Editorial: Taking genetics seriously

Since 2007, consumer genomics companies have marketed personal genome scanning services to assess users' genetic predispositions to a variety of complex diseases and traits. This study investigates early users' reasons for utilizing personal genome services, their evaluation of the technology, how they interpret the results, and how they incorporate the results into health-related decision-making. The analysis contextualizes early users' relationships to the technology, the knowledge generated by it, and how it mediates their relationship to their own health and to biomedicine more broadly. The results reveal that early users approach personal genome scanning with both optimism for genomic research and skepticism about the technology's current capabilities, which runs contrary to concerns that consumers may be ill equipped to interpret and understand genome scan results. These findings provide important qualitative insight into early users' conceptualizations of personal genomic risk assessment and illuminate their involvement in configuring this technology in the making.     

Gatekeepers or Intermediaries? The Role of Clinicians in Commercial Genomic Testing

Background

Many commentators on “direct-to-consumer” genetic risk information have raised concerns that giving results to individuals with insufficient knowledge and training in genomics may harm consumers, the health care system, and society. In response, several commercial laboratories offering genomic risk profiling have shifted to more traditional “direct-to-provider” (DTP) marketing strategies, repositioning clinicians as the intended recipients of advertising of laboratory services and as gatekeepers to personal genomic information. Increasing popularity of next generation sequencing puts a premium on ensuring that those who are charged with interpreting, translating, communicating and managing commercial genomic risk information are appropriately equipped for the job. To shed light on their gatekeeping role, we conducted a study to assess how and why early clinical users of genomic risk assessment incorporate these tools in their clinical practices and how they interpret genomic information for their patients.

Methods and Findings

We conducted qualitative in-depth interviews with 18 clinicians providing genomic risk assessment services to their patients in partnership with DNA Direct and Navigenics. Our findings suggest that clinicians learned most of what they knew about genomics directly from the commercial laboratories. Clinicians rely on the expertise of the commercial laboratories without the ability to critically evaluate the knowledge or assess risks.

Conclusions

DTP service delivery model cannot guarantee that providers will have adequate expertise or sound clinical judgment. Even if clinicians want greater genomic knowledge, the current market structure is unlikely to build the independent substantive expertise of clinicians, but rather promote its continued outsourcing. Because commercial laboratories have the most “skin in the game” financially, genetics professionals and policymakers should scrutinize the scientific validity and clinical soundness of the process by which these laboratories interpret their findings to assess whether self-interested commercial sources are the most appropriate entities for gate-keeping genomic interpretation.     

Anticipation of Personal Genomics Data Enhances Interest and Learning Environment in Genomics and Molecular Biology Undergraduate Courses

An important discussion at colleges is centered on determining more effective models for teaching undergraduates. As personalized genomics has become more common, we hypothesized it could be a valuable tool to make science education more hands on, personal, and engaging for college undergraduates. We hypothesized that providing students with personal genome testing kits would enhance the learning experience of students in two undergraduate courses at Brigham Young University: Advanced Molecular Biology and Genomics. These courses have an emphasis on personal genomics the last two weeks of the semester. Students taking these courses were given the option to receive personal genomics kits in 2014, whereas in 2015 they were not. Students sent their personal genomics samples in on their own and received the data after the course ended. We surveyed students in these courses before and after the two-week emphasis on personal genomics to collect data on whether anticipation of obtaining their own personal genomic data impacted undergraduate student learning. We also tested to see if specific personal genomic assignments improved the learning experience by analyzing the data from the undergraduate students who completed both the pre- and post-course surveys. Anticipation of personal genomic data significantly enhanced student interest and the learning environment based on the time students spent researching personal genomic material and their self-reported attitudes compared to those who did not anticipate getting their own data. Personal genomics homework assignments significantly enhanced the undergraduate student interest and learning based on the same criteria and a personal genomics quiz. We found that for the undergraduate students in both molecular biology and genomics courses, incorporation of personal genomic testing can be an effective educational tool in undergraduate science education.     

