Current Genomics - Volume 15, Issue 4, 2014

Analyses of human evolution are fundamental to understand the current gradients of human diversity. In this concern, genetic samples collected from current populations together with archaeological data are the most important resources to study human evolution. However, they are often insufficient to properly evaluate a variety of evolutionary scenarios, leading to continuous debates and discussions. A commonly applied strategy consists of the use of computer simulations based on, as realistic as possible, evolutionary models, to evaluate alternative evolutionary scenarios through statistical correlations with the real data. Computer simulations can also be applied to estimate evolutionary parameters or to study the role of each parameter on the evolutionary process. Here we review the mainly used methods and evolutionary frameworks to perform realistic spatially explicit computer simulations of human evolution. Although we focus on human evolution, most of the methods and software we describe can also be used to study other species. We also describe the importance of considering spatially explicit models to better mimic human evolutionary scenarios based on a variety of phenomena such as range expansions, range shifts, range contractions, sex-biased dispersal, long-distance dispersal or admixtures of populations. We finally discuss future implementations to improve current spatially explicit simulations and their derived applications in human evolution.

Endogenous retroviruses (ERVs) are genomic elements that are present in a wide range of vertebrates. Although the study of ERVs has been carried out mainly in humans and model organisms, recently, domestic animals have become important, and some species have begun to be analyzed to gain further insight into ERVs. Due to the availability of complete genomes and the development of new computer tools, ERVs can now be analyzed from a genome-wide viewpoint. In addition, more experimental work is being carried out to analyze the distribution, expression and interplay of ERVs within a host genome. Cats, cattle, chicken, dogs, horses, pigs and sheep have been scrutinized in this manner, all of which are interesting species in health and economic terms. Furthermore, several studies have noted differences in the number of endogenous retroviruses and in the variability of these elements among different breeds, as well as their expression in different tissues and the effects of their locations, which, in some cases, are near genes. These findings suggest a complex, intriguing relationship between ERVs and host genomes. In this review, we summarize the most important in silico and experimental findings, discuss their implications and attempt to predict future directions for the study of these genomic elements.

Age related macular degeneration (AMD) is one of the major retinal degenerative disease of ageing whose complex genetic basis remains undeciphered. The involvement of various other factors like mitochondrial genes, cytoskeletal proteins and the role of epigenetics has been described in this review. Several population based AMD genetic studies have been carried out worldwide. Despite the increased publication of reports, clinical translation still eludes this davastating disease. We suggest models to address roadblocks in clinical translation hoping that these would be beneficial to drive AMD research towards innovative biomarkers and therapeutics Therefore, addressing the need large autopsy studies and combining it with efficient use of bioinformatic tools, statistical modeling and probing SNP-biomarker association are key to time bound resolution of this disease.

Identifying gene function in specific cells is critical for understanding the processes that make cells unique. Several different methods are available to isolate actively transcribed RNA or actively translated RNA in specific cells at a chosen time point. Cell-specific mRNA isolation can be accomplished by the expression of transgenes in cells of interest, either directly from a specific promoter or using a modular system such as Gal4/UAS or Cre/lox. All of the methods described in this review, namely thiol-labeling of RNA (TU-tagging or RABT), TRAP (translating ribosome affinity purification) and INTACT (isolation of nuclei tagged in specific cell types), allow next generation sequencing, permitting the identification of enriched gene transcripts within the specific cell-type. We describe here the general concept of each method, include examples, evaluate possible problems related to each technique, and suggest the types of questions for which each method is best suited.

Understanding the Maxam-Gilbert and Sanger sequencing as the first generation, in recent years there has been an explosion of newly-developed sequencing strategies, which are usually referred to as next generation sequencing (NGS) techniques. NGS techniques have high-throughputs and produce thousands or even millions of sequences at the same time. These sequences allow for the accurate identification of microbial taxa, including uncultivable organisms and those present in small numbers. In specific applications, NGS provides a complete inventory of all microbial operons and genes present or being expressed under different study conditions. NGS techniques are revolutionizing the field of microbial ecology and have recently been used to examine several food ecosystems. After a short introduction to the most common NGS systems and platforms, this review addresses how NGS techniques have been employed in the study of food microbiota and food fermentations, and discusses their limits and perspectives. The most important findings are reviewed, including those made in the study of the microbiota of milk, fermented dairy products, and plant-, meat- and fishderived fermented foods. The knowledge that can be gained on microbial diversity, population structure and population dynamics via the use of these technologies could be vital in improving the monitoring and manipulation of foods and fermented food products. They should also improve their safety.

MicroRNAs(miRNAs) have become the center of interest in oncology. In recent years, various studies have demonstrated that miRNAs regulate gene expression by influencing important regulatory genes and thus are responsible for causing cervical cancer. Cervical cancer being the third most diagnosed cancer among the females worldwide, is the fourth leading cause of cancer related mortality. Prophylactic human papillomavirus (HPV) vaccines and new HPV screening tests, combined with traditional Pap test screening have greatly reduced cervical cancer. Yet, thousands of women continue to be diagnosed with and die of this preventable disease annually. This has necessitated the scientists to ponder over ways of evolving new methods and chalk out novel treatment protocols/strategies. As miRNA deregulation plays a key role in malignant transformation of cervical cancer along with its targets that can be exploited for both prognostic and therapeutic strategies, we have collected and reviewed the role of miRNA in cervical cancer. A systematic search was performed using PubMed for articles that report aberrant expression of miRNA in cervical cancer. The present review provides comprehensive information for 246 differentially expressed miRNAs gathered from 51 published articles that have been implicated in cervical cancer progression. Of these, more than 40 miRNAs have been reported in the literature in several instances signifying their role in the regulation of cancer. We also identified 40 experimentally validated targets, studied the cause of miRNAs dysregulation along with its mechanism and role in different stages of cervical cancer. We also identified and analysed miRNA clusters and their expression pattern in cervical cancer. This review is expected to further enhance our understanding in this field and serve as a valuable reference resource.