The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

The genetics of complex diseases

Genetic factors influence virtually every human disorder, determining disease susceptibility or resistance and interactions with environmental factors. Our recent successes in the genetic mapping and identification of the molecular basis of mendelian traits have been remarkable. Now, attention is rapidly shifting to more-complex, and more-prevalent, genetic disorders and traits that involve multiple genes and environmental effects, such as cardiovascular disease, diabetes, rheumatoid arthritis and schizophrenia. Rather than being due to specific and relatively rare mutations, complex diseases and traits result principally from genetic variation that is relatively common in the general population. Unfortunately, despite extensive efforts by many groups, only a few genetic regions and genes involved in complex diseases have been identified. Completion of the human genome sequence will be a seminal accomplishment, but it will not provide an immediate solution to the genetics of complex traits.     

Accelerated discovery of functional genomic variation in pigs

The genotype-phenotype link is a major research topic in the life sciences but remains highly complex to disentangle. Part of the complexity arises from the number of genes contributing to the observed phenotype. Despite the vast increase of molecular data, pinpointing the causal variant underlying a phenotype of interest is still challenging. In this study, we present an approach to map causal variation and molecular pathways underlying important phenotypes in pigs. We prioritize variation by utilizing and integrating predicted variant impact scores (pCADD), functional genomic information, and associated phenotypes in other mammalian species. We demonstrate the efficacy of our approach by reporting known and novel causal variants, of which many affect non-coding sequences. Our approach allows the disentangling of the biology behind important phenotypes by accelerating the discovery of novel causal variants and molecular mechanisms affecting important phenotypes in pigs. This information on molecular mechanisms could be applicable in other mammalian species, including humans.     

Mouse models and the interpretation of human GWAS in type 2 diabetes and obesity

Within the last 3 years, genome-wide association studies (GWAS) have had unprecedented success in identifying loci that are involved in common diseases. For example, more than 35 susceptibility loci have been identified for type 2 diabetes and 32 for obesity thus far. However, the causal gene and variant at a specific linkage disequilibrium block is often unclear. Using a combination of different mouse alleles, we can greatly facilitate the understanding of which candidate gene at a particular disease locus is associated with the disease in humans, and also provide functional analysis of variants through an allelic series, including analysis of hypomorph and hypermorph point mutations, and knockout and overexpression alleles. The phenotyping of these alleles for specific traits of interest, in combination with the functional analysis of the genetic variants, may reveal the molecular and cellular mechanism of action of these disease variants, and ultimately lead to the identification of novel therapeutic strategies for common human diseases. In this Commentary, we discuss the progress of GWAS in identifying common disease loci for metabolic disease, and the use of the mouse as a model to confirm candidate genes and provide mechanistic insights.     

Genetics and genomics of behavioral and psychiatric disorders

Psychiatric conditions are to some degree under genetic influences. Despite the application of advanced genetic and molecular biological technologies, the genetic bases of the human behavioral traits and psychiatric diseases remains largely unresolved. Conventional genetic linkage approaches have not yielded definitive results, possibly because of the absence of objective diagnostic tests, the complex nature of human behavior or the incomplete penetrance of psychiatric traits. However, recent studies have revealed some genes of interest using multifaceted approaches to overcome these challenges. The approaches include using families in which specific behaviors segregate as a mendelian trait, utilization of endophenotypes as biological intermediate traits, identification of psychiatric disease phenotypes in genomic disorders, and the establishment of mouse models.     

The candidate gene approach in plant genetics: a review

The candidate gene (CG) approach has been applied in plant genetics in the past decade for the characterisation and cloning of Mendelian and quantitative trait loci (QTLs). It constitutes a complementary strategy to map-based cloning and insertional mutagenesis. The goal of this paper is to present an overview of CG analyses in plant genetics. CG analysis is based on the hypothesis that known-function genes (the candidate genes) could correspond to loci controlling traits of interest. CGs refer either to cloned genes presumed to affect a given trait (`functional CGs') or to genes suggested by their close proximity on linkage maps to loci controlling the trait (`positional CGs'). In plant genetics, the most common way to identify a CG is to look for map co-segregation between CGs and loci affecting the trait. Statistical association analyses between molecular polymorphisms of the CG and variation in the trait of interest have also been carried out in a few studies. The final validation of a CG will be provided through physiological analyses, genetic transformation and/or sexual complementation. Theoretical and practical applications of validated CGs in plant genetics and breeding are discussed.     

Cerebellar ataxia and functional genomics: Identifying the routes to cerebellar neurodegeneration

Cerebellar ataxias are progressive neurodegenerative disorders characterized by atrophy of the cerebellum leading to motor dysfunction, balance problems, and limb and gait ataxia. These include among others, the dominantly inherited spinocerebellar ataxias, recessive cerebellar ataxias such as Friedreich's ataxia, and X-linked cerebellar ataxias. Since all cerebellar ataxias display considerable overlap in their disease phenotypes, common pathological pathways must underlie the selective cerebellar neurodegeneration. Therefore, it is important to identify the molecular mechanisms and routes to neurodegeneration that cause cerebellar ataxia. In this review, we discuss the use of functional genomic approaches including whole-exome sequencing, genome-wide gene expression profiling, miRNA profiling, epigenetic profiling, and genetic modifier screens to reveal the underlying pathogenesis of various cerebellar ataxias. These approaches have resulted in the identification of many disease genes, modifier genes, and biomarkers correlating with specific stages of the disease. This article is part of a Special Issue entitled: From Genome to Function.