Genomic determinants of protein folding thermodynamics in prokaryotic organisms

Here we investigate how thermodynamic properties of orthologous proteins are influenced by the genomic environment in which they evolve. We performed a comparative computational study of 21 protein families in 73 prokaryotic species and obtained the following main results. (i) Protein stability with respect to the unfolded state and with respect to misfolding are anticorrelated. There appears to be a trade-off between these two properties, which cannot be optimized simultaneously. (ii) Folding thermodynamic parameters are strongly correlated with two genomic features, genome size and G+C composition. In particular, the normalized energy gap, an indicator of folding efficiency in statistical mechanical models of protein folding, is smaller in proteins of organisms with a small genome size and a compositional bias towards A+T. Such genomic features are characteristic for bacteria with an intracellular lifestyle. We interpret these correlations in light of mutation pressure and natural selection. A mutational bias toward A+T at the DNA level translates into a mutational bias toward more hydrophobic (and in general more interactive) proteins, a consequence of the structure of the genetic code. Increased hydrophobicity renders proteins more stable against unfolding but less stable against misfolding. Proteins with high hydrophobicity and low stability against misfolding occur in organisms with reduced genomes, like obligate intracellular bacteria. We argue that they are fixed because these organisms experience weaker purifying selection due to their small effective population sizes. This interpretation is supported by the observation of a high expression level of chaperones in these bacteria. Our results indicate that the mutational spectrum of a genome and the strength of selection significantly influence protein folding thermodynamics.     

Genomics and privacy: implications of the new reality of closed data for the field

Open source and open data have been driving forces in bioinformatics in the past. However, privacy concerns may soon change the landscape, limiting future access to important data sets, including personal genomics data. Here we survey this situation in some detail, describing, in particular, how the large scale of the data from personal genomic sequencing makes it especially hard to share data, exacerbating the privacy problem. We also go over various aspects of genomic privacy: first, there is basic identifiability of subjects having their genome sequenced. However, even for individuals who have consented to be identified, there is the prospect of very detailed future characterization of their genotype, which, unanticipated at the time of their consent, may be more personal and invasive than the release of their medical records. We go over various computational strategies for dealing with the issue of genomic privacy. One can "slice" and reformat datasets to allow them to be partially shared while securing the most private variants. This is particularly applicable to functional genomics information, which can be largely processed without variant information. For handling the most private data there are a number of legal and technological approaches-for example, modifying the informed consent procedure to acknowledge that privacy cannot be guaranteed, and/or employing a secure cloud computing environment. Cloud computing in particular may allow access to the data in a more controlled fashion than the current practice of downloading and computing on large datasets. Furthermore, it may be particularly advantageous for small labs, given that the burden of many privacy issues falls disproportionately on them in comparison to large corporations and genome centers. Finally, we discuss how education of future genetics researchers will be important, with curriculums emphasizing privacy and data security. However, teaching personal genomics with identifiable subjects in the university setting will, in turn, create additional privacy issues and social conundrums.     

The Path to Enlightenment： Making Sense of Genomic and Proteomic Information

Whereas genomics describes the study of genome, mainly represented by its gene expression on the DNA or RNA level, the term proteomics denotes the study of the proteome, which is the protein complement encoded by the genome. In recent years, the number of proteomic experiments increased tremendously. While all fields of proteomics have made major technological advances, the biggest step was seen in bioinformatics. Biological information management relies on sequence and structure databases and powerful software tools to translate experimental results into meaningful biological hypotheses and answers. In this resource article, I provide a collection of databases and software available on the Internet that are useful to interpret genomic and proteomic data. The article is a toolbox for researchers who have genomic or proteomic datasets and need to put their findings into a biological context.     

Predicting biological networks from genomic data

Continuing improvements in DNA sequencing technologies are providing us with vast amounts of genomic data from an ever-widening range of organisms. The resulting challenge for bioinformatics is to interpret this deluge of data and place it back into its biological context. Biological networks provide a conceptual framework with which we can describe part of this context, namely the different interactions that occur between the molecular components of a cell. Here, we review the computational methods available to predict biological networks from genomic sequence data and discuss how they relate to high-throughput experimental methods.     

