Toward the most ideal case-control design with related and unrelated dogs in whole-exome sequencing studies

Incorporating Genetic Testing into a Breeding Program

Genetic tests are powerful tools that enable (1) a focus on genetic diversity as mating outcomes can be predicted and thus optimized to minimize or even avoid exclusion and (2) working toward breeding goals by improving a phenotype.

Using variant databases for variant prioritization and to detect erroneous genotype-phenotype associations

Background

In the search for novel causal mutations, public and/or private variant databases are nearly always used to facilitate the search as they result in a massive reduction of putative variants in one step. Practically, variant filtering is often done by either using all variants from the variant database (called the absence-approach, i.e. it is assumed that disease-causing variants do not reside in variant databases) or by using the subset of variants with an allelic frequency > 1% (called the 1%-approach). We investigate the validity of these two approaches in terms of false negatives (the true disease-causing variant does not pass all filters) and false positives (a harmless mutation passes all filters and is erroneously retained in the list of putative disease-causing variants) and compare it with an novel approach which we named the quantile-based approach. This approach applies variable instead of static frequency thresholds and the calculation of these thresholds is based on prior knowledge of disease prevalence, inheritance models, database size and database characteristics.

Results

Based on real-life data, we demonstrate that the quantile-based approach outperforms the absence-approach in terms of false negatives. At the same time, this quantile-based approach deals more appropriately with the variable allele frequencies of disease-causing alleles in variant databases relative to the 1%-approach and as such allows a better control of the number of false positives.

We also introduce an alternative application for variant database usage and the quantile-based approach. If disease-causing variants in variant databases deviate substantially from theoretical expectancies calculated with the quantile-based approach, their association between genotype and phenotype had to be reconsidered in 12 out of 13 cases.

Conclusions

We developed a novel method and demonstrated that this so-called quantile-based approach is a highly suitable method for variant filtering. In addition, the quantile-based approach can also be used for variant flagging. For user friendliness, lookup tables and easy-to-use R calculators are provided.

Electronic supplementary material

The online version of this article (doi: 10.1186/s12859-017-1951-y) contains supplementary material, which is available to authorized users.

An exome sequencing based approach for genome-wide association studies in the dog

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.

A monograph proposing the use of canine mammary tumours as a model for the study of hereditary breast cancer susceptibility genes in humans

Canines are excellent models for cancer studies due to their similar physiology and genomic sequence to humans, companion status and limited intra‐breed heterogeneity. Due to their affliction to mammary cancers, canines can serve as powerful genetic models of hereditary breast cancers. Variants within known human breast cancer susceptibility genes only explain a fraction of familial cases. Thus, further discovery is necessary but such efforts have been thwarted by genetic heterogeneity. Reducing heterogeneity is key, and studying isolated human populations have helped in the endeavour. An alternative is to study dog pedigrees, since artificial selection has resulted in extreme homogeneity. Identifying the genetic predisposition to canine mammary tumours can translate to human discoveries – a strategy currently underutilized. To explore this potential, we reviewed published canine mammary tumour genetic studies and proposed benefits of next generation sequencing canine cohorts to facilitate moving beyond incremental advances.