Human genetics: Dr Watson's base pairs

Dietary Phytoestrogens and Their Metabolites as Epigenetic Modulators with Impact on Human Health

The impact of dietary phytoestrogens on human health has been a topic of continuous debate since their discovery. Nowadays, based on their presumptive beneficial effects, the amount of phytoestrogens consumed in the daily diet has increased considerably worldwide. Thus, there is a growing need for scientific data regarding their mode of action in the human body. Recently, new insights of phytoestrogens’ bioavailability and metabolism have demonstrated an inter-and intra-population heterogeneity of final metabolites’ production. In addition, the phytoestrogens may have the ability to modulate epigenetic mechanisms that control gene expression. This review highlights the complexity and particularity of the metabolism of each class of phytoestrogens, pointing out the diversity of their bioactive gut metabolites. Futhermore, it presents emerging scientific data which suggest that, among well-known genistein and resveratrol, other phytoestrogens and their gut metabolites can act as epigenetic modulators with a possible impact on human health. The interconnection of dietary phytoestrogens’ consumption with gut microbiota composition, epigenome and related preventive mechanisms is discussed. The current challenges and future perspectives in designing relevant research directions to explore the potential health benefits of dietary phytoestrogens are also explored.

Oligogenic Inheritance Underlying Incomplete Penetrance of PROKR2 Mutations in Hypogonadotropic Hypogonadism

The role of the prokineticin 2 pathway in human reproduction, olfactory bulb morphogenesis, and gonadotropin-releasing hormone secretion is well established. Recent studies have highlighted the implication of di/oligogenic inheritance in this disorder. In the present study, we aimed to identify the genetic mechanisms that could explain incomplete penetrance in hypogonadotropic hypogonadism (HH). This study involved two unrelated Tunisian patients with HH, which was triggered by identifying a homozygous p.(Pro290Ser) mutation in the PROKR2 gene in a girl (HH1) with Kallmann syndrome (KS). The functional effect of this variant has previously been well demonstrated. Unexpectedly, her unaffected father (HH1P) and brother (HH1F) also carried this genetic variation at a homozygous state. In the second family, we identified a heterozygous p.(Lys205del) mutation in PROKR2, both in a male patient with normosmic idiopathic IHH (HH12) and his asymptomatic mother. Whole-exome sequencing in the three HH1 family members allowed the identification of additional variants in the prioritized genes. We then carried out digenic combination predictions using the oligogenic resource for variant analysis (ORVAL) software. For HH1, we found the highest number of disease-causing variant pairs. Notably, a CCDC141 variant (c.2803C > T) was involved in 18 pathogenic digenic combinations. The CCDC141 variant acts in an autosomal recessive inheritance mode, based on the digenic effect prediction data. For the second patient (HH12), prediction by ORVAL allowed the identification of an interesting pathogenic digenic combination between DUSP6 and SEMA7A genes, predicted as “dual molecular diagnosis.” The SEMA7A variant p.(Glu436Lys) is novel and predicted as a VUS by Varsome. Sanger validation revealed the absence of this variant in the healthy mother. We hypothesize that disease expression in HH12 could be induced by the digenic transmission of the SEMA7A and DUSP6 variants or a monogenic inheritance involving only the SEMA7A VUS if further functional assays allow its reclassification into pathogenic. Our findings confirm that homozygous loss-of-function genetic variations are insufficient to cause KS, and that oligogenism is most likely the main transmission mode involved in Congenital Hypogonadotropic Hypogonadism.

Toward the single-hour high-quality genome

Today, resequencing of a human genome can be performed in approximately a week using a single instrument. Thanks to a steady logarithmic rate of increase in performance for DNA sequencing platforms over the past seven years, DNA sequencing is one of the fastest developing technology fields. As the process becomes faster, it opens up possibilities within health care, diagnostics, and entirely new fields of research. Immediate genetic characterization of contagious outbreaks has been exemplified, and with such applications for the direct benefit of human health, expectations of future sensitive, rapid, high-throughput, and cost-effective technologies are steadily growing. Simultaneously, some of the limitations of a rapidly growing field have become apparent, and questions regarding the quality of some of the data deposited into databases have been raised. A human genome sequenced in only an hour is likely to become a reality in the future, but its definition may not be as certain.

Application of high-throughput DNA sequencing in phytopathology

The new sequencing technologies are already making a big impact in academic research on medically important microbes and may soon revolutionize diagnostics, epidemiology, and infection control. Plant pathology also stands to gain from exploiting these opportunities. This manuscript reviews some applications of these high-throughput sequencing methods that are relevant to phytopathology, with emphasis on the associated computational and bioinformatics challenges and their solutions. Second-generation sequencing technologies have recently been exploited in genomics of both prokaryotic and eukaryotic plant pathogens. They are also proving to be useful in diagnostics, especially with respect to viruses.