LTR retrotransposons and flowering plant genome size: emergence of the increase/decrease model

Long Terminal Repeat (LTR) retrotransposons are ubiquitous components of plant genomes. Because of their copy-and-paste mode of transposition, these elements tend to increase their copy number while they are active. In addition, it is now well established that the differences in genome size observed in the plant kingdom are accompanied by variations in LTR retrotransposon content, suggesting that LTR retrotransposons might be important players in the evolution of plant genome size, along with polyploidy. The recent availability of large genomic sequences for many crop species has made it possible to examine in detail how LTR retrotransposons actually drive genomic changes in plants. In the present paper, we provide a review of the recent publications that have contributed to the knowledge of plant LTR retrotransposons, as structural components of the genomes, as well as from an evolutionary genomic perspective. These studies have shown that plant genomes undergo genome size increases through bursts of retrotransposition, while there is a counteracting process that tends to eliminate the transposed copies from the genomes. This process involves recombination mechanisms that occur either between the LTRs of the elements, leading to the formation of solo-LTRs, or between direct repeats anywhere in the sequence of the element, leading to internal deletions. All these studies have led to the emergence of a new model for plant genome evolution that takes into account both genome size increases (through retrotransposition) and decreases (through solo-LTR and deletion formation). In the conclusion, we discuss this new model and present the future prospects in the study of plant genome evolution in relation to the activity of transposable elements.     

From sequence to function: using RNAi to elucidate mechanisms of human disease

RNA interference (RNAi) has emerged as one of the most powerful tools for functionally characterizing large sets of genomic data. Capabilities of RNAi place it at the forefront of high-throughput screens, which are able to span the human genome in search of novel targets. Although RNAi screens have been used to elucidate pathway components and discover potential drug targets in lower organisms, including Caenorhabditis elegans and Drosophila, only recently has the technology been advanced to a state in which large-scale screens can be performed in mammalian cells. In this review, we will evaluate the major advancements in the field of mammalian RNAi, specifically in terms of high-throughput assays. Crucial points of experimental design will be highlighted, as well as suggestions as to how to interpret and follow-up on potential cell death targets. Finally, we assess the prospective applications of high-throughput screens, the data they are capable of generating, and the potential for this technique to further our understanding of human disease.     

Recombinase technology: applications and possibilities

The use of recombinases for genomic engineering is no longer a new technology. In fact, this technology has entered its third decade since the initial discovery that recombinases function in heterologous systems (Sauer in Mol Cell Biol 7(6):2087–2096, 1987). The random insertion of a transgene into a plant genome by traditional methods generates unpredictable expression patterns. This feature of transgenesis makes screening for functional lines with predictable expression labor intensive and time consuming. Furthermore, an antibiotic resistance gene is often left in the final product and the potential escape of such resistance markers into the environment and their potential consumption raises consumer concern. The use of site-specific recombination technology in plant genome manipulation has been demonstrated to effectively resolve complex transgene insertions to single copy, remove unwanted DNA, and precisely insert DNA into known genomic target sites. Recombinases have also been demonstrated capable of site-specific recombination within non-nuclear targets, such as the plastid genome of tobacco. Here, we review multiple uses of site-specific recombination and their application toward plant genomic engineering. We also provide alternative strategies for the combined use of multiple site-specific recombinase systems for genome engineering to precisely insert transgenes into a pre-determined locus, and removal of unwanted selectable marker genes.     

Aging and genetic instability in yeast

There is a striking link between increasing age and the incidence of cancer in humans. One of the hallmarks of cancer, genomic instability, has been observed in all types of organisms. In the yeast Saccharomyces cerevisiae, it was recently discovered that during the replicative lifespan, aging cells switch to a state of high genomic instability that persists until they die. In considering these and other recent results, we suggest that accumulation of oxidatively damaged protein in aging cells results in the loss of function of gene products critical for maintaining genome integrity. Determining the identity of these proteins and how they become damaged represents a new challenge for understanding the relationship between age and genetic instability.     

