Molecular basis of inherited skin-blistering disorders, and therapeutic implications

Epidermolysis bullosa (EB) and associated skin-fragility syndromes are a group of inherited skin diseases characterised by trauma-induced blistering of the skin and mucous membranes. Mutations in at least 14 distinct genes encoding molecular components of the epidermis or the dermal-epidermal junction (DEJ) can cause blistering skin diseases that differ by clinical presentation and severity of the symptoms. Despite great advances in discerning the genetic basis of this group of diseases, the molecular pathways leading to symptoms are not yet fully understood. Unravelling these pathways by molecular analysis of the structure and in vitro assessment of functional properties of the human proteins involved, combined with genetic models in lower organisms, should pave the way for specific cures for inherited skin fragility.     

Biotechnological advancements in alfalfa improvement

Review of biotechnology research in alfalfa shows that molecular techniques are extensively being used for basic and applied research toward alfalfa improvement. Biotechnological approaches have been used in two major areas, genomics and transgenics. In genomics, molecular markers, structural and functional genomics allowed identification of genes of interest and their regulatory components. Alfalfa being obstinate to genetic and genomic analysis, comparative genomics is used for molecular and genetic dissection of various plant processes in alfalfa. Alternatively, transgenic approach involves incorporation of specific and useful genes into alfalfa to improve the traits of interest. Input traits to improve agronomic performance and output traits to improve forage quality, or to produce novel industrial/pharmaceutical proteins, are the focus of current transgenic research in alfalfa. However, transgenic approach is controversial requiring cautious experimental design to combat bioisafety concerns. Ideally, forage alfalfa needs to possess more fermentable carbohydrates, proteins with balanced amino acid profile that degrade slower in rumen, improved winter hardiness, better water use efficiency, pest resistance and no anti-quality factors. Concerted efforts are required to bring together maximum of these characteristic features into the alfalfa plant.     

Advances in cereal genomics and applications in crop breeding

Recent advances in cereal genomics have made it possible to analyse the architecture of cereal genomes and their expressed components, leading to an increase in our knowledge of the genes that are linked to key agronomically important traits. These studies have used molecular genetic mapping of quantitative trait loci (QTL) of several complex traits that are important in breeding. The identification and molecular cloning of genes underlying QTLs offers the possibility to examine the naturally occurring allelic variation for respective complex traits. Novel alleles, identified by functional genomics or haplotype analysis, can enrich the genetic basis of cultivated crops to improve productivity. Advances made in cereal genomics research in recent years thus offer the opportunities to enhance the prediction of phenotypes from genotypes for cereal breeding.     

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.     

Bioinformatics toolbox for narrowing rodent quantitative trait loci

Quantitative trait locus (QTL) analysis is a powerful method for localizing disease genes, but identifying the causal gene remains difficult. Rodent models of disease facilitate QTL gene identification, and causal genes underlying rodent QTL are often associated with the corresponding human diseases. Recently developed bioinformatics methods, including comparative genomics, combined cross analysis, interval-specific and genome-wide haplotype analysis, followed by sequence and expression analysis, each facilitated by public databases, provide new tools for narrowing rodent QTLs. Here we discuss each tool, illustrate its application and generate a bioinformatics strategy for narrowing QTLs. Combining these bioinformatics tools with classical experimental methods should accelerate QTL gene identification.     

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Reverse engineering gene networks to identify key drivers of complex disease phenotypes

Diseases such as obesity, diabetes, and atherosclerosis result from multiple genetic and environmental factors, and importantly, interactions between genetic and environmental factors. Identifying susceptibility genes for these diseases using genetic and genomic technologies is accelerating, and the expectation over the next several years is that a number of genes will be identified for common diseases. However, the identification of single genes for disease has limited utility, given that diseases do not originate in complex systems from single gene changes. Further, the identification of single genes for disease may not lead directly to genes that can be targeted for therapeutic intervention. Therefore, uncovering single genes for disease in isolation of the broader network of molecular interactions in which they operate will generally limit the overall utility of such discoveries. Several integrative approaches have been developed and applied to reconstructing networks. Here we review several of these approaches that involve integrating genetic, expression, and clinical data to elucidate networks underlying disease. Networks reconstructed from these data provide a richer context in which to interpret associations between genes and disease. Therefore, these networks can lead to defining pathways underlying disease more objectively and to identifying biomarkers and more-robust points for therapeutic intervention.     

