Wild species related to domesticated crops (crop wild relatives, or CWRs) represent a high level of genetic diversity that provides a practical gene pool for crop pre-breeding employed to address climate change and food demand challenges globally. Nevertheless, rapid identifying and visual tracking of alien chromosomes and sequences derived from CWRs have been a technical challenge for crop chromosome engineering. Here, a species-specific oligonucleotide (oligo) pool was developed by using the reference genome of Cucumis hystrix (HH, 2n = 2x = 24), a wild species carrying many favorable traits and interspecific compatibility with cultivated cucumber (C. sativus, CC, 2n = 2x = 14). These synthetic double-stranded oligo probes were applied to validate the assembly and characterize the chromosome architectures of C. hystrix, as well as to rapidly identify C. hystrix-chromosomes in diverse C. sativus-hystrix chromosome-engineered germplasms, including interspecific hybrid F1 (HC), synthetic allopolyploids (HHCC, CHC, and HCH) and alien additional lines (CC-H). Moreover, a ∼2Mb of C. hystrix-specific sequences, introduced into cultivated cucumber, were visualized by CWR-specific oligo-painting. These results demonstrate that the CWR-specific oligo-painting technique holds broad applicability for chromosome engineering of numerous crops, as it allows rapid identification of alien chromosomes, reliable detection of homoeologous recombination, and visual tracking of the introgression process. It is promising to achieve directed and high-precision crop pre-breeding combined with other breeding techniques, such as CRISPR/Cas9-mediated chromosome engineering.

The mating system is a central parameter of plant biology because it shapes their ecological and evolutionary properties. Therefore, determining ecological variables that influence the mating system is important for a deeper understanding of the functioning of plant populations. Here, using old concepts and recent statistical developments, we propose a new statistical tool to make inferences about ecological determinants of outcrossing in natural plant populations. The method requires codominant genotypes of seeds collected from maternal plants within different locations. Using extensive computer simulations, we demonstrated that the method is robust to the issues expected for real-world data, including the Wahlund effect, inbreeding and genotyping errors such as allele dropout and allele misclassification. Furthermore, we showed that the estimates of ecological effects and outcrossing rates can be severely biased if genotyping errors and genetic differentiation are not treated explicitly. Application of the new method to the case study of a dioecious tree (Taxus baccata) allowed revealing that female trees that grow in lower local densities have a greater tendency towards mating with relatives. Moreover, we also demonstrated that biparental inbreeding is higher in populations that are characterized by a longer mean distance between trees and a smaller mean trunk perimeter. We found these results to agree with both the theoretical predictions and the history of English yew.

Reticulate evolution, coupled with reproductive features limiting further interspecific recombinations, results in admixed mosaics of large genomic fragments from the ancestral taxa. Whole-genome sequencing (WGS) data are powerful tools to decipher such complex genomes but still too costly to be used for large populations. The aim of this work was to develop an approach to infer phylogenomic structures in diploid, triploid and tetraploid individuals from sequencing data in reduced genome complexity libraries. The approach was applied to the cultivated Citrus gene pool resulting from reticulate evolution involving four ancestral taxa, C. maxima, C. medica, C. micrantha and C. reticulata.
A genotyping by sequencing library was established with the restriction enzyme ApeKI applying one base (A) selection. Diagnostic single nucleotide polymorphisms (DSNPs) for the four ancestral taxa were mined in 29 representative varieties. A generic pipeline based on a maximum likelihood analysis of the number of read data was established to infer ancestral contributions along the genome of diploid, triploid and tetraploid individuals. The pipeline was applied to 48 diploid, four triploid and one tetraploid citrus accessions.
Among 43 598 mined SNPs, we identified a set of 15 946 DSNPs covering the whole genome with a distribution similar to that of gene sequences. The set efficiently inferred the phylogenomic karyotype of the 53 analysed accessions, providing patterns for common accessions very close to that previously established using WGS data. The complex phylogenomic karyotypes of 21 cultivated citrus, including bergamot, triploid and tetraploid limes, were revealed for the first time.
The pipeline, available online, efficiently inferred the phylogenomic structures of diploid, triploid and tetraploid citrus. It will be useful for any species whose reproductive behaviour resulted in an interspecific mosaic of large genomic fragments. It can also be used for the first generations of interspecific breeding schemes.

