Large-effect Mutations Research Articles

Quantitative evolutionary dynamics using high-resolution lineage tracking.

Evolution of large asexual cell populations underlies ∼30% of deaths worldwide, including those caused by bacteria, fungi, parasites, and cancer. However, the dynamics underlying these evolutionary processes remain poorly understood because they involve many competing beneficial lineages, most of which never rise above extremely low frequencies in the population. To observe these normally hidden evolutionary dynamics, we constructed a sequencing-based ultra high-resolution lineage tracking system in Saccharomyces cerevisiae that allowed us to monitor the relative frequencies of ∼500,000 lineages simultaneously. In contrast to some expectations, we found that the spectrum of fitness effects of beneficial mutations is neither exponential nor monotonic. Early adaptation is a predictable consequence of this spectrum and is strikingly reproducible, but the initial small-effect mutations are soon outcompeted by rarer large-effect mutations that result in variability between replicates. These results suggest that early evolutionary dynamics may be deterministic for a period of time before stochastic effects become important.

The great evolutionary divide: two genomic systems biologies of aging.

There is not one systems biology of aging, but two. Though aging can evolve in either sexual or asexual species when there is asymmetric reproduction, the evolutionary genetics of aging in species with frequent sexual recombination are quite different from those arising when sex is rare or absent. When recombination is rare, selection is expected to act chiefly on rare large-effect mutations, which purge genetic variation due to genome-wide hitchhiking. In such species, the systems biology of aging can focus on the effects of large-effect mutants, transgenics, and combinations of such genetic manipulations. By contrast, sexually outbreeding species maintain abundant genetic polymorphism within populations. In such species, the systems biology of aging can examine the genome-wide effects of selection and genetic drift on the numerous polymorphic loci that respond to laboratory selection for different patterns of aging. An important question of medical relevance is to what extent insights derived from the systems biology of aging in model species can be applied to human aging.

Quantitative genetic analysis indicates natural selection on leaf phenotypes across wild tomato species (Solanum sect. Lycopersicon; Solanaceae).

Adaptive evolution requires both raw genetic material and an accessible path of high fitness from one fitness peak to another. In this study, we used an introgression line (IL) population to map quantitative trait loci (QTL) for leaf traits thought to be associated with adaptation to precipitation in wild tomatoes (Solanum sect. Lycopersicon; Solanaceae). A QTL sign test showed that several traits likely evolved under directional natural selection. Leaf traits correlated across species do not share a common genetic basis, consistent with a scenario in which selection maintains trait covariation unconstrained by pleiotropy or linkage disequilibrium. Two large effect QTL for stomatal distribution colocalized with key genes in the stomatal development pathway, suggesting promising candidates for the molecular bases of adaptation in these species. Furthermore, macroevolutionary transitions between vastly different stomatal distributions may not be constrained when such large-effect mutations are available. Finally, genetic correlations between stomatal traits measured in this study and data on carbon isotope discrimination from the same ILs support a functional hypothesis that the distribution of stomata affects the resistance to CO2 diffusion inside the leaf, a trait implicated in climatic adaptation in wild tomatoes. Along with evidence from previous comparative and experimental studies, this analysis indicates that leaf traits are an important component of climatic niche adaptation in wild tomatoes and demonstrates that some trait transitions between species could have involved few, large-effect genetic changes, allowing rapid responses to new environmental conditions.

De novo assembly of soybean wild relatives for pan-genome analysis of diversity and agronomic traits.

Wild relatives of crops are an important source of genetic diversity for agriculture, but their gene repertoire remains largely unexplored. We report the establishment and analysis of a pan-genome of Glycine soja, the wild relative of cultivated soybean Glycine max, by sequencing and de novo assembly of seven phylogenetically and geographically representative accessions. Intergenomic comparisons identified lineage-specific genes and genes with copy number variation or large-effect mutations, some of which show evidence of positive selection and may contribute to variation of agronomic traits such as biotic resistance, seed composition, flowering and maturity time, organ size and final biomass. Approximately 80% of the pan-genome was present in all seven accessions (core), whereas the rest was dispensable and exhibited greater variation than the core genome, perhaps reflecting a role in adaptation to diverse environments. This work will facilitate the harnessing of untapped genetic diversity from wild soybean for enhancement of elite cultivars.

