Identification of additional body weight QTLs in the Berlin Fat Mouse BFMI861 lines using time series data.

The Berlin Fat Mouse Inbred line (BFMI) is a model for obesity and metabolic syndrome. The sublines BFMI861-S1 and BFMI861-S2 differ in weight despite high genetic similarity and a shared obesity-related locus. This study focused on identifying additional body weight quantitative trait loci (QTLs) by analyzing weekly weight measurements in a male population of the advanced intercross line BFMI861-S1 x BFMI861-S2. QTL analysis, utilizing 200 selectively genotyped mice (GigaMUGA) and 197 males genotyped for top SNPs, revealed a genome-wide significant QTL on Chr 15 (68.46 to 81.40 Mb) for body weight between weeks 9 to 20. Notably, this QTL disappeared (weeks 21 to 23) and reappeared (weeks 24 and 25) coinciding with a diet change. Additionally, a significant body weight QTL on Chr 16 (3.89 to 22.79 Mb) was identified from weeks 6 to 25. Candidate genes, including Gpt, Cbx6, Apol6, Apol8, Sun2 (Chr 15) and Trap1, Rrn3, Mapk1 (Chr 16), were prioritized. This study unveiled two additional body weight QTLs, one of which is novel and responsive to diet changes. These findings illuminate genomic regions influencing weight in BFMI and emphasize the utility of time series data in uncovering novel genetic factors.

Analysis of strain, sex, and diet-dependent modulation of gut microbiota reveals candidate keystone organisms driving microbial diversity in response to American and ketogenic diets.

BACKGROUND: The gut microbiota is modulated by a combination of diet, host genetics, and sex effects. The magnitude of these effects and interactions among them is important to understanding inter-individual variability in gut microbiota. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed along with several QTLs for metabolic traits. In the current study, we searched for genetic variants underlying differences in the gut microbiota in response to American and ketogenic diets, which are high in fat and vary in carbohydrate composition, between C57BL/6 J (B6) and FVB/NJ (FVB) mouse strains. RESULTS: Genetic mapping of microbial features revealed 18 loci under the QTL model (i.e., marginal effects that are not specific to diet or sex), 12 loci under the QTL by diet model, and 1 locus under the QTL by sex model. Multiple metabolic and microbial features map to the distal part of Chr 1 and Chr 16 along with eigenvectors extracted from principal coordinate analysis of measures of ß-diversity. Bilophila, Ruminiclostridium 9, and Rikenella (Chr 1) were identified as sex- and diet-independent QTL candidate keystone organisms, and Parabacteroides (Chr 16) was identified as a diet-specific, candidate keystone organism in confirmatory factor analyses of traits mapping to these regions. For many microbial features, irrespective of which QTL model was used, diet or the interaction between diet and a genotype were the strongest predictors of the abundance of each microbial trait. Sex, while important to the analyses, was not as strong of a predictor for microbial abundances. CONCLUSIONS: These results demonstrate that sex, diet, and genetic background have different magnitudes of effects on inter-individual differences in gut microbiota. Therefore, Precision Nutrition through the integration of genetic variation, microbiota, and sex affecting microbiota variation will be important to predict response to diets varying in carbohydrate composition. Video Abstract.

Whole-Genome Sequencing Data Reveal New Loci Affecting Milk Production in German Black Pied Cattle (DSN).

German Black Pied (DSN) is considered an ancestral population of the Holstein breed. The goal of the current study was to fine-map genomic loci for milk production traits and to provide sequence variants for selection. We studied genome-wide associations for milk-production traits in 2160 DSN cows. Using 11.7 million variants from whole-genome sequencing of 304 representative DSN cattle, we identified 1980 associated variants (-log10(p) ≥ 7.1) in 13 genomic loci on 9 chromosomes. The highest significance was found for the MGST1 region affecting milk fat content (-log10(p) = 11.93, MAF = 0.23, substitution effect of the minor allele (ßMA) = -0.151%). Different from Holstein, DGAT1 was fixed (0.97) for the alanine protein variant for high milk and protein yield. A key gene affecting protein content was CSN1S1 (-log10(p) = 8.47, MAF = 049, ßMA = -0.055%) and the GNG2 region (-log10(p) = 10.48, MAF = 0.34, ßMA = 0.054%). Additionally, we suggest the importance of FGF12 for protein and fat yield, HTR3C for milk yield, TLE4 for milk and protein yield, and TNKS for milk and fat yield. Selection for favored alleles can improve milk yield and composition. With respect to maintaining the dual-purpose type of DSN, unfavored linkage to genes affecting muscularity has to be investigated carefully, before the milk-associated variants can be applied for selection in the small population.

