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Sökning: WFRF:(Bryant Patrick)

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1.
  • Clark, Andrew G., et al. (författare)
  • Evolution of genes and genomes on the Drosophila phylogeny
  • 2007
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 450:7167, s. 203-218
  • Tidskriftsartikel (refereegranskat)abstract
    • Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.
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  • Barnekow, Elin, et al. (författare)
  • A Swedish Familial Genome-Wide Haplotype Analysis Identified Five Novel Breast Cancer Susceptibility Loci on 9p24.3, 11q22.3, 15q11.2, 16q24.1 and Xq21.31
  • 2023
  • Ingår i: International Journal of Molecular Sciences. - : MDPI AG. - 1661-6596 .- 1422-0067. ; 24:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Most breast cancer heritability is unexplained. We hypothesized that analysis of unrelated familial cases in a GWAS context could enable the identification of novel susceptibility loci. In order to examine the association of a haplotype with breast cancer risk, we performed a genome-wide haplotype association study using a sliding window analysis of window sizes 1–25 SNPs in 650 familial invasive breast cancer cases and 5021 controls. We identified five novel risk loci on 9p24.3 (OR 3.4; p 4.9 × 10−11), 11q22.3 (OR 2.4; p 5.2 × 10−9), 15q11.2 (OR 3.6; p 2.3 × 10−8), 16q24.1 (OR 3; p 3 × 10−8) and Xq21.31 (OR 3.3; p 1.7 × 10−8) and confirmed three well-known loci on 10q25.13, 11q13.3, and 16q12.1. In total, 1593 significant risk haplotypes and 39 risk SNPs were distributed on the eight loci. In comparison with unselected breast cancer cases from a previous study, the OR was increased in the familial analysis in all eight loci. Analyzing familial cancer cases and controls enabled the identification of novel breast cancer susceptibility loci.
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  • Barnekow, Elin, et al. (författare)
  • A Swedish Genome-Wide Haplotype Association Analysis Identifies a Novel Breast Cancer Susceptibility Locus in 8p21.2 and Characterizes Three Loci on Chromosomes 10, 11 and 16
  • 2022
  • Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:5
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The heritability of breast cancer is partly explained but much of the genetic contribution remains to be identified. Haplotypes are often used as markers of ethnicity as they are preserved through generations. We have previously demonstrated that haplotype analysis, in addition to standard SNP association studies, could give novel and more detailed information on genetic cancer susceptibility.Methods: In order to examine the association of a SNP or a haplotype to breast cancer risk, we performed a genome wide haplotype association study, using sliding window analysis of window sizes 1-25 and 50 SNPs, in 3200 Swedish breast cancer cases and 5021 controls.Results: We identified a novel breast cancer susceptibility locus in 8p21.1 (OR 2.08; p 3.92 x 10(-8)), confirmed three known loci in 10q26.13, 11q13.3, 16q12.1-2 and further identified novel subloci within these three loci. Altogether 76 risk SNPs, 3302 risk haplotypes of window size 2-25 and 113 risk haplotypes of window size 50 at p < 5 x 10(-8) on chromosomes 8, 10, 11 and 16 were identified. In the known loci haplotype analysis reached an OR of 1.48 in overall breast cancer and in familial cases OR 1.68.Conclusions: Analyzing haplotypes, rather than single variants, could detect novel susceptibility loci even in small study populations but the method requires a fairly homogenous study population.
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7.
  • Bryant, Patrick, et al. (författare)
  • Decomposing Structural Response Due to Sequence Changes in Protein Domains with Machine Learning
  • 2020
  • Ingår i: Journal of Molecular Biology. - : Elsevier BV. - 0022-2836 .- 1089-8638. ; 432:16, s. 4435-4446
  • Tidskriftsartikel (refereegranskat)abstract
    • How protein domain structure changes in response to mutations is not well understood. Some mutations change the structure drastically, while most only result in small changes. To gain an understanding of this, we decompose the relationship between changes in domain sequence and structure using machine learning. We select pairs of evolutionarily related domains with a broad range of evolutionary distances. In contrast to earlier studies, we do not find a strictly linear relationship between sequence and structural changes. We train a random forest regressor that predicts the structural similarity between pairs with an average accuracy of 0.029 IDDT ( local Distance Difference Test) score, and a correlation coefficient of 0.92. Decomposing the feature importance shows that the domain length, or analogously, size is the most important feature. Our model enables assessing deviations in relative structural response, and thus prediction of evolutionary trajectories, in protein domains across evolution.
