Using gene map science to evaluate the genetic map and eliminate disease

Genetic News

Sleep is crucial for survival and well-being. This behavioral and physiological state has been studied in all major genetically accessible model animals, including rodents, fish, flies, and worms. Genetic and optogenetic studies have identified several neurons that control sleep, making it now possible to compare circuit mechanisms across species. The "motor" of sleep across animal species is formed by neurons that depolarize at the onset of sleep to actively induce this state by directly inhibiting wakefulness. These sleep-inducing neurons are themselves controlled by inhibitory or activating upstream pathways, which act as the "drivers" of the sleep motor: arousal inhibits "sleep-active" neurons whereas various sleep-promoting "tiredness" pathways converge onto sleep-active neurons to depolarize them. This review provides the first overview of sleep-active neurons across the major model animals. The occurrence of sleep-active neurons and their regulation by upstream pathways in both vertebrate and invertebrate species suggests that these neurons are general and ancient components that evolved early in the history of nervous systems.

Understanding how activity patterns in specific neural circuits coordinate an animal’s behavior remains a key area of neuroscience research. Genetic tools and a brain of tractable complexity make Drosophila a premier model organism for these studies. Here, we review the wealth of reagents available to map and manipulate neuronal activity with light.

This FlyBook chapter summarizes the history and the current state of our understanding of the Wingless signaling pathway. Wingless, the fly homolog of the mammalian Wnt oncoproteins, plays a central role in pattern generation during development. Much of what we know about the pathway was learned from genetic and molecular experiments in Drosophila melanogaster, and the core pathway works the same way in vertebrates. Like most growth factor pathways, extracellular Wingless/Wnt binds to a cell surface complex to transduce signal across the plasma membrane, triggering a series of intracellular events that lead to transcriptional changes in the nucleus. Unlike most growth factor pathways, the intracellular events regulate the protein stability of a key effector molecule, in this case Armadillo/β-catenin. A number of mysteries remain about how the "destruction complex" destabilizes β-catenin and how this process is inactivated by the ligand-bound receptor complex, so this review of the field can only serve as a snapshot of the work in progress.

Arabidopsis thaliana could have easily escaped human scrutiny. Instead, Arabidopsis has become the most widely studied plant in modern biology despite its absence from the dinner table. Pairing diminutive stature and genome with prodigious resources and tools, Arabidopsis offers a window into the molecular, cellular, and developmental mechanisms underlying life as a multicellular photoautotroph. Many basic discoveries made using this plant have spawned new research areas, even beyond the verdant fields of plant biology. With a suite of resources and tools unmatched among plants and rivaling other model systems, Arabidopsis research continues to offer novel insights and deepen our understanding of fundamental biological processes.

Cryptococcus neoformans is a fungal pathogen that claims hundreds of thousands of lives annually. Targeted genetic manipulation through biolistic transformation in C. neoformans drove the investigation of this clinically important pathogen at the molecular level. Although costly and inefficient, biolistic transformation remains the major method for editing the Cryptococcus genome as foreign DNAs introduced by other methods such as electroporation are predominantly not integrated into the genome. Although the majority of DNAs introduced by biolistic transformation are stably inherited, the transformation efficiency and the homologous integration rate (~1–10%) are low. Here, we developed a Transient CRISPR (clustered regularly interspaced short palindromic repeat)-Cas9 coupled with Electroporation (TRACE) system for targeted genetic manipulations in the C. neoformans species complex. This method took advantages of efficient genome integration due to double-strand breaks created at specific sites by the transient CRISPR-Cas9 system and the high transformation efficiency of electroporation. We demonstrated that TRACE can efficiently generate precise single-gene deletion mutants using the ADE2 locus as an example. This system can also effectively delete multiple genes in a single transformation, as evident by the successful generation of quadruple mfα1234 mutants. In addition to generating gene deletion mutants, we complemented the ade2 mutant by integrating a wild-type ADE2 allele at the "safe haven" region (SH2) via homologous recombination using TRACE. Interestingly, introduced DNAs can be inserted at a designated genetic site without any homologous sequences, opening up numerous other applications. We expect that TRACE, an efficient, versatile, and cost-effective gene editing approach, will greatly accelerate research in this field.

