Nina Aagaard Poulsen

Genomic signatures of local directional selection in a high gene flow marine organism; the Atlantic cod (Gadus morhua).

BackgroundMarine fishes have been shown to display low levels of genetic structuring and associated high levels of gene flow, suggesting shallow evolutionary trajectories and, possibly, limited or lacking adaptive divergence among local populations. We investigated variation in 98 gene-associated single nucleotide polymorphisms (SNPs) for evidence of selection in local populations of Atlantic cod (Gadus morhua L.) across the species distribution.ResultsOur global genome scan analysis identified eight outlier gene loci with very high statistical support, likely to be subject to directional selection in local demes, or closely linked to loci under selection. Likewise, on a regional south/north transect of central and eastern Atlantic populations, seven loci displayed strongly elevated levels of genetic differentiation. Selection patterns among populations appeared to be relatively widespread and complex, i.e. outlier loci were generally not only associated with one of a few divergent local populations. Even on a limited geographical scale between the proximate North Sea and Baltic Sea populations four loci displayed evidence of adaptive evolution. Temporal genome scan analysis applied to DNA from archived otoliths from a Faeroese population demonstrated stability of the intra-population variation over 24 years. An exploratory landscape genetic analysis was used to elucidate potential effects of the most likely environmental factors responsible for the signatures of local adaptation. We found that genetic variation at several of the outlier loci was better correlated with temperature and/or salinity conditions at spawning grounds at spawning time than with geographic distance per se.ConclusionThese findings illustrate that adaptive population divergence may indeed be prevalent despite seemingly high levels of gene flow, as found in most marine fishes. Thus, results have important implications for our understanding of the interplay of evolutionary forces in general, and for the conservation of marine biodiversity under rapidly increasing evolutionary pressure from climate and fisheries induced changes in local environments.

The occurrence of noncoagulating milk and the association of bovine milk coagulation properties with genetic variants of the caseins in 3 Scandinavian dairy breeds

Substantial variation in milk coagulation properties has been observed among dairy cows. Consequently, raw milk from individual cows and breeds exhibits distinct coagulation capacities that potentially affect the technological properties and milk processing into cheese. This variation is largely influenced by protein composition, which is in turn affected by underlying genetic polymorphisms in the major milk proteins. In this study, we conducted a large screening on 3 major Scandinavian breeds to resolve the variation in milk coagulation traits and the frequency of milk with impaired coagulation properties (noncoagulation). In total, individual coagulation properties were measured on morning milk collected from 1,299 Danish Holstein (DH), Danish Jersey (DJ), and Swedish Red (SR) cows. The 3 breeds demonstrated notable interbreed differences in coagulation properties, with DJ cows exhibiting superior coagulation compared with the other 2 breeds. In addition, milk samples from 2% of DH and 16% of SR cows were classified as noncoagulating. Furthermore, the cows were genotyped for major genetic variants in the αS1- (CSN1S1), β- (CSN2), and κ-casein (CSN3) genes, revealing distinct differences in variant frequencies among breeds. Allele I of CSN2, which had not formerly been screened in such a high number of cows in these Scandinavian breeds, showed a frequency around 7% in DH and DJ, but was not detected in SR. Genetic polymorphisms were significantly associated with curd firming rate and rennet coagulation time. Thus, CSN1S1 C, CSN2 B, and CSN3 B positively affected milk coagulation, whereas CSN2 A(2), in particular, had a negative effect. In addition to the influence of individual casein genes, the effects of CSN1S1-CSN2-CSN3 composite genotypes were also examined, and revealed strong associations in all breeds, which more or less reflected the single gene results. Overall, milk coagulation is under the influence of additive genetic variation. Optimal milk for future cheese production can be ensured by monitoring the frequency of unfavorable variants and thus preventing an increase in the number of cows producing milk with impaired coagulation. Selective breeding for variants associated with superior milk coagulation can potentially increase raw milk quality and cheese yield in all 3 Scandinavian breeds.

