Genetics最新文献

Chromatin insulators are major determinants of chromosome architecture. Specific architectures induced by insulators profoundly influence nuclear processes, including how enhancers and promoters interact over long distances and between homologous chromosomes. Insulators can pair with copies of themselves in trans to facilitate homolog pairing. They can also pair with other insulators, sometimes with great specificity, inducing long-range chromosomal loops. Contrary to their canonical function of enhancer blocking, these loops can bring distant enhancers and promoters together to activate gene expression, while at the same time blocking other interactions in cis. The details of these effects depend on the choice of pairing partner, and on the orientation specificity of pairing, implicating the 3-dimensional architecture as a major functional determinant. Here we dissect the homie insulator from the Drosophila even skipped (eve) locus, to understand its substructure. We test pairing function based on homie-carrying transgenes interacting with endogenous eve. The assay is sensitive to both pairing strength and orientation. Using this assay, we found that a Su(Hw) binding site in homie is required for efficient long-range interaction, although some activity remains without it. This binding site also contributes to the canonical insulator activities of enhancer blocking and barrier function. Based on this and other results from our functional dissection, each of the canonical insulator activities, chromosomal loop formation, enhancer blocking, and barrier activity, are partially separable. Our results show the complexity inherent in insulator functions, which can be provided by an array of different proteins with both shared and distinct properties.

The contributions of genetic interactions to natural trait variation are challenging to estimate experimentally, as current approaches for detecting epistasis are often underpowered. Powerful mapping approaches such as bulk segregant analysis, wherein individuals with extreme phenotypes are pooled for genotyping, obscure epistasis by averaging over genotype combinations. To accurately characterize and quantify epistasis underlying natural trait variation, we have engineered strains of the budding yeast Saccharomyces cerevisiae to enable crosses where one parent's chromosome is fixed while the rest of the chromosomes segregate. These crosses allow us to use bulk segregant analysis to identify quantitative trait loci (QTL) whose effects depend on alleles on the fixed parental chromosome, indicating a genetic interaction with that chromosome. Our method, which we term epic-QTL (for epistatic-with-chromosome QTL) analysis, can thus identify interaction loci with high statistical power. Here we perform epic-QTL analysis of copper resistance with chromosome I or VIII fixed in a cross between divergent naturally derived strains. We find seven loci that interact significantly with chromosome VIII and none that interact with chromosome I, the smallest of the 16 budding yeast chromosomes. Each of the seven interactions alters the magnitude, rather than the direction, of an additive QTL effect. We also show that fixation of one source of variation-in this case chromosome VIII, which contains the large-effect QTL mapping to CUP1-increases power to detect the contributions of other loci to trait differences.

Tudor domain-containing proteins are conserved across the animal kingdom for their function in germline development and fertility. Previously, we demonstrated that Tudor domain-containing protein 5-like (Tdrd5l) plays an important role in the germline where it promotes male identity. However, Tdrd5l is also expressed in both the ovary and testis during later stages of germline development, suggesting that it plays a role in germline differentiation in both sexes. We found that Tdrd5l localizes to a potentially novel germline body and plays a role in post-transcriptional gene regulation. Additionally, embryos laid by Tdrd5l-mutant females exhibited reduced viability and displayed dorsal appendage defects suggesting a failure of proper dorsal-ventral (D/V) patterning. As D/V patterning is dependent on gurken (grk), we examined Grk expression during oogenesis. We observed premature accumulation of Grk protein in nurse cells indicating that translation is no longer properly repressed during mRNA transport to the oocyte. We also observed increased nurse cell accumulation of the cytoplasmic polyadenylation element binding protein Oo18 RNA-Binding Protein (Orb or CPEB), a translational activator of grk. Decreasing orb function was able to partially rescue the Tdrd5l-mutant phenotype, and so defects in Orb are likely a primary cause of the defects in Tdrd5l mutants. Our data indicate that Tdrd5l is important for translational repression of maternal mRNAs such as orb, and possibly others, following their synthesis in the nurse cells and during their transport to the oocyte.

