| 1. |
- Broeckx, Bart J. G., et al.
(författare)
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An exome sequencing based approach for genome-wide association studies in the dog
- 2017
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) are widely used to identify loci associated with phenotypic traits in the domestic dog that has emerged as a model for Mendelian and complex traits. However, a disadvantage of GWAS is that it always requires subsequent fine-mapping or sequencing to pinpoint causal mutations. Here, we performed whole exome sequencing (WES) and canine high-density (cHD) SNP genotyping of 28 dogs from 3 breeds to compare the SNP and linkage disequilibrium characteristics together with the power and mapping precision of exome-guided GWAS (EG-GWAS) versus cHD-based GWAS. Using simulated phenotypes, we showed that EG-GWAS has a higher power than cHD to detect associations within target regions and less power outside target regions, with power being influenced further by sample size and SNP density. We analyzed two real phenotypes (hair length and furnishing), that are fixed in certain breeds to characterize mapping precision of the known causal mutations. EG-GWAS identified the associated exonic and 3'UTR variants within the FGF5 and RSPO2 genes, respectively, with only a few samples per breed. In conclusion, we demonstrated that EG-GWAS can identify loci associated with Mendelian phenotypes both within and across breeds.
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| 2. |
- Hitte, Christophe, et al.
(författare)
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Genome-Wide Analysis of Long Non-Coding RNA Profiles in Canine Oral Melanomas
- 2019
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Ingår i: Genes. - : MDPI. - 2073-4425 .- 2073-4425. ; 10:6
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Tidskriftsartikel (refereegranskat)abstract
- Mucosal melanomas (MM) are rare aggressive cancers in humans, and one of the most common forms of oral cancers in dogs. Similar biological and histological features are shared between MM in both species, making dogs a powerful model for comparative oncology studies of melanomas. Although exome sequencing recently identified recurrent coding mutations in canine MM, little is known about changes in non-coding gene expression, and more particularly, in canine long non-coding RNAs (lncRNAs), which are commonly dysregulated in human cancers. Here, we sampled a large cohort (n = 52) of canine normal/tumor oral MM from three predisposed breeds (poodles, Labrador retrievers, and golden retrievers), and used deep transcriptome sequencing to identify more than 400 differentially expressed (DE) lncRNAs. We further prioritized candidate lncRNAs by comparative genomic analysis to pinpoint 26 dog-human conserved DE lncRNAs, including SOX21-AS, ZEB2-AS, and CASC15 lncRNAs. Using unsupervised co-expression network analysis with coding genes, we inferred the potential functions of the DE lncRNAs, suggesting associations with cancer-related genes, cell cycle, and carbohydrate metabolism Gene Ontology (GO) terms. Finally, we exploited our multi-breed design to identify DE lncRNAs within breeds. This study provides a unique transcriptomic resource for studying oral melanoma in dogs, and highlights lncRNAs that may potentially be diagnostic or therapeutic targets for human and veterinary medicine.
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| 3. |
- Prouteau, Anais, et al.
(författare)
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Canine Oral Melanoma Genomic and Transcriptomic Study Defines Two Molecular Subgroups with Different Therapeutical Targets
- 2022
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:2, s. 276-
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Tidskriftsartikel (refereegranskat)abstract
- Simple Summary In humans, mucosal melanoma (MM) is a rare and aggressive cancer. The canine model is frequently and spontaneously affected by MM, thus facilitating the collection of samples and the study of its genetic bases. Thanks to an integrative genomic and transcriptomic analysis of 32 canine MM samples, we identified two molecular subgroups of MM with a different microenvironment and structural variant (SV) content. We demonstrated that SVs are associated with recurrently amplified regions, and identified new candidate oncogenes (TRPM7, GABPB1, and SPPL2A) for MM. Our findings suggest the existence of two MM molecular subgroups that could benefit from dedicated therapies, such as immune checkpoint inhibitors or targeted therapies, for both human and veterinary medicine. Mucosal melanoma (MM) is a rare, aggressive clinical cancer. Despite recent advances in genetics and treatment, the prognosis of MM remains poor. Canine MM offers a relevant spontaneous and immunocompetent model to decipher the genetic bases and explore treatments for MM. We performed an integrative genomic and transcriptomic analysis of 32 canine MM samples, which identified two molecular subgroups with a different microenvironment and structural variant (SV) content. The overexpression of genes related to the microenvironment and T-cell response was associated with tumors harboring a lower content of SVs, whereas the overexpression of pigmentation-related pathways and oncogenes, such as TERT, was associated with a high SV burden. Using whole-genome sequencing, we showed that focal amplifications characterized complex chromosomal rearrangements targeting oncogenes, such as MDM2 or CDK4, and a recurrently amplified region on canine chromosome 30. We also demonstrated that the genes TRPM7, GABPB1, and SPPL2A, located in this CFA30 region, play a role in cell proliferation, and thus, may be considered as new candidate oncogenes for human MM. Our findings suggest the existence of two MM molecular subgroups that may benefit from dedicated therapies, such as immune checkpoint inhibitors or targeted therapies, for both human and veterinary medicine.
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| 4. |
- Wucher, Valentin, et al.
(författare)
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FEELnc : a tool for long non-coding RNA annotation and its application to the dog transcriptome
- 2017
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 45:8
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Tidskriftsartikel (refereegranskat)abstract
- Whole transcriptome sequencing (RNA-seq) has become a standard for cataloguing and monitoring RNA populations. One of the main bottlenecks, however, is to correctly identify the different classes of RNAs among the plethora of reconstructed transcripts, particularly those that will be translated (mRNAs) from the class of long non-coding RNAs (lncRNAs). Here, we present FEELnc (FlExible Extraction of LncRNAs), an alignment-free program that accurately annotates lncRNAs based on a Random Forest model trained with general features such as multi k-mer frequencies and relaxed open reading frames. Benchmarking versus five state-of-the-art tools shows that FEELnc achieves similar or better classification performance on GENCODE and NONCODE data sets. The program also provides specific modules that enable the user to fine-tune classification accuracy, to formalize the annotation of lncRNA classes and to identify lncRNAs even in the absence of a training set of non-coding RNAs. We used FEELnc on a real data set comprising 20 canine RNA-seq samples produced by the European LUPA consortium to substantially expand the canine genome annotation to include 10 374 novel lncRNAs and 58 640 mRNA transcripts. FEELnc moves beyond conventional coding potential classifiers by providing a standardized and complete solution for annotating lncRNAs and is freely available at https://github.com/tderrien/FEELnc.
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