Milk protein genetic variants and isoforms identified in bovine milk representing extremes in coagulation properties

A gel-based proteomic approach consisting of 2-dimensional gel electrophoresis coupled with mass spectrometry was applied for detailed protein characterization of a subset of individual milk samples with extreme rennet coagulation properties. A milk subset with either good or poor coagulation abilities was selected from 892 Danish Holstein-Friesian and Jersey cows. Screening of genetic variants of the major milk proteins resulted in the identification of common genetic variants of β-casein (CN; A(1), A(2), B), κ-CN (A, B), and β-lactoglobulin (LG; A, B), as well as a low frequency variant, κ-CN variant E, and variants not previously reported in Danish breeds (i.e., β-CN variant I and β-LG variant C). Clear differences in the frequencies of the identified genetic variants were evident between breeds and, to some extent, between coagulation groups within breeds, indicating that an underlying genetic variation of the major milk proteins affects the overall milk coagulation ability. In milk with good coagulation ability, a high prevalence of the B variants of all 3 analyzed proteins were identified, whereas poorly coagulating milk was associated with the β-CN variant A(2), κ-CN variant A or E, and β-LG variant A or C. The β-CN variant I was identified in milk with both good and poor coagulation ability, a variant that has not usually been discriminated from β-CN variant A(2) in other studied cow populations. Additionally, a detailed characterization of κ-CN isoforms was conducted. Six κ-CN isoforms varying in phosphorylation and glycosylation levels from each of the genetic variants of κ-CN were separated and identified, along with an unmodified κ-CN form at low abundance. Relative quantification showed that around 95% of total κ-CN was phosphorylated with 1 or 2 phosphates attached, whereas approximately 35% of the identified κ-CN was glycosylated with 1 to 3 tetrasaccharides. Comparing isoforms from individual samples, we found a very consistent κ-CN isoform pattern, with only minor differences in relation to breed, κ-CN genetic variant, and milk coagulation ability.

Nuclear magnetic resonance metabonomics reveals strong association between milk metabolites and somatic cell count in bovine milk

Somatic cell count (SCC) is associated with changes in milk composition, including changes in proteins, lipids, and milk metabolites. Somatic cell count is normally used as an indicator of mastitis infection. The compositional changes in protein and fat affect milk coagulation properties, and also the metabolite composition is thought to contribute to differential milk properties. Milk somatic cells comprise different cell types, which may contribute to differential milk metabolite fingerprints. In this study, milk from a relatively large number of individual cows, representing significant differences in SCC, were analyzed by nuclear magnetic resonance (NMR)-based metabonomics, and the milk metabolite profiles were analyzed for differences related to SCC. Global principal component analysis performed on 876 samples from 2 Danish dairy breeds and orthogonal projection of latent structures discriminant analysis performed on a smaller subset (n=70) representing high (SCC >7.2×10(5) cells/mL) and low (SCC <1.4×10(4) cells/mL) milk SCC identified latent variables, which could be attributed to milk with elevated SCC. In addition, partial least squares regression between the NMR milk metabolite profiles and SCC revealed a strong correlation. The orthogonal projection of latent structures discriminant analysis and partial least squares regressions pinpointed specific NMR spectral regions and thereby identification of milk metabolites that differed according to SCC. Relative quantification of the identified metabolites revealed that lactate, butyrate, isoleucine, acetate, and β-hydroxybutyrate were increased, whereas hippurate and fumarate were decreased in milk with high levels of somatic cells.

The influence of feed and herd on fatty acid composition in 3 dairy breeds (Danish Holstein, Danish Jersey, and Swedish Red)

The composition of milk fat from dairy cows is related to both genetic and environmental factors. Here, the effect of feed and herd was examined in 3 Scandinavian breeds, namely Danish Holstein-Friesian (DH), Danish Jersey (DJ), and Swedish Red (SR). In total, milk samples from 1,298 cows kept in indoor housing systems were collected from 61 conventional dairy herds in Denmark and Sweden. The fatty acid (FA) composition of milk was determined by gas chromatography and the content of α-tocopherol by HPLC. Based on the 17 individual FA determined, distinct FA profiles were observed for all breeds using univariate and multivariate statistics. The DJ cows were characterized by higher levels of saturated short-chain FA; in contrast, DH cows had higher content of unsaturated C18 FA, whereas higher levels of primarily C14:0, C14:1, C18:1 cis-9, and C18:3n-3 were evident in SR cows. This variation in milk fat composition across breeds was further reflected in different desaturase indices, which were generally higher in SR cows. In addition, α-tocopherol differed significantly among breeds, with DJ cows having the highest content. Herd-specific feeding plans were collected, and different feed items were separated into 4 broad feed categories, including grass products, maize silage, grain, and concentrate. The pronounced differences in overall feed composition among breeds were, to a large extent, due to regional differences between countries, with SR receiving higher levels of grain and grass silage compared with the Danish breeds. Within breeds, differences in feeding regimens among herds were furthermore higher in SR. Significant correlations between feed category and individual FA were observed in all breeds. Furthermore, variance components were estimated and used to determine the proportion of phenotypic variation that could be explained by herd. The herd effect for individual FA was generally lower for DH compared with the 2 other breeds. In addition, very low herd effects were shown for C14:1 and C16:1 in all breeds, suggesting that the content of these FA is mainly genetically regulated.

