUE. This study aimed to develop and validate the best prediction model of NUE, nitrogen loss (NL) and dry matter intake (DMI) for individual dairy cows in China. Results A total of 86 lactating Chinese Holstein cows were used in this study. After data editing, 704 records were obtained for calibration and validation. Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait. Results showed that the coefficient of determination (R2) of the best model in within-herd validation was 0.66 for NUE, 0.58 for NL and 0.63 for DMI. For external validation, reasonable prediction results were only observed for NUE, with R2 ranging from 0.58 to 0.63, while the R2 of the other two traits was below 0.50. The infrared waves from 973.54 to 988.46 cm−1 and daily milk yield were the most important variables for prediction. Conclusion The results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations. The model of NUE could be used for the datasets that are similar to the calibration dataset. The prediction models for NL and 3-day moving average of DMI (DMI_a) generated lower accuracies in within-herd validation. Results also indicated that information of MIR spectra variables increased the predictive ability of models. Additionally, pre-processed MIR spectra do not result in higher accuracy than original MIR spectra in the external validation. These models will be applied to large-scale data to further investigate the genetic architecture of N efficiency and further reduce the adverse impacts on the environment after more data is collected.

Global warming is expected to result in larger temperature fluctuations by which heat stress may become an important stressor for animals, affecting health and productivity. Animals can cope with and adapt to heat stress by changing their physiology. To investigate general physiological reactions to heat stress in muscle and heart tissues of chickens we combined results from three independent experiments. Two experiments studied the transcriptome profiles of heart and muscle tissues of mature chickens using heat stress adapted and nonadapted chickens. One experiment studied the epigenome changes of heat stress during chicken egg incubation. In all three datasets epigenome changes were important biological response mechanisms, which may underlie genome-wide regulation of the affected biological mechanisms. Pre and postnatal heat stress reaction showed changed expression of genes related to metabolic rate, energy, and protein metabolism. Furthermore, tissue integrity may be affected due to changed cell−cell contacts, vascularization, and growth reduction.

We have previously shown that single-step genomic best linear unbiased prediction (ssGBLUP) estimates breeding values of genomically preselected animals without preselection bias for widely recorded traits, that is traits recorded for the majority of animals in the breeding population. This study investigated the impact of genomic preselection (GPS) on accuracy and bias in ssGBLUP evaluation of genomically preselected animals for a scarcely recorded trait, that is a trait recorded for only a small proportion of the animals, which generally has a lower prediction accuracy than widely recorded traits, mainly due to having a much smaller number of phenotypes available. We used data from a commercial pig breeding program, considering feed intake as a scarcely recorded target trait, being available for ~30% of the animals with phenotypes for any trait, and average daily gain, backfat thickness and loin depth as widely recorded predictor traits, being available for >95% of the animals with phenotypes for any trait. The data contained the routine GPS implemented by commercial animal breeding programs, and we retrospectively implemented two scenarios with additional layers of GPS by discarding pedigree, genotypes and phenotypes of animals without progeny. The ssGBLUP evaluation following GPS used records only from the target trait, only from the predictor traits, or both. Accuracy for feed intake did not differ statistically across GPS scenarios, although it tended to decrease with more intense GPS. The accuracy had average values of 0.37, 0.44, and 0.45 across all GPS scenarios when, respectively, records from only the target trait, only the predictor traits, or both were used in the ssGBLUP evaluation. Considerable deflation of the genomic breeding values for feed intake was observed in the most stringent GPS scenario, due to the variance components being underestimated as a result of the limited amount of strongly preselected data. As long as (co)variance components were unbiased, no or only marginal bias was observed. These results for accuracy and bias were observed whether records of the scarcely recorded target trait, of the predictor traits, or both were used in the ssGBLUP evaluation. Our results show that for the scarcely recorded feed intake in pigs, ssGBLUP is able to estimate breeding values of preselected animals without preselection bias, similarly as previously observed for widely recorded traits.

