Peer Berg

Reindeer and caribou (Rangifer tarandus) play key ecological, cultural, and economical roles across Arctic and Subarctic regions. However, genome-wide patterns of genetic diversity and population structure in semi-domesticated reindeer from Norway remain insufficiently characterized. Here we generated a high-quality chromosome-level genome assembly (GCA_965153185.1) for Norwegian semi-domesticated Eurasian tundra reindeer (Rangifer tarandus tarandus). The genome spans 2.54 Gb, with a scaffold N50 of 75.6 Mb, 96.1% complete Benchmarking Universal Single-Copy Orthologues, and 39,855 predicted protein-coding genes. Using this reference, we performed whole-genome resequencing of 175 individuals from five reindeer populations from Norway and 28 individuals from Iceland, identifying ~19.9 million genetic variants. Genetic differentiation was low among Norwegian populations (FST = 0.005 to 0.011), but substantially higher between Norway and Iceland (FST = 0.140 to 0.161). Populations from Norway exhibited similar levels of nucleotide diversity (π = 1.39 to 1.62 × 10−3), whereas the Icelandic population showed reduced diversity (π = 0.99 × 10−3) and approximately half as many segregating variants. Analyses of runs of homozygosity (ROH) and genome-wide heterozygosity indicated low levels of recent inbreeding across all populations, with long ROHs (>8 Mb) being rare. Despite reduced genetic diversity, the Icelandic population showed limited evidence of recent inbreeding. These patterns are consistent with contrasting demographic histories, with gene flow maintaining diversity among populations from Norway, while founder effects combined with long-term isolation have shaped the Icelandic population.

Feed efficiency (FE) is a major determinant of economic and environmental sustainability in Atlantic salmon aquaculture, yet the biological drivers of FE during the saltwater (SW) phase remain poorly understood. This study aimed to develop and validate methods for predicting visceral fat percentage (VFP) and estimate its genetic relationships with growth, fillet lipid deposition, and feed-efficiency traits. A population of 836 fish from 30 families was phenotyped for growth, feed intake, and body composition traits. VFP was predicted with high accuracy using near-infrared spectroscopy on homogenized viscera (cross-validated R2 = 0.91), while fillet fat percentage (FFP) was predicted using Raman spectroscopy (cross-validated R2 = 0.58). Genetic parameters were estimated using animal models based on genomic relationships. VFP was moderately heritable (h2 = 0.28 ± 0.06) and showed a strong positive genetic correlation with feed conversion ratio (FCR; rg = 0.90), indicating that lower visceral lipid was genetically associated with improved FE. When relative visceral weight was partitioned into lipid and non-lipid components, decreased visceral lipid was specifically associated with improved FCR, whereas increased relative non-lipid organ visceral mass was associated with higher specific growth rate. FFP was only moderately genetically correlated with FCR traits (rg = 0.34-0.53). A negative partial genetic correlation between VFP and FFP conditional on body weight (rg = -0.36 ± 0.15) suggested a small allocation tradeoff between lipid compartments. Overall, visceral lipid content is a heritable and informative indicator trait for improving FE in SW Atlantic salmon.

