Genetics of gene expression responses to temperature stress in a sea urchin gene network

Stress responses play an important role in shaping species distributions and robustness to climate change. We investigated how stress responses alter the contribution of additive genetic variation to gene expression during development of the purple sea urchin, Strongylocentrotus purpuratus, under increased temperatures that model realistic climate change scenarios. We first measured gene expression responses in the embryos by RNA‐seq to characterize molecular signatures of mild, chronic temperature stress in an unbiased manner. We found that an increase from 12 to 18 °C caused widespread alterations in gene expression including in genes involved in protein folding, RNA processing and development. To understand the quantitative genetic architecture of this response, we then focused on a well‐characterized gene network involved in endomesoderm and ectoderm specification. Using a breeding design with wild‐caught individuals, we measured genetic and gene–environment interaction effects on 72 genes within this network. We found genetic or maternal effects in 33 of these genes and that the genetic effects were correlated in the network. Fourteen network genes also responded to higher temperatures, but we found no significant genotype–environment interactions in any of the genes. This absence may be owing to an effective buffering of the temperature perturbations within the network. In support of this hypothesis, perturbations to regulatory genes did not affect the expression of the genes that they regulate. Together, these results provide novel insights into the relationship between environmental change and developmental evolution and suggest that climate change may not expose large amounts of cryptic genetic variation to selection in this species.     

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long‐term adaptation of complex phenotypes.     

Gene Circuit Analysis of the Terminal Gap Gene huckebein

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network.     

Coat Color Variation and Pigmentation Gene Expression in Rhesus Macaques (Macaca mulatta)

Light-dark coat color variation is a common aspect of color diversity within and across mammalian taxa. This variation in pelage brightness is associated with aspects of evolutionary ecology, particularly for primates, but little is known about the genetic mechanisms underlying light-dark differences in pelage pigmentation. Previous work, focusing particularly on macaques (Genus Macaca), has found no clear relationship between color variation and coding sequences of key pigmentation genes. This suggests that other loci and/or gene regulatory differences underlie this variation and raises the question of how patterns of gene expression differ in light verses dark hair follicles. Here, we examine relative expression levels of pigmentation genes in hair follicles from free-ranging rhesus macaques (Macaca mulatta) showing stark light-dark coat color variation. We quantified the brightness (reflectance) of plucked hair tufts using a spectrophotometer. We extracted RNA from the follicles and used quantitative RT-PCR to measure the relative amounts of gene product (mRNA) for seven candidate pigmentation genes (MITF, MC1R, MGRN1, ATRN, SLC24A5, TYRP1, and DCT). Expression values were normalized with the house-keeping gene ACTB. All candidate genes were expressed at similar levels in dark, intermediate, and light hair, and thus, light-dark variation in macaque coat color is unlikely to be due to differences in the expression of these key pigmentation genes. This study represents the first examination of gene expression and natural color variation in a non-human primate population. Our results indicate that even in a system, like pigmentation, where a candidate-gene approach is promising, identifying important intra-specific gene regulatory differences remains challenging.     

Dynamical analysis of regulatory interactions in the gap gene system of Drosophila melanogaster

Genetic studies have revealed that segment determination in Drosophila melanogaster is based on hierarchical regulatory interactions among maternal coordinate and zygotic segmentation genes. The gap gene system constitutes the most upstream zygotic layer of this regulatory hierarchy, responsible for the initial interpretation of positional information encoded by maternal gradients. We present a detailed analysis of regulatory interactions involved in gap gene regulation based on gap gene circuits, which are mathematical gene network models used to infer regulatory interactions from quantitative gene expression data. Our models reproduce gap gene expression at high accuracy and temporal resolution. Regulatory interactions found in gap gene circuits provide consistent and sufficient mechanisms for gap gene expression, which largely agree with mechanisms previously inferred from qualitative studies of mutant gene expression patterns. Our models predict activation of Kr by Cad and clarify several other regulatory interactions. Our analysis suggests a central role for repressive feedback loops between complementary gap genes. We observe that repressive interactions among overlapping gap genes show anteroposterior asymmetry with posterior dominance. Finally, our models suggest a correlation between timing of gap domain boundary formation and regulatory contributions from the terminal maternal system.     

