Assessing the complex architecture of polygenic traits in diverged yeast populations

Phenotypic variation arising from populations adapting to different niches has a complex underlying genetic architecture. A major challenge in modern biology is to identify the causative variants driving phenotypic variation. Recently, the baker's yeast, Saccharomyces cerevisiae has emerged as a powerful model for dissecting complex traits. However, past studies using a laboratory strain were unable to reveal the complete architecture of polygenic traits. Here, we present a linkage study using 576 recombinant strains obtained from crosses of isolates representative of the major lineages. The meiotic recombinational landscape appears largely conserved between populations; however, strain-specific hotspots were also detected. Quantitative measurements of growth in 23 distinct ecologically relevant environments show that our recombinant population recapitulates most of the standing phenotypic variation described in the species. Linkage analysis detected an average of 6.3 distinct QTLs for each condition tested in all crosses, explaining on average 39% of the phenotypic variation. The QTLs detected are not constrained to a small number of loci, and the majority are specific to a single cross-combination and to a specific environment. Moreover, crosses between strains of similar phenotypes generate greater variation in the offspring, suggesting the presence of many antagonistic alleles and epistatic interactions. We found that subtelomeric regions play a key role in defining individual quantitative variation, emphasizing the importance of the adaptive nature of these regions in natural populations. This set of recombinant strains is a powerful tool for investigating the complex architecture of polygenic traits.     

Order-preserving principles underlying genotype-phenotype maps ensure high additive proportions of genetic variance

In quantitative genetics, the degree of resemblance between parents and offspring is described in terms of the additive variance (V(A)) relative to genetic (V(G)) and phenotypic (V(P)) variance. For populations with extreme allele frequencies, high V(A)/V(G) can be explained without considering properties of the genotype-phenotype (GP) map. We show that randomly generated GP maps in populations with intermediate allele frequencies generate far lower V(A)/V(G) values than empirically observed. The main reason is that order-breaking behaviour is ubiquitous in random GP maps. Rearrangement of genotypic values to introduce order-preservation for one or more loci causes a dramatic increase in V(A)/V(G). This suggests the existence of order-preserving design principles in the regulatory machinery underlying GP maps. We illustrate this feature by showing how the ubiquitously observed monotonicity of dose-response relationships gives much higher V(A)/V(G) values than a unimodal dose-response relationship in simple gene network models.     

Power of QTL mapping experiments in commercial Atlantic salmon populations, exploiting linkage and linkage disequilibrium and effect of limited recombination in males

Whereas detection and positioning of genes that affect quantitative traits (quantitative trait loci (QTL)) using linkage mapping uses only information from recombinants in the genotyped generations, linkage disequilibrium (LD) mapping uses historical recombinants. Thus, whereas linkage mapping requires large family sizes to detect and accurately position QTL, LD mapping is more dependent on the number of families sampled from the population. In commercial Atlantic salmon breeding programmes, only a small number of individuals per family are routinely phenotyped for traits such as disease resistance and meat colour. In this paper, we assess the power and accuracy of combined linkage disequilibrium linkage analysis (LDLA) to detect QTL in the commercial population using simulation. When 15 half-sib sire families (each sire mated to 30 dams, each dam with 10 progeny) were sampled from the population for genotyping, we were able to detect a QTL explaining 10% of the phenotypic variance in 85% of replicates and position this QTL within 3 cM of the true position in 70% of replicates. When recombination was absent in males, a feature of the salmon genome, power to detect QTL increased; however, the accuracy of positioning the QTL was decreased. By increasing the number of sire families sampled from the population to be genotyped to 30, we were able to increase both the proportion of QTL detected and correctly positioned (even with no recombination in males). QTL with much smaller effect could also be detected. The results suggest that even with the existing recording structure in commercial salmon breeding programmes, there is considerable power to detect and accurately position QTL using LDLA.     

Multi-way metamodelling facilitates insight into the complex input-output maps of nonlinear dynamic models

Background

The physical periphery of a biological cell is mainly described by signaling pathways which are triggered by transmembrane proteins and receptors that are sentinels to control the whole gene regulatory network of a cell. However, our current knowledge about the gene regulatory mechanisms that are governed by extracellular signals is severely limited.

Results

The purpose of this paper is three fold. First, we infer a gene regulatory network from a large-scale B-cell lymphoma expression data set using the C3NET algorithm. Second, we provide a functional and structural analysis of the largest connected component of this network, revealing that this network component corresponds to the peripheral region of a cell. Third, we analyze the hierarchical organization of network components of the whole inferred B-cell gene regulatory network by introducing a new approach which exploits the variability within the data as well as the inferential characteristics of C3NET. As a result, we find a functional bisection of the network corresponding to different cellular components.

Conclusions

Overall, our study allows to highlight the peripheral gene regulatory network of B-cells and shows that it is centered around hub transmembrane proteins located at the physical periphery of the cell. In addition, we identify a variety of novel pathological transmembrane proteins such as ion channel complexes and signaling receptors in B-cell lymphoma.     

Allele Interaction – Single Locus Genetics Meets Regulatory Biology

Background

Since the dawn of genetics, additive and dominant gene action in diploids have been defined by comparison of heterozygote and homozygote phenotypes. However, these definitions provide little insight into the underlying intralocus allelic functional dependency and thus cannot serve directly as a mediator between genetics theory and regulatory biology, a link that is sorely needed.

Methodology/Principal Findings

We provide such a link by distinguishing between positive, negative and zero allele interaction at the genotype level. First, these distinctions disclose that a biallelic locus can display 18 qualitatively different allele interaction sign motifs (triplets of +, – and 0). Second, we show that for a single locus, Mendelian dominance is not related to heterozygote allele interaction alone, but is actually a function of the degrees of allele interaction in all the three genotypes. Third, we demonstrate how the allele interaction in each genotype is directly quantifiable in gene regulatory models, and that there is a unique, one-to-one correspondence between the sign of autoregulatory feedback loops and the sign of the allele interactions.

