果蝇微小RNA及其在衰老过程中的作用

微小RNA（microRNA, miRNA）是一类长度在22 nt左右的内源非编码小RNA,广泛存在于动物、植物、病毒等多种有机体中,是机体正常衰老与疾病的重要调控因子。本文对果蝇不同生长时期miRNA的表达模式、主要衰老相关信号通路以及与衰老相关的miRNA进行了综述。在果蝇的不同发育时期均有特定的miRNA发挥重要作用,其表达模式与功能相关;miRNA参与了主要衰老分子信号通路的调控,如胰岛素/胰岛素样生长因子（IIS）通路和雷帕霉素靶蛋白（TOR）通路。研究表明,miRNA通过调控衰老相关信号通路中的靶基因,进而促进或延缓果蝇衰老,如miR-34, miR-8, miR-14, miR let7和miR-277等。因此,研究参与衰老调控的miRNA,为阐明衰老机制及抗衰老药物的设计奠定了基础。     

Genes encoding longevity: from model organisms to humans

Ample evidence from model organisms has indicated that subtle variation in genes can dramatically influence lifespan. The key genes and molecular pathways that have been identified so far encode for metabolism, maintenance and repair mechanisms that minimize age-related accumulation of permanent damage. Here, we describe the evolutionary conserved genes that are involved in lifespan regulation of model organisms and humans, and explore the reasons of discrepancies that exist between the results found in the various species. In general, the accumulated data have revealed that when moving up the evolutionary ladder, together with an increase of genome complexity, the impact of candidate genes on lifespan becomes smaller. The presence of genetic networks makes it more likely to expect impact of variation in several interacting genes to affect lifespan in humans. Extrapolation of findings from experimental models to humans is further complicated as phenotypes are critically dependent on the setting in which genes are expressed, while laboratory conditions and modern environments are markedly dissimilar. Finally, currently used methodologies may have only little power and validity to reveal genetic variation in the population. In conclusion, although the study of model organisms has revealed potential candidate genetic mechanisms determining aging and lifespan, to what extent they explain variation in human populations is still uncertain.     

The diversity of aging models

Most of the signalling pathways involved in aging regulation have been recently found well conserved at various levels throughout the evolution. Taking this into account, a diversity of model organisms, including worms, rodents, and lemurs as well, allows to address different questions: how to understand the interactions between genetic and environmental factors while challenging theories of aging, to preserve hearing integrity, to fight against senescence of neural stem cells, or to explore brain fitness from gene expression to cognitive and social behavior? Here are the main issues that can be considered, stressing the complementarities of the models. The differentiation of aging physiological aspects from those induced by age-related pathologies will also be specified. By emphasizing recent ability of technologies to promote new aging insights, we discuss towards a better understanding of mechanisms governing aging.     

Buffering mechanisms in aging: a systems approach toward uncovering the genetic component of aging

An unrealized potential to understand the genetic basis of aging in humans, is to consider the immense survival advantage of the rare individuals who live 100 years or more. The Longevity Gene Study was initiated in 1998 at the Albert Einstein College of Medicine to investigate longevity genes in a selected population: the “oldest old” Ashkenazi Jews, 95 years of age and older, and their children. The study proved the principle that some of these subjects are endowed with longevity-promoting genotypes. Here we reason that some of the favorable genotypes act as mechanisms that buffer the deleterious effect of age-related disease genes. As a result, the frequency of deleterious genotypes may increase among individuals with extreme lifespan because their protective genotype allows disease-related genes to accumulate. Thus, studies of genotypic frequencies among different age groups can elucidate the genetic determinants and pathways responsible for longevity. Borrowing from evolutionary theory, we present arguments regarding the differential survival via buffering mechanisms and their target age-related disease genes in searching for aging and longevity genes. Using more than 1,200 subjects between the sixth and eleventh decades of life (at least 140 subjects in each group), we corroborate our hypotheses experimentally. We study 66 common allelic site polymorphism in 36 candidate genes on the basis of their phenotype. Among them we have identified a candidate-buffering mechanism and its candidate age-related disease gene target. Previously, the beneficial effect of an advantageous cholesteryl ester transfer protein (CETP-VV) genotype on lipoprotein particle size in association with decreased metabolic and cardiovascular diseases, as well as with better cognitive function, have been demonstrated. We report an additional advantageous effect of the CETP-VV (favorable) genotype in neutralizing the deleterious effects of the lipoprotein(a) (LPA) gene. Finally, using literature-based interaction discovery methods, we use the set of longevity genes, buffering genes, and their age-related target disease genes to construct the underlying subnetwork of interacting genes that is expected to be responsible for longevity. Genome wide, high-throughput hypothesis-free analyses are currently being utilized to elucidate unknown genetic pathways in many model organisms, linking observed phenotypes to their underlying genetic mechanisms. The longevity phenotype and its genetic mechanisms, such as our buffering hypothesis, are similar; thus, the experimental corroboration of our hypothesis provides a proof of concept for the utility of high-throughput methods for elucidating such mechanisms. It also provides a framework for developing strategies to prevent some age-related diseases by intervention at the appropriate level.     