Evolutionarily recent, exonic mutations are strong genetic risk factors for endometrosis

Most genetic studies of endometriosis have searched for relatively common “ancestral” genetic markers, even though most diseases with decreased reproductive fitness are more likely to be impacted by recent (rare) and even de novo mutations. Whole genome/exome sequencing has now been published on nearly a million human subjects. Collectively these studies have identified thousands of rare exome variants (seen in < 1% of the general population) predicted to affect protein function. We suspect that many of these mutations contribute to reproductive disorders. We tested 27,924 rare exonic variants with a frequency < 0.01 among controls and with a minimum of 3 heterozygous individuals in both our case and control populations. non-synonymous protein-damaging exome variants for association with endometriosis. 1,537 Caucasian endometriosis patients were genotyped and compared with published population data (n>50,000). All endometriosis subjects had surgically proven disease. All DNA samples were tested using the Infinium HumanExome BeadChip (Illumina, San Diego). The significance of association was calculated using Fisher’s Exact Test. The in-silico annotation of variant function was predicted using polyphen 2 database. 21 rare exonic variants were associated with endometriosis (p<5×10-8) with a mean odds ratio of 6.7. Genes affected were: AP1M2, BTNL2, C8orf74, CLEC4F, CR1L, FAM71E2, FRAS1, GJB2, HYAL2, IKBKE, IQCH, KRTAP19-8, PMFBP1, PPM1E, RAPSN, RHBDD1, SLC24A5, SLC38A6, STAM2, THOC5, none of which have previously been associated with endometriosis. The high odds ratio suggests that these markers are stronger risk factors than the single nucleotide polymorphism (SNP) associations published to date. Nineteen of the variants are non-synonymous and 6 of the variants are reported by PolyPhen2 as “possibly damaging”. Although some of the implicated genes are involved in inflammation, macrophage activation, adhesion, and receptor and signaling activity, most variations point to proteins not previously studied in the context of endometriosis. Rare protein altering mutations of large effect contribute to the genetic risk for endometriosis. Finding of novel genes not previously implicated in endometriosis will help expand the functional understanding of the pathogenesis of endometriosis.

Genetics of epilepsy: The testimony of twins in the molecular era.

Analysis of twins with epilepsy to explore the genetic architecture of specific epilepsies, to evaluate the applicability of the 2010 International League Against Epilepsy (ILAE) organization of epilepsy syndromes, and to integrate molecular genetics with phenotypic analyses. A total of 558 twin pairs suspected to have epilepsy were ascertained from twin registries (69%) or referral (31%). Casewise concordance estimates were calculated for epilepsy syndromes. Epilepsies were then grouped according to the 2010 ILAE organizational scheme. Molecular genetic information was utilized where applicable. Of 558 twin pairs, 418 had confirmed seizures. A total of 534 twin individuals were affected. There were higher twin concordance estimates for monozygotic (MZ) than for dizygotic (DZ) twins for idiopathic generalized epilepsies (MZ = 0.77; DZ = 0.35), genetic epilepsy with febrile seizures plus (MZ = 0.85; DZ = 0.25), and focal epilepsies (MZ = 0.40; DZ = 0.03). Utilizing the 2010 ILAE scheme, the twin data clearly demonstrated genetic influences in the syndromes designated as genetic. Of the 384 tested twin individuals, 10.9% had mutations of large effect in known epilepsy genes or carried validated susceptibility alleles. Twin studies confirm clear genetic influences for specific epilepsies. Analysis of the twin sample using the 2010 ILAE scheme strongly supported the validity of grouping the "genetic" syndromes together and shows this organizational scheme to be a more flexible and biologically meaningful system than previous classifications. Successful selected molecular testing applied to this cohort is the prelude to future large-scale next-generation sequencing of epilepsy research cohorts. Insights into genetic architecture provided by twin studies provide essential data for optimizing such approaches.

