Outbreeding Species Research Articles

Founder populations of Stuckenia pectinata in restored ponds originate from genetically diverse propagule pool: A case study of urban ponds in Brussels, Belgium

Eutrophication and cyanobacteria blooms are considered major problems for the biodiversity and water quality of urban ponds. While biomanipulation techniques such as drawdown with fish removal have great potential to restore turbid ponds to a clearwater status, it remains difficult to predict if and how macrophytes will recover naturally. Here, we used individual genotyping and population genetics based on 20 nuclear microsatellite loci to investigate the recruitment and recolonization strategies of the submerged macrophyte Stuckenia pectinata (L.) Börner. More specifically, we compared the founder genetic diversity of recovering populations just after biomanipulation to the genetic diversity of spontaneous, contiguous populations that settled over an extended period of time and were within the same catchment. Our results showed that turbid ponds may contain a persistent propagule bank that allows for an immediate re-establishment of genetically diverse populations of S. pectinata once a desired clearwater state is restored. Therefore, biomanipulation without sediment removal proved to be successful for founding populations to become immediately integrated with their established populations, thus maintaining the overall diversity of this species within local areas. Additionally, our results demonstrated an excess of heterozygotes in established populations that may be caused by substantial drift in albeit small effective population sizes of this predominantly outbreeding species.

Cationic and anionic detergent buffers in sequence yield high-quality genomic DNA from diverse plant species

Because of the heterogeneity among seedlings of outbreeding species, the use of seedling tissues as a source of DNA is unsuitable for the genomic characterization of elite germplasms. High-quality DNA, free of RNA, proteins, polysaccharides, secondary metabolites, and shearing, is mandatory for downstream molecular biology applications, especially for next-generation genome sequencing and pangenome analysis aiming to capture the complete genetic diversity within a species. The study aimed to accomplish an efficient protocol for the extraction of high-quality DNA suitable for diverse plant species/tissues. We describe a reliable, and consistent protocol suitable for the extraction of DNA from 42 difficult-to-extract plant species belonging to 33 angiosperm (monocot and dicot) families, including tissues such as seeds, roots, endosperm, and flower/fruit tissues. The protocol was first optimized for the outbreeding recalcitrant trees viz., Prosopis cineraria, Conocarpus erectus, and Phoenix dactylifera, which are rich in proteins, polysaccharides, and secondary metabolites, and the quality of the extracted DNA was confirmed by downstream applications. Nine procedures were attempted to extract high-quality, impurities-free DNA from these three plant species. Extraction of the ethanol-precipitated DNA from cetyltrimethylammonium bromide (CTAB) protocol using sodium dodecyl sulfate (SDS) buffer, i.e., the extraction using a cationic (CTAB) detergent followed by an anionic (SDS) detergent was the key for high yield and high purity (1.75–1.85 against A260/280 and an A260/230 ratio of >2) DNA. A vice versa extraction procedure, i.e., SDS buffer followed by CTAB buffer, and also CTAB buffer followed by CTAB, did not yield good-quality DNA. PCR (using different primers) and restriction endonuclease digestion of the DNA extracted from these three plants validated the protocol. The accomplishment of the genome of P. cineraria using the DNA extracted using the modified protocol confirmed its applicability to genomic studies. The optimized protocol successful in extracting high-quality DNA from diverse plant species/tissues extends its applicability and is useful for accomplishing genome sequences of elite germplasm of recalcitrant plant species with quality reads.

Investigating Population Genetic Diversity and Rhizosphere Microbiota of Central Apennines’ Artemisia eriantha