Understanding how diverse cell types come together to form a functioning brain relies on the ability to specifically target these cells. This is often done using genetic tools such as the GAL4/UAS system in Drosophila melanogaster. Surprisingly, despite its extensive usage during studies of the aging brain, detailed spatiotemporal characterization of GAL4 driver lines in adult flies has been lacking. Here, we show that 3 commonly used neuronal drivers (elav[C155]-GAL4, nSyb[R57C10]-GAL4, and ChAT-GAL4) and the commonly used glial driver repo-GAL4 all show rapid and pronounced decreases in activity over the first 1.5 weeks of adult life, with activity becoming undetectable in some regions after 30 days (at 18°C). In addition to an overall decrease in GAL4 activity over time, we found notable differences in spatial patterns, mostly occurring soon after eclosion. Although all lines showed these changes, the nSyb-GAL4 line exhibited the most consistent and stable expression patterns over aging. Our findings suggest that gene transcription of key loci decreases in the aged brain, a finding broadly similar to previous work in mammalian brains. Our results also raise questions over past work on long-term expression of disease models in the brain and stress the need to find better genetic tools for ageing studies.

Studying mutation in healthy somatic tissues is the key for understanding the genesis of cancer and other genetic diseases. Mutation rate varies from site to site in the human genome by up to 100-fold and is influenced by numerous epigenetic and genetic factors including GC content, trinucleotide sequence context, and DNAse accessibility. These factors influence mutation at both local and regional scales and are often interrelated with one another, meaning that predicting mutability or uncovering its drivers requires modelling multiple factors and scales simultaneously. Historically, most investigations have focused either on analyzing the local sequence scale through triplet signatures or on examining the impact of epigenetic processes at larger scales, but not both concurrently. Additionally, sequencing technology limitations have restricted analyses of healthy mutations to coding regions (RNA-seq) or to those that have been influenced by selection (e.g. bulk samples from cancer tissue). Here, we leverage single-cell mutations and present a comprehensive analysis of epigenetic and genetic factors at multiple scales in the germline and 3 healthy somatic tissues. We create models that predict mutability with on average 2% error and find up to 63-fold variation among sites within the same tissue. We observe varying degrees of similarity between tissues: the mutability of genomic positions was 93.4% similar between liver and germline tissues, but sites in germline and skin were only 85.9% similar. We observe both universal and tissue-specific mutagenic processes in healthy tissues, with implications for understanding the maintenance of germline vs soma and the mechanisms underlying early tumorigenesis.

Experimental evolution studies are common in agricultural research, where they are often deemed "long-term selection." These are often used to perform selection mapping, which involves identifying markers that were putatively under selection based on finding signals of selection left in the genome. A challenge of previous selection mapping studies, especially in agricultural research, has been the specification of robust significance thresholds. This is in large part because long-term selection studies in crops have rarely included replication. Usually, significance thresholds in long-term selection experiments are based on outliers from an empirical distribution. This approach is prone to missing true positives or including false positives. Under laboratory conditions with model species, replicated selection has been shown to be a powerful tool, especially for the specification of significance thresholds. Another challenge is that commonly used single-marker-based statistics may identify neutral linked loci which have hitchhiked along with regions that are actually under selection. In this study, we conducted divergent, replicated selection for short and tall plant height in a random-mating maize population under real field conditions. Selection of the 5% tallest and shortest plants was conducted for 3 generations. Significance thresholds were specified using the false discovery rate for selection (FDRfS) based on a window-based statistic applied to a statistic leveraging replicated selection (FSTSum). Overall, we found 2 significant regions putatively under selection. One region was located on chromosome 3 close to the plant-height genes Dwarf1 and iAA8. We applied a haplotype block analysis to further dissect the pattern of selection in significant regions of the genome. We observed patterns of strong selection in the subpopulations selected for short plant height on chromosome 3.