The ability to predict the agronomic performance of single-crosses with high precision is essential for selecting superior candidates for hybrid breeding. With recent technological advances, thousands of new parent lines, and, consequently, millions of new hybrid combinations are possible in each breeding cycle, yet only a few hundred can be produced and phenotyped in multi-environment yield trials. Well established prediction approaches such as best linear unbiased prediction (BLUP) using pedigree data and whole-genome prediction using genomic data are limited in capturing epistasis and interactions occurring within and among downstream biological strata such as transcriptome and metabolome. Because mRNA and small RNA (sRNA) sequences are involved in transcriptional, translational and post-translational processes, we expect them to provide information influencing several biological strata. However, using sRNA data of parent lines to predict hybrid performance has not yet been addressed. Here, we gathered genomic, transcriptomic (mRNA and sRNA) and metabolomic data of parent lines to evaluate the ability of the data to predict the performance of untested hybrids for important agronomic traits in grain maize. We found a considerable interaction for predictive ability between predictor and trait, with mRNA data being a superior predictor for grain yield and genomic data for grain dry matter content, while sRNA performed relatively poorly for both traits. Combining mRNA and genomic data as predictors resulted in high predictive abilities across both traits and combining other predictors improved prediction over that of the individual predictors alone. We conclude that downstream "omics" can complement genomics for hybrid prediction, and, thereby, contribute to more efficient selection of hybrid candidates.

Biological evolution generates a surprising amount of site-specific variability in protein sequences. Yet, attempts at modeling this process have been only moderately successful, and current models based on protein structural metrics explain, at best, 60% of the observed variation. Surprisingly, simple measures of protein structure, such as solvent accessibility, are often better predictors of site-specific variability than more complex models employing all-atom energy functions and detailed structural modeling. We suggest here that these more complex models perform poorly because they lack consideration of the evolutionary process, which is, in part, captured by the simpler metrics. We compare protein sequences that are computationally designed to sequences that are computationally evolved using the same protein-design energy function and to homologous natural sequences. We find that, by a wide variety of metrics, evolved sequences are much more similar to natural sequences than are designed sequences. In particular, designed sequences are too conserved on the protein surface relative to natural sequences, whereas evolved sequences are not. Our results suggest that evolutionary simulation produces a realistic sampling of sequence space. By contrast, protein design—at least as currently implemented—does not. Existing energy functions seem to be sufficiently accurate to correctly describe the key thermodynamic constraints acting on protein sequences, but they need to be paired with realistic sampling schemes to generate realistic sequence alignments.

Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure (e.g., a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0–1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an effect from an LMM GWAS difficult. In this study, we derived transformations from the genetic effects estimated under the LMM to the OR that only rely on summary statistics. To test the proposed transformations, we used real genotypes from two large, publicly available data sets to simulate all-or-none phenotypes for a set of scenarios that differ in underlying model, disease prevalence, and heritability. Furthermore, we applied these transformations to GWAS summary statistics for type 2 diabetes generated from 108,042 individuals in the UK Biobank. In both simulation and real-data application, we observed very high concordance between the transformed OR from the LMM and either the simulated truth or estimates from logistic regression. The transformations derived and validated in this study improve the comparability of results from prospective and already performed LMM GWAS on complex diseases by providing a reliable transformation to a common comparative scale for the genetic effects.

