Whole-genome sequencing (WGS) permits comprehensive cancer genome analyses, revealing mutational signatures, imprints of DNA damage, and repair processes that have arisen in each patient’s cancer. We performed mutational signature analyses on 12,222 whole-genome–sequenced tumor-normal matched pairs from patients recruited via the UK National Health Service (NHS). We contrasted our results with two independent cancer WGS datasets—from the International Cancer Genome Consortium (ICGC) and the Hartwig Medical Foundation (HMF)—involving 18,640 whole-genome–sequenced cancers in total. Our analyses add 40 single and 18 double substitution signatures to the current mutational signature tally. We show for each organ that cancers have a limited number of common signatures and a long tail of rare signatures, and we provide a practical solution for applying this concept of common versus rare signatures to future analyses.

BackgroundCopy number variations are genome polymorphism that influence phenotypic variation and are an important source of genetic variation in populations. The aim of this study was to investigate genetic variability in the Mexican Creole chicken population using CNVs.ResultsThe Hidden Markov Model of the PennCNV software detected a total of 1924 CNVs in the genome of the 256 samples processed with Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix). The mapped CNVs comprised 1538 gains and 386 losses, resulting at population level in 1216 CNV regions (CNVRs), of which 959 gains, 226 losses and 31 complex (i.e. containing both losses and gains). The CNVRs covered a total of 47 Mb of the whole genome sequence length, corresponding to 5.12% of the chicken galGal4 autosome assembly.ConclusionsThis study allowed a deep insight into the structural variation in the genome of unselected Mexican chicken population, which up to now has not been genetically characterized. The genomic study disclosed that the population, even if presenting extreme morphological variation, cannot be organized in differentiated genetic subpopulations. Finally this study provides a chicken CNV map based on the 600 K SNP chip array jointly with a genome-wide gene copy number estimates in a native unselected for more than 500 years chicken population.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-017-0524-4) contains supplementary material, which is available to authorized users.

21Genomic and genetic variation among six Italian chicken native breeds (Livornese, 22 Mericanel della Brianza, Milanino, Bionda Piemontese, Bianca di Saluzzo and 23 Siciliana) were studied using single nucleotide polymorphism (SNP) and copy

Mastitis, the most common and expensive disease in dairy cows, implies significant losses in the dairy industry worldwide. Many efforts have been made to improve genetic mastitis resistance in dairy populations, but low heritability of this trait made this process not as effective as desired. The purpose of this study was to identify genomic regions explaining genetic variation of somatic cell count using copy number variations (CNVs) as markers in the Holstein population, genotyped with the Illumina BovineHD BeadChip. We found 24 and 47 copy number variation regions significantly associated with estimated breeding values for somatic cell score (SCS_EBVs) using SVS 8.3.1 and PennCNV-CNVRuler software, respectively. The association analysis performed with these two software allowed the identification of 18 candidate genes (TERT, NOTCH1, SLC6A3, CLPTM1L, PPARα, BCL-2, ABO, VAV2, CACNA1S, TRAF2, RELA, ELF3, DBH, CDK5, NF2, FASN, EWSR1 and MAP3K11) that result classified in the same functional cluster. These genes are also part of two gene networks, whose genes share the 'stress', 'cell death', 'inflammation' and 'immune response' GO terms. Combining CNV detection/association analysis based on two different algorithms helps towards a more complete identification of genes linked to phenotypic variation of the somatic cell count.

Multi-locus Inherited Neoplasia Allele Syndrome (MINAS) refers to individuals with germline pathogenic variants in two or more cancer susceptibility genes(CSGs). With increased use of exome/genome sequencing it would be predicted that detection of MINAS would become more frequent. Here we review recent progress in knowledge of MINAS. A systematic literature search for reports of individuals with germline pathogenic variants in 2 or more of 94 CSGs was performed. In addition, participants with multiple primary tumours who underwent genome sequencing as part of the Rare Disease arm of the UK 100,000 Genomes Project were interrogated to detect additional cases. We identified 385 MINAS cases (211 reported in the last 5 years, 6 from 100,000 genomes participants). Most (287/385) cases contained at least one pathogenic variant in either BRCA1 or BRCA2. 108/385 MINAS cases had multiple primary tumours at presentation and a subset of cases presented unusual multiple tumour phenotypes. We conclude that, as predicted, increasing numbers of individuals with MINAS are being have been reported but, except for individuals with BRCA1/BRCA2 MINAS, individual CSG combinations are generally rare. In many cases it appears that the clinical phenotype is that which would be expected from the effects of the constituent CSG variants acting independently. However, in some instances the presence of unusual tumour phenotypes and/or multiple primary tumours suggests that there may be complex interactions between the relevant MINAS CSGs. Systematic reporting of MINAS cases in a MINAS database (e.g. https://databases.lovd.nl/shared/diseases/04296) will facilitate more accurate prognostic predictions for specific CSG combinations.