Mastitis is an inflammatory disease of the mammary gland, which has a significant economic impact and is an animal welfare concern. This work examined the association between single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) with the incidence of clinical mastitis (CM). Using information from 16 half-sib pairs of Holstein-Friesian cows (32 animals in total) we searched for genomic regions that differed between a healthy (no incidence of CM) and a mastitis-prone (multiple incidences of CM) half-sib. Three cows with average sequence depth of coverage below 10 were excluded, which left 13 half-sib pairs available for comparisons. In total, 191 CNV regions were identified, which were deleted in a mastitis-prone cow, but present in its healthy half-sib and overlapped in at least nine half-sib pairs. These regions overlapped with exons of 46 genes, among which APP (BTA1), FOXL2 (BTA1), SSFA2 (BTA2), OTUD3 (BTA2), ADORA2A (BTA17), TXNRD2 (BTA17) and NDUFS6 (BTA20) have been reported to influence CM. Moreover, two duplicated CNV regions present in nine healthy individuals and absent in their mastitis-affected half-sibs overlapped with exons of a cholinergic receptor nicotinic α 10 subunit on BTA15 and a novel gene (ENSBTAG00000008519) on BTA27. One CNV region deleted in nine mastitis-affected sibs overlapped with two neighbouring long non-coding RNA sequences located on BTA12. Single nucleotide polymorphisms with differential genotypes between a healthy and a mastitis-affected sib included 17 polymorphisms with alternate alleles in eight affected and healthy half-sib families. Three of these SNPs were located introns of genes: MET (BTA04), RNF122 (BTA27) and WRN (BTA27). In summary, structural polymorphisms in form of CNVs, putatively play a role in susceptibility to CM. Specifically, sequence deletions have a greater effect on reducing resistance against mastitis, than sequence duplications have on increasing resistance against the disease.

The concept that interactions between nutrition and genetics determine phenotype was established by Garrod at the beginning of the 20th century through his ground-breaking work on inborn errors of metabolism. A century later, the science and technologies involved in sequencing of the human genome stimulated development of the scientific discipline which we now recognise as nutritional genomics (nutrigenomics). Much of the early hype around possible applications of this new science was unhelpful and raised expectations, which have not been realised as quickly as some would have hoped. However, major advances have been made in quantifying the contribution of genetic variation to a wide range of phenotypes and it is now clear that for nutrition-related phenotypes, such as obesity and common complex diseases, the genetic contribution made by SNP alone is often modest. There is much scope for innovative research to understand the roles of less well explored types of genomic structural variation, e.g. copy number variants, and of interactions between genotype and dietary factors, in phenotype determination. New tools and models, including stem cell-based approaches and genome editing, have huge potential to transform mechanistic nutrition research. Finally, the application of nutrigenomics research offers substantial potential to improve public health e.g. through the use of metabolomics approaches to identify novel biomarkers of food intake, which will lead to more objective and robust measures of dietary exposure. In addition, nutrigenomics may have applications in the development of personalised nutrition interventions, which may facilitate larger, more appropriate and sustained changes in eating (and other lifestyle) behaviours and help to reduce health inequalities.

Genomic and genetic variation among six Italian chicken native breeds (Livornese, Mericanel della Brianza, Milanino, Bionda Piemontese, Bianca di Saluzzo and Siciliana) were studied using single nucleotide polymorphism (SNP) and copy number variants (CNV) as markers. A total of 94 DNA samples genotyped with Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix) were used in the analyses. The results showed the genetic and genomic variability occurring among the six Italian chicken breeds. The genetic relationship among animals was established with a principal component analysis. The genetic diversity within breeds was calculated using heterozygosity values (expected and observed) and with Wright’s F-statistics. The individual-based CNV calling, based on log R ratio and B-allele frequency values, was done by the Hidden–Markov Model (HMM) of PennCNV software on autosomes. A hierarchical agglomerative clustering was applied in each population according to the absence or presence of definite CNV regions (CNV were grouped by overlapping of at least 1 bp). The CNV map was built on a total of 1003 CNV found in individual samples, after grouping by overlaps, resulting in 564 unique CNV regions (344 gains, 213 losses and 7 complex), for a total of 9.43 Mb of sequence and 1.03% of the chicken assembly autosome. All the approaches using SNP data showed that the Siciliana breed clearly differentiate from other populations, the Livornese breed separates into two distinct groups according to the feather colour (i.e. white and black) and the Bionda Piemontese and Bianca di Saluzzo breeds are closely related. The genetic variability found using SNP is comparable with that found by other authors in the same breeds using microsatellite markers. The CNV markers analysis clearly confirmed the SNP results.

