Historical introgression and the role of selective vs. neutral processes in structuring nuclear genetic variation (AFLP) in a circumpolar marine fish, the capelin (Mallotus villosus)

The capelin (Mallotus villosus) is a widespread marine fish species for which previous work has identified geographically distinct mtDNA clades, the frontiers of which are well within adult and larval dispersal capabilities. Here, we use AFLPs to test for the presence of nuclear gene flow among clades. In addition, we evaluate genetic structuring within one clade, the Northwest Atlantic (NWA). We found that each of the mtDNA clades corresponds with a unique nuclear DNA genetic cluster. Within the NWA clade, we detected individuals with small but significant amounts of genetic ancestry from other clades, likely due to historical introgression. Further support for historical introgression comes from analyses of variance in locus-specific differentiation, which support introgression between some clades and divergence without gene flow between others. Within the NWA, we identified two genetic clusters that correspond to sites in geographically adjacent areas. However, these clusters differ primarily at 'outlier' loci, and a genetic subdivision (K=2) was not supported by genetic clustering programs using neutral loci. Significant neutral F(ST) differentiation was found only between sites that otherwise differed at outlier loci. Thus, these populations may be in the initial stages of 'isolation by adaptation'. These results suggest strong between-clade reproductive isolation despite opportunities for gene flow and support the hypothesis that selection can contribute to divergence in otherwise 'open' systems.     

The coupling hypothesis: why genome scans may fail to map local adaptation genes

Genomic scans of multiple populations often reveal marker loci with greatly increased differentiation between populations. Often this differentiation coincides in space with contrasts in ecological factors, forming a genetic-environment association (GEA). GEAs imply a role for local adaptation, and so it is tempting to conclude that the strongly differentiated markers are themselves under ecologically based divergent selection, or are closely linked to loci under such selection. Here, we highlight an alternative and neglected explanation: intrinsic (i.e. environment-independent) pre- or post-zygotic genetic incompatibilities rather than local adaptation can be responsible for increased differentiation. Intrinsic genetic incompatibilities create endogenous barriers to gene flow, also known as tension zones, whose location can shift over time. However, tension zones have a tendency to become trapped by, and therefore to coincide with, exogenous barriers due to ecological selection. This coupling of endogenous and exogenous barriers can occur easily in spatially subdivided populations, even if the loci involved are unlinked. The result is that local adaptation explains where genetic breaks are positioned, but not necessarily their existence, which can be best explained by endogenous incompatibilities. More precisely, we show that (i) the coupling of endogenous and exogenous barriers can easily occur even when ecological selection is weak; (ii) when environmental heterogeneity is fine-grained, GEAs can emerge at incompatibility loci, but only locally, in places where habitats and gene pools are sufficiently intermingled to maintain linkage disequilibria between genetic incompatibilities, local-adaptation genes and neutral loci. Furthermore, the association between the locally adapted and intrinsically incompatible alleles (i.e. the sign of linkage disequilibrium between endogenous and exogenous loci) is arbitrary and can form in either direction. Reviewing results from the literature, we find that many predictions of our model are supported, including endogenous genetic barriers that coincide with environmental boundaries, local GEA in mosaic hybrid zones, and inverted or modified GEAs at distant locations. We argue that endogenous genetic barriers are often more likely than local adaptation to explain the majority of Fst-outlying loci observed in genome scan approaches - even when these are correlated to environmental variables.     

A strong quantitative trait locus for wing length on chromosome 2 in a wild population of great reed warblers

Wing length is a key character for essential behaviours related to bird flight such as migration and foraging. In the present study, we initiate the search for the genes underlying wing length in birds by studying a long-distance migrant, the great reed warbler (Acrocephalus arundinaceus). In this species wing length is an evolutionary interesting trait with pronounced latitudinal gradient and sex-specific selection regimes in local populations. We performed a quantitative trait locus (QTL) scan for wing length in great reed warblers using phenotypic, genotypic, pedigree and linkage map data from our long-term study population in Sweden. We applied the linkage analysis mapping method implemented in GridQTL (a new web-based software) and detected a genome-wide significant QTL for wing length on chromosome 2, to our knowledge, the first detected QTL in wild birds. The QTL extended over 25 cM and accounted for a substantial part (37%) of the phenotypic variance of the trait. A genome scan for tarsus length (a body-size-related trait) did not show any signal, implying that the wing-length QTL on chromosome 2 was not associated with body size. Our results provide a first important step into understanding the genetic architecture of avian wing length, and give opportunities to study the evolutionary dynamics of wing length at the locus level.     

