Concetta Burgarella

Mutation rate estimates for 110 Y-chromosome STRs combining population and father–son pair data

Y-chromosome microsatellites (Y-STRs) are typically used for kinship analysis and forensic identification, as well as for inferences on population history and evolution. All applications would greatly benefit from reliable locus-specific mutation rates, to improve forensic probability calculations and interpretations of diversity data. However, estimates of mutation rate from father–son transmissions are available for few loci and have large confidence intervals, because of the small number of meiosis usually observed. By contrast, population data exist for many more Y-STRs, holding unused information about their mutation rates. To incorporate single locus diversity information into Y-STR mutation rate estimation, we performed a meta-analysis using pedigree data for 80 loci and individual haplotypes for 110 loci, from 29 and 93 published studies, respectively. By means of logistic regression we found that relative genetic diversity, motif size and repeat structure explain the variance of observed rates of mutations from meiosis. This model allowed us to predict locus-specific mutation rates (mean predicted mutation rate 2.12 × 10−3, SD=1.58 × 10−3), including estimates for 30 loci lacking meiosis observations and 41 with a previous estimate of zero. These estimates are more accurate than meiosis-based estimates when a small number of meiosis is available. We argue that our methodological approach, by taking into account locus diversity, could be also adapted to estimate population or lineage-specific mutation rates. Such adjusted estimates would represent valuable information for selecting the most reliable markers for a wide range of applications.

High-density genome-wide association mapping implicates an F-box encoding gene in Medicago truncatula resistance to Aphanomyces euteiches

• The use of quantitative disease resistance (QDR) is a promising strategy for promoting durable resistance to plant pathogens, but genes involved in QDR are largely unknown. To identify genetic components and accelerate improvement of QDR in legumes to the root pathogen Aphanomyces euteiches, we took advantage of both the recently generated massive genomic data for Medicago truncatula and natural variation of this model legume. • A high-density (≈5.1 million single nucleotide polymorphisms (SNPs)) genome-wide association study (GWAS) was performed with both in vitro and glasshouse phenotyping data collected for 179 lines. • GWAS identified several candidate genes and pinpointed two independent major loci on the top of chromosome 3 that were detected in both phenotyping methods. Candidate SNPs in the most significant locus (σ(A)²= 23%) were in the promoter and coding regions of an F-box protein coding gene. Subsequent qRT-PCR and bioinformatic analyses performed on 20 lines demonstrated that resistance is associated with mutations directly affecting the interaction domain of the F-box protein rather than gene expression. • These results refine the position of previously identified QTL to specific candidate genes, suggest potential molecular mechanisms, and identify new loci explaining QDR against A. euteiches.

Recent population decline and selection shape diversity of taxol-related genes.

Taxanes are defensive metabolites produced by Taxus species (yews) and used in anticancer therapies. Despite their medical interest, patterns of natural diversity in taxane‐related genes are unknown. We examined variation at five main genes of Taxus baccata in the Iberian Peninsula, a region where unique yew genetic resources are endangered. We looked at several gene features and applied complementary neutrality tests, including diversity/divergence tests, tests solely based on site frequency spectrum (SFS) and Zeng’s compound tests. To account for specific demography, microsatellite data were used to infer historical changes in population size based on an Approximate Bayesian Computation (ABC) approach. Polymorphism‐divergence tests pointed to positive selection for genes TBT and TAT and balancing selection for DBAT. In addition, neutrality tests based on SFS found that while a recent reduction in population size may explain most statistics’ values, selection may still be in action in genes TBT and DBAT, at least in some populations. Molecular signatures on taxol genes suggest the action of frequent selective waves with different direction or intensity, possibly related to varying adaptive pressures produced by the host–enemy co‐evolution on defence‐related genes. Such natural selection processes may have produced taxane variants still undiscovered.

