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Lessons from Genome-Wide Search for Disease-Related Genes with Special Reference to HLA-Disease Associations.

ABSTRACT: The relationships between diseases and genetic factors are by no means uniform. Single-gene diseases are caused primarily by rare mutations of specific genes. Although each single-gene disease has a low prevalence, there are an estimated 5000 or more such diseases in the world. In contrast, multifactorial diseases are diseases in which both genetic and environmental factors are involved in onset. These include a variety of diseases, such as diabetes and autoimmune diseases, and onset is caused by a range of various environmental factors together with a number of genetic factors. With the astonishing advances in genome analysis technology in recent years and the accumulation of data on human genome variation, there has been a rapid progress in research involving genome-wide searches for genes related to diseases. Many of these studies have led to the recognition of the importance of the human leucocyte antigen (HLA) gene complex. Here, the current state and future challenges of genome-wide exploratory research into variations that are associated with disease susceptibilities and drug/therapy responses are described, mainly with reference to our own experience in this field.

SUBMITTER: Tokunaga K

PROVIDER: S-EPMC3978513 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Lessons from Genome-Wide Search for Disease-Related Genes with Special Reference to HLA-Disease Associations.

Tokunaga Katsushi K

Genes 20140226 1

The relationships between diseases and genetic factors are by no means uniform. Single-gene diseases are caused primarily by rare mutations of specific genes. Although each single-gene disease has a low prevalence, there are an estimated 5000 or more such diseases in the world. In contrast, multifactorial diseases are diseases in which both genetic and environmental factors are involved in onset. These include a variety of diseases, such as diabetes and autoimmune diseases, and onset is caused b ...[more]

PMID: 24705288

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Project description:BackgroundCotton is one of the most important commercial crops as the source of natural fiber, oil and fodder. To protect it from harmful pest populations number of newer transgenic lines have been developed. For quick expression checks in successful agriculture qPCR (quantitative polymerase chain reaction) have become extremely popular. The selection of appropriate reference genes plays a critical role in the outcome of such experiments as the method quantifies expression of the target gene in comparison with the reference. Traditionally most commonly used reference genes are the "house-keeping genes", involved in basic cellular processes. However, expression levels of such genes often vary in response to experimental conditions, forcing the researchers to validate the reference genes for every experimental platform. This study presents a data science driven unbiased genome-wide search for the selection of reference genes by assessing variation of > 50,000 genes in a publicly available RNA-seq dataset of cotton species Gossypium hirsutum.ResultFive genes (TMN5, TBL6, UTR5B, AT1g65240 and CYP76B6) identified by data-science driven analysis, along with two commonly used reference genes found in literature (PP2A1 and UBQ14) were taken through qPCR in a set of 33 experimental samples consisting of different tissues (leaves, square, stem and root), different stages of leaf (young and mature) and square development (small, medium and large) in both transgenic and non-transgenic plants. Expression stability of the genes was evaluated using four algorithms - geNorm, BestKeeper, NormFinder and RefFinder.ConclusionBased on the results we recommend the usage of TMN5 and TBL6 as the optimal candidate reference genes in qPCR experiments with normal and transgenic cotton plant tissues. AT1g65240 and PP2A1 can also be used if expression study includes squares. This study, for the first time successfully displays a data science driven genome-wide search method followed by experimental validation as a method of choice for selection of stable reference genes over the selection based on function alone.

Project description:Most common food grains contain gluten proteins and can cause adverse medical conditions generally known as gluten-related disorders. Celiac disease is an immune-mediated enteropathy triggered by gluten in individuals carrying a specific genetic make-up. The presence of the human leukocyte antigens (HLA)-DQ2 and HLA-DQ8 haplotypes together with gluten intake is a necessary, although not sufficient, condition, to develop celiac disease. Fine mapping of the human genome has revealed numerous genetic variants important in the development of this disease. Most of the genetic variants are small nucleotide polymorphisms located within promoters and transcriptional enhancer sequences. Their importance is underlined by an increased risk in DQ2/DQ8 carriers who also have these non-HLA alleles. In addition, several immune-mediated diseases share susceptibility loci with celiac disease, shedding light on the reasons for co-occurrence between these diseases. Finally, most of the genes potentially involved in celiac disease by fine genetic mapping of non-HLA loci were confirmed in gene expression studies. In contrast to celiac disease, very little is known about the genetic make-up of non-celiac wheat sensitivity (NCWS), a clinically defined pathology that shares symptoms and gluten dependence with the celiac disease. We recently identified differentially expressed genes and miRNAs in the intestinal mucosa of these patients. Remarkably, the differentially expressed genes were long non-coding RNAs possibly involved in the regulation of cell functions. Thus, we can speculate that important aspects of these diseases depend on alteration of regulatory genetic circuits. Furthermore, our finding suggests that innate immune response is involved in the pathogenic mechanism of NCWS. This review is intended to convey the idea that in order to fully understand celiac disease and its relationship with other gluten-related disorders, it is worth learning more about non-HLA variants.

Dataset Information

Lessons from Genome-Wide Search for Disease-Related Genes with Special Reference to HLA-Disease Associations.

Publications

Lessons from Genome-Wide Search for Disease-Related Genes with Special Reference to HLA-Disease Associations.

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