Elucidation of the genetic pathways that control red blood cell development has been a central goal of erythropoiesis research over the past decade. Notably, data from several recent studies have provided new insights into the regulation of erythroid gene transcription. Transcription profiling demonstrates that erythopoiesis is mainly controlled by a small group of lineage-restricted transcription factors (Gata1, Tal1, and Klf1). Binding site mapping using ChIP-Seq indicates that most DNA bound Gata1 and Tal1 proteins are contained within higher order complexes (Ldb1-complexes) that include the nuclear adapters Ldb1 and Lmo2. Ldb1-complexes regulate Klf1 and Ldb1-complex binding sites frequently co-localize with Klf1 at erythroid genes and cis-regulatory elements indicating strong functional synergy between Gata1, Tal1, and Klf1. Together with new data demonstrating that Ldb1 can mediate long-range promoter/enhancer interactions, these findings provide a foundation for the first comprehensive models for the global regulation of erythroid gene transcription.
Erythropoiesis; Gata1; Tal1; Klf1; Ldb1-complexes; Transcriptional regulation; ChIP-Seq
We review recently identified mechanisms of transcriptional control that ensure reliable and reproducible patterns of gene expression in natural populations of developing embryos, despite inherent fluctuations in gene regulatory processes, variations in genetic backgrounds and exposure to diverse environmental conditions. These mechanisms are not responsible for switching genes on and off. Instead, they control the fine-tuning of gene expression and ensure regulatory precision. Several such mechanisms are discussed, including redundant binding sites within transcriptional enhancers, shadow enhancers, and ‘poised’ enhancers and promoters, as well as the role of ‘redundant’ gene interactions within regulatory networks. We propose that such regulatory mechanisms provide population fitness and ‘fine-tune’ the spatial and temporal control of gene expression.
enhancer; paused polymerase; pioneer factors; robustness; gene regulatory networks
The decay rate of an mRNA and the efficiency with which it is translated are key determinants of eukaryotic gene expression. Although it was once thought that mRNA stability and translational efficiency were directly linked, the interrelationships between the two processes are considerably more complex. The decay of individual mRNAs can be triggered or antagonized by translational impairment, and alterations in the half-life of certain mRNAs can even alter translational fidelity. In this review, we consider whether mRNA translation and turnover are distinct or overlapping phases of an mRNA life cycle, and then address some of the many ways in which the two processes influence each other in eukaryotic cells.
mRNA degradation; translational repression; quality control
DNA damage checkpoints are important tumor suppressor mechanisms that halt cell cycle progression to allow time for DNA repair, or induce senescence and apoptosis to permanently remove damaged cells. Non-cell-autonomous DNA damage responses activate the innate immune system in multiple metazoan species. These responses enable clearance of damaged cells and contribute to tissue remodeling and regeneration but can also result in chronic inflammation and tissue damage. “Germline DNA damage-induced systemic stress resistance” (GDISR) is mediated by an ancestral innate immune response and results in organismal adjustments to the presence of damaged cells. We discuss GDISR as an organismal DNA damage checkpoint mechanism through which elevated somatic endurance can extend reproductive lifespan when germ cells require extended time for restoring genome stability.
Patients with cancer face an ever-widening gap between the exponential rate at which technology improves and the linear rate at which these advances are translated into clinical practice. Closing this gap will require the establishment of learning loops that intimately link lab and clinic and enable the immediate transfer of knowledge, thereby engaging highly motivated patients with cancer as true partners in research. Here, we discuss the goal of creating a distributed network that aims to place world-class resources at the disposal of select patients with cancer and their oncologists, and then use these intensively monitored individual patient experiences to improve collective understanding of how cancer works.