Understanding fatty acid (FA) composition of Atlantic salmon is demanding for breeding objective due to the sustainable transitions toward plant-based diets, which reduce omega-3 content in farmed fish. Traditional FA quantitative method using gas-chromatography (GC) are resource-intensive and sample destructive, making large-scale phenotypic analysis difficult. While Raman spectroscopy offers an alternative method, its utility for genetic evaluation on intact salmon fillets remains largely unexplored. This study aimed to estimate genetic parameters for FA traits predicted by Raman spectroscopy under semi-commercial conditions and investigate the underlying genetic architecture using genome-wide association study (GWAS) in 810 Atlantic salmon muscle intact fillet at the saltwater phase.A total of 13 FA traits were predicted using Raman scattering spectroscopy used with Partial Least Square Regression (PLSR), achieving predictive moderate to high performance (r2 = 0.64 - 0.96). Genotyping was performed using a 62K SNP array, resulting in 41,280 SNPs and 810 individuals after quality control. Heritability estimates (h²) for FA traits ranged from 0.04 ± 0.03 (eicosapentaenoic acid; EPA) to 0.44 ± 0.06 (Saturated fatty acid; SFA), which is low to moderate. A strong negative genetic correlation between polyunsaturated FA (PUFA) and other grouped FAs, such as total fat, SFA, and monounsaturated fatty acid (MUFA) showed antagonistic relationships among these FAs and further indicates that increase fillet fat is not directly increasing n-3 omega-3 FAs. Genome-wide association study identified 26 significant SNPs (21 unique SNPs) associations in 9 of 13 FA traits, supporting a polygenic structure of FA composition in Atlantic salmon. Notably, a single SNP on chromosome 5 (Affx-87018966) was associated with multiple traits (MUFA, oleic acid; OA, EPA+DHA, and docosahexaenoic acid; DHA), indicating potential shared genetic architecture. No significant associations were detected for total fat, PUFA, EPA, and alpha-linolenic acid; ALA, likely to reflect stronger environmental (dietary) influence on these traits.Our findings demonstrate that Raman spectroscopy of intact fillets retains sufficient genetic signal to support heritability estimation and genomic association analysis, offering a feasible, high-throughput phenotyping strategy for integrating FA traits into genomic selection programs in salmon breeding.

Background: The goal of managing genetic diversity is to maintain both the genomic uniqueness and adaptability of a population. This entails both maintaining heterozygosity and avoiding deleterious alleles from drifting to higher frequencies. Thus, genomic management strategies should not systematically change frequencies at neutral loci, as has been observed in current genomic management. We simulated 50 replicates of a population managed with optimal contribution selection (OCS), where inbreeding was controlled using different relationship matrices, where Van Raden method I (G _VR ), runs-of-homozygosity (G _ROH ), and identity by descent relationships (IBD) only used genomic information and a linkage analysis-based matrix (G _FGLA ) leveraged both genomic and pedigree information. Results: Across 50 simulated replicates, G _FGLA achieved the highest correlation with true IBD for both inbreeding and coancestry estimates and provided the most accurate rate of inbreeding (ΔF). G _FGLA also delivered the greatest genetic gain per unit of inbreeding and was the only scheme to remain below the inbreeding target while minimizing frequency change at neutral loci. G _VR using base population frequencies produced high genetic gain and controlled drift effectively but introduced systematic allele frequency changes towards the closest extreme frequency. Using current allele frequency resulted in high levels of inbreeding compared to the genetic gain achieved. G _ROH showed strong dependence on the minimum ROH length: short ROH improved ΔF estimation but increased allele frequency changes toward intermediate values, whereas long ROH underestimated inbreeding and reduced genetic gain. Conclusions: IBD-based matrices such as G _FGLA offer the most balanced approach for sustainable population management in OCS schemes, combining accurate relationship estimates, effective inbreeding control, and neutrality at neutral loci. In contrast, G _VR and G _ROH require calibration and cause systematic allele frequency changes.