Natural variability in bovine milk oligosaccharides from Danish Jersey and Holstein-Friesian breeds

Free oligosaccharides are key components of human milk and play multiple roles in the health of the neonate, by stimulating growth of selected beneficial bacteria in the gut, participating in development of the brain, and exerting antipathogenic activity. However, the concentration of oligosaccharides is low in mature bovine milk, normally used for infant formula, compared with both human colostrum and mature human milk. Characterization of bovine milk oligosaccharides in different breeds is crucial for the identification of viable sources for oligosaccharide purification. An improved source of oligosaccharides can lead to infant formula with improved oligosaccharide functionality. In the present study we have analyzed milk oligosaccharides by high-performance liquid chromatography chip quadrupole time-of-flight mass spectrometry and performed a detailed data analysis using both univariate and multivariate methods. Both statistical tools revealed several differences in oligosaccharide profiles between milk samples from the two Danish breeds, Jersey and Holstein-Friesians. Jersey milk contained higher relative amounts of both sialylated and the more complex neutral fucosylated oligosaccharides, while the Holstein-Friesian milk had higher abundance of smaller and simpler neutral oligosaccharides. The statistical analyses revealed that Jersey milk contains levels of fucosylated oligosaccharides significantly higher than that of Holstein-Friesian milk. Jersey milk also possesses oligosaccharides with a higher degree of complexity and functional residues (fucose and sialic acid), suggesting it may therefore offer advantages in term of a wider array of bioactivities.

Quantification of individual fatty acids in bovine milk by infrared spectroscopy and chemometrics: Understanding predictions of highly collinear reference variables

Predicting individual fatty acids (FA) in bovine milk from Fourier transform infrared (FT-IR) measurements is desirable. However, such predictions may rely on covariance structures among individual FA and total fat content. These covariance structures may change with factors such as breed and feed, among others. The aim of this study was to estimate how spectral variation associated with total fat content and breed contributes to predictions of individual FA. This study comprised 890 bovine milk samples from 2 breeds (455 Holstein and 435 Jersey). Holstein samples were collected from 20 Danish dairy herds from October to December 2009; Jersey samples were collected from 22 Danish dairy herds from February to April 2010. All samples were from conventional herds and taken while cows were housed. Moreover, in a spiking experiment, FA (C14:0, C16:0, and C18:1 cis-9) were added (spiked) to a background of commercial skim milk to determine whether signals specific to those individual FA could be obtained from the FT-IR measurements. This study demonstrated that variation associated with total fat content and breed was responsible for successful FT-IR-based predictions of FA in the raw milk samples. This was confirmed in the spiking experiment, which showed that signals specific to individual FA could not be identified in FT-IR measurements when several FA were present in the same mixture. Hence, predicted concentrations of individual FA in milk rely on covariance structures with total fat content rather than absorption bands directly associated with individual FA. If covariance structures between FA and total fat used to calibrate partial least squares (PLS) models are not conserved in future samples, these samples will show incorrect and biased FA predictions. This was demonstrated by using samples of one breed to calibrate and samples of the other breed to validate PLS models for individual FA. The 2 breeds had different covariance structures between individual FA and total fat content. The results showed that the validation samples yielded biased predictions. This may limit the usefulness of FT-IR-based predictions of individual FA in milk recording as indirect covariance structures in the calibration set must be valid for future samples. Otherwise, future samples will show incorrect predictions.

Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle

BackgroundThe milk fat profile of the Danish Holstein (DH) and Danish Jersey (DJ) show clear differences. Identification of the genomic regions, genes and biological pathways underlying the milk fat biosynthesis will improve the understanding of the biology underlying bovine milk fat production and may provide new possibilities to change the milk fat composition by selective breeding. In this study a genome wide association scan (GWAS) in the DH and DJ was performed for a detailed milk fatty acid (FA) profile using the HD bovine SNP array and subsequently a biological pathway analysis based on the SNP data was performed.ResultsThe GWAS identified in total 1,233 SNPs (FDR < 0.10) spread over 18 chromosomes for nine different FA traits for the DH breed and 1,122 SNPs (FDR < 0.10) spread over 26 chromosomes for 13 different FA traits were detected for the DJ breed. Of these significant SNPs, 108 SNP markers were significant in both DH and DJ (C14-index, BTA26; C16, BTA14; fat percentage (FP), BTA14). This was supported by an enrichment test. The QTL on BTA14 and BTA26 represented the known candidate genes DGAT and SCD. In addition we suggest ACSS3 to be a good candidate gene for the QTL on BTA5 for C10:0 and C15:0. In addition, genetic correlations between the FA traits within breed showed large similarity across breeds. Furthermore, the biological pathway analysis revealed that fat digestion and absorption (KEGG04975) plays a role for the traits FP, C14:1, C16 index and C16:1.ConclusionThere was a clear similarity between the underlying genetics of FA in the milk between DH and DJ. This was supported by the fact that there was substantial overlap between SNPs for FP, C14 index, C14:1, C16 index and C16:1. In addition genetic correlations between FA showed a similar pattern across DH and DJ. Furthermore the biological pathway analysis suggested that fat digestion and absorption KEGG04975 is important for the traits FP, C14:1, C16 index and C16:1.