The present study aimed to characterize the genetic structure of Artemisia eriantha Ten. and the diversity of the rhizosphere microbiota. Plant leaves and rhizosphere soils were sampled from three areas of Central Italy, namely Monte Corvo, Monte Portella (both from the Gran Sasso massif), and Monte Focalone (Majella massif). The plant samples were subjected to genetic structure analysis by amplified fragment length polymorphism (AFLP) markers. The microbiota from the rhizosphere soils was investigated by 16S rRNA gene metabarcoding. The within and among population variability was typical of outbreeding species. The AFLP polymorphisms revealed a marked closeness among plant populations collected in Monte Focalone and Monte Corvo, despite the geographical proximity of the latter with Monte Portella, a result confirmed by cluster, STRUCTURE, and discriminant analyses. 16S rRNA gene metabarcoding showed higher values of diversity for Monte Corvo (H, 5.7; Chao1, 445) and Monte Focalone (H′, 5.57; Chao1, 446) than Monte Portella (H′, 5.3; Chao1, 275). At the phylum level, the communities were mainly represented by Proteobacteria, Actinobacteria, and Acidobacteria (>10%). At the genus level, the Monte Focalone and Monte Corvo microbiotas were closer than Monte Portella, thus confirming the results from the plant communities. The findings provided evidence for the first time of an association between the Artemisia eriantha plant and microbiota communities. The relevance of the results in terms of biodiversity and the conservation strategies of plant and microbiota communities in the Central Apennines are discussed.

Breeding Diploid F1 Hybrid Potatoes for Propagation from Botanical Seed (TPS): Comparisons with Theory and Other Crops.

This paper reviews the progress and the way ahead in diploid F1 hybrid potato breeding by comparisons with expectations from the theory of inbreeding and crossbreeding, and experiences from other diploid outbreeding crops. Diploid potatoes can be converted from an outbreeding species, in which self-pollination is prevented by a gametophytic self-incompatibility system, into one where self-pollination is possible, either through a dominant self-incompatibility inhibitor gene (Sli) or knockout mutations in the incompatibility locus. As a result, diploid F1 hybrid breeding can be used to produce genetically uniform potato cultivars for propagation from true potato seeds by crossing two near-homozygous inbred lines, derived from a number of generations of self-pollination despite inbreeding depression. Molecular markers can be used to detect and remove deleterious recessive mutations of large effect, including those in tight repulsion linkage. Improvements to the inbred lines can be made by introducing and stacking genes and chromosome segments of large desirable effect from wild relatives by backcrossing. Improvements in quantitative traits require a number of cycles of inbreeding and crossbreeding. Seed production can be achieved by hand pollinations. F1 hybrid planting material can be delivered to farmers as true seeds or young plants, and mini-tubers derived from true seeds.

A bulked segregant analysis tool for out-crossing species (BSATOS) and QTL-based genomics-assisted prediction of complex traits in apple

IntroductionGenomic heterozygosity, self-incompatibility, and rich-in somatic mutations hinder the molecular breeding efficiency of outcrossing plants. ObjectivesWe attempted to develop an efficient integrated strategy to identify quantitative trait loci (QTLs) and trait-associated genes, to develop gene markers, and to construct genomics-assisted prediction (GAP) modes. MethodsA novel protocol, bulked segregant analysis tool for out-crossing species (BSATOS), is presented here, which is characterized by taking full advantage of all segregation patterns (including AB × AB markers) and haplotype information. To verify the effectiveness of the protocol in dealing with the complex traits of outbreeding species, three apple cross populations with 9,654 individuals were adopted. ResultsBy using BSATOS, 90, 60, and 77 significant QTLs were identified successfully and candidate genes were predicted for apple fruit weight (FW), fruit ripening date (FRD), and fruit soluble solid content (SSC), respectively. The gene-based markers were developed and genotyped for 1,396 individuals in a training population, including 145 Malus accessions and 1,251 F1 plants of the three full-sib families. GAP models were trained using marker genotype effect estimates of the training population. The prediction accuracy was 0.7658, 0.6455, and 0.3758 for FW, FRD, and SSC, respectively. ConclusionThe BSATOS and GAP models provided a convenient and efficient methodology for candidate gene mining and molecular breeding in out-crossing plant species. The BSATOS pipeline can be freely downloaded from: https://github.com/maypoleflyn/BSATOS.

Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case.

