GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary ...genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G'(ST), G''(ST), Jost's D(est) and F'(ST) through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised.
GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx.
rod.peakall@anu.edu.au.
Given the exceptional diversity of orchids (26 000+ species), improving strategies for the conservation of orchids will benefit a vast number of taxa. Furthermore, with rapidly increasing numbers of ...endangered orchids and low success rates in orchid conservation translocation programmes worldwide, it is evident that our progress in understanding the biology of orchids is not yet translating into widespread effective conservation.
We highlight unusual aspects of the reproductive biology of orchids that can have important consequences for conservation programmes, such as specialization of pollination systems, low fruit set but high seed production, and the potential for long-distance seed dispersal. Further, we discuss the importance of their reliance on mycorrhizal fungi for germination, including quantifying the incidence of specialized versus generalized mycorrhizal associations in orchids. In light of leading conservation theory and the biology of orchids, we provide recommendations for improving population management and translocation programmes.
Major gains in orchid conservation can be achieved by incorporating knowledge of ecological interactions, for both generalist and specialist species. For example, habitat management can be tailored to maintain pollinator populations and conservation translocation sites selected based on confirmed availability of pollinators. Similarly, use of efficacious mycorrhizal fungi in propagation will increase the value of ex situ collections and likely increase the success of conservation translocations. Given the low genetic differentiation between populations of many orchids, experimental genetic mixing is an option to increase fitness of small populations, although caution is needed where cytotypes or floral ecotypes are present. Combining demographic data and field experiments will provide knowledge to enhance management and translocation success. Finally, high per-fruit fecundity means that orchids offer powerful but overlooked opportunities to propagate plants for experiments aimed at improving conservation outcomes. Given the predictions of ongoing environmental change, experimental approaches also offer effective ways to build more resilient populations.
Sex‐biased dispersal is expected to generate differences in the fine‐scale genetic structure of males and females. Therefore, spatial analyses of multilocus genotypes may offer a powerful approach ...for detecting sex‐biased dispersal in natural populations. However, the effects of sex‐biased dispersal on fine‐scale genetic structure have not been explored. We used simulations and multilocus spatial autocorrelation analysis to investigate how sex‐biased dispersal influences fine‐scale genetic structure. We evaluated three statistical tests for detecting sex‐biased dispersal: bootstrap confidence intervals about autocorrelation r values and recently developed heterogeneity tests at the distance class and whole correlogram levels. Even modest sex bias in dispersal resulted in significantly different fine‐scale spatial autocorrelation patterns between the sexes. This was particularly evident when dispersal was strongly restricted in the less‐dispersing sex (mean distance <200 m), when differences between the sexes were readily detected over short distances. All tests had high power to detect sex‐biased dispersal with large sample sizes (n ≥ 250). However, there was variation in type I error rates among the tests, for which we offer specific recommendations. We found congruence between simulation predictions and empirical data from the agile antechinus, a species that exhibits male‐biased dispersal, confirming the power of individual‐based genetic analysis to provide insights into asymmetries in male and female dispersal. Our key recommendations for using multilocus spatial autocorrelation analyses to test for sex‐biased dispersal are: (i) maximize sample size, not locus number; (ii) concentrate sampling within the scale of positive structure; (iii) evaluate several distance class sizes; (iv) use appropriate methods when combining data from multiple populations; (v) compare the appropriate groups of individuals.
Chloroplast microsatellites, or simple sequence repeats (cpSSRs), are typically mononucleotide tandem repeats. When located in the noncoding regions of the chloroplast genome (cpDNA), they commonly ...show intraspecific variation in repeat number. Despite the growing number of studies applying cpSSRs, studies of economically important plants and their relatives remain over-represented. Thus, the potential of cpSSRs to offer unique insights into ecological and evolutionary processes in wild plant species has yet to be fully realized. This review provides an overview of the technical resources available to aid cpSSR discovery including a list of cpSSR primer sets available and cpDNA sequencing resources. Our updated analysis of 99 whole chloroplast genomes downloaded from GenBank confirms that potentially variable cpSSRs are abundant in the noncoding cpDNA of plants. Overall variation in the frequency of cpSSRs was extreme, ranging from one to 700 per genome (median = 93), while in 81 vascular plants, between 35 and 160 cpSSRs were detected per genome (median = 86). We offer five recommendations to aid wider development and application of cpSSRs: (i) When genus-specific cpSSR primers are available, cross-species amplification can often be fruitful. (ii) While potentially useful, universal cpSSR primers at best provide access to only a small number of variable markers. (iii) De novo sequencing of noncoding cpDNA is the most effective and efficient way to develop cpSSR markers in wild species. (iv) DNA sequencing of cpSSR alleles is essential, given the complex nature of the genetic variation associated with hypervariable cpDNA regions. (v) The reliability of cpSSR length based genetic assays need to be validated in all studies.
The flower is arguably the centrepiece of angiosperm evolution. Its primary function is to secure pollination — the transfer of pollen from the anther (male) to the stigma (female). As plants are ...sessile organisms, the extraordinary diversity of flowers in large part reflects countless alternative evolutionary solutions to achieve this critical step in the flowering plant life cycle. The majority of flowering plants, some 87% by one estimate, depend on animals for pollination, with most of these paying for the service of pollination via food rewards of nectar or pollen. As in human economic systems, however, some cheating and deception occurs, with the pollination strategy of sexual deception being one such example.
The overwhelming majority of the flowering plants are animal pollinated. While most of these species pay for the service of pollination, some plants cheat the system. In this Primer, Rod Peakall discusses a remarkable case of floral mimicry — sexually deceptive plants which secure insect pollination by offering the false promise of sex.