Analysis of strain, sex, and diet-dependent modulation of gut microbiota reveals candidate keystone organisms driving microbial diversity in response to American and ketogenic diets.

Background The gut microbiota is modulated by a combination of diet, host genetics, and sex effects. The magnitude of these effects and interactions among them is important to understanding inter-individual variability in gut microbiota. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed along with several QTL for metabolic traits. In the current study, we searched for genetic variants underlying differences in the gut microbiota in response to American and ketogenic diets, which are high in fat and vary in carbohydrate composition, between C57BL/6J (B6) and FVB/NJ (FVB) mouse strains. Results Genetic mapping of microbial features revealed 18 loci under the QTL model (i.e., marginal effects that are not specific to diet or sex), 12 loci under the QTL by diet model, and 1 locus under the QTL by sex model. Multiple metabolic and microbial features map to the distal part of Chr 1 and Chr 16 along with eigenvectors extracted from principal coordinate analysis of measures of ß-diversity. Bilophila , Ruminiclostridium 9 , and Rikenella (Chr 1) were identified as sex and diet independent QTL candidate keystone organisms and Rikenelleceae RC9 Gut Group (Chr 16) was identified as a diet-specific, candidate keystone organism in confirmatory factor analyses of traits mapping to these regions. For many microbial features, irrespective of which QTL model was used, diet or the interaction between diet and a genotype were the strongest predictors of the abundance of each microbial trait. Sex, while important to the analyses, was not as strong of a predictor for microbial abundances. Conclusions These results demonstrate that sex, diet, and genetic background have different magnitudes of effects on inter-individual differences in gut microbiota. Therefore, Precision Nutrition through the integration of genetic variation, microbiota, and sex affecting microbiota variation will be important to predict response to diets varying in carbohydrate composition.

High-density genotyping reveals candidate genomic regions for chicken body size in breeds of Asian origin.

Body size is one of the main selection indices in chicken breeding. Although often investigated, knowledge of the underlying genetic mechanisms is incomplete. The aim of the current study was to identify genomic regions associated with body size differences between Asian Game and Asian Bantam type chickens. In this study, 94 and 107 chickens from 4 Asian Game and 5 Asian Bantam type breeds, respectively, were genotyped using the chicken 580K single nucleotide polymorphism (SNP) array. A genome-wide association study (GWAS) and principal component analyses (PCA) were performed to identify genomic regions associated with body size related-traits such as wing length, shank length, shank thickness, keel length, and body weight. Hierarchical clustering of genotype data showed a clear genetic difference between the investigated Asian Game and Asian Bantam chicken types. GWAS identified 16 genomic regions associated with wing length (2, FDR ≤ 0.018), shank thickness (6, FDR ≤ 0.008), keel length (5, FDR ≤ 0.023), and body weight (3, FDR ≤ 0.041). PCA showed that the first principal component (PC1) separated the 2 chicken types and significantly correlated with the measured body size related-traits (P ≤ 2.24e-40). SNPs contributing significantly to PC1 were subjected to a more detailed investigation. This analysis identified 11 regions potentially associated with differences in body size related-traits. A region on chromosome 4 (GGA4) (17.3-21.3 Mb) was detected in both analyses GWAS and PCA. This region harbors 60 genes. Among them are myotubularin 1 (MTM1) and secreted frizzled-related protein 2 (SFPR2) which can be considered as potential candidate genes for body size related-traits. Our results clearly show that the investigated Asian Game type chicken breeds are genetically different from the Asian Bantam breeds. A region on GGA4 between 17.3 and 21.3 Mb was identified which contributes to the phenotypic difference, though further validation of candidate genes is necessary.

Review: Genetic and protein variants of milk caseins in goats.