cancer; personalized medicine; N-of-1; omics; longitudinal monitoring; learning loops; research
Gene functions, interactions, disease associations, and ecological distributions are all correlated with gene age. However, it is challenging to estimate the intricate series of evolutionary events leading to a modern day gene and then reduce this history to a single age estimate. Focusing on eukaryotic gene families, we introduce a framework in which to compare current strategies for quantifying gene age, discuss key differences between these methods, and highlight several common problems. We argue that genes with complex evolutionary histories do not have a single well-defined age. As a result, care must be taken to articulate the goals and assumptions of any analysis that uses gene age estimates. Recent algorithmic advances offer the promise of gene age estimates that are fast, accurate, and consistent across gene families. This will enable a shift to integrated genome-wide analyses of all events in gene evolutionary histories in the near future.
phylogenetics; gene age; molecular clock; eukaryotes
For centuries, philosophers and scientists have been fascinated by the principles and implications of regeneration in lower vertebrate species. Two features have made zebrafish an informative model system for determining mechanisms of regenerative events. First, they are highly regenerative, able to regrow amputated fins, as well as a lesioned brain, retina, spinal cord, heart, and other tissues. Second, they are amenable to both forward and reverse genetic approaches, with a research toolset regularly updated by an expanding community of zebrafish researchers. Zebrafish studies have helped identify new mechanistic underpinnings of regeneration in multiple tissues, and in some cases have served as a guide for contemplating regenerative strategies in mammals. Here, we review the recent history of zebrafish as a genetic model system for understanding how and why tissue regeneration occurs.
zebrafish; regeneration; stem cells; fin; spinal cord; heart; retina; brain
The autism susceptibility candidate 2 (AUTS2) gene is associated with multiple neurological diseases, including autism, and has been implicated as an important gene in human-specific evolution. Recent functional analysis of this gene has revealed a potential role in neuronal development. Here, we review the literature regarding AUTS2, including its discovery, expression, association with autism and other neurological and non-neurological traits, implication in human evolution, function, regulation, and genetic pathways. Through progress in clinical genomic analysis, the medical importance of this gene is becoming more apparent, as highlighted in this review, but more work needs to be done to discover the precise function and the genetic pathways associated with AUTS2.
AUTS2; autism; neurodevelopment; human evolution
Physico-chemical properties preclude ideal biomolecules and perfect biological functions. This inherent imperfectness leads to the generation of damage by every biological process, at all levels, from small molecules to cells. The damage is too numerous to be repaired, is partially invisible to natural selection and manifests as aging. I propose that it is the inherent imperfectness of biological systems that is the true root of the aging process. As each biomolecule generates specific forms of damage, the cumulative damage is largely non-random and is indirectly encoded in the genome. I consider this concept in light of other proposed theories of aging and integrate these disparate ideas into a single model. I also discuss the evolutionary significance of damage accumulation and strategies for reducing damage. Finally, I suggest ways to test this integrated model of aging.
Population genetics theory predicts that X (or Z) chromosomes could play disproportionate roles in speciation and evolutionary divergence, and recent genome-wide analyses have identified situations in which X- or Z-linked divergence exceeds that on the autosomes (the “faster-X effect”). Here, we summarize the current state of both the theory and data surrounding the study of faster-X evolution. Our survey indicates that the faster-X effect is pervasive across a taxonomically diverse array of evolutionary lineages. These patterns could be informative of the the dominance/recessivity of beneficial mutations and the nature of genetic variation acted upon by natural selection. We also identify several aspects of disagreement between these empirical results and the population genetic models used to interpret them. However, there are clearly delineated aspects of the problem for which additional modeling and collection of genomic data will address these discrepancies and provide novel insights into the population genetics of adaptation.
X chromosome; natural selection; genetics of adaptation; dominance
•Owing to improvements in sequencing technologies, microbial whole-genome sequencing (WGS) has emerged as a central tool to control antibiotic resistance.•WGS has been used to develop novel antibiotics and diagnostic tests.•WGS has been key to surveillance and the study of the emergence of antibiotic resistance.•Rapid WGS has the potential to be used as a tool for infection control in the clinic and, in some cases, as a primary diagnostic tool to detect resistance.
