1,721,119 research outputs found
Genetic variation in mitotic regulatory pathway genes is associated with breast tumor grade.
No full textMitotic index is an important component of histologic grade and has an etiologic role in breast tumorigenesis. Several small candidate gene studies have reported associations between variation in mitotic genes and breast cancer risk. We measured associations between 2156 single nucleotide polymorphisms (SNPs) from 194 mitotic genes and breast cancer risk, overall and by histologic grade, in the Breast Cancer Association Consortium (BCAC) iCOGS study (n = 39 067 cases; n = 42 106 controls). SNPs in TACC2 [rs17550038: odds ratio (OR) = 1.24, 95% confidence interval (CI) 1.16–1.33, P = 4.2 × 10−10) and EIF3H (rs799890: OR = 1.07, 95% CI 1.04–1.11, P = 8.7 × 10−6) were significantly associated with risk of low-grade breast cancer. The TACC2 signal was retained (rs17550038: OR = 1.15, 95% CI 1.07–1.23, P = 7.9 × 10−5) after adjustment for breast cancer risk SNPs in the nearby FGFR2 gene, suggesting that TACC2 is a novel, independent genome-wide significant genetic risk locus for low-grade breast cancer. While no SNPs were individually associated with high-grade disease, a pathway-level gene set analysis showed that variation across the 194 mitotic genes was associated with high-grade breast cancer risk (P = 2.1 × 10−3). These observations will provide insight into the contribution of mitotic defects to histological grade and the etiology of breast cancer.<br/
Construction and analysis of sequence-based integrated maps
No full textEThOS - Electronic Theses Online ServiceGBUnited Kingdo
Linkage disequilibrium maps and location databases
No full textEffective application of association mapping for complex traits requires characterization of linkage disequilibrium (LD) patterns that reflect the dominant process of recombination and its duration in addition to the more subtle influences of mutation, selection, and genetic drift. Maps expressed in linkage disequilibrium units (LDUs) reflect the influences of these factors with the use of a modified version of Malecot’s isolation-by-distance model. As a result, LDU maps are analogous to linkage maps in so far as their provision of an additive metric that is related to recombination and facilitates association-mapping studies. However, unlike linkage maps, LDUs also reflect the partly cumulative effects of multiple historical bottlenecks that account for substantial variations in LD patterns between populations. This chapter provides an overview of the data requirements and methodology used to construct LDU maps, their applications outside association mapping, and their integration into location databases
Genome variation: a review of Web resources
No full textAn enormous number of high-quality Web-based resources are now available to facilitate research into genome variation. Although identification of the most appropriate and informative resources can be challenging, a number of key sites provide links to more specialized resources that may be useful to follow up. Given ongoing research, focussing on the sequencing of many different genomes, we can expect sequence databases and their associated polymorphism-based resources to greatly increase in depth and complexity in a relatively short period of time. However, databases and tools developed to date, and described here, provide a sound basis for accommodating this next generation of genomic data. As well as sequence-oriented resources this review presents databases providing genotypic and common disease phenotype data, copy number variation, genetic maps, cytogenetic data, and gives an overview of key software tools, with the emphasis on analysis of the genetic basis of common disease.</p
Dataset to support the Southampton Doctoral Thesis 'The Influence of Germline Genotype on Breast Cancer Tumour Phenotype'
No full textSummary level data derived from The 100,000 Genomes Project, Rare Disease, Familial Breast Cancer and Cancer, Breast Cancer Recruitment Domains. Data exported via the Genomics England secure AirLock system. This includes the number of pathogenic/likely pathogenic variant identified in BRCA, PALB2, CHEK2, ATM and TP53. It compares the age of cancer onset between gene carriers and non-carriers. It also compares the Tumour Mutational Burden, Somatic Mutational Signature and Somatic Mutational Profile between gene carriers and non-carriers.</span
The systematic status of the lagoon periwinkle, <i>Littorina tenebrosa</i>
No full textEight samples of Littorina tenebrosa and L. saxatilis (Mollusca: Gastropoda) from Ireland and Britain, including pairs of each form from two locations in Ireland, were screened for genetic variation at 12 polymorphic enzyme loci using starch gel electrophoresis. Levels of polymorphism and heterozygosity were similar in L. tenebrosa and L. saxatilis, apart from a sample of L. tenebrosa from Britain which was less polymorphic than the Irish samples. No alleles were found to be unique to either form. Phylogenetic analysis using UPGMA showed that L. saxatilis and L. tenebrosa populations clustered as a monophyletic group. Nevertheless, the mean genetic distance between parapatric populations of L. saxatilis and L. tenebrosa (D=0.076) was similar to the mean for allopatric populations of either species (D=0.080). This indicates that there is a barrier to gene flow between the two forms Despite this, L. tenebrosa does not merit specific status since populations of this snail do not cluster as a distinct group, separate from L. saxatilis populations
Supplementary data to support the Southampton Doctoral thesis 'The causes and consequences of clonal haematopoiesis'
No full textThe dataset consists of two files. (i) Supplementary tables of chapter 3 (ii) supplementary tables of chapter 4. The dataset were generated by utilising genetic and phenotypic data from UK Biobank</span
Mapping a gene for rheumatoid arthritis on chromosome 18q21
No full textAlthough single chi-square analysis of the North American Rheumatoid Arthritis Consortium (NARAC) data identifies many single-nucleotide polymorphisms (SNPs) with p-values less than 0.05, none remain significant after Bonferroni correction. In contrast, CHROMSCAN evades heavy Bonferroni correction and auto-correlation between SNPs by using composite likelihood to model association across all markers in a region and permutation to assess significance. Analysis by CHROMSCAN identifies a 36-kb interval that includes the most significant SNP (msSNP) observed in a 10-Mb target suggested by linkage. Unexpectedly, stratification by gender and age of onset shows that association evidence comes almost entirely from females with age of onset less than 40. Combining evidence from a meta-analysis of linkage studies and three subsets of the NARAC data provides significant evidence for a determinant of rheumatoid arthritis in a 36-kb interval and illustrates the principle that estimates of location and its information are more powerful than estimates of p-values alone
Dataset supporting the thesis: Identification of genetic factors associated with myeloid neoplasms
No full textSupplementary tables for Chapter 2,3 and 4 of the PhD Thesis "Identification of genetic factors associated with myeloid neoplasms"</span
The influence of common polymorphisms on breast cancer
No full textBreast cancer is one of the most frequently diagnosed cancers in the Western world and a significant cause of mortality worldwide. A small proportion of cases are accounted for by high-penetrance monogenic predisposition genes; however, this explains only a small fraction (less than 5%) of all breast cancers. Increasingly with advances in molecular technology and the development of large research consortia, the locations and identities of many low-penetrance genetic variants are being discovered. However, each variant has a very small effect similar to or smaller than many of the known environmental risk factors. It is therefore unlikely that these variants will be appropriate for predictive genetic testing, although they may identify novel pathways and genes which provide new insights and targets for therapeutic intervention. The future challenges will be identifying causal variants and determining how these low-penetrance alleles interact with each other and with environmental factors in order to usefully implement them in the practice of clinical medicine. Furthermore, it is clear that breast cancer comes in many forms with the tumour pathology and immunohistochemical profile already being used routinely as prognostic indicators and to inform treatment decisions. However, these indicators of prognosis are imperfect; two apparently identical tumours may have very different outcomes in different individuals. Inherited genetic variants may well be one of the other factors that need to be taken into account in assessing prognosis and planning treatment
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