Endometriosis is associated with rare copy number variants.

Endometriosis is a complex gynecological condition that affects 6–10% of women in their reproductive years and is defined by the presence of endometrial glands and stroma outside the uterus. Twin, family, and genome-wide association (GWA) studies have confirmed a genetic role, yet only a small part of the genetic risk can be explained by SNP variation. Copy number variants (CNVs) account for a greater portion of human genetic variation than SNPs and include more recent mutations of large effect. CNVs, likely to be prominent in conditions with decreased reproductive fitness, have not previously been examined as a genetic contributor to endometriosis. Here we employ a high-density genotyping microarray in a genome-wide survey of CNVs in a case-control population that includes 2,126 surgically confirmed endometriosis cases and 17,974 population controls of European ancestry. We apply stringent quality filters to reduce the false positive rate common to many CNV-detection algorithms from 77.7% to 7.3% without noticeable reduction in the true positive rate. We detected no differences in the CNV landscape between cases and controls on the global level which showed an average of 1.92 CNVs per individual with an average size of 142.3 kb. On the local level we identify 22 CNV-regions at the nominal significance threshold (P<0.05), which is greater than the 8.15 CNV-regions expected based on permutation analysis (P<0.001). Three CNV's passed a genome-wide P-value threshold of 9.3×10−4; a deletion at SGCZ on 8p22 (P = 7.3×10−4, OR = 8.5, Cl = 2.3–31.7), a deletion in MALRD1 on 10p12.31 (P = 5.6×10−4, OR = 14.1, Cl = 2.7–90.9), and a deletion at 11q14.1 (P = 5.7×10−4, OR = 33.8, Cl = 3.3–1651). Two SNPs within the 22 CNVRs show significant genotypic association with endometriosis after adjusting for multiple testing; rs758316 in DPP6 on 7q36.2 (P = 0.0045) and rs4837864 in ASTN2 on 9q33.1 (P = 0.0002). Together, the CNV-loci are detected in 6.9% of affected women compared to 2.1% in the general population.

Fitness is strongly influenced by rare mutations of large effect in a microbial mutation accumulation experiment.

Our understanding of the evolutionary consequences of mutation relies heavily on estimates of the rate and fitness effect of spontaneous mutations generated by mutation accumulation (MA) experiments. We performed a classic MA experiment in which frequent sampling of MA lines was combined with whole genome resequencing to develop a high-resolution picture of the effect of spontaneous mutations in a hypermutator (ΔmutS) strain of the bacterium Pseudomonas aeruginosa. After ∼644 generations of mutation accumulation, MA lines had accumulated an average of 118 mutations, and we found that average fitness across all lines decayed linearly over time. Detailed analyses of the dynamics of fitness change in individual lines revealed that a large fraction of the total decay in fitness (42.3%) was attributable to the fixation of rare, highly deleterious mutations (comprising only 0.5% of fixed mutations). Furthermore, we found that at least 0.64% of mutations were beneficial and probably fixed due to positive selection. The majority of mutations that fixed (82.4%) were base substitutions and we failed to find any signatures of selection on nonsynonymous or intergenic mutations. Short indels made up a much smaller fraction of the mutations that were fixed (17.4%), but we found evidence of strong selection against indels that caused frameshift mutations in coding regions. These results help to quantify the amount of natural selection present in microbial MA experiments and demonstrate that changes in fitness are strongly influenced by rare mutations of large effect.

An atomic-resolution view of neofunctionalization in the evolution of apicomplexan lactate dehydrogenases.