Background: Genomic relationship and inbreeding estimates are either based on genetic drift (e.g. the Genomic Relationship Matrix; GRM ), homozygosity (e.g. Runs of Homozygosity; ROH), or Identity-By-Descent (IBD). A genomic IBD-based relationship matrix, G _la , is obtained by linkage analysis which uses genomic data to distinguish paternal versus maternal inheritances of chromosomal segments to replace the 50/50 probabilities used to calculate pedigree-based relationships ( A matrix). Our aim was to develop a fast approximate algorithm, FGla, to estimate the G _la matrix in large complex pedigrees making use of dense marker genotypes, and to compare G _la to A , GRM and ROH based inbreeding ( F _ROH ) in simulated and a large scale Norwegian Red Cattle (NRF) data set. Results: Given pedigree data and ≥ 3 generations of 45 k marker genotypes, marker positions were detected that unambiguously identified maternal/paternal inheritance, and inheritances at intermediate positions were imputed by the Viterbi algorithm from the positions with known inheritance. Any remaining unknown inheritances were randomly sampled (paternal or maternal), and the sampling errors that this introduced were averaged out by the large number of marker loci used (correlation between replicated estimates: 0.9998). Also, calculations were limited to the relationship coefficients that were actually needed, assuming that relationships for a limited set of candidates were needed. The accuracy of estimated G _la coefficients increased from 0.971 to 0.998, when genotyping increased from the actually genotyped NRF cattle towards all pedigreed animals. The accuracy of the GRM was 0.936, but required only genotyping of the animals whose relationships were needed. G _la relationships were approximately unbiased in the Best Linear Unbiased Prediction (BLUP) sense. Hence, if G _la based inbreeding management predicts an increase in relationships then an identical increase in true IBD relationships is expected. G _la uses the same base population as A , namely that of the pedigree. Conclusions: An approximate computationally efficient multipoint linkage analysis algorithm was developed to estimate unbiased IBD-based relationship and inbreeding coefficients. Its unbiasedness and precise definition of the base population makes it well suited for the genomic management of inbreeding and genomic optimal contribution selection. In addition, G _la based optimal contribution selection is neutral with respect to allele frequency changes.

Sustainable breeding of native breeds is essential to preserve genetic diversity and cultural heritage. Several native Nordic horse breeds are at risk of extinction and lack genetic characterization. This study aimed to analyze genetic variation and kinship within and among native Nordic horse breeds using whole genome sequence data, and to compare results from using a Finnhorse genome assembly to that of the EquCab3.0 (Thoroughbred) reference genome. The breeds Dola horse, North Swedish horse and Coldblooded Trotter showed close genetic relationship for fixation index (0.04-0.10), and in principal component analysis. The other breeds showed stronger genetic differentiation, especially the Faroese horse with fixation index above 0.21 to all other breeds. This breed had the highest genomic inbreeding of 33% and a heterozygosity of 12%. The Swedish Ardennes showed the lowest inbreeding at 14% and a heterozygosity of 16%. The North Swedish horses had the highest historical Ne of 96, estimated 13 generations back in time, and the Faroese horse the lowest (23). The mean identity by descent varied from 17% for Swedish Ardennes to 40% for Faroese horses. The choice of reference genomes gave minor to moderate differences, suggesting that a closer related reference improves precision for fine mapping and understanding of genetic landscapes of Nordic breeds. Together, the different analyses showed low genetic diversity in all breeds, and the general pattern of relatedness largely agreed with the known breed history. The results underline the importance of maintaining genetic diversity for the survival of the breeds.

Runs of Homozygosity (ROH) are commonly used to quantify autozygosity/identity‐by‐descent (IBD) in an individual or population. However, the method's accuracy at the segment level in livestock populations has only been evaluated in a few studies. Thus, the aim of this study was to determine to what extent ROH are truly IBD and estimate the proportion of IBD segments that go undetected in a simulated livestock population. We simulated a population of randomly mating animals for 100 generations. The genome consisted of a single chromosome with a SNP density of either 46 or 92 SNPs per mega base (Mb). In addition, a set of founder markers tracing IBD was recorded. ROH were detected using four different parameter combinations. Using the two sets of markers, we calculated the true positive rate, power, and overall correlation between true ( F _IBD ) and estimated inbreeding ( F _ROH ). Additionally, a new measure for within‐ROH inbreeding (F|ROH) was introduced and calculated the level of homozygosity within a ROH compared to the general expectation in the genome. The results indicate that ROH longer than 2 Mb are a reliable indicator of IBD, with the F|ROH being over 0.9 for all ROH lengths and parameter combinations. True positive rates only exceeded 0.9 consistently for ROH over 9 Mb, indicating that many of the identified ROH may be associated with common ancestors more ancient than the base population. The power was mainly controlled by the parameter stringency, that is, allowing for shorter ROH increased the power. The ROH‐based individual measure of inbreeding F _ROH was highly correlated to F _IBD while also having regression coefficients close to 1 (i.e., a 1% variation in F _ROH corresponded to a 1% variation in F _IBD ). Using stringent ROH parameters resulted in underestimation of the rate of inbreeding in the population. Increasing marker density improved predictions, including a higher true positive rate, power, higher correlations, and less underestimation of inbreeding rates.