The majority of forage grass species are obligate outbreeders. Their breeding classically consists of an initial selection on spaced plants for highly heritable traits such as disease resistances and heading date, followed by familial selection on swards for forage yield and quality traits. The high level of diversity and heterozygosity, and associated decay of linkage disequilibrium (LD) over very short genomic distances, has hampered the implementation of genomic selection (GS) in these species. However, next generation sequencing technologies in combination with the development of genomic resources have recently facilitated implementation of GS in forage grass species such as perennial ryegrass (Lolium perenne L.), switchgrass (Panicum virgatum L.), and timothy (Phleum pratense L.). Experimental work and simulations have shown that GS can increase significantly the genetic gain per unit of time for traits with different levels of heritability. The main reasons are (1) the possibility to select single plants based on their genomic estimated breeding values (GEBV) for traits measured at sward level, (2) a reduction in the duration of selection cycles, and less importantly (3) an increase in the selection intensity associated with an increase in the genetic variance used for selection. Nevertheless, several factors should be taken into account for the successful implementation of GS in forage grasses. For example, it has been shown that the level of relatedness between the training and the selection population is particularly critical when working with highly structured meta-populations consisting of several genetic groups. A sufficient number of markers should be used to estimate properly the kinship between individuals and to reflect the variability of major QTLs. It is also important that the prediction models are trained for relevant environments when dealing with traits with high genotype×environment interaction (G×E). Finally, in these outbreeding species, measures to reduce inbreeding should be used to counterbalance the high selection intensity that can be achieved in GS.

Optimizing sampling design and sequencing strategy for the genomic analysis of quantitative traits in natural populations.

Mapping the genes underlying ecologically relevant traits in natural populations is fundamental to develop a molecular understanding of species adaptation. Current sequencing technologies enable the characterization of a species' genetic diversity across the landscape or even over its whole range. The relevant capture of the genetic diversity across the landscape is critical for a successful genetic mapping of traits and there are no clear guidelines on how to achieve an optimal sampling and which sequencing strategy to implement. Here we determine, through simulation, the sampling scheme that maximizes the power to map the genetic basis of a complex trait in an outbreeding species across an idealized landscape and draw genomic predictions for the trait, comparing individual and pool sequencing strategies. Our results show that quantitative trait locus detection power and prediction accuracy are higher when more populations over the landscape are sampled and this is more cost-effectively done with pool sequencing than with individual sequencing. Additionally, we recommend sampling populations from areas of high genetic diversity. As progress in sequencing enables the integration of trait-based functional ecology into landscape genomics studies, these findings will guide study designs allowing direct measures of genetic effects in natural populations across the environment.

Genetic variation and temperature affects hybrid barriers during interspecific hybridization.

Genomic imprinting regulates parent-specific transcript dosage during seed development and is mainly confined to the endosperm. Elucidation of the function of many imprinted genes has been hampered by the lack of corresponding mutant phenotypes, and the role of imprinting is mainly associated with genome dosage regulation or allocation of resources. Disruption of imprinted genes has also been suggested to mediate endosperm-based post-zygotic hybrid barriers depending on genetic variation and gene dosage. Here, we have analyzed the conservation of a clade from the MADS-box type I class transcription factors in the closely related species Arabidopsis arenosa, A. lyrata, and A. thaliana, and show that AGL36-like genes are imprinted and maternally expressed in seeds of Arabidopsis species and in hybrid seeds between outbreeding species. In hybridizations between outbreeding and inbreeding species the paternally silenced allele of the AGL36-like gene is reactivated in the hybrid, demonstrating that also maternally expressed imprinted genes are perturbed during hybridization and that such effects on imprinted genes are specific to the species combination. Furthermore, we also demonstrate a quantitative effect of genetic diversity and temperature on the strength of the post-zygotic hybridization barrier. Markedly, a small decrease in temperature during seed development increases the survival of hybrid F1 seeds, suggesting that abiotic and genetic parameters play important roles in post-zygotic species barriers, pointing at evolutionary scenarios favoring such effects. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA562212. All sequences generated in this study have been deposited in the National Center for Biotechnology Information Sequence Read Archive (https://www.ncbi.nlm.nih.gov/sra/) with project number PRJNA562212.

