Rodney Peakall

GenAlEx 6.5

Summary: 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 Dest 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. Availability and implementation: 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. Contact: rod.peakall@anu.edu.au

Spatial autocorrelation analysis offers new insights into gene flow in the Australian bush rat, Rattus fuscipes

Abstract Dispersal is a fundamental process that influences the response of species to landscape change and habitat fragmentation. In an attempt to better understand dispersal in the Australian bush rat, Rattusfuscipes, we have combined a new multilocus autocorrelation method with hypervariable microsatellite genetic markers to investigate fine‐scale (<1 km) patterns of spatial distribution and spatial genetic structure. The study was conducted across eight trapping transects at four sites, with a total of 270 animals sampled. Spatial autocorrelation analysis of bush rat distribution revealed that, in general, animals occurred in groups or clusters of higher density (<200 m across), with intervening gaps or lower density areas. Spatial genetic autocorrelation analysis, based on seven hypervariable microsatellite loci (He= 0.8) with a total of 80 alleles, revealed a consistent pattern of significant positive local genetic structure. This genetic pattern was consistent for all transects, and for adults and sub‐adults, males and females. By testing for autocorrelation at multiple scales from 10 to 800 m we found that the extent of detectable positive spatial genetic structure exceeded 500 m. Further analyses detected significantly weaker spatial genetic structure in males compared with females, but no significant differences were detected between adults and sub adults. Results from Mantel tests and hierarchical AMOVA further support the conclusion that the distribution of bush rat genotypes is not random at the scale of our study. Instead, proximate bush rats are more genetically alike than more distant animals. We conclude that in bush rats, gene flow per generation is sufficiently restricted to generate the strong positive signal of local spatial genetic structure. Although our results are consistent with field data on animal movement, including the reported tendency for males to move further than females, we provide the first evidence for restricted gene flow in bush rats. Our study appears to be the first microsatellite‐based study of fine‐scale genetic variation in small mammals and the first to report consistent positive local genetic structure across sites, age‐classes, and sexes. The combination of new forms of autocorrelation analyses, hypervariable genetic markers and fine‐scale analysis (<1 km) may thus offer new evolutionary insights that are overlooked by more traditional larger scaled (>10 km) population genetic studies.

Comparative analysis of genetic diversity in the mangrove species Avicennia marina (Forsk.) Vierh. (Avicenniaceae) detected by AFLPs and SSRs

Abstract  Avicennia marina is an important mangrove species with a wide geographical and climatic distribution which suggests that large amounts of genetic diversity are available for conservation and breeding programs. In this study we compare the informativeness of AFLPs and SSRs for assessing genetic diversity within and among individuals, populations and subspecies of A. marina in Australia. Our comparison utilized three SSR loci and three AFLP primer sets that were known to be polymorphic, and could be run in a single analysis on a capillary electrophoresis system, using different- colored fluorescent dyes. A total of 120 individuals representing six populations and three subspecies were sampled. At the locus level, SSRs were considerably more variable than AFLPs, with a total of 52 alleles and an average heterozygosity of 0.78. Average heterozygosity for AFLPs was 0.193, but all of the 918 bands scored were polymorphic. Thus, AFLPs were considerably more efficient at revealing polymorphic loci than SSRs despite lower average heterozygosities. SSRs detected more genetic differentiation between populations (19 vs 9%) and subspecies (35 vs 11%) than AFLPs. Principal co-ordinate analysis revealed congruent patterns of genetic relationships at the individual, population and subspecific levels for both data sets. Mantel testing confirmed congruence between AFLP and SSR genetic distances among, but not within, population comparisons, indicating that the markers were segregating independently but that evolutionary groups (populations and subspecies) were similar. Three genetic criteria of importance for defining priorities for ex situ collections or in situ conservation programs (number of alleles, number of locally common alleles and number of private alleles) were correlated between the AFLP and SSR data sets. The congruence between AFLP and SSR data sets suggest that either method, or a combination, is applicable to expanded genetic studies of mangroves. The codominant nature of SSRs makes them ideal for further population-based investigations, such as mating-system analyses, for which the dominant AFLP markers are less well suited. AFLPs may be particularly useful for monitoring propagation programs and identifying duplicates within collections, since a single PCR assay can reveal many loci at once.

