Ten years of genetics and genomics: what have we achieved and where are we heading?

Mendelian or Multifactorial? Current Undergraduate Genetics Assessments Focus on Genes and Rarely Include the Environment

Undergraduate genetics courses have historically focused on simple genetic models, rather than taking a more multifactorial approach where students explore how traits are influenced by a combination of genes, the environment, and gene-by-environment interactions. While a focus on simple genetic models can provide straightforward examples to promote student learning, they do not match the current scientific understanding and can result in deterministic thinking among students. In addition, undergraduates are often interested in complex human traits that are influenced by the environment, and national curriculum standards include learning objectives that focus on multifactorial concepts. This research aims to discover to what extent multifactorial genetics is currently being assessed in undergraduate genetics courses. To address this, we analyzed over 1,000 assessment questions from a commonly used undergraduate genetics textbook; published concept assessments; and open-source, peer-reviewed curriculum materials. Our findings show that current genetics assessment questions overwhelmingly emphasize the impact of genes on phenotypes and that the effect of the environment is rarely addressed. These results indicate a need for the inclusion of more multifactorial genetics concepts, and we suggest ways to introduce them into undergraduate courses.

The road ahead in genetics and genomics

In celebration of the 20th anniversary of Nature Reviews Genetics, we asked 12 leading researchers to reflect on the key challenges and opportunities faced by the field of genetics and genomics. Keeping their particular research area in mind, they take stock of the current state of play and emphasize the work that remains to be done over the next few years so that, ultimately, the benefits of genetic and genomic research can be felt by everyone.

To celebrate the first 20 years of Nature Reviews Genetics, we asked 12 leading scientists to reflect on the key challenges and opportunities faced by the field of genetics and genomics.

Amy L. McGuire is the Leon Jaworski Professor of Biomedical Ethics and Director of the Center for Medical Ethics and Health Policy at Baylor College of Medicine. She has received numerous teaching awards at Baylor College of Medicine, was recognized by the Texas Executive Women as a Woman on the Move in 2016 and was invited to give a TedMed talk titled “There is No Genome for the Human Spirit” in 2014. In 2020, she was elected as a Hastings Center Fellow. Her research focuses on ethical and policy issues related to emerging technologies, with a particular focus on genomic research, personalized medicine and the clinical integration of novel neurotechnologies.

Stacey Gabriel is the Senior Director of the Genomics Platform at the Broad Institute since 2012 and has led platform development, execution and operation since its founding. She is Chair of Institute Scientists and serves on the institute’s executive leadership team. She is widely recognized as a leader in genomic technology and project execution. She has led the Broad’s contributions to numerous flagship projects in human genetics, including the International HapMap Project, the 1000 Genomes Project, The Cancer Genome Atlas, the National Heart, Lung, and Blood Institute’s Exome Sequencing Project and the TOPMed programme. She is Principal Investigator of the Broad’s All of Us (AoU) Genomics Center and serves on the AoU Program Steering Committee.

Sarah A. Tishkoff is the David and Lyn Silfen University Associate Professor in Genetics and Biology at the University of Pennsylvania, Philadelphia, USA, and holds appointments in the School of Medicine and the School of Arts and Sciences. She is a member of the US National Academy of Sciences and a recipient of an NIH Pioneer Award, a David and Lucile Packard Career Award, a Burroughs/Wellcome Fund Career Award and an American Society of Human Genetics Curt Stern Award. Her work focuses on genomic variation in Africa, human evolutionary history, the genetic basis of adaptation and phenotypic variation in Africa, and the genetic basis of susceptibility to infectious disease in Africa.

Ambroise Wonkam is Professor of Medical Genetics, Director of GeneMAP (Genetic Medicine of African Populations Research Centre) and Deputy Dean Research in the Faculty of Health Sciences, University of Cape Town, South Africa. He has successfully led numerous NIH- and Wellcome Trust-funded projects over the past decade to investigate clinical variability in sickle cell disease, hearing impairment genetics and the return of individual findings in genetic research in Africa. He won the competitive Clinical Genetics Society International Award for 2014 from the British Society of Genetic Medicine. He is president of the African Society of Human Genetics.

Aravinda Chakravarti is Director of the Center for Human Genetics and Genomics, the Muriel G. and George W. Singer Professor of Neuroscience and Physiology, and Professor of Medicine at New York University School of Medicine. He is an elected member of the US National Academy of Sciences, the US National Academy of Medicine and the Indian National Science Academy. He has been a key participant in the Human Genome Project, the International HapMap Project and the 1000 Genomes Project. His research attempts to understand the molecular basis of multifactorial disease. He was awarded the 2013 William Allan Award by the American Society of Human Genetics and the 2018 Chen Award by the Human Genome Organization.

Eileen E. M. Furlong is Head of the Genome Biology Department at the European Molecular Biology Laboratory (EMBL) and a member of the EMBL Directorate. She is an elected member of the European Molecular Biology Organization (EMBO) and the Academia Europaea, and a European Research Council (ERC) advanced investigator. Her group dissects fundamental principles of how the genome is regulated and how it drives cell fate decisions during embryonic development, including how developmental enhancers are organized and function within the 3D nucleus. Her work combines genetics, (single-cell) genomics, imaging and computational approaches to understand these processes. Her research has advanced the development of genomic methods for use in complex multicellular organisms.