Meiotic recombination shuffles genetic information from sexual species into gametes to create novel combinations in offspring. Thus, recombination is an important factor in inheritance, adaptation, and responses to selection. However, recombination is not a static parameter; meiotic recombination rate is sensitive to variation in the environment, especially temperature. That recombination rates change in response to both increases and decreases in temperature was reported in Drosophila a century ago, and since then in several other species. But it is still unclear what the underlying mechanism is, and whether low- and high-temperature effects are mechanistically equivalent. Here, we show that, as in Drosophila, both high and low temperatures increase meiotic crossovers in Arabidopsis thaliana. We show that, from a nadir at 18°, both lower and higher temperatures increase recombination through additional class I (interfering) crossovers. However, the increase in crossovers at high and low temperatures appears to be mechanistically at least somewhat distinct, as they differ in their association with the DNA repair protein MLH1. We also find that, in contrast to what has been reported in barley, synaptonemal complex length is negatively correlated with temperature; thus, an increase in chromosome axis length may account for increased crossovers at low temperature in A. thaliana, but cannot explain the increased crossovers observed at high temperature. The plasticity of recombination has important implications for evolution and breeding, and also for the interpretation of observations of recombination rate variation among natural populations.

Meiosis is a highly regulated process, partly due to the need to break and then repair DNA as part of the meiotic program. Post-translational modifications are widely used during meiotic events to regulate steps such as protein complex formation, checkpoint activation, and protein attenuation. In this paper, we investigate how proteins that are obligatory components of the SUMO (small ubiquitin-like modifier) pathway, one such post-translational modification, affect the Caenorhabditis elegans germline. We show that UBC-9, the E2 conjugation enzyme, and the C. elegans homolog of SUMO, SMO-1, localize to germline nuclei throughout prophase I. Mutant analysis of smo-1 and ubc-9 revealed increased recombination intermediates throughout the germline, originating during the mitotic divisions. SUMOylation mutants also showed late meiotic defects including defects in the restructuring of oocyte bivalents and endomitotic oocytes. Increased rates of noninterfering crossovers were observed in ubc-9 heterozygotes, even though interfering crossovers were unaffected. We have also identified a physical interaction between UBC-9 and DNA repair protein MRE-11. ubc-9 and mre-11 null mutants exhibited similar phenotypes at germline mitotic nuclei and were synthetically sick. These phenotypes and genetic interactions were specific to MRE-11 null mutants as opposed to RAD-50 or resection-defective MRE-11. We propose that the SUMOylation pathway acts redundantly with MRE-11, and in this process MRE-11 likely plays a structural role.

Histone deacetylases (HDACs) catalyze the removal of acetyl groups from acetylated histone tails that consequently interact more closely with DNA, leading to chromatin state refractory to transcription. Zea mays HDA108 belongs to the Rpd3/HDA1 HDAC family and is ubiquitously expressed during development. The newly isolated hda108/hda108 insertional mutant exhibited many developmental defects: significant reduction in plant height, alterations of shoot and leaf development, and alterations of inflorescence patterning and fertility. Western blot analyses and immunolocalization experiments revealed an evident increase in histone acetylation, accompanied by a marked reduction in H3K9 dimethylation, in mutant nuclei. The DNA methylation status, in the CHG sequence context, and the transcript level of ribosomal sequences were also affected in hda108 mutants, while enrichment in H3 and H4 acetylation characterizes both repetitive and nonrepetitive transcriptional up-regulated loci. RNA-Seq of both young leaf and anthers indicated that transcription factor expression is highly affected and that the pollen developmental program is disrupted in hda108 mutants. Crosses between hda108/hda108 and epiregulator mutants did not produce any double mutant progeny indicating possible genetic interactions of HDA108 with distinct epigenetic pathways. Our findings indicate that HDA108 is directly involved in regulation of maize development, fertility, and epigenetic regulation of genome activity.

Extracellular matrix barriers and inducible cytoprotective genes form successive lines of defense against chemical and microbial environmental stressors. The barrier in nematodes is a collagenous extracellular matrix called the cuticle. In Caenorhabditis elegans, disruption of some cuticle collagen genes activates osmolyte and antimicrobial response genes. Physical damage to the epidermis also activates antimicrobial responses. Here, we assayed the effect of knocking down genes required for cuticle and epidermal integrity on diverse cellular stress responses. We found that disruption of specific bands of collagen, called annular furrows, coactivates detoxification, hyperosmotic, and antimicrobial response genes, but not other stress responses. Disruption of other cuticle structures and epidermal integrity does not have the same effect. Several transcription factors act downstream of furrow loss. SKN-1/Nrf and ELT-3/GATA are required for detoxification, SKN-1/Nrf is partially required for the osmolyte response, and STA-2/Stat and ELT-3/GATA for antimicrobial gene expression. Our results are consistent with a cuticle-associated damage sensor that coordinates detoxification, hyperosmotic, and antimicrobial responses through overlapping, but distinct, downstream signaling.