This study evaluated the effects of pedigree and genomic inbreeding on survival in Danish Jersey (JER) and Holstein (HOL) dairy cows. Survival probabilities and hazard risks (HR) were estimated using Kaplan-Meier analysis and Cox proportional hazards models, with genomic inbreeding quantified through varying lengths of runs of homozygosity (ROH). The results indicated that JER cows had survival probabilities 1.3 to 4 percentage points higher after first calving and throughout later life, along with HR 22 to 29 percentage points lower compared with HOL cows. Both genomic (F_roh) and pedigree inbreeding coefficients increased HR by 1% for each 1% increase in inbreeding. Differences in F_roh based on ROH lengths revealed that longer segments (>10 Mb) increased HR by 2 to 3 percentage points, whereas shorter segments (1-2 Mb) reduced HR by 5 to 7 percentage points. Survival probabilities increased with increasing breeding values. These findings underscore the importance of managing genomic inbreeding to reduce overall culling risks and increase cow survival. Avoiding close inbreeding (ROH >5 Mb) and incorporating genomic relationships into breeding programs can promote the sustainability of dairy systems.

In recent years, Genomic Selection (GS) has accelerated genetic gain in dairy cattle breeds worldwide. Despite the evident genetic progress, several dairy populations have also encountered challenges such as heightened inbreeding rates and reduced effective population sizes. The challenge has been to find a balance between achieving substantial genetic gain while managing genetic diversity within the population, thereby mitigating the negative effects of inbreeding depression. This study aims to elucidate the impact of GS on pedigree and genomic rates of inbreeding (ΔF) and coancestry (ΔC) in Nordic Jersey (NJ) and Holstein (NH) cattle populations. Furthermore, key genetic metrics including the generation interval (L), effective population size (Ne), and future effective population size (FNe) were assessed between 2 time periods, before and after GS, and across distinct animal cohorts in both breeds: females, bulls, and approved semen-producing bulls (AI-sires). Analysis of ΔF and ΔC revealed distinct trends across the studied periods and animal groups. Notably, there was a consistent increase in yearly ΔF for most animal groups in both breeds. An exception was observed in NH AI-sires, which demonstrated a slight decrease in yearly ΔF. Moreover, NJ displayed minimal changes in yearly ΔC between the periods, whereas NH exhibited elevated ΔC values across all animal groups. Particularly striking was the substantial increase in yearly ΔC within the NH female population, surging from 0.02% to 0.39% between the periods. Implementation of GS resulted in a reduction of the generation interval across all animal cohorts in both NJ and NH breeds. However, the extent of reduction was more pronounced in males compared with females. This reduction in generation interval influenced generational changes in ΔF and ΔC. Bulls and AI-sires of both breeds exhibited reduced generational ΔF between periods, in contrast to females that demonstrated an opposing pattern. Between the periods, NJ maintained a relatively stable Ne, 29.4 before and 30.3 after GS, while NH experienced a notable decline from 54.3 to 42.8. Female groups in both breeds displayed a negative Ne trend, while males demonstrated either neutral or positive Ne developments. Regarding FNe, NJ exhibited positive FNe development with an increase from 40.7 to 57.2. The opposite was observed in NH, where FNe decreased from 198.8 to 42.7. In summary, it was evident that the genomic methods could detect differences between the populations and changes in ΔF and ΔC more efficiently than pedigree methods. GS implementation yielded positive outcomes within the NJ population regarding the rate of coancestry but the opposite was observed with NH. Moreover, analysis of ΔC data hints at the potential to decrease future ΔF through informed mating strategies. Conversely, NH faces more pressing concerns, even though ΔF remains comparatively modest in contrast to what has been observed in other Holstein populations. These findings underscore the necessity of genomic control of inbreeding and coancestry with strategic changes in the Nordic breeding schemes for dairy to ensure long-term sustainability in the forthcoming years.