Background: Single-step genomic best linear unbiased prediction (ssGBLUP) models allow the combination of genomic, pedigree, and phenotypic data into a single model, which is computationally challenging for large genotyped populations. In practice, genotypes of animals without their own phenotype and progeny, so-called genotyped selection candidates, can become available after genomic breeding values have been estimated by ssGBLUP. In some breeding programmes, genomic estimated breeding values (GEBV) for these animals should be known shortly after obtaining genotype information but recomputing GEBV using the full ssGBLUP takes too much time. In this study, first we compare two equivalent formulations of ssGBLUP models, i.e. one that is based on the Woodbury matrix identity applied to the inverse of the genomic relationship matrix, and one that is based on marker equations. Second, we present computationally-fast approaches to indirectly compute GEBV for genotyped selection candidates, without the need to do the full ssGBLUP evaluation. Results: The indirect approaches use information from the latest ssGBLUP evaluation and rely on the decomposition of GEBV into its components. The two equivalent ssGBLUP models and indirect approaches were tested on a six-trait calving difficulty model using Irish dairy and beef cattle data that include 2.6 million genotyped animals of which about 500,000 were considered as genotyped selection candidates. When using the same computational approaches, the solving phase of the two equivalent ssGBLUP models showed similar requirements for memory and time per iteration. The computational differences between them were due to the preprocessing phase of the genomic information. Regarding the indirect approaches, compared to GEBV obtained from single-step evaluations including all genotypes, indirect GEBV had correlations higher than 0.99 for all traits while showing little dispersion and level bias. Conclusions: In conclusion, ssGBLUP predictions for the genotyped selection candidates were accurately approximated using the presented indirect approaches, which are more memory efficient and computationally fast, compared to solving a full ssGBLUP evaluation. Thus, indirect approaches can be used even on a weekly basis to estimate GEBV for newly genotyped animals, while the full single-step evaluation is done only a few times within a year.

In general, the relationship between the predicted functional consequences of missense mutations mapping to genes known to be involved in human diseases and the severity of disease manifestations is weak. In this study, we tested in pigs whether missense single nucleotide polymorphisms (SNPs), predicted to have consequences on the function of genes related to lipid metabolism are associated with lipid phenotypes. Association analysis demonstrated that nine out of 72 nominally associated SNPs were classified as “highly” or “very highly consistent” in silico-predicted functional mutations and did not show association with lipid traits expected to be affected by inactivation of the corresponding gene. Although the lack of endophenotypes and the limited sample size of certain genotypic classes might have limited to some extent the reach of the current study, our data indicate that present-day bioinformatic tools have a modest ability to predict the impact of missense mutations on complex phenotypes. info:eu-repo/semantics/publishedVersion

Currently, enhancing the collaboration between related breeds is of main importance to increase the competitivity and the sustainability of local breeds. One type of collaboration is the development of an across-breed reference population that will allow a better management of local breeds. For this purpose, the genomic relatedness between the local target breed and possible breeds to be included in the reference population should be estimated. In Europe, there are several local red-pied cattle breeds that would benefit from this kind of collaboration. However, how different red-pied cattle breeds from the Benelux are related to each other and can collaborate is still unclear. The objectives of this study were therefore: (1) to estimate the level of inbreeding of the East Belgian Red and White (EBRW), the Red-Pied of the Ösling (RPO) and Dutch red-pied cattle breeds; (2) to determine the genomic relatedness of several red-pied cattle breeds, with a special focus on two endangered breeds: the EBRW and the RPO, and (3) based on the second objective, to detect animals from other breeds that were genomically close enough to be considered as advantageous in the creation of an across-breed reference population of EBRW or RPO. The estimated inbreeding levels based on runs of homozygosity were relatively low for almost all the studied breeds and especially for the EBRW and RPO. This would imply that inbreeding is currently not an issue in these two endangered breeds and that their sustainability is not threatened by their level of inbreeding. The results from the principal component analysis, the phylogenetic tree and the clustering all highlighted that the EBRW and RPO breeds were included in the genomic continuum of the studied red-pied cattle breeds and can be therefore considered as genomically close to Dutch red-pied cattle breeds, highlighting the possibility of a collaboration between these breeds. Especially, EBRW animals were closely related to Deep Red and Improved Red animals while, to a lesser extent, the RPO animals were closely related to the Meuse-Rhine-Yssel breed. Based on these results, we could use distance measures, based either on the principal component analysis or clustering, to detect animals from Dutch breeds that were genomically closest to the EBRW or RPO breeds. This will finally allow the building of an across-breed reference population for EBRW or RPO for further genomic evaluations, considering these genomically closest animals from other breeds.

Gene regulatory networks are now at the forefront of precision biology, which can help researchers better understand how genes and regulatory elements interact to control cellular gene expression, offering a more promising molecular mechanism in biological research. Interactions between the genes and regulatory elements involve different promoters, enhancers, transcription factors, silencers, insulators, and long-range regulatory elements, which occur at a ∼10 µm nucleus in a spatiotemporal manner. In this way, three-dimensional chromatin conformation and structural biology are critical for interpreting the biological effects and the gene regulatory networks. In the review, we have briefly summarized the latest processes in three-dimensional chromatin conformation, microscopic imaging, and bioinformatics, and we have presented the outlook and future directions for these three aspects.

