Browsing by Author "Diekmann, Yoan"
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- Hope for GWAS: Relevant Risk Genes Uncovered from GWAS Statistical NoisePublication . Correia, Catarina; Diekmann, Yoan; Vicente, Astrid; Pereira-Leal, JoséHundreds of genetic variants have been associated to common diseases through genome-wide association studies (GWAS), yet there are limits to current approaches in detecting true small effect risk variants against a background of false positive findings. Here we addressed the missing heritability problem, aiming to test whether there are indeed risk variants within GWAS statistical noise and to develop a systematic strategy to retrieve these hidden variants. Employing an integrative approach, which combines protein-protein interactions with association data from GWAS for 6 common diseases, we found that associated-genes at less stringent significance levels (p < 0.1) with any of these diseases are functionally connected beyond noise expectation. This functional coherence was used to identify disease-relevant subnetworks, which were shown to be enriched in known genes, outperforming the selection of top GWAS genes. As a proof of principle, we applied this approach to breast cancer, supporting well-known breast cancer genes, while pinpointing novel susceptibility genes for experimental validation. This study reinforces the idea that GWAS are under-analyzed and that missing heritability is rather hidden. It extends the use of protein networks to reveal this missing heritability, thus leveraging the large investment in GWAS that produced so far little tangible gain.
- Hope for GWAS: Relevant Risk Genes Uncovered from GWAS Statistical NoisePublication . Correia, Catarina; Diekmann, Yoan; Vicente, Astrid; Pereira-Leal, JoséHundreds of genetic variants have been associated to common diseases through genome-wide association studies (GWAS), yet there are limits to current approaches in detecting true small effect risk variants against a background of false positive findings. Here we addressed the missing heritability problem, aiming to test whether there are indeed risk variants within GWAS statistical noise and to develop a systematic strategy to retrieve these hidden variants. Employing an integrative approach, which combines protein-protein interactions with association data from GWAS for 6 common diseases, we found that associated-genes at less stringent significance levels (p < 0.1) with any of these diseases are functionally connected beyond noise expectation. This functional coherence was used to identify disease-relevant subnetworks, which were shown to be enriched in known genes, outperforming the selection of top GWAS genes. As a proof of principle, we applied this approach to breast cancer, supporting well-known breast cancer genes, while pinpointing novel susceptibility genes for experimental validation. This study reinforces the idea that GWAS are under-analyzed and that missing heritability is rather hidden. It extends the use of protein networks to reveal this missing heritability, thus leveraging the large investment in GWAS that produced so far little tangible gain.
- Multispecies Analysis of Expression Pattern Diversification in the Recently Expanded Insect Ly6 Gene FamilyPublication . Tanaka, Kohtaro; Diekmann, Yoan; Hazbun, Alexis; Hijazi, Assia; Vreede, Barbara; Roch, Fernando; Sucena, ÉlioGene families often consist of members with diverse expression domains reflecting their functions in a wide variety of tissues. However, how the expression of individual members, and thus their tissue-specific functions, diversified during the course of gene family expansion is not well understood. In this study, we approached this question through the analysis of the duplication history and transcriptional evolution of a rapidly expanding subfamily of insect Ly6 genes. We analyzed different insect genomes and identified seven Ly6 genes that have originated from a single ancestor through sequential duplication within the higher Diptera. We then determined how the original embryonic expression pattern of the founding gene diversified by characterizing its tissue-specific expression in the beetle Tribolium castaneum, the butterfly Bicyclus anynana, and the mosquito Anopheles stephensi and those of its duplicates in three higher dipteran species, representing various stages of the duplication history (Megaselia abdita, Ceratitis capitata, and Drosophila melanogaster). Our results revealed that frequent neofunctionalization episodes contributed to the increased expression breadth of this subfamily and that these events occurred after duplication and speciation events at comparable frequencies. In addition, at each duplication node, we consistently found asymmetric expression divergence. One paralog inherited most of the tissue-specificities of the founder gene, whereas the other paralog evolved drastically reduced expression domains. Our approach attests to the power of combining a well-established duplication history with a comprehensive coverage of representative species in acquiring unequivocal information about the dynamics of gene expression evolution in gene families.