Why are tall-statured energy grasses of polyploid species complexes potentially invasive? A review of their genetic variation patterns and evolutionary plasticity

Perennial tall-statured grasses are regarded as a sustainable source of renewable energy for their high yields of lignocellulosic biomass, low resource input, wide ecological tolerance and capacity for storing large amounts of atmospheric CO2 in their perennial underground rhizome systems. These same traits, that make such crops agronomically attractive and sustainable, make these species highly competitive and potentially invasive. Several perennial energy crop grasses are outbreeding species that belong to cosmopolitan polyploid species complexes, i.e. groups of interbreeding species with ploidy variation. The cultivation of such highly productive and genetically diverse crops can have unwanted consequences through the evolution of invasive species. The goal of this review is to provide the scientific community, including agronomists, breeders, users and nature managers, with an introduction to the genetic dynamics occurring within the polyploid species complexes of the emerging energy species Arundo donax, Miscanthus × giganteus, Panicum virgatum, Phalaris arundinacea and Phragmites australis, and the broad biogeographical extent of their gene flow impact. Such aspects are difficult to predict, and are not captured by invasion risk assessments and by the sustainability certifications of the bioenergy supply chain. The review integrates literature from the phylogenetic, cytology, population ecology and agronomic research and focuses on the evolutionary processes that shape invasiveness that can be activated post-introduction by the dispersal of pollen, seeds and plant fragments from the energy crops to the environment. Due to the high genetic diversity of the crops, the adverse effects that genetic drift and founder effect can have on the establishment of small populations are very unlikely. On the contrary the data collected suggests that the risk of fostering panmictic continental invasive populations is high. Agronomic measures, regulations and genetic improvements that can contain dispersal from crops are discussed, as well as urgent research needs.

High-quality, genome-wide SNP genotypic data for pedigreed germplasm of the diploid outbreeding species apple, peach, and sweet cherry through a common workflow.

High-quality genotypic data is a requirement for many genetic analyses. For any crop, errors in genotype calls, phasing of markers, linkage maps, pedigree records, and unnoticed variation in ploidy levels can lead to spurious marker-locus-trait associations and incorrect origin assignment of alleles to individuals. High-throughput genotyping requires automated scoring, as manual inspection of thousands of scored loci is too time-consuming. However, automated SNP scoring can result in errors that should be corrected to ensure recorded genotypic data are accurate and thereby ensure confidence in downstream genetic analyses. To enable quick identification of errors in a large genotypic data set, we have developed a comprehensive workflow. This multiple-step workflow is based on inheritance principles and on removal of markers and individuals that do not follow these principles, as demonstrated here for apple, peach, and sweet cherry. Genotypic data was obtained on pedigreed germplasm using 6-9K SNP arrays for each crop and a subset of well-performing SNPs was created using ASSIsT. Use of correct (and corrected) pedigree records readily identified violations of simple inheritance principles in the genotypic data, streamlined with FlexQTL software. Retained SNPs were grouped into haploblocks to increase the information content of single alleles and reduce computational power needed in downstream genetic analyses. Haploblock borders were defined by recombination locations detected in ancestral generations of cultivars and selections. Another round of inheritance-checking was conducted, for haploblock alleles (i.e., haplotypes). High-quality genotypic data sets were created using this workflow for pedigreed collections representing the U.S. breeding germplasm of apple, peach, and sweet cherry evaluated within the RosBREED project. These data sets contain 3855, 4005, and 1617 SNPs spread over 932, 103, and 196 haploblocks in apple, peach, and sweet cherry, respectively. The highly curated phased SNP and haplotype data sets, as well as the raw iScan data, of germplasm in the apple, peach, and sweet cherry Crop Reference Sets is available through the Genome Database for Rosaceae.

Overcoming challenges in variant calling: exploring sequence diversity in candidate genes for plant development in perennial ryegrass (Lolium perenne).

Revealing DNA sequence variation within the Lolium perenne genepool is important for genetic analysis and development of breeding applications. We reviewed current literature on plant development to select candidate genes in pathways that control agronomic traits, and identified 503 orthologues in L. perenne. Using targeted resequencing, we constructed a comprehensive catalogue of genomic variation for a L. perenne germplasm collection of 736 genotypes derived from current cultivars, breeding material and wild accessions. To overcome challenges of variant calling in heterogeneous outbreeding species, we used two complementary strategies to explore sequence diversity. First, four variant calling pipelines were integrated with the VariantMetaCaller to reach maximal sensitivity. Additional multiplex amplicon sequencing was used to empirically estimate an appropriate precision threshold. Second, a de novo assembly strategy was used to reconstruct divergent alleles for each gene. The advantage of this approach was illustrated by discovery of 28 novel alleles of LpSDUF247, a polymorphic gene co-segregating with the S-locus of the grass self-incompatibility system. Our approach is applicable to other genetically diverse outbreeding species. The resulting collection of functionally annotated variants can be mined for variants causing phenotypic variation, either through genetic association studies, or by selecting carriers of rare defective alleles for physiological analyses.

