Genetics最新文献

Numerous factors have been implicated in the cell-cell interactions that lead to elimination of cells via cell competition, a context-dependent process of cell selection in somatic tissues that is based on comparisons of cellular fitness. Here, we use a series of genetic tests in Drosophila to explore the relative contribution of the pleiotropic cytokine tumor necrosis factor α (TNFα) in Myc-mediated cell competition (also known as Myc supercompetition or Myc cell competition). We find that the sole Drosophila TNF, Eiger (Egr), its receptor Grindelwald (Grnd/TNF receptor), and the adaptor proteins Traf4 and Traf6 are required to eliminate wild-type "loser" cells during Myc cell competition. Although typically the interaction between Egr and Grnd leads to cell death by activating the intracellular Jun N-terminal kinase (JNK) stress signaling pathway, our experiments reveal that many components of canonical JNK signaling are dispensable for cell death in Myc cell competition, including the JNKKK Tak1, the JNKK Hemipterous and the JNK Basket. Our results suggest that Egr/Grnd signaling participates in Myc cell competition but functions in a role that is largely independent of the JNK signaling pathway.

As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. However, this approach is out of step with some modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalizes these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.

Germline cells produce gametes, which are specialized cells essential for sexual reproduction. Germline cells first amplify through several rounds of mitosis before switching to the meiotic program, which requires specific sets of proteins for DNA recombination, chromosome pairing, and segregation. Surprisingly, we previously found that some proteins of the synaptonemal complex, a prophase I meiotic structure, are already expressed and required in the mitotic region of Drosophila females. Here, to assess if additional meiotic genes were expressed earlier than expected, we isolated mitotic and meiotic cell populations to compare their RNA content. Our transcriptomic analysis reveals that all known meiosis I genes are already expressed in the mitotic region; however, only some of them are translated. As a case study, we focused on mei-W68, the Drosophila homolog of Spo11, to assess its expression at both the mRNA and protein levels and used different mutant alleles to assay for a premeiotic function. We could not detect any functional role for Mei-W68 during homologous chromosome pairing in dividing germ cells. Our study paves the way for further functional analysis of meiotic genes expressed in the mitotic region.

Recombination breaks down genetic linkage by reshuffling existing variants onto new genetic backgrounds. These dynamics are traditionally quantified by examining the correlations between alleles, and how they decay as a function of the recombination rate. However, the magnitudes of these correlations are strongly influenced by other evolutionary forces like natural selection and genetic drift, making it difficult to tease out the effects of recombination. Here we introduce a theoretical framework for analyzing an alternative family of statistics that measure the homoplasy produced by recombination. We derive analytical expressions that predict how these statistics depend on the rates of recombination and recurrent mutation, the strength of negative selection and genetic drift, and the present-day frequencies of the mutant alleles. We find that the degree of homoplasy can strongly depend on this frequency scale, which reflects the underlying timescales over which these mutations occurred. We show how these scaling properties can be used to isolate the effects of recombination, and discuss their implications for the rates of horizontal gene transfer in bacteria.

Starvation of E. coli thyA auxotrophs for the required thymine or thymidine leads to cessation of DNA synthesis and, unexpectedly, to thymineless death (TLD). Previously, TLD-alleviating defects were identified by the candidate gene approach, for their contribution to replication initiation, fork repair, or SOS induction. However, no TLD-blocking mutations were ever found, suggesting a multifactorial nature of TLD. Since (until recently) no unbiased isolation of TLD suppressors was reported, we used enrichment after insertional mutagenesis to systematically isolate TLD suppressors. Our approach was validated by isolation of known TLD-alleviating mutants in recombinational repair. At the same time, and unexpectedly for the current TLD models, most of the isolated suppressors affected general metabolism, while the strongest suppressors impacted the central metabolism. Several temperature-sensitive (Ts)-mutants in important/essential functions, like nadA, ribB or coaA, almost completely suppressed TLD at 42°C. Since blocking protein synthesis completely by chloramphenicol prevents TLD, while reducing protein synthesis to 10% alleviates TLD only slightly, we measured the level of protein synthesis in these mutants at 42°C and found it to be 20-70% of the WT, not enough reduction to explain TLD prevention. We conclude that the isolated central metabolism mutants prevent TLD by affecting specific TLD-promoting functions.

The linear mixed model (LMM) has become a standard in genetic association studies to account for population stratification and relatedness in the samples to reduce false positives. Much recent progresses in LMM focused on approximate computations. Exact methods remained computationally demanding and without theoretical assurance. The computation is particularly challenging for multiomics studies where tens of thousands of phenotypes are tested for association with millions of genetic markers. We present IDUL and IDUL† that use iterative dispersion updates to fit LMMs, where IDUL† is a modified version of IDUL that guarantees likelihood increase between updates. Practically, IDUL and IDUL† produced identical results, both are markedly more efficient than the state-of-the-art Newton-Raphson method, and in particular, both are highly efficient for additional phenotypes, making them ideal to study genetic determinants of multiomics phenotypes. Theoretically, the LMM likelihood is asymptotically unimodal, and therefore the gradient ascent algorithm IDUL† is asymptotically exact. A software package implementing IDUL and IDUL† for genetic association studies is freely available at https://github.com/haplotype/IDUL.