European wildlife has been subjected to intensifying levels of anthropogenic impact throughout the Holocene, yet the main genetic partitioning of many species is thought to still reflect the late-Pleistocene glacial refugia. We analyzed 26,342 nuclear SNPs of 464 wild boar (Sus scrofa) across the European continent to infer demographic history and reassess the genetic consequences of natural and anthropogenic forces. We found that population fragmentation, inbreeding and recent hybridization with domestic pigs have caused the spatial genetic structure to be heterogeneous at the local scale. Underlying local anthropogenic signatures, we found a deep genetic structure in the form of an arch-shaped cline extending from the Dinaric Alps, via Southeastern Europe and the Baltic states, to Western Europe and, finally, to the genetically diverged Iberian peninsula. These findings indicate that, despite considerable anthropogenic influence, the deeper, natural continental structure is still intact. Regarding the glacial refugia, our findings show a weaker signal than generally assumed, but are nevertheless suggestive of two main recolonization routes, with important roles for Southern France and the Balkans. Our results highlight the importance of applying genomic resources and framing genetic results within a species’ demographic history and geographic distribution for a better understanding of the complex mixture of underlying processes. Nasl. z nasl. zaslona. Opis vira z dne 3. 2. 02023. Skupno št. avtorjev: 21. Bibliografija: str. 142-143.

Background Current solid-phase reversible immobilization (SPRI) beads technology is widely used in molecular biology due to its convenience for DNA manipulation. However, the high performance commercial SPRI beads have no price advantage over our method. Furthermore, the use of commercially available SPRI beads standards does not provide the flexibility required for a number of specific nucleic acid handling scenarios. Results We report an efficient DNA purification strategy by combining home-made beads-suspension buffer with SPRI beads. The method tests the critical concentrations of polyethylene glycol (PEG) 8000 and beads to maximise recovery. And the composition of the SPRI beads DNA purification system (SDPS) was determined at 20% PEG 8000, 2 M NaCl and 16.3 mM MgCl2, and 1.25 mg/ml beads (1/8th original concentration). Then, we tested the DNA recovery of the SDPS, and the result showed that it was comparable to the control (AMPure XP beads). In the study, we have also developed an adjustment SPRI beads DNA purification system (ASDPS), the volume of ASDPS per reaction is 0.6× reaction volume (beads/samples). The performance of ASDPS is similar to SDPS and the control. But the cost of our methods is only about 1/24th of the control. To further assess its performance, we prepare the DNA-seq libraries to evaluate the yield, library quality, capture efficiency and consistency. We have compared all these results with the performance of the control and confirmed its efficiency. Conclusion We have proposed an alternative DNA purification approach with great flexibility, allowing researchers to manipulate DNA in different conditions. And ultimately, its application will benefit molecular biology research in the future.

Global warming has shifted phenological traits in many species, but whether species are able to track further increasing temperatures depends on the fitness consequences of additional shifts in phenological traits. To test this, we measured phenology and fitness of great tits (Parus major) with genotypes for extremely early and late egg lay dates, obtained from a genomic selection experiment. Females with early genotypes advanced lay dates relative to females with late genotypes, but not relative to nonselected females. Females with early and late genotypes did not differ in the number of fledglings produced, in line with the weak effect of lay date on the number of fledglings produced by nonselected females in the years of the experiment. Our study is the first application of genomic selection in the wild and led to an asymmetric phenotypic response that indicates the presence of constraints toward early, but not late, lay dates.

Pollen classification is considered an important task in palynology. In the Netherlands, two genera of the Urticaceae family, named Parietaria and Urtica, have high morphological similarities but induce allergy at a very different level. Therefore, distinction between these two genera is very important. Within this group, the pollen of Urtica membranacea is the only species that can be recognized easily under the microscope. For the research presented in this study, we built a dataset from 6472 pollen images and our aim was to find the best possible classifier on this dataset by analysing different classification methods, both machine learning and deep learning-based methods. For machine learning-based methods, we measured both texture and moment features based on images from the pollen grains. Varied feature selection techniques, classifiers as well as a hierarchical strategy were implemented for pollen classification. For deep learning-based methods, we compared the performance of six popular Convolutional Neural Networks: AlexNet, VGG16, VGG19, MobileNet V1, MobileNet V2 and ResNet50. Results show that compared with flat classification models, a hierarchical strategy yielded the highest accuracy with 94.5% among machine learning-based methods. Among deep learning-based methods, ResNet50 achieved an accuracy of 99.4%, slightly outperforming the other neural networks investigated. In addition, we investigated the influence on performance by changing the size of image datasets to 1000 and 500 images, respectively. Results demonstrated that on smaller datasets, ResNet50 still achieved the best classification performance. An ablation study was implemented to help understanding why the deep learning-based methods outperformed the other models investigated. Using Urticaceae pollen as an example, our research provides a strategy of selecting a classification model for pollen datasets with highly similar pollen grains to support palynologists and could potentially be applied to other image classification tasks.