Malate and lactate dehydrogenases (MDH and LDH) are homologous, core metabolic enzymes that share a fold and catalytic mechanism yet possess strict specificity for their substrates. In the Apicomplexa, convergent evolution of an unusual LDH from MDH produced a difference in specificity exceeding 12 orders of magnitude. The mechanisms responsible for this extraordinary functional shift are currently unknown. Using ancestral protein resurrection, we find that specificity evolved in apicomplexan LDHs by classic neofunctionalization characterized by long-range epistasis, a promiscuous intermediate, and few gain-of-function mutations of large effect. In canonical MDHs and LDHs, a single residue in the active-site loop governs substrate specificity: Arg102 in MDHs and Gln102 in LDHs. During the evolution of the apicomplexan LDH, however, specificity switched via an insertion that shifted the position and identity of this 'specificity residue' to Trp107f. Residues far from the active site also determine specificity, as shown by the crystal structures of three ancestral proteins bracketing the key duplication event. This work provides an unprecedented atomic-resolution view of evolutionary trajectories creating a nascent enzymatic function.

Historical contingency and its biophysical basis in glucocorticoid receptor evolution.

Understanding how chance historical events shape evolutionary processes is a central goal of evolutionary biology1–7. Direct insights into the extent and causes of evolutionary contingency have been limited to experimental systems,7–9 because it is difficult to know what happened in the deep past and to characterize other paths that evolution could have followed. Here we combine ancestral protein reconstruction, directed evolution, and biophysical analysis to explore alternate “might-have-been” trajectories during the ancient evolution of a novel protein function. We previously found that the evolution of cortisol specificity in the ancestral glucocorticoid receptor (GR) was contingent on permissive substitutions, which had no apparent effect on receptor function but were necessary for GR to tolerate the large-effect mutations that caused the shift in specificity.6 Here we show that alternative mutations that could have permitted the historical function-switching substitutions are extremely rare in the ensemble of genotypes accessible to the ancestral GR. In a library of thousands of variants of the ancestral protein, we recovered historical permissive substitutions, but no alternate permissive genotypes. Using biophysical analysis, we found that permissive mutations must satisfy at least three physical requirements—they must stabilize specific local elements of the protein structure, maintain the correct energetic balance between functional conformations, and be compatible with the ancestral and derived structures—thus revealing why permissive mutations are rare. These findings demonstrate that GR evolution depended strongly on improbable, nondeterministic events, and this contingency arose from intrinsic biophysical properties of the protein.

Tissue culture-induced heritable genomic variation in rice, and their phenotypic implications.

BackgroundSomaclonal variation generally occurs in plants regenerated from tissue culture. However, fundamental issues regarding molecular characteristics, mutation rates and mutation spectra of plant somatic variation as well as their phenotypic relevance have been addressed only recently. Moreover, these studies have reported highly discrepant results in different plant species and even in the same plant genotype.Methodology/principal findingsWe investigated heritable genomic variation induced by tissue culture in rice by whole genome re-sequencing of an extensively selfed somaclonal line (TC-reg-2008) and its wild type (WT) donor (cv. Hitomebore). We computed the overall mutation rate, single nucleotide polymorphisms (SNPs), small scale insertions/deletions (Indels) and mobilization of transposable elements (TEs). We assessed chromosomal distribution of the various types of genomic variations, tested correlations between SNPs and Indels, and examined concomitancy between TE activity and its cytosine methylation states. We also performed gene ontology (GO) analysis of genes containing nonsynonymous mutations and large-effect mutations, and assayed effects of the genomic variations on phenotypes under both normal growing condition and several abiotic stresses. We found that heritable somaclonal genomic variation occurred extensively in rice. The genomic variations distributed non-randomly across each of the 12 rice chromosomes, and affected a large number of functional genes. The phenotypic penetrance of the genomic variations was condition-dependent.Conclusions/significanceTissue culture is a potent means to generate heritable genetic variations in rice, which bear distinct difference at least in space (chromosomal distribution) from those occurred under natural settings. Our findings have provided new information regarding the mutation rate and spectrum as well as chromosomal distribution pattern of somaclonal variation in rice. Our data also suggest that rice possesses a strong capacity to canalize genetic variations under normal growing conditions to maintain phenotypic robustness, which however can be released by certain abiotic stresses to generate variable phenotypes.

The Fates of Mutant Lineages and the Distribution of Fitness Effects of Beneficial Mutations in Laboratory Budding Yeast Populations

The outcomes of evolution are determined by which mutations occur and fix. In rapidly adapting microbial populations, this process is particularly hard to predict because lineages with different beneficial mutations often spread simultaneously and interfere with one another's fixation. Hence to predict the fate of any individual variant, we must know the rate at which new mutations create competing lineages of higher fitness. Here, we directly measured the effect of this interference on the fates of specific adaptive variants in laboratory Saccharomyces cerevisiae populations and used these measurements to infer the distribution of fitness effects of new beneficial mutations. To do so, we seeded marked lineages with different fitness advantages into replicate populations and tracked their subsequent frequencies for hundreds of generations. Our results illustrate the transition between strongly advantageous lineages that decisively sweep to fixation and more moderately advantageous lineages that are often outcompeted by new mutations arising during the course of the experiment. We developed an approximate likelihood framework to compare our data to simulations and found that the effects of these competing beneficial mutations were best approximated by an exponential distribution, rather than one with a single effect size. We then used this inferred distribution of fitness effects to predict the rate of adaptation in a set of independent control populations. Finally, we discuss how our experimental design can serve as a screen for rare, large-effect beneficial mutations.

Vestigialization of an Allosteric Switch: Genetic and Structural Mechanisms for the Evolution of Constitutive Activity in a Steroid Hormone Receptor

An important goal in molecular evolution is to understand the genetic and physical mechanisms by which protein functions evolve and, in turn, to characterize how a protein's physical architecture influences its evolution. Here we dissect the mechanisms for an evolutionary shift in function in the mollusk ortholog of the steroid hormone receptors (SRs), a family of biologically essential transcription factors. In vertebrates, the activity of SRs allosterically depends on binding a hormonal ligand; in mollusks, however, the SR ortholog (called ER, because of high sequence similarity to vertebrate estrogen receptors) activates transcription in the absence of ligand and does not respond to steroid hormones. To understand how this shift in regulation evolved, we combined evolutionary, structural, and functional analyses. We first determined the X-ray crystal structure of the ER of the Pacific oyster Crassostrea gigas (CgER), and found that its ligand pocket is filled with bulky residues that prevent ligand occupancy. To understand the genetic basis for the evolution of mollusk ERs' unique functions, we resurrected an ancient SR progenitor and characterized the effect of historical amino acid replacements on its functions. We found that reintroducing just two ancient replacements from the lineage leading to mollusk ERs recapitulates the evolution of full constitutive activity and the loss of ligand activation. These substitutions stabilize interactions among key helices, causing the allosteric switch to become “stuck” in the active conformation and making activation independent of ligand binding. Subsequent changes filled the ligand pocket without further affecting activity; by degrading the allosteric switch, these substitutions vestigialized elements of the protein's architecture required for ligand regulation and made reversal to the ancestral function more complex. These findings show how the physical architecture of allostery enabled a few large-effect mutations to trigger a profound evolutionary change in the protein's function and shaped the genetics of evolutionary reversibility.

ADAPTIVE WALKS AND DISTRIBUTION OF BENEFICIAL FITNESS EFFECTS

We study the adaptation dynamics of a maladapted asexual population on rugged fitness landscapes with many local fitness peaks. The distribution of beneficial fitness effects is assumed to belong to one of the three extreme value domains, viz. Weibull, Gumbel, and Fréchet. We work in the strong selection-weak mutation regime in which beneficial mutations fix sequentially, and the population performs an uphill walk on the fitness landscape until a local fitness peak is reached. A striking prediction of our analysis is that the fitness difference between successive steps follows a pattern of diminishing returns in the Weibull domain and accelerating returns in the Fréchet domain, as the initial fitness of the population is increased. These trends are found to be robust with respect to fitness correlations. We believe that this result can be exploited in experiments to determine the extreme value domain of the distribution of beneficial fitness effects. Our work here differs significantly from the previous ones that assume the selection coefficient to be small. On taking large effect mutations into account, we find that the length of the walk shows different qualitative trends from those derived using small selection coefficient approximation.

Using genomic tools to maintain diversity and fitness in conservation programmes

Conservation programmes aim at maximizing the survival probability of populations, by minimizing the loss of genetic diversity, which allows populations to adapt to changes, and controlling inbreeding increases. The best known strategy to achieve these goals is optimizing the contributions of the parents to minimize global coancestry in their offspring. Results on neutral scenarios showed that management based on molecular coancestry could maintain more diversity than management based on genealogical coancestry when a large number of markers were available. However, if the population has deleterious mutations, managing using optimal contributions can lead to a decrease in fitness, especially using molecular coancestry, because both beneficial and harmful alleles are maintained, compromising the long-term viability of the population. We introduce here two strategies to avoid this problem: The first one uses molecular coancestry calculated removing markers with low minor allele frequencies, as they could be linked to selected loci. The second one uses a coancestry based on segments of identity by descent, which measures the proportion of genome segments shared by two individuals because of a common ancestor. We compare these strategies under two contrasting mutational models of fitness effects, one assuming many mutations of small effect and another with few mutations of large effect. Using markers at intermediate frequencies maintains a larger fitness than using all markers, but leads to maintaining less diversity. Using the segment-based coancestry provides a compromise solution between maintaining diversity and fitness, especially when the population has some inbreeding load.

Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support.

Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality traits in Bos taurus, Bos indicus, and composite beef cattle1

The aim of this study was to assess the accuracy of genomic predictions for 19 traits including feed efficiency, growth, and carcass and meat quality traits in beef cattle. The 10,181 cattle in our study had real or imputed genotypes for 729,068 SNP although not all cattle were measured for all traits. Animals included Bos taurus, Brahman, composite, and crossbred animals. Genomic EBV (GEBV) were calculated using 2 methods of genomic prediction [BayesR and genomic BLUP (GBLUP)] either using a common training dataset for all breeds or using a training dataset comprising only animals of the same breed. Accuracies of GEBV were assessed using 5-fold cross-validation. The accuracy of genomic prediction varied by trait and by method. Traits with a large number of recorded and genotyped animals and with high heritability gave the greatest accuracy of GEBV. Using GBLUP, the average accuracy was 0.27 across traits and breeds, but the accuracies between breeds and between traits varied widely. When the training population was restricted to animals from the same breed as the validation population, GBLUP accuracies declined by an average of 0.04. The greatest decline in accuracy was found for the 4 composite breeds. The BayesR accuracies were greater by an average of 0.03 than GBLUP accuracies, particularly for traits with known genes of moderate to large effect mutations segregating. The accuracies of 0.43 to 0.48 for IGF-I traits were among the greatest in the study. Although accuracies are low compared with those observed in dairy cattle, genomic selection would still be beneficial for traits that are hard to improve by conventional selection, such as tenderness and residual feed intake. BayesR identified many of the same quantitative trait loci as a genomewide association study but appeared to map them more precisely. All traits appear to be highly polygenic with thousands of SNP independently associated with each trait.

Biophysical mechanisms for large-effect mutations in the evolution of steroid hormone receptors

The genetic and biophysical mechanisms by which new protein functions evolve is a central question in evolutionary biology, biochemistry, and biophysics. Of particular interest is whether major shifts in protein function are caused by a few mutations of large effect and, if they are, the mechanisms that mediate these changes. Here we combine ancestral protein reconstruction with genetic manipulation and explicit studies of protein structure and dynamics to dissect an ancient and discrete shift in ligand specificity in the steroid receptors, a family of biologically essential hormone-controlled transcription factors. We previously found that the ancestor of the entire steroid receptor family was highly specific for estrogens, but its immediate phylogenetic descendant was sensitive only to androgens, progestogens, and corticosteroids. Here we show that this shift in function was driven primarily by two historical amino acid changes, which caused a ∼70,000-fold change in the ancestral protein's specificity. These replacements subtly changed the chemistry of two amino acids, but they dramatically reduced estrogen sensitivity by introducing an excess of interaction partners into the receptor/estrogen complex, inducing a frustrated ensemble of suboptimal hydrogen bond networks unique to estrogens. This work shows how the protein's architecture and dynamics shaped its evolution, amplifying a few biochemically subtle mutations into major shifts in the energetics and function of the protein.

Detection of selective sweeps in cattle using genome-wide SNP data

BackgroundThe domestication and subsequent selection by humans to create breeds and biological types of cattle undoubtedly altered the patterning of variation within their genomes. Strong selection to fix advantageous large-effect mutations underlying domesticability, breed characteristics or productivity created selective sweeps in which variation was lost in the chromosomal region flanking the selected allele. Selective sweeps have now been identified in the genomes of many animal species including humans, dogs, horses, and chickens. Here, we attempt to identify and characterise regions of the bovine genome that have been subjected to selective sweeps.ResultsTwo datasets were used for the discovery and validation of selective sweeps via the fixation of alleles at a series of contiguous SNP loci. BovineSNP50 data were used to identify 28 putative sweep regions among 14 diverse cattle breeds. Affymetrix BOS 1 prescreening assay data for five breeds were used to identify 85 regions and validate 5 regions identified using the BovineSNP50 data. Many genes are located within these regions and the lack of sequence data for the analysed breeds precludes the nomination of selected genes or variants and limits the prediction of the selected phenotypes. However, phenotypes that we predict to have historically been under strong selection include horned-polled, coat colour, stature, ear morphology, and behaviour.ConclusionsThe bias towards common SNPs in the design of the BovineSNP50 assay led to the identification of recent selective sweeps associated with breed formation and common to only a small number of breeds rather than ancient events associated with domestication which could potentially be common to all European taurines. The limited SNP density, or marker resolution, of the BovineSNP50 assay significantly impacted the rate of false discovery of selective sweeps, however, we found sweeps in common between breeds which were confirmed using an ultra-high-density assay scored in a small number of animals from a subset of the breeds. No sweep regions were shared between indicine and taurine breeds reflecting their divergent selection histories and the very different environmental habitats to which these sub-species have adapted.

An experimental assessment of artificial within-family selection for fitness in conservation programs

Equalizing familiar contributions is the simplest recommended strategy to maintain genetic diversity in conservation programs. However, this method implies a relaxation of natural selection and the possibility of accumulation of deleterious mutations. Computer simulations have shown that performing selection within families for fitness traits in a conservation program can be useful to alleviate such problems. We thus carried out an experiment with the model species Drosophila melanogaster in order to assess whether or not selection for fitness traits can be useful. We considered a fitness trait (pupa productivity) that was first checked to perform as a typical fitness component. The trait showed an inbreeding depression of 1.2 per 1 % increase in inbreeding and an asymmetrical response to selection with average realized heritabilities of about 0.04 in the upward direction and an order of magnitude larger (0.36) in the downward direction. The management experiment indicated that artificial within-family selection for fitness had only a marginal success for two reasons. First, there was not an appreciable decline in fitness across the experiment despite the low population sizes assumed (N = 10 or 20), even in the population not subjected to selection. This result is compatible with fitness models which imply the segregation of few deleterious mutations of large effect. Second, artificial selection within families had a limited impact on the trait, as one expects for a typical fitness component with very low heritability.