Measuring consequences of protein misfolding and cellular stress using OMICS techniques

The ambition to measure all or at least a significant fraction of relevant molecules in a cell culture or tissue sample has reached possible realization with the development of the so-called OMICS technologies. We will here briefly review current technologies and give examples of their applications in investigations related to protein misfolding diseases. We will primarily cover the classical OMICS categories GENOMICS, TRANSCRIPTOMICS, METABOLOMICS, and with some more detail PROTEOMICS. These techniques are in most cases performed by dedicated core facilities or commercial services. We will give an assessment of uses as well as limitations of these technologies supported by examples of their application in research related to protein misfolding. We will further briefly discuss genome-wide RNA interference and finally touch on bioinformatics, because the huge amounts of data typically collected with OMICS techniques requires the application of specific software to handle and stratify the data sets. Today, most biologists using OMICS-techniques must, at least in part, be able to analyze their own data using user-friendly web-based tools.

Whole genome scanning: resolving clinical diagnosis and management amidst complex data

Momentum around the era of genomic medicine is building, and with it, anticipation of the benefits that whole genome analysis (personalized or individualized genomics) will bring for the provision of health care. These technologies have the potential to revolutionize genetic diagnosis; however, the expansive data generated can lead to complex or unexpected findings, sometimes complicating clinical utility and patient benefit. Here, we use our experience with whole genome scanning microarrays, an early instance of whole genome analysis already in clinical use, to highlight fundamental challenges raised by these technologies and to discuss their medical, ethical, legal and social implications. We discuss issues that physicians and healthcare professionals will face, in particular, as the resolution of testing further increases toward full genome sequence determination. We emphasize that addressing these issues now, and starting to evolve our healthcare systems in response, will be pivotal in avoiding harms and realizing the promise of these new technologies.

Keeping up with the next generation: massively parallel sequencing in clinical diagnostics

The speed, accuracy, efficiency, and cost-effectiveness of DNA sequencing have been improving continuously since the initial derivation of the technique in the mid-1970s. With the advent of massively parallel sequencing technologies, DNA sequencing costs have been dramatically reduced. No longer is it unthinkable to sequence hundreds or even thousands of genes in a single individual with a suspected genetic disease or complex disease predisposition. Along with the benefits offered by these technologies come a number of challenges that must be addressed before wide-scale sequencing becomes accepted medical practice. Molecular diagnosticians will need to become comfortable with, and gain confidence in, these new platforms, which are based on radically different technologies compared to the standard DNA sequencers in routine use today. Experience will determine whether these instruments are best applied to sequencing versus resequencing. Perhaps most importantly, along with increasing read lengths inevitably comes increased ascertainment of novel sequence variants of uncertain clinical significance, the postanalytical aspects of which could bog down the entire field. But despite these obstacles, and as a direct result of the promises these sequencing advances present, it will likely not be long before next-generation sequencing begins to make an impact in molecular medicine. In this review, technical issues are discussed, in addition to the practical considerations that will need to be addressed as advances push toward personal genome sequencing.

Cytomics and nanobioengineering

The finding that an individual's genome differs as much as by many million variants from that of the human reference assembly diminished the great enthusiasm that every disease could be predicted based on nucleotide polymorphisms. Even individual cells of an organ may be specifically equipped to perform specific tasks and that the information of individual cells in a cell system is key information to understand function or dysfunction. Therefore, cytomics received great attention during the last years as it allows to quantitatively and qualitatively analyzing great number of individual cells, cell constituents, and of their intracellular and functional interactions in a cellular system and also giving the concept of analysis of these data.Exhaustive data extraction from multiparametric assays and multiple tests are the prerequisite for prediction of drug toxicity. Cytomics, as novel approach for unsupervised data analysis give a chance to find the most predictive parameters, which describe best the toxicity of a chemical. Cytomics is intrinsically connected to drug development and drug discovery.Focused on small structures, nanobioengineering is the ideal partner of cytomics, the systems biological discipline for cell population analysis. Realizing the idea "from the molecule to the patient" develops and offers chemical compounds, proteins, and other biomolecules, cells as well as tissues as instruments and products for a wide variety of biotechnological and biomedical applications.The integrative nanobioengineering combining different disciplines of nanotechnology will promote the development of innovative therapies and diagnostic methods. It can improve the precision of the measurements with focus on single cell analysis. By nanobioengineering and whole body imaging techniques, cytomics covers the field from molecules through bacterial cells, eukaryotic tissues, and organs to small animal live analysis. Toxicological testing and medical drug development are currently strongly broadening. It harbors the promise to substantially impact on various fields of biomedicine, drug discovery, and predictive medicine.As the number of scientific data is rising exponentially, new data analysis tools and strategies like cytomics and nanobioengineering take a lead and get closer to application. Bionanoengineering may strongly support the quantitative data supply, thus strengthening the rational for cytomics approach.