As usual in science, where one answer raises new questions, following our attempt to demystify the basic concept of honey bee breeding with our article The Basic Concept of Honey Bee Breeding Programs (Uzunov et al., 2017) questions were raised on details about the implementation of a breeding program. Aspects, such as prioritisation of the traits to select for, selection using breeding values, time management of the breeding program, and mating control, prevailed as most intriguing and are indeed aspects to which previously only limited attention has been given. These particular and relevant questions indicate, however, that the message from our previous article reached our target group. This time, we will address in more detail trait prioritisation, the timing of a breeding program and the selection process. Mating control will only be addressed in a general sense.

Enhancing smallholder chicken production and productivity is an integral component of agricultural development strategies in sub-Saharan Africa. The African Chicken Genetic Gain (ACGG) project has been testing, identifying, and disseminating tropically adapted improved breeds (TAIBs) in Africa to improve the production and productivity of the sector. We applied a multimethod approach and integrated analysis to explore the overall feasibility of TAIBs under smallholder management conditions and documented evidence for sustained adoption. We used data from a baseline survey, on-farm experiment, cluster-randomized study, and market assessment survey to analyse the technical, economic, social, and environmental feasibility of TAIBs adoption under smallholder management conditions. The multimethod approach attests TAIBs as a sustainable technological alternative to smallholder chicken producers in the region. Most smallholder farmers prefer TAIBs to indigenous breeds, and TAIBs-based production enhance producers’ consumption and income generation goals. Moreover, adopting these breeds generates higher economic gains, is socially viable, is technically feasible, and has mitigable environmental risks. However, sustained adoption requires delivery models, capacity building, marketing and financial models, and integrated risks reduction strategies. We argue that demonstrating innovations’ economic, social, technical, and ecological viability and enhancing access to efficient input and output markets are vital for sustained agricultural technology adoption.

In the past 50 years, there has been a steep increase in the demand for poultry products, met by increasing production along with genetic selection for improved growth, efficiency, health and reproduction. The selection tends to reduce the number and type of genetic resources contributing to the majority of production. The University of Alberta maintains 10 heritage chicken lines (Brown Leghorn (BL), Light Sussex (LS), New Hampshire (NH), Saskatchewan Barred Rock (SaskBR), Shaver Barred Rock (ShaverBR), Shaver Rhode Island Red (RIR), White Leghorn (WL) and three commercial crosses called Alberta Meat Control strains 1957 (AMC-1957), 1978 sire line (AMC-1978-20S) and 1978 dam line (AMC-1978-30D), that played a large role in the evolution of the poultry industry in Canada. Since these lines have not been subjected to the same intensive selection pressures as commercial counterparts, they may contain unique genetic variants lost in commercial lines. Thus, for conservation management of these lines, the first step is to assess their genetic diversity. 71 male samples from across 10 lines were analysed using whole-genome sequencing and patterns of genetic diversity and relatedness among these lines were explored. AMC-1978-30D showed the highest genetic diversity as reflected in observed and expected heterozygosity (0.327 and 0.250), percentage of polymorphic markers (~ 65%) and average recent inbreeding coefficient (−0.039), followed by AMC-1978-20S and AMC-1957. BL showed the lowest genetic diversity as reflected in observed and expected heterozygosity (0.130 and 0.116), percentage of polymorphic markers (~31%) and average recent inbreeding coefficient (0.577), followed by LS, WL and NH. Our findings highlight the need for special attention for the populations of BL, WL, LS and NH, with the largest levels of inbreeding. Our results can be used to develop a breeding strategy to optimize and conserve the genetic variation present in heritage lines.