Heterogeneous genomic differentiation between walking-stick ecotypes: "isolation by adaptation" and multiple roles for divergent selection

Genetic differentiation can be highly variable across the genome. For example, loci under divergent selection and those tightly linked to them may exhibit elevated differentiation compared to neutral regions. These represent "outlier loci" whose differentiation exceeds neutral expectations. Adaptive divergence can also increase genome-wide differentiation by promoting general barriers to neutral gene flow, thereby facilitating genomic divergence via genetic drift. This latter process can yield a positive correlation between adaptive phenotypic divergence and neutral genetic differentiation (described here as "isolation-by-adaptation"). Here, we examine both these processes by combining an AFLP genome scan of two host plant ecotypes of Timema cristinae walking-sticks with existing data on adaptive phenotypic divergence and ecological speciation in these insects. We found that about 8% of loci are outliers in multiple population comparisons. Replicated comparisons between population-pairs using the same versus different host species revealed that 1-2% of loci are subject to host-related selection specifically. Locus-specific analyses revealed that up to 10% of putatively neutral (nonoutlier) AFLP loci exhibit significant isolation-by-adaptation. Our results suggest that selection may affect differentiation directly, via linkage, or by facilitating genetic drift. They thus illustrate the varied and sometimes nonintuitive contributions of selection to heterogeneous genomic differentiation.     

Probability of detecting disease-associated single nucleotide polymorphisms in case-control genome-wide association studies

Some case-control genome-wide association studies (CCGWASs) select promising single nucleotide polymorphisms (SNPs) by ranking corresponding p-values, rather than by applying the same p-value threshold to each SNP. For such a study, we define the detection probability (DP) for a specific disease-associated SNP as the probability that the SNP will be "T-selected," namely have one of the top T largest chi-square values (or smallest p-values) for trend tests of association. The corresponding proportion positive (PP) is the fraction of selected SNPs that are true disease-associated SNPs. We study DP and PP analytically and via simulations, both for fixed and for random effects models of genetic risk, that allow for heterogeneity in genetic risk. DP increases with genetic effect size and case-control sample size and decreases with the number of nondisease-associated SNPs, mainly through the ratio of T to N, the total number of SNPs. We show that DP increases very slowly with T, and the increment in DP per unit increase in T declines rapidly with T. DP is also diminished if the number of true disease SNPs exceeds T. For a genetic odds ratio per minor disease allele of 1.2 or less, even a CCGWAS with 1000 cases and 1000 controls requires T to be impractically large to achieve an acceptable DP, leading to PP values so low as to make the study futile and misleading. We further calculate the sample size of the initial CCGWAS that is required to minimize the total cost of a research program that also includes follow-up studies to examine the T-selected SNPs. A large initial CCGWAS is desirable if genetic effects are small or if the cost of a follow-up study is large.     

Characterization of the post-translational modification of recombinant human BMP-15 mature protein

Bone morphogenetic protein-15 (BMP-15) is an oocyte-secreted factor critical for the regulation of ovarian physiology. When recombinant human BMP-15 (rhBMP-15) produced in human embryonic kidney 293 cells was subjected to SDS-PAGE analysis, two mature protein forms corresponding to 16 kDa (P16) and 17 kDa (P17) were observed. Despite the physiological relevance and critical function of BMP-15 in female reproduction, little is known about the structure of rhBMP-15. Here, we have analyzed the structure of the rhBMP-15 mature proteins (P16 and P17) using state-of-the-art proteomics technology. Our findings are as follows: (1) the N-terminal amino acid of P16 and P17 is pyroglutamic acid; (2) the Ser residue at the sixth position of P16 is phosphorylated; (3) P17 is O-glycosylated at Thr10; and (4) the C-terminal amino acid of P16 and P17 is truncated. These findings are the first knowledge of the structure of rhBMP-15 mature protein toward understanding the molecular basis of BMP-15 function and could provide an important contribution to the rapidly progressing research area involving oocyte-specific growth factors in modulation of female fertility.     