Hybrid male sterility is one of the fastest evolving intrinsic reproductive barriers between recently isolated populations. A leading explanation for the evolution of hybrid male sterility involves genomic conflicts with meiotic drivers in the male germline. There are, however, few examples directly linking meiotic drive to hybrid sterility. In this study, we report that the Sex-Ratio chromosome of Drosophila pseudoobscura, which causes X-chromosome drive within the USA subspecies, causes near-complete male sterility when it is moved into the genetic background of the Bogota subspecies. In addition, we show that this new form of sterility is genetically distinct from the sterility of F1 hybrid males in crosses between USA males and Bogota females. Our observations provide a tractable study system where noncryptic drive within species is transformed into strong hybrid sterility between very young subspecies.

Hereditary tyrosinemia type 1 is an autosomal recessive disorder caused by mutations (pathogenic variants) in fumarylacetoacetate hydrolase, an enzyme involved in tyrosine degradation. Its loss results in the accumulation of toxic metabolites that mainly affect the liver and kidneys and can lead to severe liver disease and liver cancer. Tyrosinemia type 1 has a global prevalence of approximately 1 in 100,000 births but can reach up to 1 in 1,500 births in some regions of Québec, Canada. Mutating functionally related 'modifier' genes (i.e., genes that, when mutated, affect the phenotypic impacts of mutations in other genes) is an emerging strategy for treating human genetic diseases. In vivo somatic genome editing in animal models of these diseases is a powerful means to identify modifier genes and fuel treatment development. In this study, we demonstrate that mutating additional enzymes in the tyrosine catabolic pathway through liver-specific genome editing can relieve or worsen the phenotypic severity of a murine model of tyrosinemia type 1. Neonatal gene delivery using recombinant adeno-associated viral vectors expressing Staphylococcus aureus Cas9 under the control of a liver-specific promoter led to efficient gene disruption and metabolic rewiring of the pathway, with systemic effects that were distinct from the phenotypes observed in whole-body knockout models. Our work illustrates the value of using in vivo genome editing in model organisms to study the direct effects of combining pathological mutations with modifier gene mutations in isogenic settings.

We consider how the genetic architecture underlying locally adaptive traits determines the strength of a barrier to gene flow in a mainland-island model. Assuming a general life cycle, we derive an expression for the effective migration rate when local adaptation is due to genetic variation at many loci under directional selection on the island, allowing for arbitrary fitness and dominance effects across loci. We show how the effective migration rate can be combined with classical single-locus diffusion theory to accurately predict multilocus differentiation between the mainland and island at migration-selection-drift equilibrium and determine the migration rate beyond which local adaptation collapses, while accounting for genetic drift and weak linkage. Using our efficient numerical tools, we then present a detailed study of the effects of dominance on barriers to gene flow, showing that when total selection is sufficiently strong, more recessive local adaptation generates stronger barriers to gene flow. We then study how heterogeneous genetic architectures of local adaptation affect barriers to gene flow, characterizing adaptive differentiation at migration-selection balance for different distributions of fitness effects. We find that a more heterogeneous genetic architecture generally yields a stronger genome-wide barrier to gene flow and that the detailed genetic architecture underlying locally adaptive traits can have an important effect on observable differentiation when divergence is not too large. Lastly, we study the limits of our approach as loci become more tightly linked, showing that our predictions remain accurate over a large biologically relevant domain.

Animals rely on their nervous systems to process sensory inputs, integrate these with internal signals, and produce behavioral outputs. This is enabled by the highly specialized morphologies and functions of neurons. Neuronal cells share multiple structural and physiological features, but they also come in a large diversity of types or classes that give the nervous system its broad range of functions and plasticity. This diversity, first recognized over a century ago, spurred classification efforts based on morphology, function, and molecular criteria. Caenorhabditis elegans, with its precisely mapped nervous system at the anatomical level, an extensive molecular description of most of its neurons, and its genetic amenability, has been a prime model for understanding how neurons develop and diversify at a mechanistic level. Here, we review the gene regulatory mechanisms driving neurogenesis and the diversification of neuron classes and subclasses in C. elegans. We discuss our current understanding of the specification of neuronal progenitors and their differentiation in terms of the transcription factors involved and ensuing changes in gene expression and chromatin landscape. The central theme that has emerged is that the identity of a neuron is defined by modules of gene batteries that are under control of parallel yet interconnected regulatory mechanisms. We focus on how, to achieve these terminal identities, cells integrate information along their developmental lineages. Moreover, we discuss how neurons are diversified postembryonically in a time-, genetic sex-, and activity-dependent manner. Finally, we discuss how the understanding of neuronal development can provide insights into the evolution of neuronal diversity.