The milk casein genes in goats, are highly polymorphic genes with numerous synonymous and non-synonymous mutations. So far, 20 protein variants have been reported in goats for alpha-S1-casein, eight for beta-casein, 14 for alpha-S2-casein, and 24 for kappa-casein. This review provides a comprehensive overview on identified milk casein protein variants in goat and non-coding DNA sequence variants with some affecting the expression of the casein genes. The high frequency of some casein protein variants in different goat breeds and geographical regions might reflect specific breeding goals with respect to milk processing characteristics, properties for human nutrition and health, or adaptation to the environment. Because protein names, alongside the discovery of protein variants, go through a historical process, we linked old protein names with new ones that reveal more genetic variability. The haplotypes across the cluster of the four genetically linked casein genes are recommended as a valuable genetic tool for discrimination between breeds, managing genetic diversity within and between goat populations, and breeding strategies. The enormous variation in the casein proteins and genes is crucial for producing milk and dairy products with different properties for human health and nutrition, and for genetic improvement depending on local breeding goals.

Association between Fatty Acid Composition in Hair and Energy Availability during Early Lactation in Simmental and German Holstein Cows.

This study examined (1) if fatty acids in bovine hair are influenced by dietary energy levels and (2) if the relationship between energy availability and fatty acids in hair persists across breeds and farms. Sixty-two and 59 Fleckvieh (Simmental), and 55 German Holstein cows from three farms, respectively, were fed two levels of energy concentration of roughage (6.1 and 6.5 MJ net energy for lactation/kg dry matter) and two levels of concentrate supply (150 and 250 g/kg energy-corrected milk). The average body weight was 727 kg (Simmental) and 668 kg (Holstein). The average lactation number was 3.1. Hair samples were taken in lactation weeks 4 and 8. In Simmental cows, a lower energy deficit due to a relatively higher energy intake from high energy concentration of the roughage was associated with higher C18:2n-6 and C18:3n-3 contents in hair at week 8. In cows from all three farms, higher energy intake between lactation weeks 2 and 6 correlated with higher content of C18:2n-6 in hair samples taken in lactation weeks 4 and 8. No correlation was found for C12:0. These results provide the first evidence that increased energy intake increases the contents of C18:2n-6 in hair.

A 5' UTR Mutation Contributes to Down-Regulation of Bbs7 in the Berlin Fat Mouse.

The Bardet-Biedl Syndrome 7 (Bbs7) gene was identified as the most likely candidate gene causing juvenile obesity in the Berlin Fat Mouse Inbred (BFMI) line. Bbs7 expression is significantly lower in the brain, adipose tissue, and liver of BFMI mice compared to lean C57BL/6NCrl (B6N) mice. A DNA sequence comparison between BFMI and B6N revealed 16 sequence variants in the Bbs7 promoter region. Here, we tested if these mutations contribute to the observed differential expression of Bbs7. In a cell-based dual-luciferase assay, we compared the effects of the BFMI and the B6N haplotypes of different regions of the Bbs7 promotor on the reporter gene expression. A single-nucleotide polymorphism (SNP) was identified causing a significant reduction in the reporter gene expression. This SNP (rs29947545) is located in the 5' UTR of Bbs7 at Chr3:36.613.350. The SNP is not unique to BFMI mice but also occurs in several other mouse strains, where the BFMI allele is not associated with lower Bbs7 transcript amounts. Thus, we suggest a compensatory mutation in the other mouse strains that keeps Bbs7 expression at the normal level. This compensatory mechanism is missing in BFMI mice and the cell lines tested.

QTL-mapping in the obese Berlin Fat Mouse identifies additional candidate genes for obesity and fatty liver disease.

The Berlin Fat Mouse Inbred line (BFMI) is a model for obesity and the metabolic syndrome. This study aimed to identify genetic variants associated with liver weight, liver triglycerides, and body weight using the obese BFMI sub-line BFMI861-S1. BFMI861-S1 mice are insulin resistant and store ectopic fat in the liver. In generation 10, 58 males and 65 females of the advanced intercross line (AIL) BFMI861-S1xB6N were phenotyped under a standard diet over 20 weeks. QTL analysis was performed after genotyping with the MiniMUGA Genotyping Array. Whole-genome sequencing and gene expression data of the parental lines was used for the prioritization of positional candidate genes. Three QTLs associated with liver weight, body weight, and subcutaneous adipose tissue (scAT) weight were identified. A highly significant QTL on chromosome (Chr) 1 (157-168 Mb) showed an association with liver weight. A QTL for body weight at 20 weeks was found on Chr 3 (34.1-40 Mb) overlapping with a QTL for scAT weight. In a multiple QTL mapping approach, an additional QTL affecting body weight at 16 weeks was identified on Chr 6 (9.5-26.1 Mb). Considering sequence variants and expression differences, Sec16b and Astn1 were prioritized as top positional candidate genes for the liver weight QTL on Chr 1; Met and Ica1 for the body weight QTL on Chr 6. Interestingly, all top candidate genes have previously been linked with metabolic traits. This study shows once more the power of an advanced intercross line for fine mapping. QTL mapping combined with a detailed prioritization approach allowed us to identify additional and plausible candidate genes linked to metabolic traits in the BFMI861-S1xB6N AIL. By reidentifying known candidate genes in a different crossing population the causal link with specific traits is underlined and additional evidence is given for further investigations.