Barbara Treutlein is Associate Professor of Quantitative Developmental Biology in the Department of Biosystems Science and Engineering of ETH Zurich in Basel, Switzerland. Her group uses and develops single-cell genomics approaches in combination with stem cell-based 2D and 3D culture systems to study how human organs develop and regenerate and how cell fate is regulated. For her work, Barbara has received multiple awards, including the Friedmund Neumann Prize of the Schering Foundation, the Dr. Susan Lim Award for Outstanding Young Investigator of the International Society of Stem Cell Research and the EMBO Young Investigator Award.

Alexander Meissner is a scientific member of the Max Planck Society and currently Managing Director of the Max Planck Institute (MPI) for Molecular Genetics in Berlin, Germany. He heads the Department of Genome Regulation and is a visiting scientist in the Department of Stem Cell and Regenerative Biology at Harvard University. Before his move to the MPI, he was a tenured professor at Harvard University and a senior associate member of the Broad Institute, where he co-directed the epigenomics programme. In 2018, he was elected as an EMBO member. His laboratory uses genomic tools to study developmental and disease biology with a particular focus on epigenetic regulation.

Howard Y. Chang is the Virginia and D. K. Ludwig Professor of Cancer Genomics at Stanford University and an investigator at the Howard Hughes Medical Institute. He is a physician–scientist who has focused on deciphering the hidden information in the non-coding genome. His laboratory is best known for studies of long non-coding RNAs in gene regulation and development of new epigenomic technologies. He is an elected member of the US National Academy of Sciences, the US National Academy of Medicine, and the American Academy of Arts and Sciences.

Núria López-Bigas is ICREA research Professor at the Institute for Research in Biomedicine and Associate Professor at the University Pompeu Fabra. She obtained an ERC Consolidator Grant in 2015 and was elected as an EMBO member in 2016. Her work has been recognized with the prestigious Banc de Sabadell Award for Research in Biomedicine, the Catalan National Award for Young Research Talent and the Career Development Award from the Human Frontier Science Program. Her research focuses on the identification of cancer driver mutations, genes and pathways across tumour types and in understanding the mutational processes that lead to the accumulation of mutations in cancer cells.

Eran Segal is Professor in the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science, heading a multidisciplinary laboratory with extensive experience in machine learning, computational biology and analysis of heterogeneous high-throughput genomic data. His research focuses on the microbiome, nutrition and genetics, and their effect on health and disease and aims to develop personalized medicine based on big data from human cohorts. He has published more than 150 publications and received several awards and honours for his work, including the Overton and the Michael Bruno awards. He was recently elected as an EMBO member and as a member of the Israel Young Academy.

Jin-Soo Kim is Director of the Center for Genome Engineering in the Institute for Basic Science in Daejon, South Korea. He has received numerous awards, including the 2017 Asan Award in Medicine, the 2017 Yumin Award in Science and the 2019 Research Excellence Award (Federation of Asian and Oceanian Biochemists and Molecular Biologists). He was featured as one of ten Science Stars of East Asia in Nature (558, 502–510 (2018)) and has been recognized as a highly cited researcher by Clarivate Analytics since 2018. His work focuses on developing tools for genome editing in biomedical research.

Molecular Structure, Binding Affinity, and Biological Activity in the Epigenome

Development of valid structure–activity relationships (SARs) is a key to the elucidation of pathomechanisms of epigenetic diseases and the development of efficient, new drugs. The present review is based on selected methodologies and applications supplying molecular structure, binding affinity and biological activity data for the development of new SARs. An emphasis is placed on emerging trends and permanent challenges of new discoveries of SARs in the context of proteins as epigenetic drug targets. The review gives a brief overview and classification of the molecular background of epigenetic changes, and surveys both experimental and theoretical approaches in the field. Besides the results of sophisticated, cutting edge techniques such as cryo-electron microscopy, protein crystallography, and isothermal titration calorimetry, examples of frequently used assays and fast screening techniques are also selected. The review features how different experimental methods and theoretical approaches complement each other and result in valid SARs of the epigenome.

Multilevel comparative bioinformatics to investigate evolutionary relationships and specificities in gene annotations: an example for tomato and grapevine

Background

“Omics” approaches may provide useful information for a deeper understanding of speciation events, diversification and function innovation. This can be achieved by investigating the molecular similarities at sequence level between species, allowing the definition of ortholog and paralog genes. However, the spreading of sequenced genome, often endowed with still preliminary annotations, requires suitable bioinformatics to be appropriately exploited in this framework.

Results

We presented here a multilevel comparative approach to investigate on genome evolutionary relationships and peculiarities of two fleshy fruit species of relevant agronomic interest, Solanum lycopersicum (tomato) and Vitis vinifera (grapevine). We defined 17,823 orthology relationships between tomato and grapevine reference gene annotations. The resulting orthologs are associated with the detected paralogs in each species, permitting the definition of gene networks, useful to investigate the different relationships. The reconciliation of the compared collections in terms of an updating of the functional descriptions was also exploited. All the results were made accessible in ComParaLogs, a dedicated bioinformatics platform available at http://biosrv.cab.unina.it/comparalogs/gene/search.