Understanding the evolutionary histories of invasive species is critical to adopt appropriate management strategies, but this process can be exceedingly complex to unravel. As illustrated in this study of the worldwide invasion of the woodwasp Sirex noctilio, population genetic analyses using coalescent-based scenario testing together with Bayesian clustering and historical records provide opportunities to address this problem. The pest spread from its native Eurasian range to the Southern Hemisphere in the 1900s and recently to Northern America, where it poses economic and potentially ecological threats to planted and native Pinus spp. To investigate the origins and pathways of invasion, samples from five continents were analysed using microsatellite and sequence data. The results of clustering analysis and scenario testing suggest that the invasion history is much more complex than previously believed, with most of the populations being admixtures resulting from independent introductions from Europe and subsequent spread among the invaded areas. Clustering analyses revealed two major source gene pools, one of which the scenario testing suggests is an as yet unsampled source. Results also shed light on the microevolutionary processes occurring during introductions, and showed that only few specimens gave rise to some of the populations. Analyses of microsatellites using clustering and scenario testing considered against historical data drastically altered our understanding of the invasion history of S. noctilio and will have important implications for the strategies employed to fight its spread. This study illustrates the value of combining clustering and ABC methods in a comprehensive framework to dissect the complex patterns of spread of global invaders.

BACKGROUND: The wild relatives of crops represent a major source of valuable traits for crop improvement. These resources are threatened by habitat destruction, land use changes, and other factors, requiring their urgent collection and long-term availability for research and breeding from ex situ collections. We propose a method to identify gaps in ex situ collections (i.e. gap analysis) of crop wild relatives as a means to guide efficient and effective collecting activities.
RESULTS: The methodology prioritizes among taxa based on a combination of sampling, geographic, and environmental gaps. We apply the gap analysis methodology to wild taxa of the Phaseolus genepool. Of 85 taxa, 48 (56.5%) are assigned high priority for collecting due to lack of, or under-representation, in genebanks, 17 taxa are given medium priority for collecting, 15 low priority, and 5 species are assessed as adequately represented in ex situ collections. Gap \"hotspots\", representing priority target areas for collecting, are concentrated in central Mexico, although the narrow endemic nature of a suite of priority species adds a number of specific additional regions to spatial collecting priorities.
CONCLUSIONS: Results of the gap analysis method mostly align very well with expert opinion of gaps in ex situ collections, with only a few exceptions. A more detailed prioritization of taxa and geographic areas for collection can be achieved by including in the analysis predictive threat factors, such as climate change or habitat destruction, or by adding additional prioritization filters, such as the degree of relatedness to cultivated species (i.e. ease of use in crop breeding). Furthermore, results for multiple crop genepools may be overlaid, which would allow a global analysis of gaps in ex situ collections of the world\'s plant genetic resources.

DNA pooling is a cost-effective approach for collecting information on marker allele frequency in genetic studies. It is often suggested as a screening tool to identify a subset of candidate markers from a very large number of markers to be followed up by more accurate and informative individual genotyping. In this article, we investigate several statistical properties and design issues related to this two-stage design, including the selection of the candidate markers for second-stage analysis, statistical power of this design, and the probability that truly disease-associated markers are ranked among the top after second-stage analysis. We have derived analytical results on the proportion of markers to be selected for second-stage analysis. For example, to detect disease-associated markers with an allele frequency difference of 0.05 between the cases and controls through an initial sample of 1000 cases and 1000 controls, our results suggest that when the measurement errors are small (0.005), approximately 3% of the markers should be selected. For the statistical power to identify disease-associated markers, we find that the measurement errors associated with DNA pooling have little effect on its power. This is in contrast to the one-stage pooling scheme where measurement errors may have large effect on statistical power. As for the probability that the disease-associated markers are ranked among the top in the second stage, we show that there is a high probability that at least one disease-associated marker is ranked among the top when the allele frequency differences between the cases and controls are not <0.05 for reasonably large sample sizes, even though the errors associated with DNA pooling in the first stage are not small. Therefore, the two-stage design with DNA pooling as a screening tool offers an efficient strategy in genomewide association studies, even when the measurement errors associated with DNA pooling are nonnegligible. For any disease model, we find that all the statistical results essentially depend on the population allele frequency and the allele frequency differences between the cases and controls at the disease-associated markers. The general conclusions hold whether the second stage uses an entirely independent sample or includes both the samples used in the first stage and an independent set of samples.

The Warao Indian village of Jobure has two modes for height within its adult male population. One mode is at 158 cm and the second occurs at 169 cm. Mean height for adult males and females for this village is significantly higher (alpha less than or equal to 0.05) than for the other Warao villages studied. Examination of the males involved shows that all unusually tall males, except two, are siblings or first cousins and are related to a taller than average village patriarch who is married to the tallest woman in the village. The Warao possess a social system that encourages the formation of small enclaves that are biased samples of the general population and consist of closely related individuals. The physical environment is such that villages only short distances apart may be socially isolated, thus inhibiting gene flow from adjacent settlements. The height distribution observed in the village of Jobure is considered to be the result of repetitive sampling along kinship lines and has been preserved by the physical and social environment.