Recent technological advances in the field of genomics offer conservation managers and practitioners new tools to explore for conservation applications. Many of these tools are well developed and used by other life science fields, while others are still in development. Considering these technological possibilities, choosing the right tool(s) from the toolbox is crucial and can pose a challenging task. With this in mind, we strive to inspire, inform and illuminate managers and practitioners on how conservation efforts can benefit from the current genomic and biotechnological revolution. With inspirational case studies we show how new technologies can help resolve some of the main conservation challenges, while also informing how implementable the different technologies are. We here focus specifically on small population management, highlight the potential for genetic rescue, and discuss the opportunities in the field of gene editing to help with adaptation to changing environments. In addition, we delineate potential applications of gene drives for controlling invasive species. We illuminate that the genomic toolbox offers added benefit to conservation efforts, but also comes with limitations for the use of these novel emerging techniques.

Background We previously reported a familial thyroid follicular cell carcinoma (FCC) in a large number of Dutch German longhaired pointers and identified two deleterious germline mutations in the TPO gene associated with disease predisposition. However, the somatic mutation profile of the FCC in dogs has not been investigated at a genome-wide scale. Results Herein, we comprehensively investigated the somatic mutations that potentially contribute to the inherited tumor formation and progression using high depth whole-genome sequencing. A GNAS p.A204D missense mutation was identified in 4 out of 7 FCC tumors by whole-genome sequencing and in 20 out of 32 dogs’ tumors by targeted sequencing. In contrast to this, in the human TC, mutations in GNAS gene have lower prevalence. Meanwhile, the homologous somatic mutation in humans has not been reported. These findings suggest a difference in the somatic mutation landscape between TC in these dogs and human TC. Moreover, tumors with the GNAS p.A204D mutation had a significantly lower somatic mutation burden in these dogs. Somatic structural variant and copy number alterations were also investigated, but no potential driver event was identified. Conclusion This study provides novel insight in the molecular mechanism of thyroid carcinoma development in dogs. German longhaired pointers carrying GNAS mutations in the tumor may be used as a disease model for the development and testing of novel therapies to kill the tumor with somatic mutations in the GNAS gene.

Phenotypes on individual animals are required for breeding programs to be able to select for traits. However, phenotyping individual animals can be difficult and time-consuming, especially for traits related to health, welfare, and performance. Individual broiler behavior could serve as a proxy for these traits when recorded automatically and reliably on many animals. Sensors could record individual broiler behavior, yet different sensors can differ in their assessment. In this study a comparison was made between a passive radio frequency identification (RFID) system (grid of antennas underneath the pen) and video tracking for the determination of location and movement of 3 color-marked broilers at d 18. Furthermore, a systems comparison of derived behavioral metrics such as space usage, locomotion activity and apparent feeding and drinking behavior was made. Color-marked broilers simplified the computer vision task for YOLOv5 to detect, track, and identify the animals. Animal locations derived from the RFID-system and based on video were largely in agreement. Most location differences (77.5%) were within the mean radius of the antennas’ enclosing circle (≤128 px, 28.15 cm), and 95.3% of the differences were within a one antenna difference (≤256 px, 56.30 cm). Animal movement was not always registered by the RFID-system whereas video was sensitive to detection noise and the animal's behavior (e.g., pecking). The method used to determine location and the systems’ sensitivities to movement led to differences in behavioral metrics. Behavioral metrics derived from video are likely more accurate than RFID-system derived behavioral metrics. However, at present, only the RFID-system can provide individual identification for non-color marked broilers. A combination of verifiable and detailed video with the unique identification of RFID could make it possible to identify, describe, and quantify a wide range of individual broiler behaviors.

11 Pág. Departamento de Reproducción animal, A classical chicken semen diluent (Lake's 7.1 diluent) was modified to have lowered osmolalities (ranging from 290 to 410 mOsm/kg). The modified medium with physiological osmolality of 325 mOsm/kg allowed cold storage of fresh semen for several days with very little loss of membrane integrity and motility, while high osmolalities inhibited motility. This modified medium was then used as base for freezing medium to test effects of the type and concentration of cryoprotective agent (CPA), and the cooling rate (CR). A number of CPAs (methylformamide, methylacetamide, dimethylformamide (DMF), dimethylacetamide (DMA), diethylformamide, and propylene glycol) were first compared by freezing semen with 0.6 mol/l of the respective CPA at a cooling rate of 250 °C/min. Post-thaw motility and membrane integrity were highest with DMA and DMF. Finally, in more detailed factorial experiments, semen from individual cocks or pooled semen was frozen using CRs of 4, 50, 250, and 440 °C/min and DMA concentrations ([DMA]) of 0.4, 0.6, 1.0, and 1.5 mol/l. Straws from each semen sample x treatment combination were divided for semen assessment at three different research groups for sperm motility, membrane integrity, kinked tails, and DNA fragmentation, using microscopy, computer assisted motility analysis, and flow cytometry. There were clear effects of both CR and [DMA] and their interaction. CRs 50 and 250 °C/min gave best post-thaw sperm performance. Higher DMA concentrations gave better post-thaw membrane integrity, but concentrations above 1.0 mol/l can decrease sperm velocity or even inhibit sperm motility. Therefore [DMA] may best be 0.6-1.0 mol/l at a CR of 50-250 °C/min., Funding from the Dutch Ministry of Agriculture, Nature and Food Quality (project KB-Dier, WOT-03-436-077) and from European Union's Horizon 2020 Research and Innovation Programme (project IMAGE, grant agreement no 677353) are gratefully acknowledged.