Conclusions

The aim of the work was to suggest a reliable approach to detect all similarities of gene loci between two species based on the integration of results from different levels of information, such as the gene, the transcript and the protein sequences, overcoming possible limits due to exclusive protein versus protein comparisons. This to define reliable ortholog and paralog genes, as well as species specific gene loci in the two species, overcoming limits due to the possible draft nature of preliminary gene annotations. Moreover, reconciled functional descriptions, as well as common or peculiar enzymatic classes and protein domains from tomato and grapevine, together with the definition of species-specific gene sets after the pairwise comparisons, contributed a comprehensive set of information useful to comparatively exploit the two species gene annotations and investigate on differences between species with climacteric and non-climacteric fruits. In addition, the definition of networks of ortholog genes and of associated paralogs, and the organization of web-based interfaces for the exploration of the results, defined a friendly computational bench-work in support of comparative analyses between two species.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2420-y) contains supplementary material, which is available to authorized users.

Which attributes of whole genome sequencing tests are most important to the general population? Results from a German preference study

Objective

The aim of this study was to identify the preferences for whole genome sequencing (WGS) tests without genetic counseling.

Methods

A discrete choice experiment was conducted where participants chose between two hypothetical alternatives consisting of the following attributes: test accuracy, test costs, identified diseases, probability of disease occurrence, and data access. People from the general German population aged ≥18 years were eligible to participate in the survey. We estimated generalized linear mixed effects models, latent class mixed-logit models, and the marginal willingness to pay.

Results

Three hundred and one participants were included in the final analysis. Overall, the most favored WGS testing attributes were 95% test accuracy, report of severe hereditary diseases and 40% probability of disease development, test costs of €1,000, and access to test results for researchers. Subgroup analysis, however, showed differences in these preferences between males and females. For example, males preferred reporting of results at a 10% probability of disease development and females preferred reporting of results at a 40% probability. The test cost, participant’s educational level, and access to data influenced the willingness to participate in WGS testing in reality.

Conclusion

The German general population was aware of the importance of genetic research and preferred to provide their own genetic data for researchers. However, among others, the reporting of results with a comparatively relatively low probability of disease development at a level of 40%, and the test accuracy of 95% had a high preference. This shows that the results and consequences of WGS testing without genetic counseling are hard to assess for individuals. Therefore, WGS testing should be supported by qualified genetic counseling, where the attributes and consequences are explained.

Genetic linkage analysis using DNA markers in sweetpotato

Sweetpotato is one of the most important food crop species in the world, with more than 104,000,000 tons produced each year, and the breeding of superior cultivars with agronomically important traits, such as improved disease resistance, yield, and nutrient richness, is necessary, especially in developing countries. However, as a result of the crop's complex genomic architecture, which results from its hexaploidy (2n = 6× = 90), high heterozygosity, huge genome, and outcrossing nature, the analysis of genetic linkage in sweetpotato has been challenging. In addition, the lack of whole genome sequences or gene annotations for cultivated hexaploids has interrupted the validation of mapped QTL regions and gene cloning. In spite of these technical difficulties, linkage map construction and QTL mapping analysis have been reported. This review summarizes the results of these linkage analyses, which used SSR, AFLP, and retrotransposon-based molecular markers, and describes future directions for the genetic analysis and marker-assisted breeding of this important but genetically complex crop species.

Maps of context-dependent putative regulatory regions and genomic signal interactions

Gene transcription is regulated mainly by transcription factors (TFs). ENCODE and Roadmap Epigenomics provide global binding profiles of TFs, which can be used to identify regulatory regions. To this end we implemented a method to systematically construct cell-type and species-specific maps of regulatory regions and TF-TF interactions. We illustrated the approach by developing maps for five human cell-lines and two other species. We detected ∼144k putative regulatory regions among the human cell-lines, with the majority of them being ∼300 bp. We found ∼20k putative regulatory elements in the ENCODE heterochromatic domains suggesting a large regulatory potential in the regions presumed transcriptionally silent. Among the most significant TF interactions identified in the heterochromatic regions were CTCF and the cohesin complex, which is in agreement with previous reports. Finally, we investigated the enrichment of the obtained putative regulatory regions in the 3D chromatin domains. More than 90% of the regions were discovered in the 3D contacting domains. We found a significant enrichment of GWAS SNPs in the putative regulatory regions. These significant enrichments provide evidence that the regulatory regions play a crucial role in the genomic structural stability. Additionally, we generated maps of putative regulatory regions for prostate and colorectal cancer human cell-lines.

Systems Medicine: hype or revolution?

Research and innovation in healthcare can change existing practices aiming at constant improvement of diagnosis, treatment and prevention. As a new holistic approach Systems Medicine (SM) may revolutionize the healthcare system. This paper analyzes ethical and economic obstacles of SMs development from a niche innovation to a standard solution. We adapt a model of innovation theory to structure the barriers of adopting SM to become standard in the medical system. SM has the potential to change the medical system if barriers to this innovation can be overcome. The article discusses the potential of SM in becoming the future health paradigm considering these barriers and provides an overview of the current situation.