Yeast exomer is a heterotetrameric complex that is assembled at the trans-Golgi network, which is required for the delivery of a distinct set of proteins to the plasma membrane using ChAPs (Chs5-Arf1 binding proteins) Chs6 and Bch2 as dedicated cargo adaptors. However, our results show a significant functional divergence between them, suggesting an evolutionary specialization among the ChAPs. Moreover, the characterization of exomer mutants in several fungi indicates that exomer’s function as a cargo adaptor is a late evolutionary acquisition associated with several gene duplications of the fungal ChAPs ancestor. Initial gene duplication led to the formation of the two ChAPs families, Chs6 and Bch1, in the Saccaromycotina group, which have remained functionally redundant based on the characterization of Kluyveromyces lactis mutants. The whole-genome duplication that occurred within the Saccharomyces genus facilitated a further divergence, which allowed Chs6/Bch2 and Bch1/Bud7 pairs to become specialized for specific cellular functions. We also show that the behavior of S. cerevisiae Chs3 as an exomer cargo is associated with the presence of specific cytosolic domains in this protein, which favor its interaction with exomer and AP-1 complexes. However, these domains are not conserved in the Chs3 proteins of other fungi, suggesting that they arose late in the evolution of fungi associated with the specialization of ChAPs as cargo adaptors.

Basement membranes are extracellular matrices essential for embryonic development in animals. Peroxidasins are extracellular peroxidases implicated in the unique sulfilimine cross-links between type IV basement membrane collagens. Loss of function in the Caenorhabditis elegans peroxidasin PXN-2 results in fully penetrant embryonic or larval lethality. Using genetic suppressor screening, we find that the requirement for PXN-2 in development can be bypassed by gain of function in multiple genes encoding other basement membrane components, or proteins implicated in cell-matrix attachment. We identify multiple alleles of let-805, encoding the transmembrane protein myotactin, which suppress phenotypes of pxn-2 null mutants and of other basement membrane mutants such as F-spondin/spon-1. These let-805 suppressor alleles cause missense alterations in two pairs of FNIII repeats in the extracellular domain; they act dominantly and have no detectable phenotypes alone, suggesting they cause gain of function. We also identify suppressor missense mutations affecting basement membrane components type IV collagen (emb-9, let-2) and perlecan (unc-52), as well as a mutation affecting spectraplakin (vab-10), a component of the epidermal cytoskeleton. These suppressor alleles do not bypass the developmental requirement for core structural proteins of the basement membrane such as laminin or type IV collagen. In conclusion, putative gain-of-function alterations in matrix proteins or in cell-matrix receptors can overcome the requirement for certain basement membrane proteins in embryonic development, revealing previously unknown plasticity in the genetic requirements for the extracellular matrix.

Several in vitro studies have suggested that canonical microRNA (miRNA) biogenesis requires the DICER cofactors TARBP2 and PRKRA for processing of pre-miRNAs to mature miRNAs. To investigate the roles of TARBP2 and PRKRA in miRNA biogenesis in vivo, and to determine possible functional redundancy, we first compared the phenotypes of Tarbp2 and Prkra single and double mutants. In contrast to Dicer –/– embryos, which die by embryonic day 7.5 (E7.5), single Tarbp2 –/– and Prkra –/– mice survive beyond E7.5 and either die perinatally or survive and exhibit cranial/facial abnormalities, respectively. In contrast, only a few Tarbp2 –/–; Prkra –/– double mutants survived beyond E12.5, suggesting genetic redundancy between Tarbp2 and Prkra during embryonic development. Sequencing of miRNAs from single-mutant embryos at E15.5 revealed changes in abundance and isomiR type in Tarbp2 –/–, but not Prkra –/–, embryos, demonstrating that TARBP2, but not PRKRA, functions in miRNA biogenesis of a subclass of miRNAs, and suggesting that functional redundancy between TARBP2 and PRKRA does not involve miRNA biogenesis.