From phenotype to gene: Detecting disease-specific gene functional modules via a text-based human disease phenotype network construction

Currently, some efforts have been devoted to the text analysis of disease phenotype data, and their results indicated that similar disease phenotypes arise from functionally related genes. These related genes work together, as a functional module, to perform a desired cellular function. We constructed a text-based human disease phenotype network and detected 82 disease-specific gene functional modules, each corresponding to a different phenotype cluster, by means of graph-based clustering and mapping from disease phenotype to gene. Since genes in such gene functional modules are functionally related and cause clinically similar diseases, they may share common genetic origin of their associated disease phenotypes. We believe the investigation may facilitate the ultimate understanding of the common pathophysiologic basis of associated diseases.     

Decoding cis-regulatory systems in ascidians

Ascidians, or sea squirts, are lower chordates, and share basic gene repertoires and many characteristics, both developmental and physiological, with vertebrates. Therefore, decoding cis-regulatory systems in ascidians will contribute toward elucidating the genetic regulatory systems underlying the developmental and physiological processes of vertebrates. cis-Regulatory DNAs can also be used for tissue-specific genetic manipulation, a powerful tool for studying ascidian development and physiology. Because the ascidian genome is compact compared with vertebrate genomes, both intergenic regions and introns are relatively small in ascidians. Short upstream intergenic regions contain a complete set of cis-regulatory elements for spatially regulated expression of a majority of ascidian genes. These features of the ascidian genome are a great advantage in identifying cis-regulatory sequences and in analyzing their functions. Function of cis-regulatory DNAs has been analyzed for a number of tissue-specific and developmentally regulated genes of ascidians by introducing promoter-reporter fusion constructs into ascidian embryos. The availability of the whole genome sequences of the two Ciona species, Ciona intestinalis and Ciona savignyi, facilitates comparative genomics approaches to identify cis-regulatory DNAs. Recent studies demonstrate that computational methods can help identify cis-regulatory elements in the ascidian genome. This review presents a comprehensive list of ascidian genes whose cis-regulatory regions have been subjected to functional analysis, and highlights the recent advances in bioinformatics and comparative genomics approaches to cis-regulatory systems in ascidians.     

Genomic approaches to plant stress tolerance

Past efforts to improve plant tolerance to drought, high salinity and low-temperature through breeding and genetic engineering have had limited success owing to the genetic complexity of stress responses. Progress is now anticipated through comparative genomics studies of an evolutionarily diverse set of model organisms, and through the use of techniques such as high-throughput analysis of expressed sequence tags, large-scale parallel analysis of gene expression, targeted or random mutagenesis, and gain-of-function or mutant complementation. The discovery of novel genes, determination of their expression patterns in response to abiotic stress, and an improved understanding of their roles in stress adaptation (obtained by the use of functional genomics) will provide the basis of effective engineering strategies leading to greater stress tolerance.     

