| 11. |
- Lee, James J, et al.
(author)
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Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals.
- 2018
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In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 50:8, s. 1112-1121
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Journal article (peer-reviewed)abstract
- Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1million individuals and identify 1,271independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
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| 12. |
- McCarthy, Shane, et al.
(author)
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A reference panel of 64,976 haplotypes for genotype imputation
- 2016
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 48:10, s. 1279-1283
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Journal article (peer-reviewed)abstract
- We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.
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| 13. |
- Mulder, Kevin P., et al.
(author)
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Evolutionary dynamics of an expressed MHC class IIβ beta locus in the Ranidae (Anura) uncovered by genome walking and high-throughput amplicon sequencing
- 2017
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In: Developmental and Comparative Immunology. - Oxford : Elsevier. - 0145-305X .- 1879-0089. ; 76, s. 177-188
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Journal article (peer-reviewed)abstract
- The Major Histocompatibility Complex (MHC) is a genomic region encoding immune loci that are important and frequently used markers in studies of adaptive genetic variation and "disease resistance. Given the primary role of infectious diseases in contributing to global amphibian declines, we characterized the hypervariable exon 2 and flanking introns of the MHC Class II beta chain for 17 species of frogs in the Ranidae, a speciose and cosmopolitan family facing widespread pathogen infections and declines. We find high levels of genetic variation concentrated in the Peptide Binding Region (PBR) of the exon. Ten codons are under positive selection, nine of which are located in the mammal-defined PBR. We hypothesize that the tenth codon (residue 21) is an amphibian-specific PBR site that may be important in disease resistance. Trans-species and trans-generic polymorphisms are evident from exon-based genealogies, and co-phylogenetic analyses between intron, exon and mitochondrial based reconstructions reveal incongruent topologies, likely due to different locus histories. We developed two sets of barcoded adapters that reliably amplify a single and likely functional locus in all screened species using both 454 and Illumina based sequencing methods. These primers provide a resource for multiplexing and directly sequencing hundreds of samples in a single sequencing run, avoiding the labour and chimeric sequences associated with cloning, and enabling MHC population genetic analyses. Although the primers are currently limited to the 17 species we tested, these sequences and protocols provide a useful genetic resource and can serve as a starting point for future disease, adaptation and conservation studies across a range of anuran taxa.
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| 14. |
- Schmit, Stephanie L, et al.
(author)
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Novel Common Genetic Susceptibility Loci for Colorectal Cancer.
- 2019
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 111:2, s. 146-157
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Journal article (peer-reviewed)abstract
- Background: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk.Methods: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided.Results: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0.Conclusions: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.
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| 15. |
- Sullivan, Devin P., et al.
(author)
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Deep learning is combined with massive-scale citizen science to improve large-scale image classification
- 2018
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In: Nature Biotechnology. - : NATURE PUBLISHING GROUP. - 1087-0156 .- 1546-1696. ; 36:9, s. 820-
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Journal article (peer-reviewed)abstract
- Pattern recognition and classification of images are key challenges throughout the life sciences. We combined two approaches for large-scale classification of fluorescence microscopy images. First, using the publicly available data set from the Cell Atlas of the Human Protein Atlas (HPA), we integrated an image-classification task into a mainstream video game (EVE Online) as a mini-game, named Project Discovery. Participation by 322,006 gamers over 1 year provided nearly 33 million classifications of subcellular localization patterns, including patterns that were not previously annotated by the HPA. Second, we used deep learning to build an automated Localization Cellular Annotation Tool (Loc-CAT). This tool classifies proteins into 29 subcellular localization patterns and can deal efficiently with multi-localization proteins, performing robustly across different cell types. Combining the annotations of gamers and deep learning, we applied transfer learning to create a boosted learner that can characterize subcellular protein distribution with F1 score of 0.72. We found that engaging players of commercial computer games provided data that augmented deep learning and enabled scalable and readily improved image classification.
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