Conclusion/Significance

The concept of allele interaction refines single locus genetics substantially, and it provides a direct link between classical models of gene action and gene regulatory biology. Together with available empirical data, our results indicate that allele interaction can be exploited experimentally to identify and explain intricate intra- and inter-locus feedback relationships in eukaryotes.     

Nisin对幽门螺杆菌生物学作用的实验研究

目的：探讨乳链菌肽（Nisin)在柠檬酸的协同作用下对幽门螺杆菌（Helicobacter pylori,Hp)的生物学作用,寻求一种新的防治Hp微生态制剂,为临床治疗Hp提供理论和实践指导。方法：运用国际通用的药敏试验方法纸片法（Kirby-Bauer)和倾注培养法（Pour Culture)对96例从胃病患者分离出的临床株Nisin和柠檬酸协同作用的生物学实验,然后电镜观察被Nisin作用后的Hp菌株细胞结构并进行分析处理。结果：Nisin在柠檬酸的协同作用下对Hp具有明显的抑杀作用,电镜观察被作用后的Hp菌株细胞质膜破碎和细胞发生球形样变。结论：Nisin作用机制主要表现在对Hp菌株的细胞质膜上。     

Gene regulatory networks generating the phenomena of additivity, dominance and epistasis

We show how the phenomena of genetic dominance, overdominance, additivity, and epistasis are generic features of simple diploid gene regulatory networks. These regulatory network models are together sufficiently complex to catch most of the suggested molecular mechanisms responsible for generating dominant mutations. These include reduced gene dosage, expression or protein activity (haploinsufficiency), increased gene dosage, ectopic or temporarily altered mRNA expression, increased or constitutive protein activity, and dominant negative effects. As classical genetics regards the phenomenon of dominance to be generated by intralocus interactions, we have studied two one-locus models, one with a negative autoregulatory feedback loop, and one with a positive autoregulatory feedback loop. To include the phenomena of epistasis and downstream regulatory effects, a model of a three-locus signal transduction network is also analyzed. It is found that genetic dominance as well as overdominance may be an intra- as well as interlocus interaction phenomenon. In the latter case the dominance phenomenon is intimately connected to either feedback-mediated epistasis or downstream-mediated epistasis. It appears that in the intra- as well as the interlocus case there is considerable room for additive gene action, which may explain to some degree the predictive power of quantitative genetic theory, with its emphasis on this type of gene action. Furthermore, the results illuminate and reconcile the prevailing explanations of heterosis, and they support the old conjecture that the phenomenon of dominance may have an evolutionary explanation related to life history strategy.     

The hive bee to forager transition in honeybee colonies: the double repressor hypothesis

In summer, the honeybee (Apis mellifera) worker population consists of two temporal castes, a hive bee group performing a multitude of tasks including nursing inside the nest, and a forager group specialized on collecting nectar, pollen, water and propolis. Elucidation of the regulatory mechanisms responsible for the hive bee to forager transition holds a prominent position within present day sociobiology. Here we suggest a new explanation dubbed the "double repressor hypothesis" aimed to account for the substantial amount of empirical data in this field. This is the first time where both the regular transition and starvation-induced precocious transition are explained within the same regulatory framework. We suggest that the transition is under regulatory control by an internal and an external repressor of the allatoregulatory central nervous system, where these two repressors modulate a positive regulatory feedback loop involving juvenile hormone (JH) and the lipoprotein vitellogenin. The concepts of age-neutrality, fixed and variable response thresholds and reinforcement are integral parts of our explanation, and in addition they are given explicit physiological content. The hypothesis is represented by a differential equations model at the level of the individual bee, and by a discrete individual-based colony model. The two models generate predictions in accordance with empirical data concerning the cumulative probability of becoming a forager, mean age at onset of foraging, reversal of foragers, time window of reversal, relationship between JH titre and onset of foraging, relative representations of genotypic groups, and effects of forager depletion and confinement.     

The regulatory anatomy of honeybee lifespan

Honeybee workers (Apis mellifera) may be classified as either short-lived summer bees or long-lived winter bees in temperate zones. The protein status appears to be a major determinant of honeybee lifespan, and the lipoprotein vitellogenin seems to play a crucial role. Here, we give a review of the role of the vitellogenin in honeybee workers, and present a data-driven mathematical model describing the dynamics of this representative protein in the individual bee as a function of its task profile under various regimes. The results support the hypothesis that vitellogenin is a true storage protein that is utilized for various metabolic purposes including the synthesis of brood food. Except for workers having been foragers for many days, they also suggest that the previous life histories of workers do not constrain them from becoming winter bees as long as they get ample food and time to build up their protein reserves before wintering. The results also indicate that it may not be necessary to introduce the ovary as a storage organ for vitellogenin in order to generate normal winter bees. The insights gained from these results are then discussed in a broader gerontological and life history context. Remarkably similar features concerning regulation of ageing in Caenorhabditis elegans, Drosophila melanogaster and honeybees are pointed out and discussed. Furthermore, we show that in contrast to the "mutation accumulation" and the "antagonistic pleiotropy" evolutionary theories of ageing, the "disposable soma" theory is capable of explaining the bimodal longevity distribution of honeybees when interpreted in a group selection context. Finally, by showing that depletion of nutrient stores can be actively controlled by pathways connected to regulation of ageing, we strengthen the claim that age-based division of labour, with performance of risky tasks delayed until late in life by workers with depleted nutrient stores, may have evolved as an energy-saving mechanism in insect colonies.