Effects of DGAT1 on milk performance in Sudanese Butana × Holstein crossbred cattle.

The improvement of milk production of indigenous Sudanese cattle such as Bos indicus Butana and its cross with Holstein is a major goal of the Sudanese government to ensure sufficient healthy nutrition in the country. In this study, we investigated the K232A polymorphism of diacylglycerol acyltransferase (DGAT1), a well-known modulator of milk production in other breeds. We determined allele frequencies and the allele effects on milk production. Therefore, 93 purebred Butana and 203 Butana × Holstein crossbred cattle were genotyped using competitive allele-specific PCR assays. Association analysis was performed using a linear mixed model in R. In purebred Butana cattle, the lysine DGAT1 protein variant K232, which is found to be associated with higher fat and protein contents, as well as higher fat yield was highly frequent at 0.929, while its frequency in Butana × Holstein crossbred cattle was 0.394. Significant effects were found on milk yield (P = 7.6 × 10-20), fat yield (P = 2.2 × 10-17), protein yield (P = 2.0 × 10-19) and lactose yield (P = 4.0 × 10-18) in crossbred cattle. As expected, the protein variant K232 was disadvantageous since it was decreasing milk, protein, and lactose yields by 1.741 kg, 0.063 kg and 0.084 kg, respectively. No significant effects were found for milk fat, protein, and lactose contents. The high frequency of the lysine DGAT1 protein variant K232 in Butana cattle could contribute to their high milk fat content in combination with low milk yield. In Butana × Holstein crossbred cattle, the DGAT1 marker can be used for effective selection and thus genetic improvement of milk production.

Validation of somatic cell score-associated SNPs from Holstein cattle in Sudanese Butana and Butana × Holstein crossbred cattle.

The Bos indicus zebu cattle Butana is the most commonly used indigenous dairy cattle breed in Sudan. In the last years, high-yielding Holstein dairy cattle were introgressed into Butana cattle to improve their milk yield and simultaneously keep their good adaption to extreme environmental conditions. With the focus on the improvement of milk production, other problems arose such as an increased susceptibility to mastitis. Thus, genetic selection for mastitis resistance should be considered to maintain healthy and productive cows. In this study, we tested 10 single nucleotide polymorphisms (SNPs) which had been associated with somatic cell score (SCS) in Holstein cattle for association with SCS in 37 purebred Butana and 203 Butana × Holstein crossbred cattle from Sudan. Animals were genotyped by competitive allele-specific PCR assays and association analysis was performed using a linear mixed model. All 10 SNPs were segregating in the crossbred Butana × Holstein populations, but only 8 SNPs in Sudanese purebred Butana cattle. The SNP on chromosome 13 was suggestively associated with SCS in the Butana × Holstein crossbred population (rs109441194, 13:79,365,467, PBF = 0.054) and the SNP on chromosome 19 was significantly associated with SCS in both populations (rs41257403, 19:50,027,458, Butana: PBF = 0.003, Butana × Holstein: PBF = 6.2 × 10-16). The minor allele of both SNPs showed an increase in SCS. Therefore, selection against the disadvantageous minor allele could be used for genetic improvement of mastitis resistance in the studied populations. However, investigations in a bigger population and across the whole genome are needed to identify additional genomic loci.

miRNA profiling in intrauterine exosomes of pregnant cattle on day 7.