Following recent improvements in sequencing technologies, whole-genome sequencing (WGS) is positioned to become an essential tool in the control of antibiotic resistance, a major threat in modern healthcare. WGS has already found numerous applications in this area, ranging from the development of novel antibiotics and diagnostic tests through to antibiotic stewardship of currently available drugs via surveillance and the elucidation of the factors that allow the emergence and persistence of resistance. Numerous proof-of-principle studies have also highlighted the value of WGS as a tool for day-to-day infection control and, for some pathogens, as a primary diagnostic tool to detect antibiotic resistance. However, appropriate data analysis platforms will need to be developed before routine WGS can be introduced on a large scale.
whole-genome sequencing; antibiotic resistance; surveillance; diagnostics
Genome instability contributes to cancer development and accelerates age-related pathologies as evidenced by a variety of congenital cancer susceptibility and progeroid syndromes that are caused by defects in genome maintenance mechanisms. DNA damage response pathways that are mediated through the tumor suppressor p53 play an important role in the cell intrinsic responses to genome instability, including a transient cell cycle arrest, senescence and apoptosis. Both senescence and apoptosis are powerful tumor suppressive pathways preventing the uncontrolled proliferation of transformed cells. However, both pathways can potentially deplete stem and progenitor cell pools, thus promoting tissue degeneration and organ failure, which are both hallmarks of aging. p53 signaling is also involved in mediating non-cell autonomous interactions with the innate immune system and in the systemic adjustments during the aging process. The network of p53 target genes thus functions as an important regulator of cancer prevention and the physiology of aging.
Alternative pre-mRNA splicing determines the protein output of most neuronally expressed genes. Many examples have been described of protein function being modulated by coding changes in different mRNA isoforms. Several recent studies demonstrate that through the coupling of splicing to other processes of mRNA metabolism alternative splicing can also act as an on/off switch for gene expression. Other regulated splicing events may determine how an mRNA is utilized in its later cytoplasmic life by changing its localization or translation. These studies make clear that the multiple steps of post-transcriptional gene regulation are strongly linked. Together these regulatory process play key roles in all aspects of the cell biology of neurons, from their initial differentiation, to their choice of connections, and finally to their function with mature circuits.
RNA binding proteins; nonsense-mediated mRNA decay; intron retention; RNA localization; post-transcriptional gene regulation
•Nuclear localised lncRNAs regulate the expression of both local and distal genes.•lncRNAs can function locally to regulate enhancer–promoter interactions.•lncRNAs can interact with chromatin at many different locations genome wide.•RNA–protein–DNA and RNA–DNA interactions guide lncRNAs to their target sites.
Several nuclear localised intergenic long noncoding RNAs (lncRNAs) have been ascribed regulatory roles in transcriptional control and their number is growing rapidly. Initially, these transcripts were shown to function locally, near their sites of synthesis, by regulating the expression of neighbouring genes. More recently, lncRNAs have been demonstrated to interact with chromatin at several thousand different locations across multiple chromosomes and to modulate large-scale gene expression programs. Although the molecular mechanisms involved in targeting lncRNAs to distal binding sites remain poorly understood, the spatial organisation of the genome may have a role in specifying lncRNA function. Recent advances indicate that intergenic lncRNAs may exert more widespread effects on gene regulation than previously anticipated.
long noncoding RNA; transcription; chromatin conformation; RNA–protein interactions
The cell cycle requires cells to duplicate their chromatin, DNA, and histones, while retaining a subset of epigenetic marks, in a highly coordinated manner. The WEE1 kinase was identified as an important regulator during S phase, preventing entry into mitosis until DNA replication has been completed. Interestingly, WEE1 has also emerged as a key player in regulating histone synthesis. It phosphorylates histone H2B at tyrosine 37 in the nucleosomes found upstream of the histone gene cluster, which suppresses histone transcription in late S phase. These observations highlight a dual role for WEE1 as both a mitotic gatekeeper and a surveyor of chromatin synthesis, providing a direct link between epigenetics and cell cycle progression. Importantly, this link has implications for the design of novel epigenetic inhibitors targeting cancers that display elevated expression of this kinase.