Gene expression divergence and the origin of hybrid dysfunctions

Hybrids between closely related species are often sterile or inviable as a consequence of failed interactions between alleles from the different species. Most genetic studies have focused on localizing the alleles associated with these failed interactions, but the mechanistic/biochemical nature of the failed interactions is poorly understood. This review discusses recent studies that may contribute to our understanding of these failed interactions. We focus on the possible contribution of failures in gene expression as an important contributor to hybrid dysfunctions. Although regulatory pathways that share elements in highly divergent taxa may contribute to hybrid dysfunction, various studies suggest that misexpression may be disproportionately great in regulatory pathways containing rapidly evolving, particularly male-biased, genes. We describe three systems that have been analyzed recently with respect to global patterns of gene expression in hybrids versus pure species, each in Drosophila. These studies reveal that quantitative misexpression of genes is associated with hybrid dysfunction. Misexpression of genes has been documented in sterile hybrids relative to pure species, and variation in upstream factors may sometimes cause the over- or under-expression of genes resulting in hybrid sterility or inviability. Studying patterns of evolution between species in regulatory pathways, such as spermatogenesis, should help in identifying which genes are more likely to be contributors to hybrid dysfunction. Ultimately, we hope more functional genetic studies will complement our understanding of the genetic disruptions leading to hybrid dysfunctions and their role in the origin of species.     

多组学大数据整合分析揭示早期胚胎发育过程中基因表达调控信息的变化规律

摘要 目的：探究哺乳动物早期胚胎发育过程中基因表达调控信息的变化规律。方法：收集小鼠早期胚胎发育各时期的RNA-seq,ATAC-seq,MethylC-Seq和H3K4me3 ChIP-seq数据进行整合分析,观察小鼠早期胚胎发育各时期转录因子表达量的变化,计算各时期基因表达量与转录因子结合位点数量及染色质可及性的相关性,筛选各时期表达量前10%的基因,统计其表达量和转录因子占比,并进行启动子可及性分析。根据前期报道的转录因子三节点调控网络,对早期胚胎各时期转录因子调控网络的富集模式进行分析。根据多组学数据分析结果,推测早期胚胎发育调控过程中转录因子和表观遗传修饰信息的共调控模型。结果：转录因子数量和调控关系变化以及染色质可及性、DNA甲基化修饰、组蛋白修饰等表观遗传修饰共同调控早期胚胎发育各时期的基因表达,这些因素在不同时期发挥不同程度的调控作用。结论：转录因子和表观遗传修饰在早期胚胎发育过程中动态调控基因表达。     

Modeling genetic regulatory dynamics in neural development.

We model genetic regulatory networks in the framework of continuous-time recurrent networks. The network parameters are determined from gene expression level time series data using genetic algorithms. We have applied the method to expression data from the development of rat central nervous system, where the active genes cluster into four groups, within which the temporal expression patterns are similar. The data permit us to identify approximately the interactions between these groups of genes. We find that generally a single time series is of limited value in determining the interactions in the network, but multiple time series collected in related tissues or under treatment with different drugs can fix their values much more precisely.     

A Boolean Model of the Gene Regulatory Network Underlying Mammalian Cortical Area Development

The cerebral cortex is divided into many functionally distinct areas. The emergence of these areas during neural development is dependent on the expression patterns of several genes. Along the anterior-posterior axis, gradients of Fgf8, Emx2, Pax6, Coup-tfi, and Sp8 play a particularly strong role in specifying areal identity. However, our understanding of the regulatory interactions between these genes that lead to their confinement to particular spatial patterns is currently qualitative and incomplete. We therefore used a computational model of the interactions between these five genes to determine which interactions, and combinations of interactions, occur in networks that reproduce the anterior-posterior expression patterns observed experimentally. The model treats expression levels as Boolean, reflecting the qualitative nature of the expression data currently available. We simulated gene expression patterns created by all possible networks containing the five genes of interest. We found that only of these networks were able to reproduce the experimentally observed expression patterns. These networks all lacked certain interactions and combinations of interactions including auto-regulation and inductive loops. Many higher order combinations of interactions also never appeared in networks that satisfied our criteria for good performance. While there was remarkable diversity in the structure of the networks that perform well, an analysis of the probability of each interaction gave an indication of which interactions are most likely to be present in the gene network regulating cortical area development. We found that in general, repressive interactions are much more likely than inductive ones, but that mutually repressive loops are not critical for correct network functioning. Overall, our model illuminates the design principles of the gene network regulating cortical area development, and makes novel predictions that can be tested experimentally.