A significant number of people are affected by various multifactorial diseases such as diabetes, cardiovascular diseases, cancer worldwide. Multifactorial diseases are associated with multiple gene defects in combination with lifestyle and environmental factors. Although multifactorial diseases often cluster in families, they do not have a clear pattern of inheritance. Besides, the genetic variants associated with the complex disease are often common polymorphisms; therefore, to determine disease mechanisms, disease-associated genes must be identified and analyzed in combination. For these reasons, multifactorial diseases are difficult to study and contain many unanswered questions regarding their etiology. We have observed great technological progress in genomics and computing in the last decade, increasing the resolution of our understanding of human genetics and diseases. Researchers can now analyse massive quantities of genomic data, by computational and experimental approaches means, to unravel the pathogenesis of complex diseases.
However, diseases with a complex etiopathogenesis; those caused by several variants in different genes, for example, require more advanced investigations. Different approaches have been carried out in an attempt to understand how genetics contribute to the development of the diseases and the interaction of other factors that constitute diseases. With massive genetic and genomic data generated by next-generation sequencing technologies, the combination of computational and experimental approaches could provide the tools needed to answer some fundamental questions provide much-needed conclusions.
Therefore, this topic aims to recruit in-depth computational and experimental approaches that dissect the fundamental principles of the role of genetics and genomics in multifactorial diseases. Seeking to address questions like: what is the relative contribution of the genetic, epigenetic, microbiome, and environmental factors? How can genomics data be used to tackle big unanswered questions; such as, what causes the variation in phenotypes, disease susceptibility, and drug responses?
This research topic aims to raise awareness of the role of genetics and genomics in multifactorial diseases. We welcome the submissions related to, but not limited to, the following topics:
• High throughput methods based on genomic, epigenomic, transcriptomic, proteomic approaches in different models to identify molecular profiles associated with multifactorial diseases;
• Identification of novel genomic variations associated with multifactorial disease;
• Combination of different approaches to identify the mechanism underlying the complex phenotypes in multifactorial diseases;
• Assessment of gene function using genome editing tools;
• Integrating genomics into medicine. Development of personalized medicine based on the genetic data of each individual;
• Decoding multifactorial phenotypes;
• Large-scale genome sequencing data associated with multifactorial diseases.
A significant number of people are affected by various multifactorial diseases such as diabetes, cardiovascular diseases, cancer worldwide. Multifactorial diseases are associated with multiple gene defects in combination with lifestyle and environmental factors. Although multifactorial diseases often cluster in families, they do not have a clear pattern of inheritance. Besides, the genetic variants associated with the complex disease are often common polymorphisms; therefore, to determine disease mechanisms, disease-associated genes must be identified and analyzed in combination. For these reasons, multifactorial diseases are difficult to study and contain many unanswered questions regarding their etiology. We have observed great technological progress in genomics and computing in the last decade, increasing the resolution of our understanding of human genetics and diseases. Researchers can now analyse massive quantities of genomic data, by computational and experimental approaches means, to unravel the pathogenesis of complex diseases.
However, diseases with a complex etiopathogenesis; those caused by several variants in different genes, for example, require more advanced investigations. Different approaches have been carried out in an attempt to understand how genetics contribute to the development of the diseases and the interaction of other factors that constitute diseases. With massive genetic and genomic data generated by next-generation sequencing technologies, the combination of computational and experimental approaches could provide the tools needed to answer some fundamental questions provide much-needed conclusions.
Therefore, this topic aims to recruit in-depth computational and experimental approaches that dissect the fundamental principles of the role of genetics and genomics in multifactorial diseases. Seeking to address questions like: what is the relative contribution of the genetic, epigenetic, microbiome, and environmental factors? How can genomics data be used to tackle big unanswered questions; such as, what causes the variation in phenotypes, disease susceptibility, and drug responses?
This research topic aims to raise awareness of the role of genetics and genomics in multifactorial diseases. We welcome the submissions related to, but not limited to, the following topics:
• High throughput methods based on genomic, epigenomic, transcriptomic, proteomic approaches in different models to identify molecular profiles associated with multifactorial diseases;
• Identification of novel genomic variations associated with multifactorial disease;
• Combination of different approaches to identify the mechanism underlying the complex phenotypes in multifactorial diseases;
• Assessment of gene function using genome editing tools;
• Integrating genomics into medicine. Development of personalized medicine based on the genetic data of each individual;
• Decoding multifactorial phenotypes;
• Large-scale genome sequencing data associated with multifactorial diseases.