Intrauterine exosomes have been identified to be involved in the embryo development and implantation. The aim of this study was to explore the role of miRNAs in intrauterine exosomes in bovine pregnancy. Intrauterine exosomes were collected from uterine flushing fluids of three donor and three recipient Xianan cows 7 days after fertilization. Intrauterine exosomes miRNAs were extracted and the exosomal miRNAs expression levels were analyzed. Sixty miRNAs differed significantly in their amounts between donors and recipients (p-value < 0.05, |log2(FoldChange)| > 1). Twenty-two miRNAs were upregulated and 38 downregulated in the group of donor cows. The bta-miR-184 was the most significant (P Benjamini-Hochberg < 0.001). A total of 9,775 target genes were predicted using the 60 miRNAs. GO and KEGG analysis showed that the target genes were enriched in several biological processes or pathways associated with embryo implantation and endometrial development, such as cell adhesion, cell junction, focal adhesion, and Rap1 signaling pathway. Our findings suggest that, in cattle early pregnancy stage, these differently expressed miRNAs in intrauterine exosomes involved in embryo implantation and endometrial development, which may exert a significant effect and influence the uterine microenvironment for embryo implantation. These results could provide reference for screening and exploring the intrauterine exosomal miRNA affecting embryo implantation.

Identification of four novel QTL linked to the metabolic syndrome in the Berlin Fat Mouse.

BACKGROUND: The Berlin Fat Mouse Inbred line (BFMI) is a model for obesity and the metabolic syndrome. This study aimed to identify genetic variants associated with impaired glucose metabolism using the obese lines BFMI861-S1 and BFMI861-S2, which are genetically closely related, but differ in several traits. BFMI861-S1 is insulin resistant and stores ectopic fat in the liver, whereas BFMI861-S2 is insulin sensitive. METHODS: In generation 10, 397 males of an advanced intercross line (AIL) BFMI861-S1 × BFMI861-S2 were challenged with a high-fat, high-carbohydrate diet and phenotyped over 25 weeks. QTL-analysis was performed after selective genotyping of 200 mice using the GigaMUGA Genotyping Array. Additional 197 males were genotyped for 7 top SNPs in QTL regions. For the prioritization of positional candidate genes whole genome sequencing and gene expression data of the parental lines were used. RESULTS: Overlapping QTL for gonadal adipose tissue weight and blood glucose concentration were detected on chromosome (Chr) 3 (95.8-100.1 Mb), and for gonadal adipose tissue weight, liver weight, and blood glucose concentration on Chr 17 (9.5-26.1 Mb). Causal modeling suggested for Chr 3-QTL direct effects on adipose tissue weight, but indirect effects on blood glucose concentration. Direct effects on adipose tissue weight, liver weight, and blood glucose concentration were suggested for Chr 17-QTL. Prioritized positional candidate genes for the identified QTL were Notch2 and Fmo5 (Chr 3) and Plg and Acat2 (Chr 17). Two additional QTL were detected for gonadal adipose tissue weight on Chr 15 (67.9-74.6 Mb) and for body weight on Chr 16 (3.9-21.4 Mb). CONCLUSIONS: QTL mapping together with a detailed prioritization approach allowed us to identify candidate genes associated with traits of the metabolic syndrome. In addition, we provided evidence for direct and indirect genetic effects on blood glucose concentration in the insulin-resistant mouse line BFMI861-S1.

A deletion containing a CTCF-element in intron 8 of the Bbs7 gene is partially responsible for juvenile obesity in the Berlin Fat Mouse.

The Berlin Fat Mouse Inbred (BFMI) line is a model for juvenile obesity. Previous studies on crosses between BFMI and C57Bl/6N (B6N) have identified a recessive defect causing juvenile obesity on chromosome 3 (jObes1). Bbs7 was identified as the most likely candidate gene for the observed effect. Comparative sequence analysis showed a 1578 bp deletion in intron 8 of Bbs7 in BFMI mice. A CTCF-element is located inside this deletion. To investigate the functional effect of this deletion, it was introduced into B6N mice using CRISPR/Cas9. Two mice containing the target deletion were obtained (B6N Bbs7emI8∆1 and Bbs7emI8∆2) and were subsequently mated to BFMI and B6N to generate two families suitable for complementation. Inherited alleles were determined and body composition was measured by quantitative magnetic resonance. Evidence for a partial complementation (13.1-15.1%) of the jObes1 allele by the CRISPR/Cas9 modified B6N Bbs7emI8∆1 and Bbs7emI8∆2 alleles was found. Mice carrying the complementation alleles had a 23-27% higher fat-to-lean ratio compared to animals which have a B6N allele (P(Bbs7emI8∆1) = 4.25 × 10-7; P(Bbs7emI8∆2) = 3.17 × 10-5). Consistent with previous findings, the recessive effect of the BFMI allele was also seen for the B6N Bbs7emI8∆1 and Bbs7emI8∆2 alleles. However, the effect size of the B6N Bbs7emI8∆1 and Bbs7emI8∆2 alleles was smaller than the BFMI allele, and thus showed only a partial complementation. Findings suggest additional variants near Bbs7 in addition to or interacting with the deletion in intron 8.