Genetic Diversity and Structure of Lolium Species Surveyed on Nuclear Simple Sequence Repeat and Cytoplasmic Markers.

To assess the genetic diversity and population structure of Lolium species, we used 32 nuclear simple sequence repeat (SSR) markers and 7 cytoplasmic gene markers to analyze a total of 357 individuals from 162 accessions of 9 Lolium species. This survey revealed a high level of polymorphism, with an average number of alleles per locus of 23.59 and 5.29 and an average PIC-value of 0.83 and 0.54 for nuclear SSR markers and cytoplasmic gene markers, respectively. Analysis of molecular variance (AMOVA) revealed that 16.27 and 16.53% of the total variation was due to differences among species, with the remaining 56.35 and 83.47% due to differences within species and 27.39 and 0% due to differences within individuals in 32 nuclear SSR markers set and 6 chloroplast gene markers set, respectively. The 32 nuclear SSR markers detected three subpopulations among 357 individuals, whereas the 6 chloroplast gene markers revealed three subpopulations among 160 accessions in the STRUCTURE analysis. In the clustering analysis, the three inbred species clustered into a single group, whereas the outbreeding species were clearly divided, especially according to nuclear SSR markers. In addition, almost all Lolium multiflorum populations were clustered into group C4, which could be further divided into three subgroups, whereas Lolium perenne populations primarily clustered into two groups (C2 and C3), with a few lines that instead grouped with L. multiflorum (C4) or Lolium rigidum (C6). Together, these results will useful for the use of Lolium germplasm for improvement and increase the effectiveness of ryegrass breeding.

Breeding system, gene dispersal and small-scale spatial genetic structure of a threatened food tree species, Pentadesma butyracea (Clusiaceae) in Benin

Pentadesma butyracea Sabine, a rain forest food tree species, plays a vital role in the socio-economic livelihood of some West African rural communities due to its various products. However, its scattered populations are threatened in Benin. Defining appropriate conservation strategies requires a good knowledge of mating patterns and their consequences for population genetics. The outcrossing rate, levels of correlated paternity and fine-scale spatial genetic structure of adults and maternal sibships were estimated for one small population and three large populations in Benin using microsatellite markers. Similar outcrossing rates (88–95%) were found in all populations, showing that P. butyracea is mainly an outbreeding species. We found no evidence of inbreeding depression from a decay of inbreeding with age. The spatial genetic structure within the large populations (Sp statistic = 0.003–0.038) was consistent with isolation-by-distance expectations, showing that gene dispersal is spatially limited. Limited pollen dispersal is highlighted by the decay of the degree of correlated paternity between sibships with spatial distance. The mean pollen dispersal distance was estimated between 50 m and 450 m, but up to 21% pollen may migrate from external sources. The smallest population displayed slightly higher correlated paternity than the large populations (r p = 0.37 vs. r p = 0.17–0.30). In conclusion, our results suggest that small populations may show a reduction in sire numbers in seed, while the fragmented populations, large and small, are connected through gene flow. There is little inbreeding and no evidence of inbreeding depression.

Marker-trait association analysis for agronomic and compositional traits in sainfoin (Onobrychis viciifolia).

Sainfoin (Onobrychis viciifolia) is a perennial forage legume with great potential for use in sustainable agriculture due to its low input requirements, good drought tolerance, and production of forage rich in polyphenolic compounds, which are beneficial for animal health. However, its distribution and cultivation are limited due to its moderate agronomic performance and a general lack of well adapted, highly yielding cultivars. Faster progress in breeding is imperative, but is often hampered by the complex inheritance of traits and limited knowledge on the genetic composition of this tetraploid, outbreeding species. Molecular genetic tools might aid phenotypic selection; however, to date no information on marker-trait associations is available for sainfoin. Hence, the goal of the present study was to detect marker-trait associations in a biparental F1 population. Single plants were screened for recently developed genetic markers and phenotyped for important agronomic traits and concentrations of different polyphenolic compounds. Significant trait-associated markers (TAM) were detected for plant height (11), plant vigor (1), and seed yield (7). These three traits were positively correlated with each other and shared some TAMs. Correlations among markers suggested that two independent loci control these three vigor-related traits. One additional, independent TAM was detected for the share of prodelphinidins in total condensed tannins. Our results provide insight into the genetic control of important traits of sainfoin, and the TAMs reported here could assist selection in combination with phenotypic assessment.

A high-density, multi-parental SNP genetic map on apple validates a new mapping approach for outcrossing species.

Quantitative trait loci (QTL) mapping approaches rely on the correct ordering of molecular markers along the chromosomes, which can be obtained from genetic linkage maps or a reference genome sequence. For apple (Malus domestica Borkh), the genome sequence v1 and v2 could not meet this need; therefore, a novel approach was devised to develop a dense genetic linkage map, providing the most reliable marker-loci order for the highest possible number of markers. The approach was based on four strategies: (i) the use of multiple full-sib families, (ii) the reduction of missing information through the use of HaploBlocks and alternative calling procedures for single-nucleotide polymorphism (SNP) markers, (iii) the construction of a single backcross-type data set including all families, and (iv) a two-step map generation procedure based on the sequential inclusion of markers. The map comprises 15 417 SNP markers, clustered in 3 K HaploBlock markers spanning 1 267 cM, with an average distance between adjacent markers of 0.37 cM and a maximum distance of 3.29 cM. Moreover, chromosome 5 was oriented according to its homoeologous chromosome 10. This map was useful to improve the apple genome sequence, design the Axiom Apple 480 K SNP array and perform multifamily-based QTL studies. Its collinearity with the genome sequences v1 and v3 are reported. To our knowledge, this is the shortest published SNP map in apple, while including the largest number of markers, families and individuals. This result validates our methodology, proving its value for the construction of integrated linkage maps for any outbreeding species.

Rapid purging of genetic load in a metapopulation and consequences for range expansion in an invasive plant

Invasive species often display high fitness despite bottlenecks and inbreeding during establishment. We address this paradox through simulations and experiments that assess the potential for purging of genetic load during range expansion. Success of invaders often depends on the production of vigorous inbred offspring allowing for rapid population growth after colonization. Substantial genetic load of outbreeding species reduces the fitness of offspring as inbreeding ensues during the establishment of populations. In our simulations, sustained selfing or outcrossing within isolated populations did little to remove deleterious mutations. Conversely, inbreeding combined with periodic gene flow resulted in efficient purging and accelerated rates of range expansion. Purging efficiency was dependent on initial genetic diversity levels, in line with predictions that multiple introductions facilitate invasion and the evolution of more aggressive invaders. Simulation predictions were tested using the invasive species Brachypodium sylvaticum. Homozygous populations on B. sylvaticum’s range periphery displayed lower inbreeding depression compared to heterozygous populations near introduction sites. Empirical tests with B. sylvaticum demonstrate that purging of genetic load is a plausible scenario promoting range expansion during invasion.

Phylogenetic analysis of Festuca–Lolium complex using SRAP markers

The Lolium and Festuca genera have been treated as the most important groupings of temperate grasses in forage production and the turf industry. The two genera undoubtedly represent a closely allied complex of related species. The objective of this study was to obtain an overview of the diversity and genetic relationships among 59 accessions of 32 species of the Lolium–Festuca complex using sequence related amplified polymorphism (SRAP) markers. In total, 22 primer combinations amplified 269 polymorphic bands which were detected with an average of 12.23 alleles per SRAP locus. The average polymorphic rate (P) between the species studied was 100 %, demonstrating their high degree of genetic diversity. According to the POPGENE and AMOVA analyses, the inter-genera diversity and the variance between the two genera were both under 50 %. The dendrograms derived either by NTSYS or MEGA in addition to the PCO were consistent and clearly illustrated the relationships among representatives of the Lolium genus as well as the subgenus Festuca, Schedonorus and Leucopoa within the Festuca genus. The result of this study strongly supported the previous morphological separation into a “broad leaved” and “fine-leaved” clades, and it once again demonstrated the close relationship between the Lolium genus and the Schedonorus subgenus. This study also suggested the inclusion of F. mairei in subg. Schedonorus and to divide subgenus Leucopoa by moving sect. Leucopoa and sect. Breviaristatae into different subgenera. The analysis method described provides new methodologies for determining the phylogeny of these outbreeding species.