Genomic approach to studying nutritional requirements of Clostridium tyrobutyricum and other Clostridia causing late blowing defects

Clostridium tyrobutyricum is the main microorganism responsible for the late blowing defect in hard and semi-hard cheeses, causing considerable economic losses to the cheese industry. Deeper knowledge of the metabolic requirements of this microorganism can lead to the development of more effective control approaches. In this work, the amino acids and B vitamins essential for sustaining the growth of C. tyrobutyricum were investigated using a genomic approach. As the first step, the genomes of four C. tyrobutyricum strains were analyzed for the presence of genes putatively involved in the biosynthesis of amino acids and B vitamins. Metabolic pathways could be reconstructed for all amino acids and B vitamins with the exception of biotin (vitamin B7) and folate (vitamin B9). The biotin pathway was missing the enzyme amino-7-oxononanoate synthase that catalyzes the condensation of pimeloyl-ACP and l-alanine to 8-amino-7-oxononanoate. In the folate pathway, the missing genes were those coding for para-aminobenzoate synthase and aminodeoxychorismate lyase enzymes. These enzymes are responsible for the conversion of chorismate into para-aminobenzoate (PABA). Two C. tyrobutyircum strains whose genome was analyzed in silico as well as other 10 strains isolated from cheese were tested in liquid media to confirm these observations. 11 strains showed growth in a defined liquid medium containing biotin and PABA after 6-8 days of incubation. No strain showed growth when only one or none of these compounds were added, confirming the observations obtained in silico. Furthermore, the genome analysis was extended to genomes of single strains of other Clostridium species potentially causing late blowing, namely Clostridium beijerinckii, Clostridium sporogenes and Clostridium butyricum. Only the biotin biosynthesis pathway was incomplete for C. butyricum and C. beijerincki. In contrast, C. sporogenes showed missing enzymes in biosynthesis pathways of several amino acids as well as biotin, folate, and cobalamin (vitamin B12). These observations agree with the results of growth experiments of these species in liquid media reported in the literature. The results of this study suggest that biotin and folate are potential targets for reducing late blowing in cheese and highlight the usefulness of genomic analysis for identifying essential nutrients in bacteria.

Alzheimer's as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks

Alzheimer's disease (AD), and many neurodegenerative disorders, are multifactorial in nature. They involve a combination of genomic, epigenomic, interactomic and environmental factors. Progress is being made, and these complex diseases are beginning to be understood as having their origin in altered states of biological networks at the cellular level. In the case of AD, genomic susceptibility and mechanisms leading to (or accompanying) the impairment of the central Amyloid Precursor Protein (APP) processing and tau networks are widely accepted as major contributors to the diseased state. The derangement of these networks may result in both the gain and loss of functions, increased generation of toxic species (e.g., toxic soluble oligomers and aggregates) and imbalances, whose effects can propagate to supra-cellular levels. Although well sustained by empirical data and widely accepted, this global perspective often overlooks the essential roles played by the main counteracting homeostatic networks (e.g., protein quality control/proteostasis, unfolded protein response, protein folding chaperone networks, disaggregases, ER-associated degradation/ubiquitin proteasome system, endolysosomal network, autophagy, and other stress-protective and clearance networks), whose relevance to AD is just beginning to be fully realized. In this chapter, an integrative perspective is presented. Alzheimer's disease is characterized to be a result of: (a) intrinsic genomic/epigenomic susceptibility and, (b) a continued dynamic interplay between the deranged networks and the central homeostatic networks of nerve cells. This interplay of networks will underlie both the onset and rate of progression of the disease in each individual. Integrative Systems Biology approaches are required to effect its elucidation. Comprehensive Systems Biology experiments at different 'omics levels in simple model organisms, engineered to recapitulate the basic features of AD may illuminate the onset and sequence of events underlying AD. Indeed, studies of models of AD in simple organisms, differentiated cells in culture and rodents are beginning to offer hope that the onset and progression of AD, if detected at an early stage, may be stopped, delayed, or even reversed, by activating or modulating networks involved in proteostasis and the clearance of toxic species. In practice, the incorporation of next-generation neuroimaging, high-throughput and computational approaches are opening the way towards early diagnosis well before irreversible cell death. Thus, the presence or co-occurrence of: (a) accumulation of toxic Aβ oligomers and tau species; (b) altered splicing and transcriptome patterns; (c) impaired redox, proteostatic, and metabolic networks together with, (d) compromised homeostatic capacities may constitute relevant 'AD hallmarks at the cellular level' towards reliable and early diagnosis. From here, preventive lifestyle changes and tailored therapies may be investigated, such as combined strategies aimed at both lowering the production of toxic species and potentiating homeostatic responses, in order to prevent or delay the onset, and arrest, alleviate, or even reverse the progression of the disease.