Effects of breed and casein genetic variants on protein profile in milk from Swedish Red, Danish Holstein, and Danish Jersey cows

In selecting cows for higher milk yields and milk quality, it is important to understand how these traits are affected by the bovine genome. The major milk proteins exhibit genetic polymorphism and these genetic variants can serve as markers for milk composition, milk production traits, and technological properties of milk. The aim of this study was to investigate the relationships between casein (CN) genetic variants and detailed protein composition in Swedish and Danish dairy milk. Milk and DNA samples were collected from approximately 400 individual cows each of 3 Scandinavian dairy breeds: Swedish Red (SR), Danish Holstein (DH), and Danish Jersey (DJ). The protein profile with relative concentrations of α-lactalbumin, β-lactoglobulin, and α(S1)-, α(S2)-, κ-, and β-CN was determined for each milk sample using capillary zone electrophoresis. The genetic variants of the α(S1)- (CSN1S1), β- (CSN2), and κ-CN (CSN3) genes for each cow were determined using TaqMan SNP genotyping assays (Applied Biosystems, Foster City, CA). Univariate statistical models were used to evaluate the effects of composite genetic variants, α(S1)-β-κ-CN, on the protein profile. The 3 studied Scandinavian breeds differed from each other regarding CN genotypes, with DH and SR having similar genotype frequencies, whereas the genotype frequencies in DJ differed from the other 2 breeds. The similarities in genotype frequencies of SR and DH and differences compared with DJ were also seen in milk production traits, gross milk composition, and protein profile. Frequencies of the most common composite α(S1)-β-κ-CN genotype BB/A(2)A(2)/AA were 30% in DH and 15% in SR, and cows that had this genotype gave milk with lower relative concentrations of κ- and β-CN and higher relative concentrations of αS-CN, than the majority of the other composite genotypes in SR and DH. The effect of composite genotypes on relative concentrations of the milk proteins was not as pronounced in DJ. The present work suggests that a higher frequency of BB/A(1)A(2)/AB, together with a decrease in BB/A(2)A(2)/AA, could have positive effects on DH and SR milk regarding, for example, the processing of cheese.

Comparative analysis of inflamed and non-inflamed colon biopsies reveals strong proteomic inflammation profile in patients with ulcerative colitis

BackgroundAccurate diagnostic and monitoring tools for ulcerative colitis (UC) are missing. Our aim was to describe the proteomic profile of UC and search for markers associated with disease exacerbation. Therefore, we aimed to characterize specific proteins associated with inflamed colon mucosa from patients with acute UC using mass spectrometry-based proteomic analysis.MethodsBiopsies were sampled from rectum, sigmoid colon and left colonic flexure from twenty patients with active proctosigmoiditis and from four healthy controls for proteomics and histology. Proteomic profiles of whole colonic biopsies were characterized using 2D-gel electrophoresis, and peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was applied for identification of differently expressed protein spots.ResultsA total of 597 spots were annotated by image analysis and 222 of these had a statistically different protein level between inflamed and non-inflamed tissue in the patient group. Principal component analysis clearly grouped non-inflamed samples separately from the inflamed samples indicating that the proteomic signature of colon mucosa with acute UC is strong. Totally, 43 individual protein spots were identified, including proteins involved in energy metabolism (triosephosphate isomerase, glycerol-3-phosphate-dehydrogenase, alpha enolase and L-lactate dehydrogenase B-chain) and in oxidative stress (superoxide dismutase, thioredoxins and selenium binding protein).ConclusionsA distinct proteomic profile of inflamed tissue in UC patients was found. Specific proteins involved in energy metabolism and oxidative stress were identified as potential candidate markers for UC.