For organisms with limited vagility and/or occupying patchy habitats, we often encounter nonrandom patterns of genetic affinity over relatively small spatial scales, labelled fine-scale genetic ...structure. Both the extent and decay rate of that pattern can be expected to depend on numerous interesting demographic, ecological, historical, and mating system factors, and it would be useful to be able to compare different situations. There is, however, no heterogeneity test currently available for fine-scale genetic structure that would provide us with any guidance on whether the differences we encounter are statistically credible. Here, we develop a general nonparametric heterogeneity test, elaborating on standard autocorrelation methods for pairs of individuals. We first develop a 'pooled within-population' correlogram, where the distance classes (lags) can be defined as functions of distance. Using that pooled correlogram as our null-hypothesis reference frame, we then develop a heterogeneity test of the autocorrelations among different populations, lag-by-lag. From these single-lag tests, we construct an analogous test of heterogeneity for multilag correlograms. We illustrate with a pair of biological examples, one involving the Australian bush rat, the other involving toadshade trillium. The Australian bush rat has limited vagility, and sometimes occupies patchy habitat. We show that the autocorrelation pattern diverges somewhat between continuous and patchy habitat types. For toadshade trillium, clonal replication in Piedmont populations substantially increases autocorrelation for short lags, but clonal replication is less pronounced in mountain populations. Removal of clonal replicates reduces the autocorrelation for short lags and reverses the sign of the difference between mountain and Piedmont correlograms.
The use of diversity metrics has a long history in population ecology, while population genetic work has been dominated by variance-derived metrics instead, a technical gap that has slowed ...cross-communication between the fields. Interestingly, Rao's Quadratic Entropy (RQE), comparing elements for 'degrees of divergence', was originally developed for population ecology, but has recently been deployed for evolutionary studies. We here translate RQE into a continuous diversity analogue, and then construct a multiply nested diversity partition for alleles, individuals, populations, and species, each component of which exhibits the behavior of proper diversity metrics, and then translate these components into 0,1-scaled form. We also deploy non-parametric statistical tests of the among-stratum components and novel tests of the homogeneity of within-stratum diversity components at any hierarchical level. We then illustrate this new analysis with eight nSSR loci and a pair of close Australian marsupial (Antechinus) congeners, using both 'different is different' and 'degree of difference' distance metrics. The total diversity in the collection is larger than that within either species, but most of the within-species diversity is resident within single populations. The combined A. agilis collection exhibits more diversity than does the combined A. stuartii collection, possibly attributable to localized differences in either local ecological disturbance regimes or differential levels of population isolation. Beyond exhibiting different allelic compositions, the two congeners are becoming more divergent for the arrays of allele sizes they possess.
Sexually deceptive plants achieve pollination by enticing specific male insects as pollinators using a combination of olfactory, visual, and morphological mimicry. The sexually deceptive orchid genus
...Chiloglottis
is comprised of some 30 species with predominantly dull green-red flowers except for the dark insectiform calli/callus structure from the labellum lamina. This unique structure mimics the female of the pollinator and potentially enhances the visibility of the mimic. However, the chemical and genetic basis for the color of these structures remains poorly understood across the genus. The goal of this study was to investigate the flower color biochemistry and patterns of gene expression across the anthocyanin and flavonol glycoside biosynthetic pathway within the calli structures across the three distinct clades of
Chiloglottis
(Formicifera, Reflexa, and Valida) using chemical and transcriptome analysis. Our phylogenomic analysis confirmed the close sister relationship between the Reflexa/Formicifera clades and reaffirms the basal position of the Valida clade. Additionally, the biochemical basis of the dark calli/callus structures is conserved across the genus. Nonetheless, the proportion of methoxylated anthocyanin and flavonol glycoside derivatives and the mean gene expression levels appear to differentiate the Reflexa and Formicifera clades from the Valida clade. In future studies, it will be of interest to tease apart the role of phylogeny, environment, pollinators, and other factors as potential drivers of the observed biochemistry and gene expression differences. It will also be important to characterize the function of candidate genes such as
DFR
,
LDOX,
and
FLS
in this fascinating case of flower color mimicry.
The Orchidaceae is rivaled only by the Asteraceae as the largest plant family, with the estimated number of species exceeding 25,000 and encompassing more than 700 genera. To gain insights into the ...mechanisms driving species diversity across both global and local scales, well-supported phylogenies targeting different taxonomic groups and/or geographical regions will be crucial. High-throughput sequencing technologies have revolutionized the field of molecular phylogenetics by simplifying the process of obtaining genome-scale sequence data. Consequently, there has been an explosive growth of such data in public repositories. Here we took advantage of this unprecedented access to transcriptome data from predominantly non-phylogenetic studies to assess if it can be repurposed to gain rapid and accurate phylogenetic insights across the orchids. Exhaustive searches revealed transcriptomic data for more than 100 orchid species spanning 5 subfamilies, 13 tribes, 21 subtribes, and 50 genera that were amendable for exploratory phylotranscriptomic analysis. Next, we performed re-assembly of the transcriptomes before strategic selection of the final samples based on a gene completeness evaluation. Drawing on these data, we report phylogenetic analyses at both deep and shallow evolutionary scales
via
maximum likelihood and shortcut coalescent species tree methods. In this perspective, we discuss some key outcomes of this study and conclude by highlighting other complementary, albeit rarely explored, insights beyond phylogenetic analysis that repurposed multi-tissue transcriptome can offer.
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