De novo prediction of cis-regulatory elements and modules through integrative analysis of a large number of ChIP datasets

BACKGROUND

In eukaryotes, transcriptional regulation is usually mediated by interactions of multiple transcription factors (TFs) with their respective specific cis-regulatory elements (CREs) in the so-called cis-regulatory modules (CRMs) in DNA. Although the knowledge of CREs and CRMs in a genome is crucial to elucidate gene regulatory networks and understand many important biological phenomena, little is known about the CREs and CRMs in most eukaryotic genomes due to the difficulty to characterize them by either computational or traditional experimental methods. However, the exponentially increasing number of TF binding location data produced by the recent wide adaptation of chromatin immunoprecipitation coupled with microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) technologies has provided an unprecedented opportunity to identify CRMs and CREs in genomes. Nonetheless, how to effectively mine these large volumes of ChIP data to identify CREs and CRMs at nucleotide resolution is a highly challenging task.

RESULTS

We have developed a novel graph-theoretic based algorithm DePCRM for genome-wide de novo predictions of CREs and CRMs using a large number of ChIP datasets. DePCRM predicts CREs and CRMs by identifying overrepresented combinatorial CRE motif patterns in multiple ChIP datasets in an effective way. When applied to 168 ChIP datasets of 56 TFs from D. melanogaster, DePCRM identified 184 and 746 overrepresented CRE motifs and their combinatorial patterns, respectively, and predicted a total of 115,932 CRMs in the genome. The predictions recover 77.9% of known CRMs in the datasets and 89.3% of known CRMs containing at least one predicted CRE. We found that the putative CRMs as well as CREs as a whole in a CRM are more conserved than randomly selected sequences.

CONCLUSION

Our results suggest that the CRMs predicted by DePCRM are highly likely to be functional. Our algorithm is the first of its kind for de novo genome-wide prediction of CREs and CRMs using larger number of transcription factor ChIP datasets. The algorithm and predictions will hopefully facilitate the elucidation of gene regulatory networks in eukaryotes. All the predicted CREs, CRMs, and their target genes are available at http://bioinfo.uncc.edu/mniu/pcrms/www/.

Public perceptions of cohort studies and biobanks in Germany

Cohort studies and biobank projects have led to public discussions in several European countries in the past. In Germany, many medium-sized studies are currently running successfully in terms of respondent rates. However, EU-wide research on general public perceptions of biobanks and cohort studies have shown that Germany is among those countries where people express the highest reluctance for providing body material and other data for research purposes. Because of early efforts of the just-initiated German National Cohort Study, we are able to begin to investigate in greater detail how various groups of people across Germany reflect and discuss the ongoing implementation of cohort studies and biobanking in Germany. Our research is based on 15 focus group discussions in four German regions, as well as on Eurobarometer poll data on biobanking.

ComPlEx: conservation and divergence of co-expression networks in A. thaliana, Populus and O. sativa

Background

Divergence in gene regulation has emerged as a key mechanism underlying species differentiation. Comparative analysis of co-expression networks across species can reveal conservation and divergence in the regulation of genes.

Results

We inferred co-expression networks of A. thaliana, Populus spp. and O. sativa using state-of-the-art methods based on mutual information and context likelihood of relatedness, and conducted a comprehensive comparison of these networks across a range of co-expression thresholds. In addition to quantifying gene-gene link and network neighbourhood conservation, we also applied recent advancements in network analysis to do cross-species comparisons of network properties such as scale free characteristics and gene centrality as well as network motifs. We found that in all species the networks emerged as scale free only above a certain co-expression threshold, and that the high-centrality genes upholding this organization tended to be conserved. Network motifs, in particular the feed-forward loop, were found to be significantly enriched in specific functional subnetworks but where much less conserved across species than gene centrality. Although individual gene-gene co-expression had massively diverged, up to ~80% of the genes still had a significantly conserved network neighbourhood. For genes with multiple predicted orthologs, about half had one ortholog with conserved regulation and another ortholog with diverged or non-conserved regulation. Furthermore, the most sequence similar ortholog was not the one with the most conserved gene regulation in over half of the cases.

Conclusions

We have provided a comprehensive analysis of gene regulation evolution in plants and built a web tool for Comparative analysis of Plant co-Expression networks (ComPlEx, http://complex.plantgenie.org/). The tool can be particularly useful for identifying the ortholog with the most conserved regulation among several sequence-similar alternatives and can thus be of practical importance in e.g. finding candidate genes for perturbation experiments.

The role of transposable elements in health and diseases of the central nervous system

First discovered in maize by Barbara McClintock in the 1940s, transposable elements (TEs) are DNA sequences that in some cases have the ability to move along chromosomes or "transpose" in the genome. This revolutionary finding was initially met with resistance by the scientific community and viewed by some as heretical. A large body of knowledge has accumulated over the last 60 years on the biology of TEs. Indeed, it is now known that TEs can generate genomic instability and reconfigure gene expression networks both in the germline and somatic cells. This review highlights recent findings on the role of TEs in health and diseases of the CNS, which were presented at the 2013 Society for Neuroscience meeting. The work of the speakers in this symposium shows that TEs are expressed and active in the brain, challenging the dogma that neuronal genomes are static and revealing that they are susceptible to somatic genomic alterations. These new findings on TE expression and function in the CNS have major implications for understanding the neuroplasticity of the brain, which could hypothetically have a role in shaping individual behavior and contribute to vulnerability to disease.