植物逆境胁迫抗性的功能基因组研究策略

植物对逆境胁迫抗性的功能基因组研究主要是寻找胁迫抗性位点在相关物种基因组中的保守位置,发现胁迫反应中的高度保守序列,确定植物胁迫反应的调控机理,进而得到植物对逆境胁迫抗性的关键代谢途径和其中的关键调控因子,为进一步选择用于改良植物对逆境胁迫抗性的关键基因奠定基础。本文从主要模式植物(苔藓类植物、复苏植物、盐土植物和甜土植物)、主要技术策略(基因的差异表达分析、基因表达序列标签、cDNA芯片技术。基因表达序列分析和基因敲除和突变体筛选分析)和生物信息学方法(数据分析的生物信息学方法设计到序列比较、比较基因组学、电子克隆)等三个方面对国内外植物逆境胁迫抗性的功能基因组研究策略作了全面综述。     

Disease-Aging Network Reveals Significant Roles of Aging Genes in Connecting Genetic Diseases

One of the challenging problems in biology and medicine is exploring the underlying mechanisms of genetic diseases. Recent studies suggest that the relationship between genetic diseases and the aging process is important in understanding the molecular mechanisms of complex diseases. Although some intricate associations have been investigated for a long time, the studies are still in their early stages. In this paper, we construct a human disease-aging network to study the relationship among aging genes and genetic disease genes. Specifically, we integrate human protein-protein interactions (PPIs), disease-gene associations, aging-gene associations, and physiological system–based genetic disease classification information in a single graph-theoretic framework and find that (1) human disease genes are much closer to aging genes than expected by chance; and (2) diseases can be categorized into two types according to their relationships with aging. Type I diseases have their genes significantly close to aging genes, while type II diseases do not. Furthermore, we examine the topological characters of the disease-aging network from a systems perspective. Theoretical results reveal that the genes of type I diseases are in a central position of a PPI network while type II are not; (3) more importantly, we define an asymmetric closeness based on the PPI network to describe relationships between diseases, and find that aging genes make a significant contribution to associations among diseases, especially among type I diseases. In conclusion, the network-based study provides not only evidence for the intricate relationship between the aging process and genetic diseases, but also biological implications for prying into the nature of human diseases.     

Identifying causal genes and dysregulated pathways in complex diseases

In complex diseases, various combinations of genomic perturbations often lead to the same phenotype. On a molecular level, combinations of genomic perturbations are assumed to dys-regulate the same cellular pathways. Such a pathway-centric perspective is fundamental to understanding the mechanisms of complex diseases and the identification of potential drug targets. In order to provide an integrated perspective on complex disease mechanisms, we developed a novel computational method to simultaneously identify causal genes and dys-regulated pathways. First, we identified a representative set of genes that are differentially expressed in cancer compared to non-tumor control cases. Assuming that disease-associated gene expression changes are caused by genomic alterations, we determined potential paths from such genomic causes to target genes through a network of molecular interactions. Applying our method to sets of genomic alterations and gene expression profiles of 158 Glioblastoma multiforme (GBM) patients we uncovered candidate causal genes and causal paths that are potentially responsible for the altered expression of disease genes. We discovered a set of putative causal genes that potentially play a role in the disease. Combining an expression Quantitative Trait Loci (eQTL) analysis with pathway information, our approach allowed us not only to identify potential causal genes but also to find intermediate nodes and pathways mediating the information flow between causal and target genes. Our results indicate that different genomic perturbations indeed dys-regulate the same functional pathways, supporting a pathway-centric perspective of cancer. While copy number alterations and gene expression data of glioblastoma patients provided opportunities to test our approach, our method can be applied to any disease system where genetic variations play a fundamental causal role.     

Ecological genomics: understanding gene and genome function in the natural environment

The field of ecological genomics seeks to understand the genetic mechanisms underlying responses of organisms to their natural environments. This is being achieved through the application of functional genomic approaches to identify and characterize genes with ecological and evolutionary relevance. By its very nature, ecological genomics is an interdisciplinary field. In this review, we consider the significance of this new area of study from both an ecological and genomic perspective using examples from the recent literature. We submit that by considering more fully an ecological context, researchers may gain additional insights into the underlying genetic basis of ecologically relevant phenotypic variation. Likewise, genomic approaches are beginning to offer new insights into higher-level biological phenomena that previously occupied the realm of ecological investigation only. We discuss various approaches that are likely to be useful in ecological genomic studies and offer thoughts on where this field is headed in the future.