Monozygotic (MZ) twins stem from the same single fertilized egg and therefore share all their inherited genetic variation. This is one of the unequivocal facts on which genetic epidemiology and twin studies are based. To what extent this also implies that MZ twins share genotypes in adult tissues is not precisely established, but a common pragmatic assumption is that MZ twins are 100% genetically identical also in adult tissues. During the past decade, this view has been challenged by several reports, with observations of differences in post-zygotic copy number variations (CNVs) between members of the same MZ pair. In this study, we performed a systematic search for differences of CNVs within 38 adult MZ pairs who had been misclassified as dizygotic (DZ) twins by questionnaire-based assessment. Initial scoring by PennCNV suggested a total of 967 CNV discordances. The within-pair correlation in number of CNVs detected was strongly dependent on confidence score filtering and reached a plateau of r = 0.8 when restricting to CNVs detected with confidence score larger than 50. The top-ranked discordances were subsequently selected for validation by quantitative polymerase chain reaction (qPCR), from which one single ~120kb deletion in NRXN1 on chromosome 2 (bp 51017111–51136802) was validated. Despite involving an exon, no sign of cognitive/mental consequences was apparent in the affected twin pair, potentially reflecting limited or lack of expression of the transcripts containing this exon in nerve/brain.

Objectives: One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia. Methods: Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging. Results: The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity—connections among high degree “rich club” nodes, “feeder” connections to these rich club nodes, and “local” connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length. Conclusions: Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA. (JINS, 2016, 22, 240–249)

Monozygotic (MZ) twins are genetically identical at conception, making them informative subjects for studies on somatic mutations. Copy number variants (CNVs) are responsible for a substantial part of genetic variation, have relatively high mutation rates, and are likely to be involved in phenotypic variation. We conducted a genome-wide survey for post-twinning de novo CNVs in 1,097 MZ twin pairs. Comparisons between MZ twins were made by CNVs measured in DNA from blood or buccal epithelium with the Affymetrix 6.0 microarray and two calling algorithms. In addition, CNV concordance rates were compared between the different sources of DNA, and gene-enrichment association analyses were conducted for thought problems (TP) and attention problems (AP) using CNVs concordant within MZ pairs. We found a total of 153 putative post-twinning de novo CNVs >100 kb, of which the majority resided in 15q11.2. Based on the discordance of raw intensity signals a selection was made of 20 de novo CNVs for a qPCR validation experiments. Two out of 20 post-twinning de novo CNVs were validated with qPCR in the same twin pair. The 13-year-old MZ twin pair that showed two discordances in CN in 15q11.2 in their buccal DNA did not show large phenotypic differences. From the remaining 18 putative de novo CNVs, 17 were deletions or duplications that were concordant within MZ twin pairs. Concordance rates within twin pairs of CNV calls with CN ≠ 2 were ~80%. Buccal epithelium-derived DNA showed a slightly but significantly higher concordance rate, and blood-derived DNA showed significantly more concordant CNVs per twin pair. The gene-enrichment analyses on concordant CNVs showed no significant associations between CNVs overlapping with genes involved in neuronal processes and TP or AP after accounting for the source of DNA.

With the desire to assess genetic variation across the lifespan in large-scale collaborative projects, one question is whether inference of copy number (CN) is sensitive to the source of material for deoxyribonucleic acid (DNA) analysis (e.g., blood and buccal) and another question is whether CN is stable as individuals age. Here, we address these questions by applying Affymetrix 6.0 single nucleotide polymorphism (SNP) micro-arrays to 1,472 DNA samples from 710 individuals from the Netherlands Twin Register, including twin and non-twin individuals (372 with buccal and blood derived DNA and 388 with longitudinal data). Similar concordance for CN and genotype inference between samples from the same individual [or from the monozygotic (MZ) co-twins] was found for blood and buccal tissues. There was a small but statistically significant decrease in across-tissue concordance compared with concordance of samples from the same tissue type. No temporal effect was seen on CN variation from the 388 individuals sampled at two time points ranging from 1 to 12 years apart. The majority of our individuals were sampled at age younger than 20 years. Genotype concordance was very high (R2 > 99%) between co-twins from 43 MZ pairs. For 75 dizygotic (DZ) pairs, R2 was ≈65%. CN estimates were highly consistent between co-twins from MZ pairs for both deletions (R2 ≈ 90%) and duplications (R2 ≈ 86%). For DZ, these were similar for within-individual comparisons, but naturally lower between co-twins (R2 ≈ 50–60%). These results suggest that DNA from buccal samples perform as well as DNA from blood samples on the current generation of micro-array technologies.