Narrow genetic base in forest restoration with holm oak (Quercus ilex L.) in Sicily

In order to empirically assess the effect of actual seed sampling strategy on genetic diversity of holm oak (Quercus ilex) forestations in Sicily, we have analysed the genetic composition of two seedling lots (nursery stock and plantation) and their known natural seed origin stand by means of six nuclear microsatellite loci. Significant reduction in genetic diversity and significant difference in genetic composition of the seedling lots compared to the seed origin stand were detected. The female and the total effective number of parents were quantified by means of maternity assignment of seedlings and temporal changes in allele frequencies. Extremely low effective maternity numbers were estimated (Nfe ≈ 2–4) and estimates accounting for both seed and pollen donors gave also low values (Ne ≈ 35–50). These values can be explained by an inappropriate forestry seed harvest strategy limited to a small number of spatially close trees.RésuméDe manière à évaluer empiriquement l’effet sur la diversité génétique de la stratégie couramment utilisée pour échantillonner des graines en forêts de chêne vert en Sicile, nous avons analysé la composition génétique de deux lots de semis (en pépinière et en plantation) et de leur peuplement naturel d’origine à l’aide de six marqueurs nucléaires microsatellites. Une réduction significative de la diversité génétique et des différences significatives dans la composition génétique des lots de semis comparés à leur peuplement d’origine ont été détectées. Le nombre de mères efficace et le nombre d’ascendants total efficace ont été quantifiés en recherchant l’origine maternelle des semis et par une quantification temporelle des fréquences alléliques. Des nombres efficaces extrêmement faibles ont été estimés pour les mères (Nfe ≈ 2–4) et les estimations concernant les deux parents sont aussi faibles (Ne ≈ 35–50). Ces valeurs peuvent s’expliquer par une stratégie de récolte de graines inappropriée, se limitant à un très petit nombre de géniteurs spatiallement proches.

Characterization of Demographic Expansions From Pairwise Comparisons of Linked Microsatellite Haplotypes

This work extends the methods of demographic inference based on the distribution of pairwise genetic differences between individuals (mismatch distribution) to the case of linked microsatellite data. Population genetics theory describes the distribution of mutations among a sample of genes under different demographic scenarios. However, the actual number of mutations can rarely be deduced from DNA polymorphisms. The inclusion of mutation models in theoretical predictions can improve the performance of statistical methods. We have developed a maximum-pseudolikelihood estimator for the parameters that characterize a demographic expansion for a series of linked loci evolving under a stepwise mutation model. Those loci would correspond to DNA polymorphisms of linked microsatellites (such as those found on the Y chromosome or the chloroplast genome). The proposed method was evaluated with simulated data sets and with a data set of chloroplast microsatellites that showed signal for demographic expansion in a previous study. The results show that inclusion of a mutational model in the analysis improves the estimates of the age of expansion in the case of older expansions.

Single-nucleotide polymorphism discovery and diversity in the model legume Medicago truncatula

Extensive genomic resources are available in the model legume Medicago truncatula. Here, we present the discovery and design of the first array of single‐nucleotide polymorphism (SNP) markers in M. truncatula through large‐scale Sanger resequencing of genomic fragments spanning the genome, in a diverse panel of 16 M. truncatula accessions. Both anonymous fragments and fragments targeting candidate genes for flowering phenology and symbiosis were surveyed for nucleotide variation in almost 230 kb of unique genomic regions. A set of 384 SNP markers was designed for an Illuminas GoldenGate assay, genotyped on a collection of 192 inbred lines (CC192) representing the geographical range of the species and used to survey the diversity of two natural populations. Finally, 86% of the tested SNPs were of high quality and exhibited polymorphism in the CC192 collection. Even at the population level, we detected polymorphism for more than 50% of the selected SNPs. Analysis of the allele frequency spectrum in the CC192 showed a reduced ascertainment bias, mostly limited to very rare alleles (frequency <0.01). The substantial polymorphism detected at the species and population levels, the high marker quality and the potential to survey large samples of individuals make this set of SNP markers a valuable tool to improve our understanding of the effect of demographic and selective factors that shape the natural genetic diversity within the selfing species Medicago truncatula.