Thyroid carcinomas originating from follicular cells of the thyroid gland occur in both humans and dogs and they have highly similar histomorphologic patterns. In dogs, thyroid carcinomas have not been extensively investigated, especially concerning the familial origin of thyroid carcinomas. Here we report familial thyroid follicular cell carcinomas confirmed by histology in 54 Dutch origin German longhaired pointers. From the pedigree, 45 of 54 histopathologically confirmed cases are closely related to a pair of first-half cousins in the past, indicating a familial disease. In addition, genetics contributed more to the thyroid follicular cell carcinoma than other factors by an estimated heritability of 0.62 based on pedigree. The age of diagnosis ranged between 4.5 and 13.5 years, and 76% of cases were diagnosed before 10 years of age, implying an early onset of disease. We observed a significant higher pedigree-based inbreeding coefficient in the affected dogs (mean F 0.23) compared to unaffected dogs (mean F 0.14), suggesting the contribution of inbreeding to tumour development. The unique occurrence of familial thyroid follicular cell carcinoma in this dog population and the large number of affected dogs make this population an important model to identify the genetic basis of familial thyroid follicular cell carcinoma in this breed and may contribute to the research into pathogenesis, prevention and treatment in humans. This article is protected by copyright. All rights reserved.

Assisted propagation of the European eel will lead to a closed production cycle supplying the aquaculture industry with juvenile glass eels. Females require long-term weekly treatment with pituitary extract (PE), which is stressful and causes abnormalities in oogenesis. We tested the effects of 17α-methyltestosterone (17 MT), as potent androgen activating the androgen receptor, and 17β-estradiol (E2), as an inducer of vitellogenesis, to shorten the duration of PE treatment.Four groups of feminized eels were subjected to a simulated migration and subsequent injection with implants containing 17 MT (17 MT-group), E2 (E2-group) or 17 MT plus E2 (17 MT + E2-group) to test for synergistic effects, or without any steroids as controls (C-group). The effects of a 2-months treatment were investigated by determining the eye index (EI), hepatosomatic and gonadosomatic index (HSI and GSI, respectively), plasma steroid concentrations by liquid chromatography mass spectrometry (LCMS), gonadal histology, expression of androgen receptors a and b (ara, arb); estrogen receptor 1 (esr1); FSH receptor (fshr); vitellogenin receptor (vtgr) and aromatase (cyp19), and the required number of weekly PE injections to fully mature. For many parameters, both the 17 MT and E2 groups showed an increase vs. controls, with the 17 MT + E2 group showing a synergistic effect, as seen for EI, GSI (3.4 for 17 MT and for E2, 6.6 for 17 MT + E2), oocyte diameter and ara, arb and esr1 expression. Concentrations of almost all focal steroids decreased with simulated migration and steroid treatment. Only eels of the 17 MT-group showed increased expression of cyp19 and of fshr, while fshr expression increased 44-fold in the 17 MT + E2 group, highlighting that co-implantation is most effective in raising fshr mRNA levels. Specific for eels of the E2 groups were vitellogenesis-associated changes such as an increase of HSI, plasma E2, and presence of yolk in the oocytes. Steroid treatments reduced the duration of PE treatment, again synergistically for co-implantation. In conclusion, E2 is necessary to start vitellogenesis, but 17 MT has specific effects on cyp19 and fshr expression. The combination is necessary for synergistic effects and as such, steroid implants could be applied in assisted reproduction protocols for European eel to improve oocyte quality leading to the production of more vital larvae.