Transmission distortion and genetic incompatibilities between alleles in a multigenerational mouse advanced intercross line.

While direct additive and dominance effects on complex traits have been mapped repeatedly, additional genetic factors contributing to the heterogeneity of complex traits have been scarcely investigated. To assess genetic background effects, we investigated transmission ratio distortions (TRDs) of alleles from parent to offspring using an advanced intercross line (AIL) of an initial cross between the mouse inbred strains C57BL/6NCrl (B6N) and BFMI860-12 [Berlin Fat Mouse Inbred (BFMI)]. A total of 341 males of generation 28 and their respective 61 parents and 66 grandparents were genotyped using Mega Mouse Universal Genotyping Arrays. TRDs were investigated using allele transmission asymmetry tests, and pathway overrepresentation analysis was performed. Sequencing data were used to test for overrepresentation of nonsynonymous SNPs (nsSNPs) in TRD regions. Genetic incompatibilities were tested using the Bateson-Dobzhansky-Muller two-locus model. A total of 62 TRD regions were detected, many in close proximity to the telocentric centromere. TRD regions contained 44.5% more nsSNPs than randomly selected regions (182 vs 125.9 ± 17.0, P < 1 × 10-4). Testing for genetic incompatibilities between TRD regions identified 29 genome-wide significant incompatibilities between TRD regions [P(BF) < 0.05]. Pathway overrepresentation analysis of genes in TRD regions showed that DNA methylation, epigenetic regulation of RNA, and meiotic/meiosis regulation pathways were affected independent of the parental origin of the TRD. Paternal BFMI TRD regions showed overrepresentation in the small interfering RNA biogenesis and in the metabolism of lipids and lipoproteins. Maternal B6N TRD regions harbored genes involved in meiotic recombination, cell death, and apoptosis pathways. The analysis of genes in TRD regions suggests the potential distortion of protein-protein interactions influencing obesity and diabetic retinopathy as a result of disadvantageous combinations of allelic variants in Aass, Pgx6, and Nme8. Using an AIL significantly improves the resolution at which we can investigate TRD. Our analysis implicates distortion of protein-protein interactions as well as meiotic drive as the underlying mechanisms leading to the observed TRD in our AIL. Furthermore, genes with large amounts of nsSNPs located in TRD regions are more likely to be involved in pathways that are related to the phenotypic differences between the parental strains. Genes in these TRD regions provide new targets for investigating genetic adaptation, protein-protein interactions, and determinants of complex traits such as obesity.

Genomic diversity and relationship analyses of endangered German Black Pied cattle (DSN) to 68 other taurine breeds based on whole-genome sequencing.