Interaction-based evolution: how natural selection and nonrandom mutation work together

BACKGROUND

The modern evolutionary synthesis leaves unresolved some of the most fundamental, long-standing questions in evolutionary biology: What is the role of sex in evolution? How does complex adaptation evolve? How can selection operate effectively on genetic interactions? More recently, the molecular biology and genomics revolutions have raised a host of critical new questions, through empirical findings that the modern synthesis fails to explain: for example, the discovery of de novo genes; the immense constructive role of transposable elements in evolution; genetic variance and biochemical activity that go far beyond what traditional natural selection can maintain; perplexing cases of molecular parallelism; and more.

PRESENTATION OF THE HYPOTHESIS

Here I address these questions from a unified perspective, by means of a new mechanistic view of evolution that offers a novel connection between selection on the phenotype and genetic evolutionary change (while relying, like the traditional theory, on natural selection as the only source of feedback on the fit between an organism and its environment). I hypothesize that the mutation that is of relevance for the evolution of complex adaptation-while not Lamarckian, or "directed" to increase fitness-is not random, but is instead the outcome of a complex and continually evolving biological process that combines information from multiple loci into one. This allows selection on a fleeting combination of interacting alleles at different loci to have a hereditary effect according to the combination's fitness.

TESTING AND IMPLICATIONS OF THE HYPOTHESIS

This proposed mechanism addresses the problem of how beneficial genetic interactions can evolve under selection, and also offers an intuitive explanation for the role of sex in evolution, which focuses on sex as the generator of genetic combinations. Importantly, it also implies that genetic variation that has appeared neutral through the lens of traditional theory can actually experience selection on interactions and thus has a much greater adaptive potential than previously considered. Empirical evidence for the proposed mechanism from both molecular evolution and evolution at the organismal level is discussed, and multiple predictions are offered by which it may be tested.

REVIEWERS

This article was reviewed by Nigel Goldenfeld (nominated by Eugene V. Koonin), Jürgen Brosius and W. Ford Doolittle.

"He who sees things grow from the beginning will have the finest view of them" a systematic review of genetic studies on psychological traits in infancy

This paper reviews the studies that have aimed to identify genes influencing psychological traits in infancy (from birth to age 12 months). The review also addresses why genetic research in infancy is worthwhile and what genetic approaches such as genome-wide association studies and next generation sequencing could offer infant genetics. The results revealed that: (a) all studies (N=26) have employed a candidate gene association design; (b) existing studies have most commonly focused on the Dopamine receptor D4 (DRD4) and the Serotonin transporter promoter (5-HTTLPR) gene polymorphisms; (c) phenotypes that have been assessed are temperament, attachment, and attention. Two further studies included both temperament and electrophysiological markers; (d) among many unreplicated findings, the most promising result appeared to be an association between the long DRD4 polymorphism and several "positive" temperament characteristics from birth to 4-months of age and at 12-months of age. It is concluded that, to date, there are limited, and mixed, findings regarding the possible association of genes with psychological phenotypes in infancy.

Isoform level expression profiles provide better cancer signatures than gene level expression profiles

BACKGROUND

The majority of mammalian genes generate multiple transcript variants and protein isoforms through alternative transcription and/or alternative splicing, and the dynamic changes at the transcript/isoform level between non-oncogenic and cancer cells remain largely unexplored. We hypothesized that isoform level expression profiles would be better than gene level expression profiles at discriminating between non-oncogenic and cancer cellsgene level.

METHODS

We analyzed 160 Affymetrix exon-array datasets, comprising cell lines of non-oncogenic or oncogenic tissue origins. We obtained the transcript-level and gene level expression estimates, and used unsupervised and supervised clustering algorithms to study the profile similarity between the samples at both gene and isoform levels.

RESULTS

Hierarchical clustering, based on isoform level expressions, effectively grouped the non-oncogenic and oncogenic cell lines with a virtually perfect homogeneity-grouping rate (97.5%), regardless of the tissue origin of the cell lines. However, gene levelthis rate was much lower, being 75% at best based on the gene level expressions. Statistical analyses of the difference between cancer and non-oncogenic samples identified the existence of numerous genes with differentially expressed isoforms, which otherwise were not significant at the gene level. We also found that canonical pathways of protein ubiquitination, purine metabolism, and breast-cancer regulation by stathmin1 were significantly enriched among genes thatshow differential expression at isoform level but not at gene level.

CONCLUSIONS

In summary, cancer cell lines, regardless of their tissue of origin, can be effectively discriminated from non-cancer cell lines at isoform level, but not at gene level. This study suggests the existence of an isoform signature, rather than a gene signature, which could be used to distinguish cancer cells from normal cells.

