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Most commercial laying hens suffer from sternum (keel) bone damage including deviations and fractures. X-raying hens, followed by segmenting and assessing the keel bone, is a key to automating the monitoring of keel bone condition. The aim of the current work is to train a deep learning model to segment the keel bone out of whole-body x-ray images. We obtained full-body x-ray images of laying hens (n = 1,051) and manually drew the outline of the keel bone on each image. Using the annotated images, a U-net model was then trained to segment the keel bone. The proposed model was evaluated using 5-fold cross validation. We obtained high segmentation accuracy (Dice coefficients of 0.88–0.90) repeatably over several validation folds. In conclusion, automatic segmentation of the keel bone from full-body x-ray images is possible with good accuracy. Segmentation is a requirement for automated measurements of keel geometry and density, which can subsequently be connected to susceptibility to keel deviations and fractures.

Lepidium campestre(L.) or field cress is a multifaceted oilseed plant, which is not yet domesticated. Moreover, the molecular and genetic mechanisms underlying the domestication traits of field cress remain largely elusive. The overarching goal of this study is to identify quantitative trait loci (QTL) that are fundamental for domestication of field cress. Mapping and dissecting quantitative trait variation may provide important insights into genomic trajectories underlying field cress domestication. We used 7624 single nucleotide polymorphism (SNP) markers for QTL mapping in 428 F2interspecific hybrid individuals, while field phenotyping was conducted in F2:3segregating families. We applied multiple QTL mapping algorithms to detect and estimate the QTL effects for seven important domestication traits of field cress. Verification of pod shattering across sites revealed that the non-shattering lines declined drastically whereas the shattering lines increased sharply, possibly due to inbreeding followed by selection events. In total, 1461 of the 7624 SNP loci were mapped to eight linkage groups (LGs), spanning 571.9 cM map length. We identified 27 QTL across all LGs of field cress genome, which captured medium to high heritability, implying that genomics-assisted selection could deliver domesticated lines in field cress breeding. The use of high throughput genotyping can accelerate the process of domestication in novel crop species. This is the first QTL mapping analysis in the field cress genome that may lay a foundational framework for positional or functional QTL cloning, introgression as well as genomics-assisted breeding in field cress domestication.

Rennet coagulation of milk is crucial to cheese production and poorly coagulating milk could lead to losses and reduced quality. Heritability for milk coagulation has previously been estimated to be between 0.28 and 0.45 indicating that genetic selection can be used to manipulate this trait. There are strong phenotypic and genetic correlations between relative proportions of the different milk proteins and the coagulation trait. The 4 casein (CN) proteins are expressed by the genes CSN1S1, CSN2, CSN1S2, and CSN3located in a cluster on bovine chromosome 6. To better understand the effect of genetic variation in the CN genes on milk coagulation, blood and milk samples from 30 Swedish red dairy cattle (RDC) with divergent coagulation properties is chosen from a previous observational study on 600 RDC cows. DNA from the 30 cows was sequenced for the CN genes to determine the theoretical AA sequence and to look for genetic variation in the introns and untranslated regions of the exons. The aim of this study is to confirm the protein-based genetic variants previously reported, while also searching for additional genetic variation, specifically synonymous variants in the exons of 30 cows. We observed genetic variation in 116 SNPs in the region of the known CN genes where 10% of the SNPs are exon variants and the remaining 90% are intron variants. 2.5% of the SNPs are found in the 5′- or 3′- UTR regions of the exons, 2% are synonymous variants and 6% are missense variants which concurred with the known protein variants for CSN1S1, CSN2and CSN3. Furthermore, 6% of the SNPs are splice polypyrimidine tract intron variants. The 2 genetic variants in the 5′- and 3′- UTR in CSN1S1and CSN3are found together with protein variants CSN1S1Cand CSN3B. As both UTR variants are associated with gain and loss off different micro RNA and transcription factors it could explain differences in expression of the genetic protein variants. Preliminary chi-squared analysis on the small sample set as well as comparison with previous GWAS studies showed potential connections between the identified SNPs and coagulation properties of milk. By advancing the knowledge of the connection between the DNA sequence and the functional properties of the CN proteins we hope to learn more about the cheese coagulation properties of milk from RDC.