German Black Pied cattle (Deutsches Schwarzbuntes Niederungsrind, DSN) are an endangered dual-purpose cattle breed originating from the North Sea region. The population comprises about 2,500 cattle and is considered one of the ancestral populations of the modern Holstein breed. The current study aimed at defining the breeds closest related to DSN cattle, characterizing their genomic diversity and inbreeding. In addition, the detection of selection signatures between DSN and Holstein was a goal. Relationship analyses using fixation index (FST), phylogenetic, and admixture analyses were performed between DSN and 68 other breeds from the 1000 Bull Genomes Project. Nucleotide diversity, observed heterozygosity, and expected heterozygosity were calculated as metrics for genomic diversity. Inbreeding was measured as excess of homozygosity (FHom) and genomic inbreeding (FRoH) through runs of homozygosity (RoHs). Region-wide FST and cross-population-extended haplotype homozygosity (XP-EHH) between DSN and Holstein were used to detect selection signatures between the two breeds, and RoH islands were used to detect selection signatures within DSN and Holstein. DSN showed a close genetic relationship with breeds from the Netherlands, Belgium, Northern Germany, and Scandinavia, such as Dutch Friesian Red, Dutch Improved Red, Belgian Red White Campine, Red White Dual Purpose, Modern Angler, Modern Danish Red, and Holstein. The nucleotide diversity in DSN (0.151%) was higher than in Holstein (0.147%) and other breeds, e.g., Norwegian Red (0.149%), Red White Dual Purpose (0.149%), Swedish Red (0.149%), Hereford (0.145%), Angus (0.143%), and Jersey (0.136%). The FHom and FRoH values in DSN were among the lowest. Regions with high FST between DSN and Holstein, significant XP-EHH regions, and RoH islands detected in both breeds harbor candidate genes that were previously reported for milk, meat, fertility, production, and health traits, including one QTL detected in DSN for endoparasite infection resistance. The selection signatures between DSN and Holstein provide evidence of regions responsible for the dual-purpose properties of DSN and the milk type of Holstein. Despite the small population size, DSN has a high level of diversity and low inbreeding. FST supports its relatedness to breeds from the same geographic origin and provides information on potential gene pools that could be used to maintain diversity in DSN.

Design and performance of a bovine 200 k SNP chip developed for endangered German Black Pied cattle (DSN).

BACKGROUND: German Black Pied cattle (DSN) are an endangered dual-purpose breed which was largely replaced by Holstein cattle due to their lower milk yield. DSN cattle are kept as a genetic reserve with a current herd size of around 2500 animals. The ability to track sequence variants specific to DSN could help to support the conservation of DSN's genetic diversity and to provide avenues for genetic improvement. RESULTS: Whole-genome sequencing data of 304 DSN cattle were used to design a customized DSN200k SNP chip harboring 182,154 variants (173,569 SNPs and 8585 indels) based on ten selection categories. We included variants of interest to DSN such as DSN unique variants and variants from previous association studies in DSN, but also variants of general interest such as variants with predicted consequences of high, moderate, or low impact on the transcripts and SNPs from the Illumina BovineSNP50 BeadChip. Further, the selection of variants based on haplotype blocks ensured that the whole-genome was uniformly covered with an average variant distance of 14.4 kb on autosomes. Using 300 DSN and 162 animals from other cattle breeds including Holstein, endangered local cattle populations, and also a Bos indicus breed, performance of the SNP chip was evaluated. Altogether, 171,978 (94.31%) of the variants were successfully called in at least one of the analyzed breeds. In DSN, the number of successfully called variants was 166,563 (91.44%) while 156,684 (86.02%) were segregating at a minor allele frequency > 1%. The concordance rate between technical replicates was 99.83 ± 0.19%. CONCLUSION: The DSN200k SNP chip was proved useful for DSN and other Bos taurus as well as one Bos indicus breed. It is suitable for genetic diversity management and marker-assisted selection of DSN animals. Moreover, variants that were segregating in other breeds can be used for the design of breed-specific customized SNP chips. This will be of great value in the application of conservation programs for endangered local populations in the future.

Genomic Loci Affecting Milk Production in German Black Pied Cattle (DSN).

German Black Pied cattle (DSN) is an endangered population of about 2,550 dual-purpose cattle in Germany. Having a milk yield of about 2,500 kg less than the predominant dairy breed Holstein, the preservation of DSN is supported by the German government and the EU. The identification of the genomic loci affecting milk production in DSN can provide a basis for selection decisions for genetic improvement of DSN in order to increase market chances through the improvement of milk yield. A genome-wide association analysis of 30 milk traits was conducted in different lactation periods and numbers. Association using multiple linear regression models in R was performed on 1,490 DSN cattle genotyped with BovineSNP50 SNP-chip. 41 significant and 20 suggestive SNPs affecting milk production traits in DSN were identified, as well as 15 additional SNPs for protein content which are less reliable due to high inflation. The most significant effects on milk yield in DSN were detected on chromosomes 1, 6, and 20. The region on chromosome 6 was located nearby the casein gene cluster and the corresponding haplotype overlapped the CSN3 gene (casein kappa). Associations for fat and protein yield and content were also detected. High correlation between traits of the same lactation period or number led to some SNPs being significant for multiple investigated traits. Half of all identified SNPs have been reported in other studies, previously. 15 SNPs were associated with the same traits in other breeds. The other associated SNPs have been reported previously for traits such as exterior, health, meat and carcass, production, and reproduction traits. No association could be detected between DGAT1 and other known milk genes with milk production traits despite the close relationship between DSN and Holstein. The results of this study confirmed that many SNPs identified in other breeds as associated with milk traits also affect milk traits in dual-purpose DSN cattle and can be used for further genetic analysis to identify genes and causal variants that affect milk production in DSN cattle.

