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• Key message: Pronounced additive genetic variation and high narrow-sense heritability for lesion length caused by Neonectria neomacrospora were found in a Nordmann fir progeny test. Significant inbreeding depression was detected in traits important for Christmas tree production. Recurrent selection for multiple traits would be successful for Christmas tree quality traits. • Context: The fungal pathogen N. neomacrospora causes severe damage in Nordmann fir Christmas trees in Denmark. Family variation in disease susceptibility in the species has not been investigated before. This is the first combined genetic analysis of susceptibility to N. neomacrospora and Christmas tree traits in Nordmann fir. • Aims: Evaluate the genetic variation of susceptibility to N. neomacrospora and five Christmas tree traits in Nordmann fir. • Methods: Five Christmas tree traits were measured on 2413 trees in a progeny test. Artificial inoculation was conducted on detached twigs of full-sib progenies with a N. neomacrospora isolate to assess the resistance/susceptibility. Observed variation was partitioned into genetic and environmental causes to understand the heritable control of the traits. • Results: Pronounced additive genetic variation was observed in susceptibility to N. neomacrospora and Christmas tree traits. Narrow-sense heritability for susceptibility to N. neomacrospora was 0.63. Significant differences between selfings and outcrossed trees were detected for all traits. Significant improvement for Christmas tree quality could be observed in the breeding process. • Conclusion: Resistance to N. neomacrospora disease and other Christmas tree characteristics can be improved through recurrent selection. [ABSTRACT FROM AUTHOR]

Context Nordmann fir, a widely used Christmas tree species in Europe, has, since 2011, been increasingly damaged by a canker disease caused by Neonectria neomacrospora. Aims The objective was to study the genetic variation and genotype by environment interaction in the susceptibility of Nordmann fir to N. neomacrospora. Methods Damage caused by N. neomacrospora was evaluated using a visual scale in three Nordmann fir clonal seed orchards in Denmark, partly containing the same clones. Results Damage due to N. neomacrospora was substantial at all three sites, and no clone was completely resistant to N. neomacrospora, but a large genetic variation in the susceptibility was detected among clones. Estimates of single-site individual broad-sense heritability for susceptibility varied between 0.38 and 0.47. The average type-B genetic correlation for damage score across sites was 0.34. Conclusion Genetic variation was very pronounced, and significant G × E interactions were detected for susceptibility. Further investigations of narrow-sense heritability, expression of the trait in younger material, and identification of the cause of G × E for N. neomacrospora susceptibility in Nordmann fir across different sites are recommended. [ABSTRACT FROM AUTHOR]

Background: A whole-genome association study of 4631 progeny-tested Nordic Red dairy cattle bulls using imputed next-generation sequencing data revealed a major quantitative trait locus (QTL) that affects birth index (BI) on Bos taurus autosome (BTA) 23. We analyzed this QTL to identify which of the component traits of BI are affected and understand its molecular basis. Results: A genome-wide scan of BI in Nordic Red dairy cattle detected major QTL on BTA6, 14 and 23. The strongest associated single nucleotide polymorphism (SNP) on BTA23 was located at 13,313,896 bp with -log10(p) = 50.63. Analyses of component traits showed that the QTL had a large effect on stillbirth. Based on the 10 most strongly associated SNPs with stillbirth, we constructed a haplotype. Among this haplotype's alleles, HAPQTL had a large negative effect on stillbirth. No animals were found to be homozygous for HAPQTL. Analysis of stillbirth records that were categorized by carrier status for HAPQTL of the sire and maternal grandsire suggested that this haplotype had a recessive mode of inheritance. Illumina BovineHD BeadChip genotypes and genotype intensity data indicated a chromosomal deletion between 12.28 and 12.81 Mbp on BTA23. An independent set of Illumina Bovine50k BeadChip genotypes identified a recessive lethal haplotype that spanned the deleted region. Conclusions: A deleted region of approximately 500 kb that spans three genes on BTA23 was identified and is a strong candidate QTL with a large effect on BI by increasing stillbirth. [ABSTRACT FROM AUTHOR]

Background: A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population. Methods: The data consisted of de-regressed proofs (DRP) for 5 214 genotyped and 9 374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect. Results: Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods. Conclusions: The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix. [ABSTRACT FROM AUTHOR]

• Context: Many tree breeding programmes rely entirely on clonal seed orchards as the link between breeding activities and forestry, and are thereby also exposed to yearly fluctuations in the orchard crops. • Aims: The main objective was to study the impact of year and clone fluctuations in strobili production on genetic worth, as well as on genetic diversity, of 18 consecutive commercial seed orchard crops. • Methods: In a mature Abies nordmanniana clonal seed orchard, a yearly visual assessment of female and male strobili was carried out on a total of 18 clones (260 ramets), and coupled with clone breeding values. • Results: Despite large annual and clone variation, and year-by-clone interaction in strobili production, the orchard's genetic worth was somewhat uniform when considering four evaluated traits in the 11 years of superior or medium crop size. These years accounted for 95% of the accumulated cone crop over the whole period (18 years). Noteworthy deviations were only seen in the seven poorest seed years, comprising the remaining 5% of the total cone crop, where genetic diversity measures were also low. • Conclusion: Avoiding small crop years seems to be a reasonable way to avoid fluctuations in the commercial seed orchard product. [ABSTRACT FROM AUTHOR]

Background: Discovery of tumor-selective antibodies or antibody fragments is a promising approach for delivering therapeutic agents to antigen over-expressing cancers. Therefore it is important to develop methods for the identification of target- and function specific antibodies for effective drug delivery. Here we describe a highly selective and sensitive method for characterizing the internalizing potential of multivalently displayed antibodies or ligands conjugated to liposomes into tumor cells. The assay requires minute amounts of histidine-tagged ligand and relies on the non-covalent coupling of these antibodies to fluorescent liposomes containing a metal ion-chelating lipid. Following incubation of cells with antibody-conjugated liposomes, surface bound liposomes are gently removed and the remaining internalized liposomes are quantitated based on fluorescence in a high throughput manner. We have termed this methodology "Chelated Ligand Internalization Assay", or CLIA. Results: The specificity of the assay was demonstrated with different antibodies to the ErbB-2 and EGF receptors. Antibody-uptake correlated with receptor expression levels in tumor cell lines with a range of receptor expression. Furthermore, Ni-NTA liposomes containing doxorubicin were used to screen for the ability of antibodies to confer target-specific cytotoxicity. Using an anti-ErbB2 single chain Fv (scFv) (F5) antibody, cytotoxicity could be conferred to ErbB2-overexpressing cells; however, a poly(ethylene glycol)-linked lipid (DSPE-PEG-NTA-Ni) was necessary to allow for efficient loading of the drug and to reduce nonspecific drug leakage during the course of the assay. Conclusion: The CLIA method we describe here represents a rapid, sensitive and robust assay for the identification and characterization of tumor-specific antibodies capable of high drug-delivery efficiency when conjugated to liposomal nanocarriers. [ABSTRACT FROM AUTHOR]

Background: A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population., Methods: The data consisted of de-regressed proofs (DRP) for 5,214 genotyped and 9,374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect., Results: Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods., Conclusions: The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix.