Unraveling the history of the genus Gallus through whole genome sequencing.

The genus Gallus is distributed across a large part of Southeast Asia and has received special interest because the domestic chicken, Gallus gallus domesticus, has spread all over the world and is a major protein source for humans. There are four species: the red junglefowl (G. gallus), the green junglefowl (G. varius), the Lafayette's junglefowl (G. lafayettii) and the grey junglefowl (G. sonneratii). The aim of this study is to reconstruct the history of these species by a whole genome sequencing approach and resolve inconsistencies between well supported topologies inferred using different data and methods. Using deep sequencing, we identified over 35 million SNPs and reconstructed the phylogeny of the Gallus genus using both distance (BioNJ) and maximum likelihood (ML) methods. We observed discrepancies according to reconstruction methods and genomic components. The two most supported topologies were previously reported and were discriminated by using phylogenetic and gene flow analyses, based on ABBA statistics. Terminology fix requested by the deputy editor led to support a scenario with G. gallus as the earliest branching lineage of the Gallus genus, instead of G. varius. We discuss the probable causes for the discrepancy. A likely one is that G. sonneratii samples from parks or private collections are all recent hybrids, with roughly 10% of their autosomal genome originating from G. gallus. The removal of those regions is needed to provide reliable data, which was not done in previous studies. We took care of this and additionally included two wild G. sonneratii samples from India, showing no trace of introgression. This reinforces the importance of carefully selecting and validating samples and genomic components in phylogenomics.

Network impact on persistence in a finite population dynamic diffusion model: application to an emergent seed exchange network.

Dynamic extinction colonisation models (also called contact processes) are widely studied in epidemiology and in metapopulation theory. Contacts are usually assumed to be possible only through a network of connected patches. This network accounts for a spatial landscape or a social organization of interactions. Thanks to social network literature, heterogeneous networks of contacts can be considered. A major issue is to assess the influence of the network in the dynamic model. Most work with this common purpose uses deterministic models or an approximation of a stochastic Extinction-Colonisation model (sEC) which are relevant only for large networks. When working with a limited size network, the induced stochasticity is essential and has to be taken into account in the conclusions. Here, a rigorous framework is proposed for limited size networks and the limitations of the deterministic approximation are exhibited. This framework allows exact computations when the number of patches is small. Otherwise, simulations are used and enhanced by adapted simulation techniques when necessary. A sensitivity analysis was conducted to compare four main topologies of networks in contrasting settings to determine the role of the network. A challenging case was studied in this context: seed exchange of crop species in the Réseau Semences Paysannes (RSP), an emergent French farmers׳ organisation. A stochastic Extinction-Colonisation model was used to characterize the consequences of substantial changes in terms of RSP׳s social organization on the ability of the system to maintain crop varieties.

Contribution of an additive locus to genetic variance when inheritance is multi-factorial with implications on interpretation of GWAS.

Although the effects of linkage disequilibrium (LD) on partition of genetic variance have received attention in quantitative genetics, there has been little discussion on how this phenomenon affects attribution of variance to a given locus. This paper reinforces the point that standard metrics used for assessing the contribution of a locus to variance can be misleading when there is linkage LD and that factors such as distribution of effects and of allelic frequencies over loci, or existence of frequency-dependent effects, play a role as well. An apparently new metric is proposed for measuring how much of the variability is contributed by a locus when LD exists. Effects of intervening factors, such as type and extent of LD, number of loci, distribution of effects, and of allelic frequencies over loci, as well as a model for generating frequency-dependent effects, are illustrated via hypothetical simulation scenarios. Implications on the interpretation of genome-wide association studies (GWAS), as typically carried out in human genetics, where single marker regression and the assumption of a sole quantitative trait locus (QTL) are common, are discussed. It is concluded that the standard attributions to variance contributed by a single QTL from a GWAS analysis may be misleading, conceptually and statistically, when a trait is complex and affected by sets of many genes in linkage disequilibrium. Yet another factor to consider in the "missing heritability" saga?.

Rapid rise and fall of selfish sex-ratio X chromosomes in Drosophila simulans: spatiotemporal analysis of phenotypic and molecular data.

Sex-ratio drive, which has been documented in several Drosophila species, is induced by X-linked segregation distorters. Contrary to Mendel's law of independent assortment, the sex-ratio chromosome (X(SR)) is inherited by more than half the offspring of carrier males, resulting in a female-biased sex ratio. This segregation advantage allows X(SR) to spread in populations, even if it is not beneficial for the carriers. In the cosmopolitan species D. simulans, the Paris sex-ratio is caused by recently emerged selfish X(SR) chromosomes. These chromosomes have triggered an intragenomic conflict, and their propagation has been halted over a large area by the evolution of complete drive suppression. Previous molecular population genetics analyses revealed a selective sweep indicating that the invasion of X(SR) chromosomes was very recent in Madagascar (likely less than 100 years ago). Here, we show that X(SR) chromosomes are now declining at this location as well as in Mayotte and Kenya. Drive suppression is complete in the three populations, which display little genetic differentiation and share swept haplotypes, attesting to a common and very recent ancestry of the X(SR) chromosomes. Patterns of DNA sequence variation also indicate a fitness cost of the segmental duplication involved in drive. The data suggest that X(SR) chromosomes started declining first on the African continent, then in Mayotte, and finally in Madagascar and strongly support a scenario of rapid cycling of X chromosomes. Once drive suppression has evolved, standard X(ST) chromosomes locally replace costly X(SR) chromosomes in a few decades.

Assessing the impact of transgenerational epigenetic variation on complex traits.

Loss or gain of DNA methylation can affect gene expression and is sometimes transmitted across generations. Such epigenetic alterations are thus a possible source of heritable phenotypic variation in the absence of DNA sequence change. However, attempts to assess the prevalence of stable epigenetic variation in natural and experimental populations and to quantify its impact on complex traits have been hampered by the confounding effects of DNA sequence polymorphisms. To overcome this problem as much as possible, two parents with little DNA sequence differences, but contrasting DNA methylation profiles, were used to derive a panel of epigenetic Recombinant Inbred Lines (epiRILs) in the reference plant Arabidopsis thaliana. The epiRILs showed variation and high heritability for flowering time and plant height ( approximately 30%), as well as stable inheritance of multiple parental DNA methylation variants (epialleles) over at least eight generations. These findings provide a first rationale to identify epiallelic variants that contribute to heritable variation in complex traits using linkage or association studies. More generally, the demonstration that numerous epialleles across the genome can be stable over many generations in the absence of selection or extensive DNA sequence variation highlights the need to integrate epigenetic information into population genetics studies.

quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation.

UNLABELLED: quantiNemo is an individual-based, genetically explicit stochastic simulation program. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. quantiNemo is highly flexible at various levels: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography, mating system, etc. quantiNemo is coded in C++ using an object-oriented approach and runs on any computer platform. AVAILABILITY: Executables for several platforms, user's manual, and source code are freely available under the GNU General Public License at http://www2.unil.ch/popgen/softwares/quantinemo.

Selective sweep at a quantitative trait locus in the presence of background genetic variation.

We model selection at a locus affecting a quantitative trait (QTL) in the presence of genetic variance due to other loci. The dynamics at the QTL are related to the initial genotypic value and to the background genetic variance of the trait, assuming that background genetic values are normally distributed, under three different forms of selection on the trait. Approximate dynamics are derived under the assumption of small mutation effect. For similar strengths of selection on the trait (i.e, gradient of directional selection beta) the way background variation affects the dynamics at the QTL critically depends on the shape of the fitness function. It generally causes the strength of selection on the QTL to decrease with time. The resulting neutral heterozygosity pattern resembles that of a selective sweep with a constant selection coefficient corresponding to the early conditions. The signature of selection may also be blurred by mutation and recombination in the later part of the sweep. We also study the race between the QTL and its genetic background toward a new optimum and find the conditions for a complete sweep. Overall, our results suggest that phenotypic traits exhibiting clear-cut molecular signatures of selection may represent a biased subset of all adaptive traits.

Hitchhiking both ways: effect of two interfering selective sweeps on linked neutral variation.

The neutral polymorphism pattern in the vicinity of a selective sweep can be altered by both stochastic and deterministic factors. Here, we focus on the impact of another selective sweep in the region of influence of a first one. We study the signature left on neutral polymorphism by positive selection at two closely linked loci, when both beneficial mutations reach fixation. We show that, depending on the timing of selective sweeps and on their selection coefficients, the two hitchhiking effects can interfere with each other, leading to less reduction in heterozygosity than a single selective sweep of the same magnitude and more importantly to an excess of intermediate-frequency variants relative to neutrality under some parameter values. This pattern can be sustained and potentially alter the detection of positive selection, including by provoking spurious detection of balancing selection. In situations where positive selection is suspected a priori at several closely linked loci, the polymorphism pattern in the region may also be informative about their selective histories.

Challenges for effective marker-assisted selection in plants.

The basic principle of Marker-Assisted Selection (MAS) is to exploit Linkage Disequilibrium (LD) between markers and QTLs. With strong enough LD, MAS should in theory be easier, faster, cheaper, or more efficient than classical (phenotypic) selection. I briefly review the major MAS methods, describing some 'success stories' where MAS was applied successfully in the context of plant breeding, and detailing other cases where efficiency was not as high as expected. I discuss the possible causes explaining the difference between theoretical expectations and practical observations. Finally, I review the principal challenges and issues that must be tackled to make marker-assisted selection in plants more effective in the future, namely: managing and controlling QTL stability to apply MAS to complex traits, and integrating MAS in traditional breeding practices to make it more economically attractive and applicable in developing countries.

Molecular signature of epistatic selection: interrogating genetic interactions in the sex-ratio meiotic drive of Drosophila simulans.

Fine scale analyses of signatures of selection allow assessing quantitative aspects of a species' evolutionary genetic history, such as the strength of selection on genes. When several selected loci lie in the same genomic region, their epistatic interactions may also be investigated. Here, we study how the neutral polymorphism pattern was shaped by two close recombining loci that cause 'sex-ratio' meiotic drive in Drosophila simulans, as an example of strong selection with potentially strong epistasis. We compare the polymorphism data observed in a natural population with the results of forward stochastic simulations under several contexts of epistasis between the candidate loci for the drive. We compute the likelihood of different possible scenarios, in order to determine which configuration is most consistent with the data. Our results highlight that fine scale analyses of well-chosen candidate genomic regions provide information-rich data that can be used to investigate the genotype-phenotype-fitness map, which can hardly be studied in genome-wide analyses. We also emphasize that initial conditions and time of observation (here, time after the interruption of a partial selective sweep) are crucial parameters in the interpretation of real data, while these are often overlooked in theoretical studies.

Cancer- and behavior-related genes are targeted by selection in the Tasmanian devil (Sarcophilus harrisii).

Devil Facial Tumor Disease (DFTD) is an aggressive cancer notorious for its rare etiology and its impact on Tasmanian devil populations. Two regions underlying an evolutionary response to this cancer were recently identified using genomic time-series pre- and post-DTFD arrival. Here, we support that DFTD shaped the genome of the Tasmanian devil in an even more extensive way than previously reported. We detected 97 signatures of selection, including 148 protein coding genes having a human orthologue, linked to DFTD. Most candidate genes are associated with cancer progression, and an important subset of candidate genes has additional influence on social behavior. This confirms the influence of cancer on the ecology and evolution of the Tasmanian devil. Our work also demonstrates the possibility to detect highly polygenic footprints of short-term selection in very small populations.

The hitchhiking effect of an autosomal meiotic drive gene.

Transmission-ratio distortion is a departure from a 1:1 segregation of alleles in the gametes of a heterozygous individual. The so-called driving allele is strongly selected regardless of its effect on the fitness of the carrying individual. It may then have an important impact on neutral polymorphism due to the genetic hitchhiking effect. We study this hitchhiking effect in the case of true meiotic drive in autosomes and show that it is more dependent on the recombination rate than in the classical case of a gene positively selected at the organism level.

Two- and three-locus tests for linkage analysis using recombinant inbred lines.

We consider fixed recombinant inbred lines (RILs) derived either by selfing or by full-sib mating; when applicable, we also consider intermated recombinant inbreds (IRIs). First, we show that the usual estimate of recombination fraction based on RIL data is biased, and we provide an estimate where the major part of that bias is removed. Second, we derive simple formulas to compute the frequencies of genotypes at three loci in RILs. We describe the nonindependence of multiple recombinations arising in RIL recombination data even though there may be no interference in each meiosis. Finally, we give formulas for interference tests, gene mapping, or QTL detection in RIL populations.

Blocks of chromosomes identical by descent in a population: Models and predictions.

With the highly dense genomic data available nowadays, ignoring linkage between genes would result in a huge loss of information. One way to prevent such a loss is to focus on the blocks of chromosomes shared identical by descent (IBD) in populations. The development of the theoretical framework modelling IBD processes is essential to support the advent of new tools such as haplotype phasing, imputation, inferring population structure and demographic history, mapping loci or detecting signatures of selection. This article aims to present the relevant models used in this context, and specify the underlying definitions of identity by descent that are yet to be gathered at one place. In light of this, we derived a general expression for the expected IBD block length, for any population model at any generation after founding.

Toward a theory of marker-assisted gene pyramiding.

We investigate the best way to combine into a single genotype a series of target genes identified in different parents (gene pyramiding). Assuming that individuals can be selected and mated according to their genotype, the best method corresponds to an optimal succession of crosses over several generations (pedigree). For each pedigree, we compute the probability of success from the known recombination fractions between the target loci, as well as the number of individuals (population sizes) that should be genotyped over successive generations until the desired genotype is obtained. We provide an algorithm that generates and compares pedigrees on the basis of the population sizes they require and on their total duration (in number of generations) and finds the best gene-pyramiding scheme. Examples are given for eight target genes and are compared to a reference genotype selection method with random mating. The best gene-pyramiding method combines the eight targets in three generations less than the reference method while requiring fewer genotypings.

Marker-assisted introgression of favorable alleles at quantitative trait loci between maize elite lines.