Programs of Gene Expression During the Laying Down of Memory Formation as Revealed by DNA Microarrays

Many experiments in the past have demonstrated the requirement of de novo gene expression during memory formation. In contrast to the initial reductionistic view that genes relevant to learning and memory would be easily found and would provide a simple key to understand this brain function, it is becoming apparent that the genetic contribution to memory is complex. Previous approaches have been focused on individual genes or genetic pathways and failed to address the massively parallel nature of genome activities and collective behavior of the genes that ultimately control the molecular mechanisms underlying brain function. In view of the broad variety of genes and the cross talk of genetic pathways involved in this regulation, only gene expression profiles may reflect the complete behavior of regulatory pathways. In this review we illustrate how DNA microarray-based gene expression profiling may help to dissect and analyze the complex mechanisms involved in gene regulation during the acquisition and storage of memory in the mammalian brain.     

Genetic regulation of longevity and age-associated diseases through the methionine sulfoxide reductase system

Methionine sulfoxide reductase enzymes are a protective system against biological oxidative stress in aerobic organisms. Modifications to this antioxidant system have been shown to impact the lifespan of several model system organisms. In humans, methionine oxidation of critical proteins and deficiencies in the methionine sulfoxide reductase system have been linked to age-related diseases, including cancer and neurodegenerative disease. Substrates for methionine sulfoxide reductases have been reviewed multiple times, and are still an active area of discovery. In contrast, less is known about the genetic regulation of methionine sulfoxide reductases. In this review, we discuss studies on the genetic regulation of the methionine sulfoxide reductase system with relevance to longevity and age-related diseases. A better understanding of genetic regulation for methionine sulfoxide reductases may lead to new therapeutic approaches for age-related diseases in the future.     

A more efficient search strategy for aging genes based on connectivity

MOTIVATION: Many aging genes have been found from unbiased screens in model organisms. Genetic interventions promoting longevity are usually quantitative, while in many other biological fields (e.g. development) null mutations alone have been very informative. Therefore, in the case of aging the task is larger and the need for a more efficient genetic search strategy is especially strong. RESULTS: The topology of genetic and metabolic networks is organized according to a scale-free distribution, in which hubs with large numbers of links are present. We have developed a computational model of aging genes as the hubs of biological networks. The computational model shows that, after generalized damage, the function of a network with scale-free topology can be significantly restored by a limited intervention on the hubs. Analyses of data on aging genes and biological networks support the applicability of the model to biological aging. The model also might explain several of the properties of aging genes, including the high degree of conservation across different species. The model suggests that aging genes tend to have a higher number of connections and therefore supports a strategy, based on connectivity, for prioritizing what might otherwise be a random search for aging genes.     

Genetic evidence for common pathways in human age‐related diseases

Aging is the single largest risk factor for chronic disease. Studies in model organisms have identified conserved pathways that modulate aging rate and the onset and progression of multiple age‐related diseases, suggesting that common pathways of aging may influence age‐related diseases in humans as well. To determine whether there is genetic evidence supporting the notion of common pathways underlying age‐related diseases, we analyzed the genes and pathways found to be associated with five major categories of age‐related disease using a total of 410 genomewide association studies (GWAS). While only a small number of genes are shared among all five disease categories, those found in at least three of the five major age‐related disease categories are highly enriched for apoliprotein metabolism genes. We found that a more substantial number of gene ontology (GO) terms are shared among the 5 age‐related disease categories and shared GO terms include canonical aging pathways identified in model organisms, such as nutrient‐sensing signaling, translation, proteostasis, stress responses, and genome maintenance. Taking advantage of the vast amount of genetic data from the GWAS, our findings provide the first direct evidence that conserved pathways of aging simultaneously influence multiple age‐related diseases in humans as has been demonstrated in model organisms.     