In Drosophila, key developmental transitions are governed by the steroid hormone ecdysone. A number of neuropeptide-activated signaling pathways control ecdysone production in response to environmental signals, including the insulin signaling pathway, which regulates ecdysone production in response to nutrition. Here, we find that the Membrane Attack Complex/Perforin-like protein Torso-like, best characterized for its role in activating the Torso receptor tyrosine kinase in early embryo patterning, also regulates the insulin signaling pathway in Drosophila. We previously reported that the small body size and developmental delay phenotypes of torso-like null mutants resemble those observed when insulin signaling is reduced. Here we report that, in addition to growth defects, torso-like mutants also display metabolic and nutritional plasticity phenotypes characteristic of mutants with impaired insulin signaling. We further find that in the absence of torso-like, the expression of insulin-like peptides is increased, as is their accumulation in insulin-producing cells. Finally, we show that Torso-like is a component of the hemolymph and that it is required in the prothoracic gland to control developmental timing and body size. Taken together, our data suggest that the secretion of Torso-like from the prothoracic gland influences the activity of insulin signaling throughout the body in Drosophila.

Proper mitochondrial activity depends upon proteins encoded by genes in the nuclear and mitochondrial genomes that must interact functionally and physically in a precisely coordinated manner. Consequently, mito-nuclear allelic interactions are thought to be of crucial importance on an evolutionary scale, as well as for manifestation of essential biological phenotypes, including those directly relevant to human disease. Nonetheless, detailed molecular understanding of mito-nuclear interactions is still lacking, and definitive examples of such interactions in vivo are sparse. Here we describe the characterization of a mutation in Drosophila ND23, a nuclear gene encoding a highly conserved subunit of mitochondrial complex 1. This characterization led to the discovery of a mito-nuclear interaction that affects the ND23 mutant phenotype. ND23 mutants exhibit reduced lifespan, neurodegeneration, abnormal mitochondrial morphology, and decreased ATP levels. These phenotypes are similar to those observed in patients with Leigh syndrome, which is caused by mutations in a number of nuclear genes that encode mitochondrial proteins, including the human ortholog of ND23. A key feature of Leigh syndrome, and other mitochondrial disorders, is unexpected and unexplained phenotypic variability. We discovered that the phenotypic severity of ND23 mutations varies depending on the maternally inherited mitochondrial background. Sequence analysis of the relevant mitochondrial genomes identified several variants that are likely candidates for the phenotypic interaction with mutant ND23, including a variant affecting a mitochondrially encoded component of complex I. Thus, our work provides an in vivo demonstration of the phenotypic importance of mito-nuclear interactions in the context of mitochondrial disease.

Locomotion is one of the most prominent behaviors in the nematode Caenorhabditis elegans. Neuronal circuits that ultimately produce coordinated dorso-ventral sinusoidal bends mediate this behavior. Synchronized locomotion requires an intricate balance between excitation and inhibition at the neuromuscular junctions (NMJ), the complex cellular and molecular mechanisms of which are not fully understood. Here, we describe the role of a cell adhesion molecule CASY-1, which functions to maintain this balance at the NMJ. In this study, we dissect out mechanisms by which the longer CASY-1A isoform could be affecting the excitatory cholinergic signaling at the NMJ by modulating the activity of sensory neurons. Mutants in casy-1 appear to have hyperactive sensory neurons, resulting in accelerated locomotion and motor circuit activity. These sensory neurons mediate increased motor activity via enhanced glutamate release. Using genetic, pharmacological, and optogenetic manipulations, we establish that CASY-1A is required to monitor the activity of these neurons. Our study illustrates a novel neuromodulatory role of CASY-1-mediated signaling in regulating the excitation-inhibition balance of the motor circuit.