WEE1; Histones; Tyrosine phosphorylation; Epigenetics; Cancer; Cell cycle
Cell-cell fusion in sexually reproducing organisms is a mechanism to merge gamete genomes, and in multicellular organisms, it is a strategy to sculpt organs such as muscles, bones, and placenta. Moreover, this mechanism has been implicated in pathological conditions such as infection and cancer. Study of genetic model organisms has uncovered a unifying principle: cell fusion is a genetically programmed process. This process can be divided in three stages: (i) competence: cell induction and differentiation, (ii) commitment: cell determination, migration and adhesion, and (iii) cell fusion: membrane merging and cytoplasmic mixing. Recent work has led to the discovery of fusogens, cell fusion proteins that are necessary and sufficient to fuse cell membranes. Two unrelated families of fusogens have been discovered, one in mouse placenta and one in Caenorhabditis elegans (Syncytins and F proteins, respectively). Current research aims to identify new fusogens and determine the mechanisms by which fusogens merge membranes.
The ethical landscape in the field of genomics is rapidly shifting. Plummeting sequencing costs, along with ongoing advances in bioinformatics, now make it possible to generate an enormous volume of genomic data about vast numbers of people. The informational richness, complexity, and frequently uncertain meaning of these data, coupled with evolving norms surrounding the sharing of data and samples and persistent privacy concerns, have generated a range of approaches to the ethical management of genomic information. As calls increase for the expanded use of broad or even open consent, and as controversy grows about how best to handle incidental genomic findings, these approaches, informed by normative analysis and empirical data, will continue to evolve alongside the science.
ethics; informed consent; privacy; identifiability; data sharing; return of results
Variation in voluntary exercise behavior is an important determinant of long-term human health. Increased physical activity is used as a preventative measure or therapeutic intervention for disease, and a sedentary lifestyle has generally been viewed as unhealthy. Predisposition to engage in voluntary activity is heritable and induces protective metabolic changes, but its complex genetic/genomic architecture has only recently begun to emerge. We first present a brief historical perspective and summary of the known benefits of voluntary exercise. Second, we describe human and mouse model studies using genomic and transcriptomic approaches to reveal the genetic architecture of exercise. Third, we discuss the merging of genomic information and physiological observations, revealing systems and networks that lead to a more complete mechanistic understanding of how exercise protects against disease pathogenesis. Finally, we explore potential regulation of physical activity through epigenetic mechanisms, including those that persist across multiple generations.
wheel running; physical activity; quantitative trait loci (QTL); expression quantitative trait loci (eQTL); genomics; collaborative cross
The premise of genetic analysis is that a causal link exists between phenotypic and allelic variation. Yet it has long been documented that mutant phenotypes are not a simple result of a single DNA lesion, but rather are due to interactions of the focal allele with other genes and the environment. Although an experimentally rigorous approach focused on individual mutations and isogenic control strains has facilitated amazing progress within genetics and related fields, a glimpse back suggests that a vast complexity has been omitted from our current understanding of allelic effects. Armed with traditional genetic analyses and the foundational knowledge they have provided, we argue that the time and tools are ripe to return to the under-explored aspects of gene function and embrace the context-dependent nature of genetic effects. We assert that a broad understanding of genetic effects and the evolutionary dynamics of alleles requires identifying how mutational outcomes depend upon the “wild-type” genetic background. Furthermore, we discuss how best to exploit genetic background effects to broaden genetic research programs.
Genetic Background; Epistasis; Genotype by Environment Interaction; Genetic Analysis; Penetrance; Expressivity
•Multiple mechanisms coordinate the cell cycle and neuronal differentiation.•Lengthening of G1 phase is functionally important for differentiation.•Cell cycle components can directly and independently affect neurogenesis.•Differentiation factors can directly affect the cell cycle structure and machinery.