Microarray challenges in ecology

Microarrays are used to measure simultaneously the amount of mRNAs transcribed from many genes. They were originally designed for gene expression profiling in relatively simple biological systems, such as cell lines and model systems under constant laboratory conditions. This poses a challenge to ecologists who increasingly want to use microarrays to unravel the genetic mechanisms underlying complex interactions among organisms and between organisms and their environment. Here, we discuss typical experimental and statistical problems that arise when analyzing genome-wide expression profiles in an ecological context. We show that experimental design and environmental confounders greatly influence the identification of candidate genes in ecological microarray studies, and that following several simple recommendations could facilitate the analysis of microarray data in ecological settings.     

Conserved signaling pathways genetically associated with longevity across the species

Advanced age is an independent risk factor for natural death and common diseases, such as cardiovascular diseases, dementia, and cancers, which are life-threatening and cause disabilities. On the other hand, individual with healthy longevity is a plausible model for successful aging. Thus, search for longevity-associated genes and pathways likely provides a unique approach to understand the genetic mechanisms underlying aging and healthspan, and emerging evidence from model organisms has highlighted the significance of genetic components in longevity. Here we reviewed the uses of model organisms including yeast, ciliate, nematode, arthropod, fish, rodent, and primate as well as human to identify the genetic determinants of longevity and discussed the genetic contributions of conserved longevity pathways, such as adrenergic system, AMPK, insulin/IGF-1, and mTOR signaling pathways.     

Gene-Expression Profiling of Experimental Autoimmune Encephalomyelitis

Experimental autoimmune encephalomyelitis (EAE) is a mouse model that serves as an experimental tool for studying the etiology, pathogenesis, as well as new therapeutic approaches of multiple sclerosis (MS). EAE is a polygenic chronic inflammatory demyelinating disease of the nervous system that involves the interaction between genetic and environmental factors. Previous studies have identified multiple quantitative trait loci (QTL) controlling different aspects of disease pathogenesis. However, progress in identifying new susceptibility genes outside the MHC locus has been slow. With the advent of new global methods for genetic analysis such as large-scale sequencing, gene expression profiling combined with classic linkage analysis and congenic and physical mapping progress is considerably accelerating. Here we review our preliminary work on the use of gene expression mapping to identify new putative genetic pathways contributing to the pathogenesis of EAE.     

A roadmap for the genetic analysis of renal aging

Several studies show evidence for the genetic basis of renal disease, which renders some individuals more prone than others to accelerated renal aging. Studying the genetics of renal aging can help us to identify genes involved in this process and to unravel the underlying pathways. First, this opinion article will give an overview of the phenotypes that can be observed in age‐related kidney disease. Accurate phenotyping is essential in performing genetic analysis. For kidney aging, this could include both functional and structural changes. Subsequently, this article reviews the studies that report on candidate genes associated with renal aging in humans and mice. Several loci or candidate genes have been found associated with kidney disease, but identification of the specific genetic variants involved has proven to be difficult. CUBN, UMOD, and SHROOM3 were identified by human GWAS as being associated with albuminuria, kidney function, and chronic kidney disease (CKD). These are promising examples of genes that could be involved in renal aging, and were further mechanistically evaluated in animal models. Eventually, we will provide approaches for performing genetic analysis. We should leverage the power of mouse models, as testing in humans is limited. Mouse and other animal models can be used to explain the underlying biological mechanisms of genes and loci identified by human GWAS. Furthermore, mouse models can be used to identify genetic variants associated with age‐associated histological changes, of which Far2, Wisp2, and Esrrg are examples. A new outbred mouse population with high genetic diversity will facilitate the identification of genes associated with renal aging by enabling high‐resolution genetic mapping while also allowing the control of environmental factors, and by enabling access to renal tissues at specific time points for histology, proteomics, and gene expression.