Resilience is the capacity of an animal to be minimally affected by disturbances or rapidly return to the state pertained before exposure to a disturbance. Resilience indicators can be estimated from longitudinal production data, using deviations of observed from expected production levels. One component of resilience is disease resilience, which includes general disease resistance. Natural antibodies (NAbs) are an indicator trait for general disease resistance. The aim of this study was to perform a genome-wide association study (GWAS) for resilience indicators and NAbs in a Rhode Island purebred layer line and study potential overlap in genomic regions detected for these traits. For 2,494 hens, deviations (i.e., differences) between observed weekly egg production and expected weekly egg production were calculated. Resilience indicators were then defined as the natural logarithm of the variance of deviations, skewness of deviations, and lag-one autocorrelation of deviations. For a subset of 1,221 hens genotyped with the 60 K Illumina SNP BeadChip, NAbs binding keyhole-limpet hemocyanin were available (isotypes IgM and IgG). Heritabilities, estimated with a linear mixed animal model, were 0.39 for IgM and 0.20 for IgG, and ranged from 0.03 to 0.18 for the resilience indicators. No significant associations were found in the GWAS, except for a single chromosomal region for the skewness of egg deviations in wk 25 to 83 of the laying period. The absence of significant peaks for NAbs and resilience indicators suggests that there are no genes with major effect and that the traits are likely under polygenic control in this line.

Sequencing ancient DNA to high coverage is often limited by sample quality and cost. Imputing missing genotypes can potentially increase information content and quality of ancient data, but requires different computational approaches than modern DNA imputation. Ancient imputation beyond humans has not been investigated. In this study we report results of a systematic evaluation of imputation of three whole genome ancient Sus scrofa samples from the Early and Late Neolithic (∼7,100–4,500 BP), to test the utility of imputation. We show how issues like genetic architecture and, reference panel divergence, composition and size affect imputation accuracy. We evaluate a variety of imputation methods, including Beagle5, GLIMPSE, and Impute5 with varying filters, pipelines, and variant calling methods. We achieved genotype concordance in most cases reaching above 90%; with the highest being 98% with ∼2,000,000 variants recovered using GLIMPSE. Despite this high concordance the sources of diversity present in the genotypes called in the original high coverage genomes were not equally imputed leading to biases in downstream analyses; a trend toward genotypes most common in the reference panel is observed. This demonstrates that the current reference panel does not possess the full diversity needed for accurate imputation of ancient Sus, due to missing variations from Near Eastern and Mesolithic wild boar. Imputation of ancient Sus scrofa holds potential but should be approached with caution due to these biases, and suggests that there is no universal approach for imputation of non-human ancient species.

Summary The pig breeding system provides a unique framework to study recessive defects and the consequence on the phenotype. We examined a commercial synthetic Duroc population for recessive defects and identified a haplotype on chromosome 9 significantly affecting pre‐weaning mortality. To identify the causal variant underlying the mortality, we examined sequence data of four carrier animals and 21 non‐carrier animals from the same population. The results yield a strong candidate causal stop‐gained variant (NM_001099928.1:c.541C>T) affecting the MYO7A gene in complete linkage disequilibrium with the lethal haplotype. The variant leads to an impaired (p.Gln181*) MYO7A protein that truncates 2032 amino acids from the protein. We examined a litter from a carrier sow inseminated by a carrier boar. From the resulting piglets, two confirmed homozygous piglets suffered from severe balance difficulties and the inability to walk properly. The variant segregates at a carrier frequency of 8.2% in the evaluated population and will be gradually purged from the population, improving animal welfare. Finally, this 'natural knockout' will increase our understanding of the functioning of the MYO7A gene and provides a potential model for Usher syndrome in humans.

Red dairy breeds are a valuable cultural and historical asset, and often a source of unique genetic diversity. However, they have difficulties competing with other, more productive, dairy breeds. Improving competitiveness of Red dairy breeds, by accelerating their genetic improvement using genomic selection, may be a promising strategy to secure their long-term future. For many Red dairy breeds, establishing a sufficiently large breed-specific reference population for genomic prediction is often not possible, but may be overcome by adding individuals from another breed. Relatedness between breeds strongly decides the benefit of adding another breed to the reference population. To prioritize among available breeds, the effective number of chromosome segments (Me) can be used as an indicator of relatedness between individuals from different breeds. The Me is also an important parameter in determining the accuracy of genomic prediction. The Me can be estimated both within a population and between 2 populations or breeds, as the reciprocal of the variance of genomic relationships. We investigated relatedness between 6 Dutch Red cattle breeds, Groningen White Headed (GWH), Dutch Friesian (DF), Meuse-Rhine-Yssel (MRY), Dutch Belted (DB), Deep Red (DR), and Improved Red (IR), focusing primarily on the Me, to predict which of those breeds may benefit from including reference animals of the other breeds. All of these breeds, except MRY, are under high risk of extinction. Our results indicated high variability of Me, especially between Me ranging from ∼3,500 to ∼17,400, indicating different levels of relatedness between the breeds. Two clusters are especially important, one formed by MRY, DR, and IR, and the other comprising DF and DB. Although relatedness between breeds within each of these 2 clusters is high, across-breed genomic prediction is still limited by the current number of genotyped individuals, which for many breeds is low. However, adding MRY individuals would increase the reference population of DR substantially. We estimated that between 11 and 133 individuals from other breeds are needed to achieve accuracy of genomic prediction equivalent to using one additional individual from the same breed. Given the variation in size of the breeds in this study, the benefit of a multibreed reference population is expected to be lower for larger breeds than for the smaller ones.