Transposable elements and viruses as factors in adaptation and evolution: an expansion and strengthening of the TE-Thrust hypothesis

In addition to the strong divergent evolution and significant and episodic evolutionary transitions and speciation we previously attributed to TE-Thrust, we have expanded the hypothesis to more fully account for the contribution of viruses to TE-Thrust and evolution. The concept of symbiosis and holobiontic genomes is acknowledged, with particular emphasis placed on the creativity potential of the union of retroviral genomes with vertebrate genomes. Further expansions of the TE-Thrust hypothesis are proposed regarding a fuller account of horizontal transfer of TEs, the life cycle of TEs, and also, in the case of a mammalian innovation, the contributions of retroviruses to the functions of the placenta. The possibility of drift by TE families within isolated demes or disjunct populations, is acknowledged, and in addition, we suggest the possibility of horizontal transposon transfer into such subpopulations. “Adaptive potential” and “evolutionary potential” are proposed as the extremes of a continuum of “intra-genomic potential” due to TE-Thrust. Specific data is given, indicating “adaptive potential” being realized with regard to insecticide resistance, and other insect adaptations. In this regard, there is agreement between TE-Thrust and the concept of adaptation by a change in allele frequencies. Evidence on the realization of “evolutionary potential” is also presented, which is compatible with the known differential survivals, and radiations of lineages. Collectively, these data further suggest the possibility, or likelihood, of punctuated episodes of speciation events and evolutionary transitions, coinciding with, and heavily underpinned by, intermittent bursts of TE activity.

Quick, "imputation-free" meta-analysis with proxy-SNPs

Background

Meta-analysis (MA) is widely used to pool genome-wide association studies (GWASes) in order to a) increase the power to detect strong or weak genotype effects or b) as a result verification method. As a consequence of differing SNP panels among genotyping chips, imputation is the method of choice within GWAS consortia to avoid losing too many SNPs in a MA. YAMAS (Yet Another Meta Analysis Software), however, enables cross-GWAS conclusions prior to finished and polished imputation runs, which eventually are time-consuming.

Results

Here we present a fast method to avoid forfeiting SNPs present in only a subset of studies, without relying on imputation. This is accomplished by using reference linkage disequilibrium data from 1,000 Genomes/HapMap projects to find proxy-SNPs together with in-phase alleles for SNPs missing in at least one study. MA is conducted by combining association effect estimates of a SNP and those of its proxy-SNPs. Our algorithm is implemented in the MA software YAMAS. Association results from GWAS analysis applications can be used as input files for MA, tremendously speeding up MA compared to the conventional imputation approach. We show that our proxy algorithm is well-powered and yields valuable ad hoc results, possibly providing an incentive for follow-up studies. We propose our method as a quick screening step prior to imputation-based MA, as well as an additional main approach for studies without available reference data matching the ethnicities of study participants. As a proof of principle, we analyzed six dbGaP Type II Diabetes GWAS and found that the proxy algorithm clearly outperforms naïve MA on the p-value level: for 17 out of 23 we observe an improvement on the p-value level by a factor of more than two, and a maximum improvement by a factor of 2127.

Conclusions

YAMAS is an efficient and fast meta-analysis program which offers various methods, including conventional MA as well as inserting proxy-SNPs for missing markers to avoid unnecessary power loss. MA with YAMAS can be readily conducted as YAMAS provides a generic parser for heterogeneous tabulated file formats within the GWAS field and avoids cumbersome setups. In this way, it supplements the meta-analysis process.

High-throughput and parallel SNP discovery in selected candidate genes in Eucalyptus camaldulensis using Illumina NGS platform

Next generation sequencing (NGS) technologies have revolutionized the pace and scale of genomics- and transcriptomics-based SNP discovery across different plant and animal species. Herein, 72-base paired-end Illumina sequencing was employed for high-throughput, parallel and large-scale SNP discovery in 41 growth-related candidate genes in Eucalyptus camaldulensis. Approximately 100 kb of genome from 96 individuals was amplified and sequenced using a hierarchical DNA/PCR pooling strategy and assembled over corresponding E. grandis reference. A total of 1191 SNPs (minimum 5% other allele frequency) were identified with an average frequency of 1 SNP/83.9 bp, whereas in exons and introns, it was 1 SNP/108.4 bp and 1 SNP/65.6 bp, respectively. A total of 75 insertions and 89 deletions were detected of which approximately 15% were exonic. Transitions (Tr) were in excess than transversions (Tv) (Tr/Tv: 1.89), but exceeded in exons (Tr/Tv: 2.73). In exons, synonymous SNPs (Ka) prevailed over the non-synonymous SNPs (Ks; average Ka/Ks ratio: 0.72, range: 0-3.00 across genes). Many of the exonic SNPs/indels had potential to change amino acid sequence of respective genes. Transcription factors appeared more conserved, whereas enzyme coding genes appeared under relaxed control. Further, 541 SNPs were classified into 196 'equal frequency' (EF) blocks with almost similar minor allele frequencies to facilitate selection of one tag-SNP/EF-block. There were 241 (approximately 20%) 'zero-SNP' blocks with absence of SNPs in surrounding ±60 bp windows. The data thus indicated enormous extant and unexplored diversity in E. camaldulensis in the studied genes with potential applications for marker-trait associations.