An open question in human evolution is the importance of polygenic adaptation: adaptive changes in the mean of a multifactorial trait due to shifts in allele frequencies across many loci. In recent years, several methods have been developed to detect polygenic adaptation using loci identified in genome-wide association studies (GWAS). Though powerful, these methods suffer from limited interpretability: they can detect which sets of populations have evidence for polygenic adaptation, but are unable to reveal where in the history of multiple populations these processes occurred. To address this, we created a method to detect polygenic adaptation in an admixture graph, which is a representation of the historical divergences and admixture events relating different populations through time. We developed a Markov chain Monte Carlo (MCMC) algorithm to infer branch-specific parameters reflecting the strength of selection in each branch of a graph. Additionally, we developed a set of summary statistics that are fast to compute and can indicate which branches are most likely to have experienced polygenic adaptation. We show via simulations that this method—which we call PolyGraph—has good power to detect polygenic adaptation, and applied it to human population genomic data from around the world. We also provide evidence that variants associated with several traits, including height, educational attainment, and self-reported unibrow, have been influenced by polygenic adaptation in different populations during human evolution.

Conflict between organisms can lead to a reciprocal adaptation that manifests as an increased evolutionary rate in genes mediating the conflict. This adaptive signature has been observed in RNA-interference (RNAi) pathway genes involved in the suppression of viruses and transposable elements in Drosophila melanogaster, suggesting that a subset of Drosophila RNAi genes may be locked in an arms race with these parasites. However, it is not known whether rapid evolution of RNAi genes is a general phenomenon across invertebrates, or which RNAi genes generally evolve adaptively. Here we use population genomic data from eight invertebrate species to infer rates of adaptive sequence evolution, and to test for past and ongoing selective sweeps in RNAi genes. We assess rates of adaptive protein evolution across species using a formal meta-analytic framework to combine data across species and by implementing a multispecies generalized linear mixed model of mutation counts. Across species, we find that RNAi genes display a greater rate of adaptive protein substitution than other genes, and that this is primarily mediated by positive selection acting on the genes most likely to defend against viruses and transposable elements. In contrast, evidence for recent selective sweeps is broadly spread across functional classes of RNAi genes and differs substantially among species. Finally, we identify genes that exhibit elevated adaptive evolution across the analyzed insect species, perhaps due to concurrent parasite-mediated arms races.

Variational modules, sets of pleiotropically covarying traits, affect phenotypic evolution, and therefore are predicted to reflect functional modules, such that traits within a variational module also share a common function. Such an alignment of function and pleiotropy is expected to facilitate adaptation by reducing the deleterious effects of mutations, and by allowing coordinated evolution of functionally related sets of traits. Here, we adopt a high-dimensional quantitative genetic approach using a large number of gene expression traits in Drosophila serrata to test whether functional grouping, defined by gene ontology (GO terms), predicts variational modules. Mutational or standing genetic covariance was significantly greater than among randomly grouped sets of genes for 38% of our functional groups, indicating that GO terms can predict variational modularity to some extent. We estimated stabilizing selection acting on mutational covariance to test the prediction that functional pleiotropy would result in reduced deleterious effects of mutations within functional modules. Stabilizing selection within functional modules was weaker than that acting on randomly grouped sets of genes in only 23% of functional groups, indicating that functional alignment can reduce deleterious effects of pleiotropic mutation but typically does not. Our analyses also revealed the presence of variational modules that spanned multiple functions.