Transmembrane helices that form two opposite homodimeric interactions: an asparagine scan study of alphaM and beta2 integrins

Integrins are alpha/beta heterodimers, but recent in vitro and in vivo experiments also suggest an ability to associate through their transmembrane domains to form homomeric interactions. While the results of some in vitro experiments are consistent with an interaction mediated by a GxxxG-like motif, homo-oligomers observed after in vivo cross-linking are consistent with an almost opposite helix-helix interface. We have shown recently that both models of interaction are compatible with evolutionary conservation data, and we predicted that the alpha-helices in both models would have a similar rotational orientation. Herein, we have tested our prediction using in vitro asparagine scan of five consecutive residues along the GxxxG-like motif of the transmembrane domain of alpha and beta integrins, alphaM and beta2. We show that Asn-mediated dimerization occurs twice for every turn of the helix, consistent with two almost opposite forms of interaction as suggested previously for alphaIIb and beta3 transmembrane domains. The orientational parameters helix tilt and rotational orientation of each of these two Asn-stabilized dimers were measured by site-specific infrared dichroism (SSID) in model lipid bilayers and were found to be consistent with our predicted computational models. Our results highlight an intrinsic tendency for integrin transmembrane alpha-helices to form two opposite types of homomeric interaction in addition to their heteromeric interactions and suggest that integrins may form complex and specific networks at the transmembrane domain during function.     

Costs versus benefits: best possible and best practical treatment regimens for HIV

Current HIV therapy, although highly effective, may cause very serious side effects, making adherence to the prescribed regimen difficult. Mathematical modeling may be used to evaluate alternative treatment regimens by weighing the positive results of treatment, such as higher levels of helper T cells, against the negative consequences, such as side effects and the possibility of resistance mutations. Although estimating the weights assigned to these factors is difficult, current clinical practice offers insight by defining situations in which therapy is considered “worthwhile”. We therefore use clinical practice, along with the probability that a drug-resistant mutation is present at the start of therapy, to suggest methods of rationally estimating these weights. In our underlying model, we use ordinary differential equations to describe the time course of in-host HIV infection, and include populations of both activated CD4⁺ T cells and CD8⁺ T cells. We then determine the best possible treatment regimen, assuming that the effectiveness of the drug can be continually adjusted, and the best practical treatment regimen, evaluating all patterns of a block of days “on” therapy followed by a block of days “off” therapy. We find that when the tolerance for drug-resistant mutations is low, high drug concentrations which maintain low infected cell populations are optimal. In contrast, if the tolerance for drug-resistant mutations is fairly high, the optimal treatment involves periods of reduced drug exposure which consequently boost the immune response through increased antigen exposure. We elucidate the dependence of the optimal treatment regimen on the pharmacokinetic parameters of specific antiviral agents.     

A spatial scan statistic for survival data

Spatial scan statistics with Bernoulli and Poisson models are commonly used for geographical disease surveillance and cluster detection. These models, suitable for count data, were not designed for data with continuous outcomes. We propose a spatial scan statistic based on an exponential model to handle either uncensored or censored continuous survival data. The power and sensitivity of the developed model are investigated through intensive simulations. The method performs well for different survival distribution functions including the exponential, gamma, and log-normal distributions. We also present a method to adjust the analysis for covariates. The cluster detection method is illustrated using survival data for men diagnosed with prostate cancer in Connecticut from 1984 to 1995.     

Spatial cluster detection for censored outcome data

While numerous methods have been proposed to test for spatial cluster detection, in particular for discrete outcome data (e.g., disease incidence), few have been available for continuous data that are subject to censoring. This article provides an extension of the spatial scan statistic (Kulldorff, 1997, Communications in Statistics 26, 1481-1496) for censored outcome data and further proposes a simple spatial cluster detection method by utilizing cumulative martingale residuals within the framework of the Cox's proportional hazards models. Simulations have indicated good performance of the proposed methods, with the practical applicability illustrated by an ongoing epidemiology study which investigates the relationship of environmental exposures to asthma, allergic rhinitis/hayfever, and eczema.