A coordination complex system for generic, ultrafast, and sensitive multimode fluorescent staining of biomolecules

Gel electrophoresis staining methodologies documented thus far are largely utilized in a biomolecule context-dependent manner. We report herein the development of a generic, ultrafast, and sensitive multimode fluorescent system for the efficient identification of DNA, RNA, and proteins. Interaction between a positively charged, planar ligand-based coordination complex with partner biomolecule leads to aggregation-induced fluorescence quenching and allows for the image contrast generation within one minute. Alternatively, successive reactions of the biomolecule-loaded gel with cation and ligand, in either order of sequence, provide an equally effective staining efficacy. Image contrast reversal is accomplished through a facile washing or photobleaching procedure. The versatility in the applicable target species and signal generation modes provides a hint at the design of novel staining structures and potentially enables the high-throughput readout of biomolecules.

Somatic genetics empowers the mouse for modeling and interrogating developmental and disease processes

With recent advances in genomic technologies, candidate human disease genes are being mapped at an accelerated pace. There is a clear need to move forward with genetic tools that can efficiently validate these mutations in vivo. Murine somatic mutagenesis is evolving to fulfill these needs with tools such as somatic transgenesis, humanized rodents, and forward genetics. By combining these resources one is not only able to model disease for in vivo verification, but also to screen for mutations and pathways integral to disease progression and therapeutic intervention. In this review, we briefly outline the current advances in somatic mutagenesis and discuss how these new tools, especially the piggyBac transposon system, can be applied to decipher human biology and disease.

Implication of next-generation sequencing on association studies

Background

Next-generation sequencing technologies can effectively detect the entire spectrum of genomic variation and provide a powerful tool for systematic exploration of the universe of common, low frequency and rare variants in the entire genome. However, the current paradigm for genome-wide association studies (GWAS) is to catalogue and genotype common variants (5% < MAF). The methods and study design for testing the association of low frequency (0.5% < MAF ≤ 5%) and rare variation (MAF ≤ 0.5%) have not been thoroughly investigated. The 1000 Genomes Project represents one such endeavour to characterize the human genetic variation pattern at the MAF = 1% level as a foundation for association studies. In this report, we explore different strategies and study designs for the near future GWAS in the post-era, based on both low coverage pilot data and exon pilot data in 1000 Genomes Project.

Results

We investigated the linkage disequilibrium (LD) pattern among common and low frequency SNPs and its implication for association studies. We found that the LD between low frequency alleles and low frequency alleles, and low frequency alleles and common alleles are much weaker than the LD between common and common alleles. We examined various tagging designs with and without statistical imputation approaches and compare their power against de novo resequencing in mapping causal variants under various disease models. We used the low coverage pilot data which contain ~14 M SNPs as a hypothetical genotype-array platform (Pilot 14 M) to interrogate its impact on the selection of tag SNPs, mapping coverage and power of association tests. We found that even after imputation we still observed 45.4% of low frequency SNPs which were untaggable and only 67.7% of the low frequency variation was covered by the Pilot 14 M array.

Conclusions

This suggested GWAS based on SNP arrays would be ill-suited for association studies of low frequency variation.

Positional information resolves structural variations and uncovers an evolutionarily divergent genetic locus in accessions of Arabidopsis thaliana

Genome sequencing of closely related individuals has yielded valuable insights that link genome evolution to phenotypic variations. However, advancement in sequencing technology has also led to an escalation in the number of poor quality–drafted genomes assembled based on reference genomes that can have highly divergent or haplotypic regions. The self-fertilizing nature of Arabidopsis thaliana poses an advantage to sequencing projects because its genome is mostly homozygous. To determine the accuracy of an Arabidopsis drafted genome in less conserved regions, we performed a resequencing experiment on a ∼371-kb genomic interval in the Landsberg erecta (Ler-0) accession. We identified novel structural variations (SVs) between Ler-0 and the reference accession Col-0 using a long-range polymerase chain reaction approach to generate an Illumina data set that has positional information, that is, a data set with reads that map to a known location. Positional information is important for accurate genome assembly and the resolution of SVs particularly in highly duplicated or repetitive regions. Sixty-one regions with misassembly signatures were identified from the Ler-0 draft, suggesting the presence of novel SVs that are not represented in the draft sequence. Sixty of those were resolved by iterative mapping using our data set. Fifteen large indels (>100 bp) identified from this study were found to be located either within protein-coding regions or upstream regulatory regions, suggesting the formation of novel alleles or altered regulation of existing genes in Ler-0. We propose future genome-sequencing experiments to follow a clone-based approach that incorporates positional information to ultimately reveal haplotype-specific differences between accessions.

Yeast systems biology: the challenge of eukaryotic complexity

In this chapter, we present an up-to-date view of the optimal characteristics of the yeast Saccharomyces cerevisiae as a model eukaryote for systems biology studies, with main molecular mechanisms, biological networks, and sub-cellular organization essentially conserved in all eukaryotes, derived from a complex common ancestor. The existence of advanced tools for molecular studies together with high-throughput experimental and computational methods, most of them being implemented and validated in yeast, with new ones being developed, is opening the way to the characterization of the core modular architecture and complex networks essential to all eukaryotes. Selected examples of the latest discoveries in eukaryote complexity and systems biology studies using yeast as a reference model and their applications in biotechnology and medicine are presented.