Many studies have reported genetic interventions that have an effect on mouse life span; however, it is crucial to discriminate between manipulations of aging and aging-independent causes of life extension. Here, we used the Gompertz equation to determine whether previously reported aging-related mouse genes statistically affect the demographic rate of aging. Of 30 genetic manipulations previously reported to extend life span, for only two we found evidence of retarding demographic aging: Cisd2 and hMTH1. Of 24 genetic manipulations reported to shorten life span and induce premature aging features, we found evidence of five accelerating demographic aging: Casp2, Fn1, IKK-β, JunD, and Stub1. Overall, our reassessment found that only 15% of the genetic manipulations analyzed significantly affected the demographic rate of aging as predicted, suggesting that a relatively small proportion of interventions affecting longevity do so by regulating the rate of aging. By contrast, genetic manipulations affecting longevity tend to impact on aging-independent mortality. Our meta-analysis of multiple mouse longevity studies also reveals substantial variation in the controls used across experiments, suggesting that a short life span of controls is a potential source of bias. Overall, the present work leads to a reassessment of genes affecting the aging process in mice, with broad implications for our understanding of the genetics of mammalian aging and which genes may be more promising targets for drug discovery.

We present a conceptually simple, sensitive, precise, and essentially nonstatistical solution for the analysis of genome variation in haploid organisms. The generation of a Perfect Match Genomic Landscape (PMGL), which computes intergenome identity with single nucleotide resolution, reveals signatures of variation wherever a query genome differs from a reference genome. Such signatures encode the precise location of different types of variants, including single nucleotide variants, deletions, insertions, and amplifications, effectively introducing the concept of a general signature of variation. The precise nature of variants is then resolved through the generation of targeted alignments between specific sets of sequence reads and known regions of the reference genome. Thus, the perfect match logic decouples the identification of the location of variants from the characterization of their nature, providing a unified framework for the detection of genome variation. We assessed the performance of the PMGL strategy via simulation experiments. We determined the variation profiles of natural genomes and of a synthetic chromosome, both in the context of haploid yeast strains. Our approach uncovered variants that have previously escaped detection. Moreover, our strategy is ideally suited for further refining high-quality reference genomes. The source codes for the automated PMGL pipeline have been deposited in a public repository.

Insulin resistance is associated with obesity, cardiovascular disease, non-alcoholic fatty liver disease, and type 2 diabetes. These complications are exacerbated by a high-calorie diet, which we used to model type 2 diabetes in Drosophila melanogaster. Our studies focused on the fat body, an adipose- and liver-like tissue that stores fat and maintains circulating glucose. A gene regulatory network was constructed to predict potential regulators of insulin signaling in this tissue. Genomic characterization of fat bodies suggested a central role for the transcription factor Seven-up (Svp). Here, we describe a new role for Svp as a positive regulator of insulin signaling. Tissue-specific loss-of-function showed that Svp is required in the fat body to promote glucose clearance, lipid turnover, and insulin signaling. Svp appears to promote insulin signaling, at least in part, by inhibiting ecdysone signaling. Svp also impairs the immune response possibly via inhibition of antimicrobial peptide expression in the fat body. Taken together, these studies show that gene regulatory networks can help identify positive regulators of insulin signaling and metabolic homeostasis using the Drosophila fat body.

Dermatophytes include fungal species that infect humans, as well as those that also infect other animals or only grow in the environment. The dermatophyte species Trichophyton rubrum is a frequent cause of skin infection in immunocompetent individuals. While members of the T. rubrum species complex have been further categorized based on various morphologies, their population structure and ability to undergo sexual reproduction are not well understood. In this study, we analyze a large set of T. rubrum and T. interdigitale isolates to examine mating types, evidence of mating, and genetic variation. We find that nearly all isolates of T. rubrum are of a single mating type, and that incubation with T. rubrum "morphotype" megninii isolates of the other mating type failed to induce sexual development. While the region around the mating type locus is characterized by a higher frequency of SNPs compared to other genomic regions, we find that the population is remarkably clonal, with highly conserved gene content, low levels of variation, and little evidence of recombination. These results support a model of recent transition to asexual growth when this species specialized to growth on human hosts.



Genetic Diseases

When medical researchers want to investigate serious genetic diseases, they have to find ways to locate the corresponding risk genes. There are relatively few of these risk genes out of the 100,000 genes in the human cell, so it obviously is not an easy task...
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All of the genes carried by a single gamete; the DNA content of an individual, which includes all 44 autosomes, 2 sex chromosomes, and the mitochondrial DNA.