This article reports the marker-assisted introgression of favorable alleles at three quantitative trait loci (QTL) for earliness and grain yield among maize elite lines. The QTL were originally detected in 1992 by means of ANOVA in a population of 96 recombinant inbred lines (RILs). Introgression started from a selected RIL, which was crossed three times to one of the original parents and then self-fertilized, leading to BC(3)S(1) progenies. Markers were used to assist both foreground and background selection at each generation. At the end of the program, the effect of introgression was assessed phenotypically in agronomic trials, and QTL detection was performed by composite interval mapping among BC(3)S(1) progenies. The marker-assisted introgression proved successful at the genotypic level, as analyzed by precision graphical genotypes, although no emphasis was put on the reduction of linkage drag around QTL. Also, QTL positions were generally sustained in the introgression background. For earliness, the magnitude and sign of the QTL effects were in good agreement with those expected from initial RIL analyses. Conversely, for yield, important discrepancies were observed in the magnitude and sign of the QTL effects observed after introgression, when compared to those expected from initial RIL analyses. These discrepancies are probably due to important genotype-by-environment interactions.

Efficiently tracking selection in a multiparental population: the case of earliness in wheat.

Multiparental populations are innovative tools for fine mapping large numbers of loci. Here we explored the application of a wheat Multiparent Advanced Generation Inter-Cross (MAGIC) population for QTL mapping. This population was created by 12 generations of free recombination among 60 founder lines, following modification of the mating system from strict selfing to strict outcrossing using the ms1b nuclear male sterility gene. Available parents and a subset of 380 SSD lines of the resulting MAGIC population were phenotyped for earliness and genotyped with the 9K i-Select SNP array and additional markers in candidate genes controlling heading date. We demonstrated that 12 generations of strict outcrossing rapidly and drastically reduced linkage disequilibrium to very low levels even at short map distances and also greatly reduced the population structure exhibited among the parents. We developed a Bayesian method, based on allelic frequency, to estimate the contribution of each parent in the evolved population. To detect loci under selection and estimate selective pressure, we also developed a new method comparing shifts in allelic frequency between the initial and the evolved populations due to both selection and genetic drift with expectations under drift only. This evolutionary approach allowed us to identify 26 genomic areas under selection. Using association tests between flowering time and polymorphisms, 6 of these genomic areas appeared to carry flowering time QTL, 1 of which corresponds to Ppd-D1, a major gene involved in the photoperiod sensitivity. Frequency shifts at 4 of 6 areas were consistent with earlier flowering of the evolved population relative to the initial population. The use of this new outcrossing wheat population, mixing numerous initial parental lines through multiple generations of panmixia, is discussed in terms of power to detect genes under selection and association mapping. Furthermore we provide new statistical methods for use in future analyses of multiparental populations.

Mapping the epigenetic basis of complex traits.

Quantifying the impact of heritable epigenetic variation on complex traits is an emerging challenge in population genetics. Here, we analyze a population of isogenic Arabidopsis lines that segregate experimentally induced DNA methylation changes at hundreds of regions across the genome. We demonstrate that several of these differentially methylated regions (DMRs) act as bona fide epigenetic quantitative trait loci (QTL(epi)), accounting for 60 to 90% of the heritability for two complex traits, flowering time and primary root length. These QTL(epi) are reproducible and can be subjected to artificial selection. Many of the experimentally induced DMRs are also variable in natural populations of this species and may thus provide an epigenetic basis for Darwinian evolution independently of DNA sequence changes.

Distribution of parental genome blocks in recombinant inbred lines.

We consider recombinant inbred lines obtained by crossing two given homozygous parents and then applying multiple generations of self-crossings or full-sib matings. The chromosomal content of any such line forms a mosaic of blocks, each alternatively inherited identically by descent from one of the parents. Quantifying the statistical properties of such mosaic genomes has remained an open challenge for many years. Here, we solve this problem by taking a continuous chromosome picture and assuming crossovers to be noninterfering. Using a continuous-time random walk framework and Markov chain theory, we determine the statistical properties of these identical-by-descent blocks. We find that successive block lengths are only very slightly correlated. Furthermore, the blocks on the ends of chromosomes are larger on average than the others, a feature understandable from the nonexponential distribution of block lengths.

Genome-wide epigenetic perturbation jump-starts patterns of heritable variation found in nature.

We extensively phenotyped 6000 Arabidopsis plants with experimentally perturbed DNA methylomes as well as a diverse panel of natural accessions in a common garden. We found that alterations in DNA methylation not only caused heritable phenotypic diversity but also produced heritability patterns closely resembling those of the natural accessions. Our findings indicate that epigenetically induced and naturally occurring variation in complex traits share part of their polygenic architecture and may offer complementary adaptation routes in ecological settings.