ASSIsT: an automatic SNP scoring tool for in- and outbreeding species.

ASSIsT (Automatic SNP ScorIng Tool) is a user-friendly customized pipeline for efficient calling and filtering of SNPs from Illumina Infinium arrays, specifically devised for custom genotyping arrays. Illumina has developed an integrated software for SNP data visualization and inspection called GenomeStudio® (GS). ASSIsT builds on GS-derived data and identifies those markers that follow a bi-allelic genetic model and show reliable genotype calls. Moreover, ASSIsT re-edits SNP calls with null alleles or additional SNPs in the probe annealing site. ASSIsT can be employed in the analysis of different population types such as full-sib families and mating schemes used in the plant kingdom (backcross, F1, F2), and unrelated individuals. The final result can be directly exported in the format required by the most common software for genetic mapping and marker–trait association analysis. ASSIsT is developed in Python and runs in Windows and Linux.Availability and implementation: The software, example data sets and tutorials are freely available at http://compbiotoolbox.fmach.it/assist/.Contact: eric.vandeweg@wur.nl

Condition Dependent Effects on Sex Allocation and Reproductive Effort in Sequential Hermaphrodites

Theory predicts the optimal timing of sex change will be the age or size at which half of an individual's expected fitness comes through reproduction as a male and half through reproduction as a female. In this way, sex allocation across the lifetime of a sequential hermaphrodite parallels the sex allocation of an outbreeding species exhibiting a 1∶1 ratio of sons to daughters. However, the expectation of a 1∶1 sex ratio is sensitive to variation in individual condition. If individuals within a population vary in condition, high-condition individuals are predicted to make increased allocations to the sex with the higher variance in reproductive success. An oft-cited example of this effect is seen in red deer, Cervus elaphus, in which mothers of high condition are more likely to produce sons, while those in low condition are more likely to produce daughters. Here, we show that individual condition is predicted to similarly affect the pattern of sex allocation, and thus the allocation of reproductive effort, in sequential hermaphrodites. High-condition sex-changers are expected to obtain more than half of their fitness in the high-payoff second sex and, as a result, are expected to reduce the allocation of reproductive effort in the initial sex. While the sex ratio in populations of sequential hermaphrodites is always skewed towards an excess of the initial sex, condition dependence is predicted to increase this effect.

Bayesian QTL analyses using pedigreed families of an outcrossing species, with application to fruit firmness in apple

Proof of concept of Bayesian integrated QTL analyses across pedigree-related families from breeding programs of an outbreeding species. Results include QTL confidence intervals, individuals' genotype probabilities and genomic breeding values. Bayesian QTL linkage mapping approaches offer the flexibility to study multiple full sib families with known pedigrees simultaneously. Such a joint analysis increases the probability of detecting these quantitative trait loci (QTL) and provide insight of the magnitude of QTL across different genetic backgrounds. Here, we present an improved Bayesian multi-QTL pedigree-based approach on an outcrossing species using progenies with different (complex) genetic relationships. Different modeling assumptions were studied in the QTL analyses, i.e., the a priori expected number of QTL varied and polygenic effects were considered. The inferences include number of QTL, additive QTL effect sizes and supporting credible intervals, posterior probabilities of QTL genotypes for all individuals in the dataset, and QTL-based as well as genome-wide breeding values. All these features have been implemented in the FlexQTL(™) software. We analyzed fruit firmness in a large apple dataset that comprised 1,347 individuals forming 27 full sib families and their known ancestral pedigrees, with genotypes for 87 SSR markers on 17 chromosomes. We report strong or positive evidence for 14 QTL for fruit firmness on eight chromosomes, validating our approach as several of these QTL were reported previously, though dispersed over a series of studies based on single mapping populations. Interpretation of linked QTL was possible via individuals' QTL genotypes. The correlation between the genomic breeding values and phenotypes was on average 90 %, but varied with the number of detected QTL in a family. The detailed posterior knowledge on QTL of potential parents is critical for the efficiency of marker-assisted breeding.