DISPERSAL, PHILOPATRY, AND INFIDELITY: DISSECTING LOCAL GENETIC STRUCTURE IN SUPERB FAIRY-WRENS (MALURUS CYANEUS)

Abstract Dispersal influences evolution, demography, and social characteristics but is generally difficult to study. Here we combine long‐term demographic data from an intensively studied population of superb fairy‐wrens(Malurus cyaneus) and multivariate spatial autocorrelation analyses of microsatellite genotypes to describe dispersal behavior in this species. The demographic data revealed: (1) sex‐biased dispersal: almost all individuals that dispersed into the study area over an eight‐year period were female (93%; n 5 153); (2) high rates of extragroup infidelity (66% of offspring), which also facilitated local gene dispersal; and (3) skewed lifetime reproductive success in both males and females. These data led to three expectations concerning the patterns of fine‐scale genetic structure: (1) little or no spatial genetic autocorrelation among females, (2) positive spatial genetic autocorrelation among males, and (3) a heterogeneous genetic landscape. Global autocorrelation analysis of the genotypes present in the study population confirmed the first two expectations. A novel two‐dimensional local autocorrelation analysis confirmed the third and provided new insight into the patterns of genetic structure across the two‐dimensional landscape. We highlight the potential of autocorrelation analysis to infer evolutionary processes but also emphasize that genetic patterns in space cannot be fully understood without an appropriate and intensive sampling regime and detailed knowledge of the individuals genotyped.

A heterogeneity test for fine‐scale genetic structure

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.

DOES SELECTION ON FLORAL ODOR PROMOTE DIFFERENTIATION AMONG POPULATIONS AND SPECIES OF THE SEXUALLY DECEPTIVE ORCHID GENUS OPHRYS

Abstract —Sexually deceptive orchids from the genus Ophrys attract their pollinators primarily through the chemical mimicry of female hymenopteran sex pheromones, thereby deceiving males into attempted matings with the orchid labellum. Floral odor traits are crucial for the reproductive success of these pollinator‐limited orchids, as well as for maintaining reproductive isolation through the attraction of specific pollinators. We tested for the signature of pollinator‐mediated selection on floral odor by comparing intra and interspecific differentiation in odor compounds with that found at microsatellite markers among natural populations. Three regions from southern Italy were sampled. We found strong floral odor differentiation among allopatric populations within species, among allopatric species and among sympatric species. Population differences in odor were also reflected in significant variation in the attractivity of floral extracts to the pollinator, Colletes cunicularius. Odor compounds that are electrophysiologically active in C. cunicularius males, especially alkenes, were more strongly differentiated among conspecific populations than nonactive compounds in the floral odor. In marked contrast to these odor patterns, there was limited population or species level differentiation in microsatellites (FST range 0.005 to 0.127, mean FST 0.075). We propose that the strong odor differentiation and lack of genetic differentiation among sympatric taxa indicates selection imposed by the distinct odor preferences of different pollinating species. Within species, low FST values are suggestive of large effective population sizes and indicate that divergent selection rather than genetic drift accounts for the strong population differentiation in odor. The higher differentiation in active versus non‐active odor compounds suggests that divergent selection among orchid populations may be driven by local pollinator preferences for those particular compounds critical for pollinator attraction.

Chloroplast simple sequence repeats (cpSSRs): technical resources and recommendations for expanding cpSSR discovery and applications to a wide array of plant species.

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.

Genetic spatial autocorrelation can readily detect sex‐biased dispersal

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.

Short tandem repeat (STR) DNA markers are hypervariable and informative in Cannabis sativa: implications for forensic investigations

Short tandem repeat (STR) markers are the DNA marker of choice in forensic analysis of human DNA. Here we extend the application of STR markers to Cannabis sativa and demonstrate their potential for forensic investigations. Ninety-three individual cannabis plants, representing drug and fibre accessions of widespread origin were profiled with five STR makers. A total of 79 alleles were detected across the five loci. All but four individuals from a single drug-type accession had a unique multilocus genotype. An analysis of molecular variance (AMOVA) revealed significant genetic variation among accessions, with an average of 25% genetic differentiation. By contrast, only 6% genetic difference was detected between drug and fibre crop accessions and it was not possible to unequivocally assign plants as either drug or fibre type. However, our results suggest that drug strains may typically possess lower genetic diversity than fibre strains, which may ultimately provide a means of genetic delineation. Our findings demonstrate the promise of cannabis STR markers to provide information on: (1) agronomic type, (2) the geographical origin of drug seizures, and (3) evidence of conspiracy in production of clonally propagated drug crops.

Social constraint and an absence of sex‐biased dispersal drive fine‐scale genetic structure in white‐winged choughs

This study used eight polymorphic microsatellite loci to examine the relative effects of social organization and dispersal on fine‐scale genetic structure in an obligately cooperative breeding bird, the white‐winged chough (Corcorax melanorhamphos). Using both individual‐level and population‐level analyses, it was found that the majority of chough groups consisted of close relatives and there was significant differentiation among groups (FST = 0.124). However, spatial autocorrelation analysis revealed strong spatial genetic structure among groups up to 2 km apart, indicating above average relatedness among neighbours. Multiple analyses showed a unique lack of sex‐biased dispersal. As such, choughs may offer a model species for the study of the evolution of sex‐biased dispersal in cooperatively breeding birds. These findings suggest that genetic structure in white‐winged choughs reflects the interplay between social barriers to dispersal resulting in large family groups that can remain stable over long periods of times, and short dispersal distances which lead to above average relatedness among neighbouring groups.