Sex-specific genetic architecture in response to American and ketogenic diets.

BACKGROUND/OBJECTIVES: There is a growing appreciation for individual responses to diet. In a previous study, mouse strain-specific responses to American and ketogenic diets were observed. In this study, we searched for genetic variants underlying differences in the responses to American and ketogenic diets between C57BL/6J (B6) and FVB/NJ (FVB) mouse strains. RESULTS: Genetic mapping of fat and lean mass gain revealed QTLs on Chromosome (Chr) 1 at 191.6 Mb (Fmgq1) (P < 0.001, CI = 180.2-194.4 Mb), Chr5 at 73.7 Mb (Fmgq2, Lmgq1) (P < 0.001, CI = 66.1-76.6 Mb), and Chr7 at 40.5 Mb (Fmgq3) (P < 0.01, CI = 36.6-44.5 Mb). Analysis of serum HDL cholesterol concentration identified a significant (P < 0.001, CI = 160.6-176.1 Mb) QTL on Chr1 at 168.6 Mb (Hdlq1). Causal network inference suggests that HDL cholesterol and fat mass gain are both linked to Fmgq1. CONCLUSIONS: Strong sex effects were identified at both Fmgq2 and Lmgq1, which are also diet-dependent. Interestingly, Fmgq2 and Fmgq3 affect fat gain directly, while Fmgq1 influences fat gain directly and via an intermediate change in serum cholesterol. These results demonstrate how precision nutrition will be advanced through the integration of genetic variation and sex in physiological responses to diets varied in carbohydrate composition.

Capture Sequencing to Explore and Map Rare Casein Variants in Goats.

Genetic variations in the four casein genes CSN1S1, CSN2, CSN1S2, and CSN3 have obtained substantial attention since they affect the milk protein yield, milk composition, cheese processing properties, and digestibility as well as tolerance in human nutrition. Furthermore, milk protein variants are used for breed characterization, biodiversity, and phylogenetic studies. The current study aimed at the identification of casein protein variants in five domestic goat breeds from Sudan (Nubian, Desert, Nilotic, Taggar, and Saanen) and three wild goat species [Capra aegagrus aegagrus (Bezoar ibex), Capra nubiana (Nubian ibex), and Capra ibex (Alpine ibex)]. High-density capture sequencing of 33 goats identified in total 22 non-synonymous and 13 synonymous single nucleotide polymorphisms (SNPs), of which nine non-synonymous and seven synonymous SNPs are new. In the CSN1S1 gene, the new non-synonymous SNP ss7213522403 segregated in Alpine ibex. In the CSN2 gene, the new non-synonymous SNPs ss7213522526, ss7213522558, and ss7213522487 were found exclusively in Nubian and Alpine ibex. In the CSN1S2 gene, the new non-synonymous SNPs ss7213522477, ss7213522549, and ss7213522575 were found in Nubian ibex only. In the CSN3 gene, the non-synonymous SNPs ss7213522604 and ss7213522610 were found in Alpine ibex. The identified DNA sequence variants led to the detection of nine new casein protein variants. New variants were detected for alpha S1 casein in Saanen goats (CSN1S1 ∗C1), Bezoar ibex (CSN1S1 ∗J), and Alpine ibex (CSN1S1 ∗K), for beta and kappa caseins in Alpine ibex (CSN2 ∗F and CSN3 ∗X), and for alpha S2 casein in all domesticated and wild goats (CSN1S2 ∗H), in Nubian and Desert goats (CSN1S2 ∗I), or in Nubian ibex only (CSN1S2 ∗J and CSN1S2 ∗K). The results show that most novel SNPs and protein variants occur in the critically endangered Nubian ibex. This highlights the importance of the preservation of this endangered breed. Furthermore, we suggest validating and further characterizing the new casein protein variants.