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8.
  • Bryant, Patrick (författare)
  • Deep learning for protein complex structure prediction
  • 2023
  • Ingår i: Current opinion in structural biology. - : Elsevier BV. - 0959-440X .- 1879-033X. ; 79
  • Tidskriftsartikel (refereegranskat)abstract
    • Recent developments in the structure prediction of protein complexes have resulted in accuracies rivalling experimental methods in many cases. The high accuracy is mainly observed in dimeric complexes and other problems such as protein disorder and predicting the structure of host-pathogen in-teractions remain. This review highlights the foundation for current accurate structure prediction of protein complexes and possible ways to address the remaining limitations.
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  • Bryant, Patrick, et al. (författare)
  • Estimating the impact of mobility patterns on COVID-19 infection rates in 11 European countries
  • 2020
  • Ingår i: PeerJ. - : PeerJ. - 2167-8359. ; 8
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: As governments across Europe have issued non-pharmaceutical interventions (NPIs) such as social distancing and school closing, the mobility patterns in these countries have changed. Most states have implemented similar NPIs at similar time points. However, it is likely different countries and populations respond differently to the NPIs and that these differences cause mobility patterns and thereby the epidemic development to change.Methods: We build a Bayesian model that estimates the number of deaths on a given day dependent on changes in the basic reproductive number, R-0, due to differences in mobility patterns. We utilise mobility data from Google mobility reports using five different categories: retail and recreation, grocery and pharmacy, transit stations, workplace and residential. The importance of each mobility category for predicting changes in R-0 is estimated through the model.Findings: The changes in mobility have a considerable overlap with the introduction of governmental NPIs, highlighting the importance of government action for population behavioural change. The shift in mobility in all categories shows high correlations with the death rates 1 month later. Reduction of movement within the grocery and pharmacy sector is estimated to account for most of the decrease in R-0.Interpretation: Our model predicts 3-week epidemic forecasts, using real-time observations of changes in mobility patterns, which can provide governments with direct feedback on the effects of their NPIs. The model predicts the changes in a majority of the countries accurately but overestimates the impact of NPIs in Sweden and Denmark and underestimates them in France and Belgium. We also note that the exponential nature of all epidemiological models based on the basic reproductive number, R-0 cause small errors to have extensive effects on the predicted outcome.
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10.
  • Bryant, Patrick, et al. (författare)
  • Exome sequencing in a Swedish family with PMS2 mutation with varying penetrance of colorectal cancer : investigating the presence of genetic risk modifiers in colorectal cancer risk
  • 2023
  • Ingår i: European Journal of Cancer Prevention. - 0959-8278 .- 1473-5709. ; 32:2, s. 113-118
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective  Lynch syndrome is caused by germline mutations in the mismatch repair (MMR) genes, such as the PMS2 gene, and is characterised by a familial accumulation of colorectal cancer. The penetrance of cancer in PMS2 carriers is still not fully elucidated as a colorectal cancer risk has been shown to vary between PMS2 carriers, suggesting the presence of risk modifiers.Methods  Whole exome sequencing was performed in a Swedish family carrying a PMS2 missense mutation [c.2113G>A, p.(Glu705Lys)]. Thirteen genetic sequence variants were further selected and analysed in a case-control study (724 cases and 711 controls).Results  The most interesting variant was an 18 bp deletion in gene BAG1. BAG1 has been linked to colorectal tumour progression with poor prognosis and is thought to promote colorectal tumour cell survival through increased NF-κB activity.Conclusions  We conclude the genetic architecture behind the incomplete penetrance of PMS2 is complicated and must be assessed in a genome wide manner using large families and multifactorial analysis.
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