Bone fracture in egg laying hens is a growing welfare and economic concern in the industry. Although environmental conditions and management (especially nutrition) can exacerbate it, the primary cause of bone weakness and the resulting fractures is believed to have a genetic basis. To test this hypothesis, we performed a genome-wide association study to identify the loci associated with bone strength in laying hens. Genotype and phenotype data were obtained from 752 laying hens belonging to the same pure line population. These hens were genotyped for 580,961 SNPs, with 232,021 SNPs remaining after quality control. Each of the SNPs were tested for association with tibial breaking strength using the family-based score test for association. A total of 52 SNPs across chromosomes 1, 3, 8, and 16 were significantly associated with tibial breaking strength with the genome-wide significance threshold set as a corrected Pvalue of 10e−5. Based on the local linkage disequilibrium around the significant SNPs, 5 distinct and novel QTLs were identified on chromosomes 1 (2 QTLs), 3 (1 QTL), 8 (1 QTL) and 16 (1 QTL). The strongest association was detected within the QTL region on chromosome 8, with the most significant SNP having a corrected Pvalue of 4e−7. A number of candidate genes were identified within the QTL regions, including the BRD2gene that is required for normal bone physiology. Bone-related pathways involving some of the genes were also identified including chloride channel activity, which regulates bone reabsorption, and intermediate filament organization, which plays a role in the regulation of bone mass. Our result supports previous studies that suggest that bone strength is highly regulated by genetics. It is therefore possible to reduce bone fractures in laying hens through genetic selection and ultimately improve hen welfare.

Genomic Selection is an important topic in quantitative genetics and breeding. Not only does it allow the full use of current molecular genetic technologies, it stimulates also the development of new methods and models. Genomic selection, if fully implemented in commercial farming, should have a major impact on the productivity of various agricultural systems. But suggested approaches need to be applicable in commercial breeding populations. Many of the published research studies focus on methodologies. We conclude from the reviewed publications, that a stronger focus on strategies for the implementation of genomic selection in advanced breeding lines, introduction of new varieties, hybrids or multi-line crosses is needed. Efforts to find solutions for a better prediction and integration of environmental influences need to continue within applied breeding schemes. Goals of the implementation of genomic selection into crop breeding should be carefully defined and crop breeders in the private sector will play a substantial part in the decision-making process. However, the lack of published results from studies within, or in collaboration with, private companies diminishes the knowledge on the status of genomic selection within applied breeding programmes. Studies on the implementation of genomic selection in plant breeding need to evaluate models and methods with an enhanced emphasis on population-specific requirements and production environments. Adaptation of methods to breeding schemes or changes to breeding programmes for a better integration of genomic selection strategies are needed across species. More openness with a continuous exchange will contribute to successes.

Arctic charr (Salvelinus alpinus) is a high-value species for the Nordic aquaculture. The highly variable reproductive performance that is commonly observed in commercial farms is hindering the expansion of the Arctic charr industry in Sweden. Traits related to sperm motility (total motility; curvilinear velocity; average path velocity; straight-line velocity) and concentration can play a pivotal role in male fertility. Selective breeding practices could offer solutions and contribute to improving male fertility. The current study aimed to investigate the magnitude of genetic variance for sperm quality traits in a selectively bred population of Arctic charr from Sweden and evaluate the possibility of their improvement through selection. Sperm motility and concentration were recorded using a computer-assisted semen analysis (CASA) system and a NucleoCounter, respectively, in over 400 males from year-class 2017. Double digest restriction-site associated DNA sequencing (ddRAD-seq) was applied in a subset of the recorded animals (n = 329), resulting in the detection of over 5000 single nucleotide polymorphisms (SNPs). Moderate heritability estimates were obtained for the recorded semen traits using both pedigree (0.21–0.32; SE 0.09) and genomic (0.23–0.26; SE 0.09) relationship matrices. A genome-wide association study (GWAS) detected a single SNP significantly associated (P < 1e-05) with total sperm motility on chromosome LG7 in relatively close proximity (500 Kb) to PTPN11a gene previously associated with sperm quality traits in mammals. Moreover, weighted single-step genomic best linear unbiased prediction (WssGBLUP) pinpointed genomic regions explaining more than 3 % of the additive genetic variance for both the motility traits and the sperm concentration. Finally, the efficiency of genomic prediction was tested using a 3-fold cross-validation scheme. Higher prediction accuracy for total motility and velocities (both curvilinear and average path) was obtained using genomic information (0.26–0.29, SE 0.03–0.06) compared to pedigree (0.20–0.28, SE 0.04–0.07), while for sperm concentration a pedigree-based model (0.22 SE 0.03) was more efficient than the genomic model (0.14 SE 0.04). Overall, our results indicate that the recorded sperm quality traits are heritable, and could be improved through selective breeding practices.