Adaptation to climate through flowering phenology: a case study in Medicago truncatula

Local climatic conditions likely constitute an important selective pressure on genes underlying important fitness‐related traits such as flowering time, and in many species, flowering phenology and climatic gradients strongly covary. To test whether climate shapes the genetic variation on flowering time genes and to identify candidate flowering genes involved in the adaptation to environmental heterogeneity, we used a large Medicago truncatula core collection to examine the association between nucleotide polymorphisms at 224 candidate genes and both climate variables and flowering phenotypes. Unlike genome‐wide studies, candidate gene approaches are expected to enrich for the number of meaningful trait associations because they specifically target genes that are known to affect the trait of interest. We found that flowering time mediates adaptation to climatic conditions mainly by variation at genes located upstream in the flowering pathways, close to the environmental stimuli. Variables related to the annual precipitation regime reflected selective constraints on flowering time genes better than the other variables tested (temperature, altitude, latitude or longitude). By comparing phenotype and climate associations, we identified 12 flowering genes as the most promising candidates responsible for phenological adaptation to climate. Four of these genes were located in the known flowering time QTL region on chromosome 7. However, climate and flowering associations also highlighted largely distinct gene sets, suggesting different genetic architectures for adaptation to climate and flowering onset.

Demographic inference through approximate-Bayesian-computation skyline plots

The skyline plot is a graphical representation of historical effective population sizes as a function of time. Past population sizes for these plots are estimated from genetic data, without a priori assumptions on the mathematical function defining the shape of the demographic trajectory. Because of this flexibility in shape, skyline plots can, in principle, provide realistic descriptions of the complex demographic scenarios that occur in natural populations. Currently, demographic estimates needed for skyline plots are estimated using coalescent samplers or a composite likelihood approach. Here, we provide a way to estimate historical effective population sizes using an Approximate Bayesian Computation (ABC) framework. We assess its performance using simulated and actual microsatellite datasets. Our method correctly retrieves the signal of contracting, constant and expanding populations, although the graphical shape of the plot is not always an accurate representation of the true demographic trajectory, particularly for recent changes in size and contracting populations. Because of the flexibility of ABC, similar approaches can be extended to other types of data, to multiple populations, or to other parameters that can change through time, such as the migration rate.

Discontinuities in quinoa biodiversity in the dry Andes: an 18-century perspective based on allelic genotyping

History and environment shape crop biodiversity, particularly in areas with vulnerable human communities and ecosystems. Tracing crop biodiversity over time helps understand how rural societies cope with anthropogenic or climatic changes. Exceptionally well preserved ancient DNA of quinoa (Chenopodium quinoa Willd.) from the cold and arid Andes of Argentina has allowed us to track changes and continuities in quinoa diversity over 18 centuries, by coupling genotyping of 157 ancient and modern seeds by 24 SSR markers with cluster and coalescence analyses. Cluster analyses revealed clear population patterns separating modern and ancient quinoas. Coalescence-based analyses revealed that genetic drift within a single population cannot explain genetic differentiation among ancient and modern quinoas. The hypothesis of a genetic bottleneck related to the Spanish Conquest also does not seem to apply at a local scale. Instead, the most likely scenario is the replacement of preexisting quinoa gene pools with new ones of lower genetic diversity. This process occurred at least twice in the last 18 centuries: first, between the 6th and 12th centuries—a time of agricultural intensification well before the Inka and Spanish conquests—and then between the 13th century and today—a period marked by farming marginalization in the late 19th century likely due to a severe multidecadal drought. While these processes of local gene pool replacement do not imply losses of genetic diversity at the metapopulation scale, they support the view that gene pool replacement linked to social and environmental changes can result from opposite agricultural trajectories.