Demographic inference methods in population genetics typically assume that the ancestry of a sample can be modeled by the Kingman coalescent. A defining feature of this stochastic process is that it generates genealogies that are binary trees: no more than two ancestral lineages may coalesce at the same time. However, this assumption breaks down under several scenarios. For example, pervasive natural selection and extreme variation in offspring number can both generate genealogies with "multiple-merger" events in which more than two lineages coalesce instantaneously. Therefore, detecting violations of the Kingman assumptions (e.g. due to multiple mergers) is important both for understanding which forces have shaped the diversity of a population and for avoiding fitting misspecified models to data. Current methods to detect deviations from Kingman coalescence in genomic data rely primarily on the site frequency spectrum (SFS). However, the signatures of some non-Kingman processes (e.g. multiple mergers) in the SFS are also consistent with a Kingman coalescent with a time-varying population size. Here, we present a new statistical test for determining whether the Kingman coalescent with any population size history is consistent with population data. Our approach is based on information contained in the two-site joint frequency spectrum (2-SFS) for pairs of linked sites, which has a different dependence on the topologies of genealogies than the SFS. Our statistical test is global in the sense that it can detect when the genome-wide genetic diversity is inconsistent with the Kingman model, rather than detecting outlier regions, as in selection scan methods. We validate this test using simulations, and then apply it to demonstrate that genomic diversity data from Drosophila melanogaster is inconsistent with the Kingman coalescent.

Population genetic theory, and the empirical methods built upon it, often assume that individuals pair randomly for reproduction. However, natural populations frequently violate this assumption, which may potentially confound genome-wide association studies, selection scans, and demographic inference. Within several recently admixed human populations, empirical genetic studies have reported a correlation in global ancestry proportion between spouses, referred to as ancestry-assortative mating. Here, we use forward genomic simulations to link correlations in global ancestry proportion between mates to the underlying mechanistic mate-choice process. We consider the impacts of two types of mate-choice model, using either ancestry-based preferences or social groups as the basis for mate pairing. We find that multiple mate-choice models can produce the same correlations in global ancestry proportion between spouses; however, we also highlight alternative analytic approaches and circumstances in which these models may be distinguished. With this work, we seek to highlight potential pitfalls when interpreting correlations in empirical data as evidence for a particular model of human mating practices, as well as to offer suggestions toward development of new best practices for analysis of human ancestry-assortative mating.

Transposable elements are DNA sequences that can move and replicate within genomes. Broadly, there are 2 types: autonomous elements, which encode the necessary enzymes for transposition, and nonautonomous elements, which rely on the enzymes produced by autonomous elements for their transposition. Nonautonomous elements have been proposed to regulate the numbers of transposable elements, which is a possible explanation for the persistence of transposition activity over long evolutionary times. However, previous modeling studies indicate that interactions between autonomous and nonautonomous elements usually result in the extinction of one type. Here, we study a stochastic model that allows for the stable coexistence of autonomous and nonautonomous retrotransposons. We determine the conditions for this coexistence and derive an analytical expression for the stationary distribution of their copy numbers, showing that nonautonomous elements regulate stochastic fluctuations and the number of autonomous elements in stationarity. We find that the stationary variances of each element can be expressed as a function of the average copy numbers and their covariance, enabling data comparison and model validation. These results suggest that continued transposition activity of transposable elements, regulated by nonautonomous elements, is a possible evolutionary outcome that could for example explain the long coevolutionary history of autonomous LINE1 and nonautonomous Alu element transposition in the human ancestry.

Hybrid incompatibilities are a critical component of species barriers and may arise due to negative interactions between divergent regulatory elements in parental species. We used a comparative approach to identify common themes in the regulatory phenotypes associated with hybrid male sterility in two divergent rodent crosses, dwarf hamsters and house mice. We investigated three potential characteristic gene expression phenotypes in hybrids including the propensity of transgressive differentially expressed genes toward over or underexpression, the influence of developmental stage on patterns of misexpression, and the role of the sex chromosomes on misexpression phenotypes. In contrast to near pervasive overexpression in hybrid house mice, we found that misexpression in hybrid dwarf hamsters was dependent on developmental stage. In both house mouse and dwarf hamster hybrids, however, misexpression increased with the progression of spermatogenesis, although to varying extents and with potentially different consequences. In both systems, we detected sex chromosome-specific overexpression in stages of spermatogenesis where inactivated X chromosome expression was expected, but the hybrid overexpression phenotypes were fundamentally different. Importantly, misexpression phenotypes support the presence of multiple developmental blocks to spermatogenesis in dwarf hamster hybrids, including a potential role of meiotic stalling or breakdown early in spermatogenesis. Collectively, we demonstrate that while there are some similarities in hybrid expression phenotypes of house mice and dwarf hamsters, there are also clear differences that point toward unique mechanisms underlying hybrid male sterility. Our results highlight the potential of comparative approaches in helping to understand the causes and consequences of disrupted gene expression in speciation.