Backfat is an important trait in pork production, and it has been included in the breeding objectives of genetic companies for decades. Although adipose tissue is a good energy storage, excessive fat results in reduced efficiency and economical losses. A large QTL for backfat thickness on chromosome 5 is still segregating in different commercial pig breeds. We fine mapped this QTL region using a genome-wide association analysis (GWAS) with 133,358 genotyped animals from five commercial populations (Landrace, Pietrain, Large White, Synthetic, and Duroc) imputed to the porcine 660K SNP chip. The lead SNP was located at 5:66103958 (G/A) within the third intron of the CCND2 gene, with the G allele associated with more backfat, while the A allele is associated with less backfat. We further phased the QTL region to discover a core haplotype of five SNPs associated with low backfat across three breeds. Linkage disequilibrium analysis using whole-genome sequence data revealed three candidate causal variants within intronic regions and downstream of the CCND2 gene, including the lead SNP. We evaluated the association of the lead SNP with the expression of the genes in the QTL region (including CCND2) in a large cohort of 100 crossbred samples, sequenced in four different tissues (lung, spleen, liver, muscle). Results show that the A allele increases the expression of CCND2 in an additive way in three out of four tissues. Our findings indicate that the causal variant for this QTL region is a regulatory variant within the third intron of the CCND2 gene affecting the expression of CCND2.

Recent developments allowed generating multiple high-quality ‘omics’ data that could increase the predictive performance of genomic prediction for phenotypes and genetic merit in animals and plants. Here, we have assessed the performance of parametric and nonparametric models that leverage transcriptomics in genomic prediction for 13 complex traits recorded in 478 animals from an outbred mouse population. Parametric models were implemented using the best linear unbiased prediction, while nonparametric models were implemented using the gradient boosting machine algorithm. We also propose a new model named GTCBLUP that aims to remove between-omics-layer covariance from predictors, whereas its counterpart GTBLUP does not do that. While gradient boosting machine models captured more phenotypic variation, their predictive performance did not exceed the best linear unbiased prediction models for most traits. Models leveraging gene transcripts captured higher proportions of the phenotypic variance for almost all traits when these were measured closer to the moment of measuring gene transcripts in the liver. In most cases, the combination of layers was not able to outperform the best single-omics models to predict phenotypes. Using only gene transcripts, the gradient boosting machine model was able to outperform best linear unbiased prediction for most traits except body weight, but the same pattern was not observed when using both single nucleotide polymorphism genotypes and gene transcripts. Although the GTCBLUP model was not able to produce the most accurate phenotypic predictions, it showed the highest accuracies for breeding values for 9 out of 13 traits. We recommend using the GTBLUP model for prediction of phenotypes and using the GTCBLUP for prediction of breeding values.

Little is known about the biology of grey-cheeked and black crested mangabeys (Lophocebus albigena and Lophocebus aterrimus, respectively). As these primates face threats in the wild, well-monitored zoo-housed populations with up to date registries are becoming increasingly valuable to acquire species knowledge and to support conservation efforts. We used international studbooks to extract demographic and genetic information on 519 mangabeys to investigate how life history and parent-related variables influence maximum longevity and juvenile mortality. Generalized linear mixed models, as well as survival analyses, were applied. Results showed that females lived significantly longer than males, which is not uncommon in primates. Furthermore, our results indicated that the maximum longevity is lower for individuals living in European zoos versus individuals from North American zoos, which may be due to a combination of environmental differences and potential founder effects. We also show that the maternal maximum longevity is positively related to the maximum longevity of the offspring, which may be explained by the inheritance of “good genes“. However, the age of the mother at the moment of birth was negatively related to the maximum longevity of the offspring, which contradicts literature that states that, in primates, more experienced and thus older mothers will raise their offspring better than less experienced mothers. Instead, it is more likely that an “optimal age range” exists for breeding mothers. Our study provides insights into the population biology of captive mangabeys and may be helpful for identifying future research priorities to optimize primate health and welfare directly ex situ, and indirectly in situ.