We describe the results from genetic dissection of a QTL region on chicken chromosome 2, shown to affect egg weight and quality in an earlier genome scan of an F2 intercross between two divergent egg layer lines. As the 90% confidence intervals for the detected QTL covered tens of centiMorgans, new analyses were needed. The datasets were reanalysed with denser marker intervals to characterise the QTL region. Analysis of a candidate gene from the original QTL region, vimentin, did not support its role in controlling egg white thinning. Even after reanalysis with additional seven markers in the QTL area, the 90% confidence intervals remained large or even increased, suggesting the presence of multiple linked QTL for the traits. A grid search fitting two QTL on chromosome 2 for each trait suggested that there are two distinct QTL areas affecting egg white thinning in both production periods and egg weight in the late production period. The results indicate possible pleiotropic effects of some of the QTL on egg quality and egg weight. However, it was not possible to make a distinction between close linkage versus pleiotropic effects.

Skeletal damage is a challenge for laying hens, as the adaptations for egg laying make them susceptible to osteoporosis. We know that activity, growth and puberty influence skeletal quality genetics. However, in this story, we follow the process of resolving a QTL for skeletal quality to a single gene. Providing both a nutritional and a genetic solution and illustrating another level of complexity. Using divergently selected populations in an F2 cross, a QTL for skeletal quality was described. Utilising a series of experiments in the commercial founder line the QTL was fine mapped on chromosome 1 and the differences in physiology of hens that segregated for markers at the locus defined e.g. tibia breaking strength 200.4 vs 218.1 Newton (p< 0.002). Transcriptome profiling of tibia from the high and low bone strength genotype revealed a highly differentially expressed gene co localising to the QTL, the enzyme cystathionine beta synthase (CBS). CBS is a component of one carbon metabolism. Plasma homocysteine, the substrate of CBS had a higher concentration in the genotype associated with poor bone quality. Homocysteine interferes with crosslinking of the collagen matrix, critical to bone formation. Homocysteine can be re-methylated into methionine, a limiting amino acid in laying hens, using betaine as a methyl donor. Testing the hypothesis that reducing plasma homocysteine by feeding betaine, a widely available feed additive, would improve bone quality in laying hens proved successful.This is just one component of a complex trait and its elucidation took us along unexpected routes. However, I am optimistic that with modern tools and an open mind we can progress more quickly. Alongside understanding the factors that determine skeletal quality genetics, the discovery of the mechanisms behind complex traits, although rarely easy, offer the potential for novel interventions to improve animal health and production.

Abstract.: A multiple-marker mapping approach was used to search for quantitative trait loci (QTLs) affecting production, health, and fertility traits in Finnish Ayrshire dairy cattle. As part of a whole-genome scan, altogether 469 bulls were genotyped for six microsatellite loci in 12 families on Chromosome (Chr) 23. Both multiple-marker interval mapping with regression and maximum-likelihood methods were applied with a granddaughter design. Eighteen traits, belonging to 11 trait groups, were included in the analysis. One QTL exceeded experiment level and one QTL genome level significance thresholds. Across-families analysis provided strong evidence (Pexperiment= 0.0314) for a QTL affecting live weight. The QTL for live weight maps between markers BM1258 and BoLA DRBP1. A QTL significant at genome level (Pgenome= 0.0087) was mapped for veterinary treatment, and the putative QTL probably affects susceptibility to milk fever or ketosis. In addition, three traits exceeded the chromosome 5% significance threshold: protein percentage of milk, calf mortality (sire), and milking speed. In within-family analyses, protein percentage was associated with markers in one family (LOD score = 4.5).