The intricate balance between proliferation and differentiation is of fundamental importance in the development of the central nervous system (CNS). The division versus differentiation decision influences both the number and identity of daughter cells produced, thus critically shaping the overall microstructure and function of the CNS. During the past decade, significant advances have been made to characterise the changes in the cell cycle during differentiation, and to uncover the multiple bidirectional links that coordinate these two processes. Here, we explore the nature and mechanistic basis of these links in the context of the developing CNS, highlighting new insights into transcriptional, post-translational, and epigenetic levels of interaction.
cell cycle; differentiation; neurogenesis
Genotype-phenotype relations are usually inferred from a deterministic point of view. For example, quantitative trait loci (QTL), which describe regions of the genome associated with a particular phenotype, are based on a mean trait difference between genotype categories. However, living systems comprise huge numbers of cells (the ‘particles’ of biology). Each cell can exhibit substantial phenotypic individuality, which can have dramatic consequences at the organismal level. Now, with technology capable of interrogating individual cells, it is time to consider how genotypes shape the probability laws of single cell traits. The possibility of mapping single cell probabilistic trait loci (PTL), which link genomic regions to probabilities of cellular traits, is a promising step in this direction. This approach requires thinking about phenotypes in probabilistic terms, a concept that statistical physicists have been applying to particles for a century. Here, I describe PTL and discuss their potential to enlarge our understanding of genotype-phenotype relations.
QTL; GWAS; probabilistic trait locus (PTL); single cell; stochasticity; complex traits
Mobile elements compose more than half of the human genome, but until recently their large-scale detection was time-consuming and challenging. With the development of new high-throughput sequencing technologies, the complete spectrum of mobile element variation in humans can now be identified and analyzed. Thousands of new mobile element insertions have been discovered, yielding new insights into mobile element biology, evolution, and genomic variation. We review several high-throughput methods, with an emphasis on techniques that specifically target mobile element insertions in humans, and we highlight recent applications of these methods in evolutionary studies and in the analysis of somatic alterations in human cancers.
retrotransposon; mobile DNA element; high-throughput sequencing; polymorphism; somatic insertion; cancer
Cohesins are mutated in a significant number of tumors of various types making them an attractive target for chemotherapeutic intervention. However, cohesins have a spectrum of cellular roles including sister chromatid cohesion, transcription, replication, and repair. Which of these roles are central to cancer biology and which roles can be exploited for therapeutic intervention? Genetic interaction networks in yeast have identified synthetic lethal interactions between mutations in cohesin and replication fork mediators. These interactions are conserved in worms and in human cells suggesting that inhibition of replication fork stability mediators such as poly (ADP-ribose) polymerase (PARP) could result in the specific killing of tumors with cohesin mutations. These findings also highlight the utility of genetic interaction networks in model organisms for the identification of clinically relevant interactions. Here we review this type of approach, emphasizing the power of synthetic lethal interactions to reveal new avenues for development of cancer therapeutics.
synthetic lethality; cohesion; replication fork; PARP; cancer; genetic networks
Progress in evolutionary genomics is tightly coupled with the development of new technologies to collect high-throughput data. The availability of next-generation sequencing technologies has the potential to revolutionize genomic research and enable us to focus on a large number of outstanding questions that previously could not be addressed effectively. Indeed, we are now able to study genetic variation on a genome-wide scale, characterize gene regulatory processes at unprecedented resolution, and soon, we expect that individual labs might be able to rapidly sequence new genomes. However, at present, the analysis of next-generation sequencing data is challenging, in particular because most sequencing platforms provide short reads, which are difficult to align and assemble. In addition, only little is known about sources of variation that are associated with next-generation sequencing study designs. A better understanding of the sources of error and bias in sequencing data is essential, especially in the context of studies of variation at dynamic quantitative traits.