Long Span DNA Paired-End-Tag (DNA-PET) Sequencing Strategy for the Interrogation of Genomic Structural Mutations and Fusion-Point-Guided Reconstruction of Amplicons

Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. While genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs, the current application of PET sequencing with short insert size DNA can be insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We employed a recently developed procedure to generate PET sequencing data using large DNA inserts of 10–20 kb and compared their characteristics with short insert (1 kb) libraries for their ability to identify SVs. Our results suggest that although short insert libraries bear an advantage in identifying small deletions, they do not provide significantly better breakpoint resolution. In contrast, large inserts are superior to short inserts in providing higher physical genome coverage for the same sequencing cost and achieve greater sensitivity, in practice, for the identification of several classes of SVs, such as copy number neutral and complex events. Furthermore, our results confirm that large insert libraries allow for the identification of SVs within repetitive sequences, which cannot be spanned by short inserts. This provides a key advantage in studying rearrangements in cancer, and we show how it can be used in a fusion-point-guided-concatenation algorithm to study focally amplified regions in cancer.     

From lab to lifestyle: translating genomics into healthcare practices

Contemporary genomic sciences are uncovering genetic factors implicated in common complex diseases such as type 2 diabetes. It is suggested that such knowledge could be developed into tests for susceptibility to the disease that would allow preventive action through lifestyle modification. This paper presents research on responses to this suggestion by genetic specialists, diabetologists, and general practitioners – three groups of health professionals whose practices are likely to be affected by such testing services. It shows how the responses of the different groups are related to the professional culture of practice. I suggest that the perspective a profession has of its potential role in relation to the emerging technology can illuminate the early stages of co-constitution by which the technology that is used and the community of practice that use it are mutually reshaped.     

Meet the neighbours: tools to dissect nuclear structure and function

The eukaryotic cell nucleus displays a high degree of spatial organization, with discrete functional subcompartments that provide microenvironments where specialized processes take place. Concordantly, the genome also adopts defined conformations that, in part, enable specific genomic regions to interface with these functional centers. Yet the roles of many subcompartments and the genomic regions that contact them have not been explored fully. More fundamentally, it is not entirely clear how genome organization impacts function, and vice versa. The past decade has witnessed the development of a new breed of methods that are capable of assessing the spatial organization of the genome. These stand to further our understanding of the relationship between genome structure and function, and potentially assign function to various nuclear subcompartments. Here, we review the principal techniques used for analyzing genomic interactions, the functional insights they have afforded and discuss the outlook for future advances in nuclear structure and function dynamics.     

Genome-wide identification of novel genomic islands that contribute to Salmonella virulence in mouse systemic infection

Salmonella pathogenicity islands are inserted into the genome by horizontal gene transfer and are required for expression of full virulence. Here, we performed tRNA scanning of the genome of Salmonella enterica serovar Typhimurium and compared it with that of nonpathogenic Escherichia coli in order to identify genomic islands that contribute to Salmonella virulence. Using deletion analysis, we identified four genomic islands that are required for virulence in the mouse infection model. One of the newly identified pathogenicity islands was the pheV- tRNA-located genomic island, which is comprised of 26 126 bp, and encodes 22 putative genes, including STM3117–STM3138. We also showed that the pheV tRNA-located genomic island is widely distributed among different nontyphoid Salmonella serovars. Furthermore, genes including STM3118–STM3121 were identified as novel virulence-associated genes within the pheV- tRNA-located genomic island. These results indicate that a Salmonella -specific pheV- tRNA genomic island is involved in Salmonella pathogenesis among the nontyphoid Salmonella serovars.     

GI-POP: A combinational annotation and genomic island prediction pipeline for ongoing microbial genome projects

Sequencing of microbial genomes is important because of microbial-carrying antibiotic and pathogenetic activities. However, even with the help of new assembling software, finishing a whole genome is a time-consuming task. In most bacteria, pathogenetic or antibiotic genes are carried in genomic islands. Therefore, a quick genomic island (GI) prediction method is useful for ongoing sequencing genomes. In this work, we built a Web server called GI-POP (http://gipop.life.nthu.edu.tw) which integrates a sequence assembling tool, a functional annotation pipeline, and a high-performance GI predicting module, in a support vector machine (SVM)-based method called genomic island genomic profile scanning (GI-GPS). The draft genomes of the ongoing genome projects in contigs or scaffolds can be submitted to our Web server, and it provides the functional annotation and highly probable GI-predicting results. GI-POP is a comprehensive annotation Web server designed for ongoing genome project analysis. Researchers can perform annotation and obtain pre-analytic information include possible GIs, coding/non-coding sequences and functional analysis from their draft genomes. This pre-analytic system can provide useful information for finishing a genome sequencing project.